Theories and Effects of Economic Growth [1 ed.] 9781622571178, 9781612097954

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Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

ECONOMIC ISSUES, PROBLEMS AND PERSPECTIVES

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THEORIES AND EFFECTS OF ECONOMIC GROWTH

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ECONOM MIC ISSUES, PROBLEMS AN ND PERSPECT TIVES

THEORIESS AND EFFEC CTS OF ECONO OMIC GROWT TH

RICHARD D L. BER RTRAND

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Scien nce Publisheers, Inc. N York New Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Library of Congress Cataloging-in-Publication Data Theories and effects of economic growth / editor, Richard L. Bertrand. p. cm. Includes index. ISBN 978-1-62257-117-8 (E-Book) 1. Economic development. I. Bertrand, Richard L. HD75.T47724 2011 338.9--dc23 2011032634

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CONTENTS vii 

Preface Chapter 1

Chapter 2

Cohesion, Growth and Development Since the Industrial Revolution Espen Moe 

Chapter 3

Worldwide Rankings in Economic Growth: Authors, Institutions and Publication Trends during 1992-2002 Vicente German-Soto 

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Five Ways to Combat Misleading Information about Economic Growth Roefie Hueting 

Chapter 5

Chapter 6

Chapter 7

31 

53 

Economic Growth, Inequality and Fiscal Policies: A Survey of the Macroeconomics Literature Leonel Muinelo-Gallo and Oriol Roca-Sagalés 

101 

Energy Efficiency and Carbon Trading – Towards a Greener Malaysia T. H. Oh 

123 

Influence of the Economic Conjuncture on SME Investment: Empirical Evidence Using Dynamic Panel Estimators Silvia Mendes, Paulo Maçãs Nunes and Zélia Serrasqueiro 

143 

The Convergence Hypothesis of Economic Growth Displayed in Advanced Economies Sahar Bahmani 

159 

Chapter 8

Economic Growth and Environment Interactions Serkan Gürlük 

Chapter 9

What Is the Optimal Rate of Inflation for Long-Run Growth? A Cross-Country Analysis Hakan Yilmazkuday 

Chapter 10

1 

Welfare Effects of National Climate Policies and the Growth Rate of Interdependent Economies

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189 

203 

vi

Contents Karl Farmer and Andreas Rainer 

Chapter 11

Does R&D Increase Economic Growth? Bernard C. Beaudreau 

Chapter 12

The Determinants of Economic Growth in Emerging Economies: A Comparative Analysis Pasquale Tridico 

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Index

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..243 271

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PREFACE Positive economic growth is a major goal for all countries, promising a better standard of living and more opportunities, higher levels of employment, lower poverty rates, more productivity, efficiency and success. In this new book, the authors present current research in the study of the theories and effects of global economic growth. Topics discussed in this compilation include cohesion, growth and development since the industrial revolution; worldwide rankings in economic growth; the relationship between economic growth and income inequality; economic growth and environment interactions and the optimal rate of inflation for long-run growth. Chapter 1 – Welfare, to which all economic action is directed, is defined as the satisfaction of wants derived from our dealings with scarce goods. It is a category of personal experience and not measurable in cardinal units. Therefore the authors have to make do with indicators that are measurable in cardinal units and that are arguably influencing welfare. The cardinal indicator and the ordinal welfare have, of course, to develop in the same direction. Economic growth is generally defined as increase of national income (NI) (or GDP) as a measure of production. However, according to the subject matter of economics economic growth can mean nothing other than increase in welfare. Welfare is dependent on more factors than solely production. It is also dependent on employment, income distribution, labour conditions, leisure time and the scarce possible uses of the non-human-made physical surroundings: the environmental functions. These objectives or ends are often conflicting. Therefore welfare can increase with decreasing production. The narrow minded, theoretically wrong definition of economic growth is especially threatening the current and future availability of environmental functions, the most fundamental scarce and consequently economic goods at the disposal of humanity. These fall outside the market and outside the measurement of NI. Correct information is decisive for the coming into being of the preferences of individuals and institutions and consequently for the decision making process. Therefore it is of the utmost importance to correct the current misleading information. In this contribution five relatively simple ways are discussed to correct the wrong information about economic growth. Environmental sustainability is defined. National income ex asymmetric entries and environmentally sustainable national income (eSNI) are discussed. It is shown why it is implausible that sustainability can be attained with growing production.

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Richard L. Bertrand

Chapter 2 – The chapter focuses on the relationship between cohesion and economic growth and development. Theoretically, I combine Joseph Schumpeter and Mancur Olson. Structural economic change is what makes a state grow in the long term. However, policies of structural change are politically risky as they create redistributive effects and are fought by vested interests. I suggest that cohesion stimulates growth by making it politically safer for decision-makers to pursue policies of structural change. Paired comparisons between Britain, France, Germany, the US and Japan during five core industries and five time periods since the Industrial Revolution provides a tentative qualitative test. Chapter 3 – Economic growth is a highly important area for economists, governments and society. However, how much have the authors learned? Which individuals have more investigations? What journals made more contributions to economic growth? Which theoretical model is the most empirically tested? How is the hall of fame of economic growth institutions integrated? The aim of this chapter is to build a bibliographic analysis and offer a viewing of the current state of investigation of economic growth. Empirical work is based on 30 leading journals in Economics and database covers eleven years (1992-2002). As a result, I offer rankings of journals, individuals, institutions and countries. It is observed that the theoretical analysis dominated the merely empirical one in the economic growth field, while the endogenous theory had more publications than the exogenous theory. Also, I estimate a Logit model to try to explain the authors’ decision on the model used to analyze economic growth and its determinants. I think these rankings and trends highlighted by economic growth are a helpful guide to graduate students, faculty members, and academics, and also to measure the relevance of this topic. Chapter 4 – The relationship between economic growth and income inequality has attracted a great deal of attention in recent years. The growth experience of several countries during the last decades with different behaviors in terms of economic inequalities has generated a growing strand of theoretical and empirical literature trying to explain these events. Although one could argue that economic growth and inequality influence each other, it is also possible that different public policies could influence the relationship between both macro aggregates. Fiscal policy has traditionally been considered an effective instrument trough which to influence aggregate demand, the distribution of income and wealth, and the economy’s capacity to produce goods and services. Therefore, a correct selection of the composition and combination of these policies has become of crucial importance for the purpose of achieving a broad-based stable path of economic growth across countries. Within this framework, this chapter reviews the evolution of economic literature that analyzes the relationship between growth and inequality. The authors perform a comparative analysis of different theoretical and empirical developments, with particular focus on the importance, in terms of size and composition, of different fiscal policies, explaining that relationship. Chapter 5 – It is a known fact that the total energy being consumed today is at a rate that has never been seen before in the human history. As the world becomes more developed, this has led to a significant increase in industrial activity which consequently results in a massive increase of pollutants being released to the atmosphere, water and soil, altering their composition, and causing harmful effects on the environment and human health. Although environmental problems are not an issue of interest to the world until the last century, some historical events have shown that the concerns on the effect of certain man-made pollutants

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Preface

ix

on human health have begun some centuries ago. Air pollutants mainly come from discharges of gases from industry, motor vehicles and domestic wood burning. The most widespread pollutant which is called primary pollutant is none other than the major greenhouse gas (GHG), carbon dioxide (CO2). Chapter 6 – Based on a sample of 1845 Portuguese SMEs for the period 1999-2006, and using the two-step estimation method in order to solve the problem of sample bias as a consequence of the matter of survival, the authors investigate if the economic conjuncture has significant effects on the investment of Portuguese SMEs. The empirical evidence obtained by using dynamic panel estimators, corresponding to the second step of the estimation method, lets us conclude that the economic conjuncture has a significant impact on investment by Portuguese SMEs: 1) higher reference interest rates for loans have a restricting effect on investment; and 2) economic growth, in terms of Gross National Product, contributes to increased investment. In addition, the empirical evidence obtained from probit regressions, corresponding to the first step of the estimation method, also allows us to conclude that: 1) higher reference interest rates for loans contribute to diminished probability of the survival of Portuguese SMEs; and 2) economic growth contributes to increased probability of the survival of Portuguese SMEs. In general the authors find the economic conjuncture has a significant impact on investment by Portuguese SMEs. Concerning companies’ intrinsic determinants: 1) Investment in the Previous Period; 2) Cash Flow; 3) Sales; 4) Debt; 5) Age; and 6) Growth Opportunities, the empirical evidence obtained allows the authors to conclude that: 1) investment in the previous period and cash flow are positive determinants of investment in Portuguese SMEs; 2) debt is a restrictive determinant of investment in Portuguese SMEs; and 3) sales, age and growth opportunities are neither positive nor restrictive factors of investment by Portuguese SMEs. Summarizing, the empirical evidence obtained in this study lets us conclude that investment by Portuguese SMEs is persistent, since the authors find a positive and statistically significant relationship between investment in the previous period and investment in the current period. In addition, the authors find that investment by Portuguese SMEs is dependent on the economic conjuncture (interest rates and GNP) and the financial situation of SMEs (cash flow and debt). Given the importance of SMEs in Portugal for stimulating economic growth and employment, the authors suggest considerable reinforcement of financial support from government bodies to SMEs that are limited financially. This financial support could be particularly relevant at times of economic recession. Chapter 7 – Positive economic growth is a major goal for all countries and long-run economic growth is an important focus, rather than observing what is happening in the shortrun because ups and downs in business cycles and other short-run fluctuations in economic growth are unable to give an accurate picture of the overall performance of an economy and may lead to biased observations. When countries experience growth at small rates, though this may not be regarded as a significant improvement, it is essential to understand that it is thanks to these small changes that accumulate over time to eventually having a very large impact on an economy’s performance, helping them to become more and more developed. No matter how small the changes, each improvement should be regarded as helping any economy in the right direction. Investment, economic resources of capital, land and labor and technological progress are argued to be vital essentials when it comes to the economic growth of a country because they are highly needed, which will be discussed extensively in this chapter. The authors will also look at five positive advantages that come along with economic

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growth for a country. First, income inequality, the gap between the rich and poor, decreases, secondly, economic growth has helped to significantly decrease the amount of global poverty that persists, third, economic growth is linked to the improvement in the quality of life of the citizens in an economy, fourth, economic growth leads to further specialization and exchange, and finally, economic growth improves the global position of a country. The authors will look at how the four Asian tigers and five new Euro countries, the nine countries to be analyzed with their respective data in this chapter, have moved from being considered developing economies to now being included in the category of advanced economies, which is regarded as the ultimate goal being achieved for any country that started off as a less developed economy. These countries once suffered from very little economic activity and industrialization, high population growth was a major obstacle to hurdle over, and low levels of standard of living, but went on to becoming proof of the convergence hypothesis, which states that the GDP growth rates of less developed countries will rise faster than richer countries, tightening the gap between the two categories of countries due to the catching-up process, leading to their convergence. Merging and the idea of catching-up are both to be expected because the poorer countries can copy and incorporate the methods and techniques used by the rich countries and also because when you are already an industrialized country, you cannot grow too rapidly as was once the case before, since diminishing returns can be ever so present. Initially, industrialized countries may have grown at rapid rates but eventually, that rate slows down due to diminishing returns. In this chapter, by using data from these nine countries, it is shown that small rates of growth over time contributed to helping them transition from being developing countries to advanced countries, proving that the convergence hypothesis is valid. Chapter 8 – Economic growth has negative impacts on environment at the first phases of development. After passing a threshold, it affects the environmental quality positively Economic development strategies indicate differences in various regions of the world because countries have different economic backgrounds and economic structure. Scale, production composition and technological effects have given forms the environmental impacts of economic growth. The negative environmental effects of the economic growth start with increasing of population, and then turn to positive by transition to knowledgeproducing industries through high technology. Developed countries have some advantages because they have finance for infrastructure investments. Yet, it is very difficult to implement environmental policies due to weak economic structure. The most important way to prevent global environmental pollution is to act together. If developed countries use technology transfer for the benefits of themselves and developing countries by giving up excessive consumer roles, economic growth creates much more positive impacts on environmental quality and natural resources than expected. Chapter 9 – Although the relationship between financial development and growth is almost obvious, the effect of inflation on the finance-growth nexus is still a subject of debate. In particular, what is the optimal rate of inflation for long-run growth? To answer this question, I analyze the relation between finance, inflation and growth by using a semiparametric graphical approach. I find that the optimal level of inflation that leads to higher long-run growth rates is around 10 percent. I also show that the positive effects of low inflation on growth are more apparent when there are high levels of financial depth. Finally, when both the levels of inflation and financial depth are low, the growth rate of the economy is volatile.

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Chapter 10 – After COP15 in Copenhagen 2009, national interests dominate negotiations for Post-Kyoto policies to mitigate global climate change. While enforceability on national levels clearly betters the prospects for global climate policy, there is the concern that national emission targets are set not ambitiously enough to prevent catastrophic climate change. This chapter investigates whether and why these concerns might be warranted within an overlapping generations’ model of two internationally interdependent economies with producer greenhouse gas emissions and national emission permits systems. The authors find that when the natural growth rate of the world economy is less than the real interest rate national permits reduction diminishes the welfare in both countries. Moreover, net foreign debtor countries (USA) have minor incentives than net foreign creditor areas (EU) to implement a more stringent climate policy. In general, it remains open whether dynamic inefficiency betters the prospects for national climate policy. Chapter 11 – Responding to the productivity slowdown in the mid-1970s, Western countries invested trillions of dollars in R&D, the idea being that R&D is a key determinant ofgrowth. In 2007, a total of $1.145 trillion was invested in R&D worldwide [16]. Unfortunately, thirty-five years after the fact, growth rates have not returned to their postWWII levels, which raises the obvious question, does R&D actually increase growth? This paper examines the science behind the policy. More precisely, it examines thetheory of R&Dbased growth and the evidence. It comes to the conclusion that thescience that underlies R&D-based growth is surprisingly weak. For example, there is little theory behind the R&Dgrowth nexus. Similarly, there is little empirical evidence that R&D increases growth. Moreover, when examined from the point of view of the underlying physics, R&D-growth runs contrary to the very laws that govern material processes, a result that is consistent with t he reported failure of R&D to restore growth levels. Chapter 12 – Over the past decade Emerging and Transition Economies (ETE) have been experiencing economic growth and a consistent institutional change. The aim of this paper is twofold. First of all, a cross-country analysis of a group of ETE in the period 1998-2008 will be carried out in order to understand what determines economic growth among these countries. Secondly, a comparative analysis will be carried out. The countries will be classified according to their socio-economic models, and I will investigate whether institutions may have an impact on growth. The central hypothesis is that explaining economic growth is a complex issue which needs positive interaction of several socioeconomic and institutional factors. My analysis suggests that countries can grow with their own “style of capitalism”, and the determinant of economic growth is the ability of each country to associate appropriate governance and institutions with education level, export activity and non-income dimensions of human development.

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Chapter 1

FIVE WAYS TO COMBAT MISLEADING INFORMATION ABOUT ECONOMIC GROWTH Roefie Hueting The Hague, The Netherlands

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ABSTRACT Welfare, to which all economic action is directed, is defined as the satisfaction of wants derived from our dealings with scarce goods. It is a category of personal experience and not measurable in cardinal units. Therefore we have to make do with indicators that are measurable in cardinal units and that are arguably influencing welfare. The cardinal indicator and the ordinal welfare have, of course, to develop in the same direction. Economic growth is generally defined as increase of national income (NI) (or GDP) as a measure of production. However, according to the subject matter of economics economic growth can mean nothing other than increase in welfare. Welfare is dependent on more factors than solely production. It is also dependent on employment, income distribution, labour conditions, leisure time and the scarce possible uses of the nonhuman-made physical surroundings: the environmental functions. These objectives or ends are often conflicting. Therefore welfare can increase with decreasing production. The narrow minded, theoretically wrong definition of economic growth is especially threatening the current and future availability of environmental functions, the most fundamental scarce and consequently economic goods at the disposal of humanity. These fall outside the market and outside the measurement of NI. Correct information is decisive for the coming into being of the preferences of individuals and institutions and consequently for the decision making process. Therefore it is of the utmost importance to correct the current misleading information. In this contribution five relatively simple ways are discussed to correct the wrong information about economic growth. Environmental sustainability is defined. National income ex asymmetric entries and environmentally sustainable national income (eSNI) are discussed. It is shown why it is implausible that sustainability can be attained with growing production.

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1. ECONOMIC GROWTH ACCORDING TO THE SUBJECT MATTER OF ECONOMICS The view now accepted by the mainstream of economic thought is that the phenomena arising from scarcity together form a logical entity, irrespective of the end for which the scarce means are employed. This is referred to as the formal or indifferent concept of welfare, a term probably introduced by Rosenstein-Rodan (1927). What he wrote can be summarized as follows. The subjective state of welfare or the total economic utility that people endeavour to achieve in their economic activities is a quantity determined purely formally. It encompasses all that has been striven after, to the extent that scarce goods have had to be used for achievement thereof, irrespective of (indifferent to) whether such pursuit springs from egoistic or altruistic, from ethical or unethical motives, from ‘real’ or ‘imaginary’ wants. It was Robbins ([1932] 1952) and Hennipman (1940, 1943, 1962, 1995), among others, who elaborated the formal concept of welfare and formulated its consequences for economic theory. For these authors, the subject matter of economics is demarcated by the criterion of scarcity. The subject matter of economics is defined as the problem of choice with regard to the use of scarce, alternatively applicable means for the satisfaction of classifiable wants. According to Hennipman it is therefore logical and consistent to interpret welfare, the end and result of economic activity, as the overall satisfaction of wants pursued or obtained by means of economic goods or, more precisely as the balance of the positive utility over the negative utility caused by external effects or productive efforts. In Hennipman’s view economic activity can serve all kinds of ends. The ends themselves are meta-economic and are not for economists to judge. They cannot be derived from economic theory, nor are they amenable to it, they must be taken as given, as data. In the same vein, Robbins writes: ‘There are no economic ends as such; there are only economic problems involved in the achievement of ends’. Maximizing or even just increasing the social product (NI) should therefore, in Hennipman’s view, no longer be considered a necessary end that can lay claim to logical priority. All those objectives aspired to by economic subjects that conflict with that end belong logically and in their entirety to the domain of economic policy. If preference is given to those objectives, he writes, this does not mean a sacrifice of welfare on the strength of ‘non economic’ considerations, as it is still frequently represented, since economic goods are then being utilized in accordance with the wants of the subjects and thus to the benefit of their welfare. Proceeding from the work of these authors, Hueting (l974/1980) posits the following. All economic activity is aimed at the satisfaction of wants, and consequently the term economic growth can mean nothing other than increase in welfare defined as the satisfaction of wants derived from our dealings with scarce goods. Welfare is not a quantity that can be measured directly ‘from outside’; it is a category of individual experience. It is for this reason that the statistician focuses in practice on charting trends in factors that can be measured and that can plausibly be argued to have an influence on welfare. These factors will not generally be strictly proportional to welfare but must at any rate satisfy the condition that they tend consistently in the same direction as the welfare they are indicating, positive or negative. The following welfare-influencing factors can be distinguished:

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Five Ways to Combat Misleading Information about Economic Growth 1. 2. 3. 4. 5. 6. 7.

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the package of goods and services produced; scarce environmental functions; time, that is leisure time; the distribution of scarce goods, that is income distribution; the conditions under which scarce goods are acquired, that is labour conditions; employment, or involuntary unemployment; and future security, to the extent that this depends on our dealings with scarce goods, and specifically the vital functions of the environment.

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These factors are often in conflict with one another, although this is not always the case. For scarce goods it holds by definition, however, that more of one is less of another, for a good is scarce when something else has to be sacrificed in order to obtain it (sacrificed alternative, opportunity cost). The days when environmental functions were free goods are gone. All other things remaining equal (including technological state of the art), more production therefore means less environment and vice versa. When, in the margin, for whatever motive, preference is given to the environment over production and a government proceeds to impose controls on production processes and consumption habits that lead to a smaller volume of goods and services produced, there will be an increase in the overall satisfaction of wants obtained by means of scarce goods. A decrease in production will then lead to greater welfare. It is therefore misleading to identify growth of national income with an increase in welfare, economic growth and economic success, as is still common practice even today. This terminology is fundamentally erroneous in its implications, to the detriment of the environment, and it should therefore be outlawed, in much the same way as discriminatory language against women.

2. THE CONCEPT OF ENVIRONMENTAL SUSTAINABILITY The concept of environmental sustainability denotes a state of dynamic equilibrium between production and natural resources. J.S. Mill (1876) wrote that he sincerely hoped that people would be content to be stationary, for the sake of posterity, long before necessity compels them to it. This pronouncement can be interpreted as being based on considerations of intergenerational equity. In the context of sustainable national income (see Section 7) this means that it is investigated under which conditions the possibilities to use our non-humanmade physical surroundings can be passed on to future generations undamaged. In the twentieth century the notion of sustainability has been extended to encompass other aspects of the environmental issue, such as the relation with the living world (nature) and pollution; see IUCN (1980)]. In the process, the principle of preferences for intergenerational equity has always remained a core element of the concept. This implied a state of dynamic equilibrium with the available natural resources and with the living world, and abatement of pollution, to the extent of its significance for future generations. Uncompensated exportation of anthropogenic environmental risks to future generations was rejected as inadmissible. To establish an appropriate maximum environmental burden to meet these preferences was seen as a task for natural scientists. In other words, sustainability was taken to mean that the environmental

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capital - defined as the possible uses, or functions, of the environment and natural resources provided by nature and capable of being scientifically established, should remain intact; see Kapp (1950), Daly (1973), Hueting (1974/1980), and Goodland (1995). This implies a dynamic equilibrium, in which (ceteris paribus) the functions of the nonhuman-made physical surroundings remain available. Measures taken to allow for the permanent availability of functions should be derived from scientifically based presuppositions. Whether these measures are sufficient can of course only be evaluated after the event, again using natural science. So in this view environmental sustainability is an objective concept to the extent that natural science is objective. Whether or not individuals and institutions want to attain environmental sustainability depends on their preferences which are evidently subjective.1 The equilibrium is dynamic because both geological processes and human activities are continuously changing the state of our planet. In the report Our Common Future (1987), also known as the Brundtland report, the concept of sustainability was clearly linked to the issue of intergenerational equity. In Our Common Future this was phrased as follows: 'Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs'. Many countries have by now subscribed to sustainable development as defined in the Brundtland report. However, the report is according to Hueting (1990) a matter of conflicting goals, because it is pleading for both sustainability and production growth; see Section 8.

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3. THE CONCEPT OF COMPETING ENVIRONMENTAL FUNCTIONS In the theoretical basis for the calculation of environmentally sustainable national income (eSNI, see Section 7), the environment is defined as the non-human-made physical surrounding, or elements thereof, on which humanity is entirely dependent in all its doings, whether they be producing, consuming, breathing or recreating. These physical surroundings encompass water, air, soil, natural resources, including energy resources, plant and animal species and the life support systems (including ecosystems) of our planet. It is true that our observable surroundings are largely human-built. However, houses, roads, machines and farm crops are the result of two complementary factors: labour, that is technology, and elements of the physical surroundings as here intended. Our crops, for example, have been bred or manipulated from genetic material taken from natural ecosystems; this material was not created by human beings and sooner or later we shall most probably have to fall back on it. We therefore continue to be dependent on the functions of the physical surroundings as here intended, including the functions of ‘gene pool’ (or: ‘gene reserve’), ‘habitat for biological species’, ‘water as raw material for drinking water’, ‘air for the physiological functioning of human beings, animals and plants’, ‘soil for cultivating crops’ and the many functions of nonrenewable natural resources. Producing is defined, in accordance with standard economic theory, as the adding of value. This value is added to the physical elements of our environment. In this process one good is transformed into another in order to satisfy wants. The values are added by labour, that is hands and brains, with the brains guiding the hands, so that we are concerned 1

Because they reflect the feelings of subjects

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ultimately with two factors: labour (technology) and environment. Thus, both consumption goods and capital goods embody a combination of the physical elements of the environment, on the one hand, and labour, accumulated or otherwise, on the other. In this view, labour and environment are the two factors with which humanity has to make do in securing a desired level of consumption. If environmental functions are lost we are left literally empty-handed. Environment and labour are thus complementary. Annual production as measured in the standard national income is therefore accompanied by a physical flow of goods. Put differently, regardless of whether the products are actually physical, in production and consumption there will always be an interaction with the physical environment and consequently always a physical burden on that environment. This environmental pressure is, obviously, a form of environmental use. In our physical surroundings (the environment) a great number of possible uses can be distinguished, which are essential for production, consumption, breathing, et cetera, and thus for human existence. These are called environmental functions, or in short: functions (see Hueting 1969, 1974/1980). These functions have come into being largely via processes proceeding at a geological or evolutionary pace. For the life support systems it is unfeasible ever completely to be replaced by technology, as is shown by Goodland (1995). It is thanks to these life support systems, which are under threat of disruption, that indispensable (or vital) environmental functions remain available. Life support systems are understood to mean the processes that maintain the conditions necessary for life on earth. This comes down to maintaining equilibria within narrow margins. The processes may be of a biological or physico-chemical nature, or a combination thereof. Examples of biological processes include the carbon and nutrient cycles, involving the extraction of such substances as carbon dioxide, water and minerals from the abiotic environment during creation of biomass, and the return of these substances to the abiotic environment during decomposition of the biomass. Examples of physico-chemical processes include the water cycle and regulation of the thickness of the stratospheric ozone layer. These examples show that there is interaction between the processes, whereby equilibrium may be disturbed. The water cycle, for example, may be disturbed by large-scale deforestation. Climate change is a disturbance of the carbon cycle. As long as the use of a function does not hamper the use of an other or the same function, so as long as environmental functions are not scarce, an insufficiency of labour, that is intellect or technology, is the sole factor limiting production growth, as measured in standard NI. As soon as one use of a function is at the expense of another or the same function (by excessive use), though, or threatens to be so in the future, a second limiting factor is introduced. As an illustration, once certain water pollutant thresholds have been exceeded, use of the function ‘dumping ground for waste’ may come to compete with the function ‘drinking water’. An example of excessive use of one and the same function ‘water to accommodate the habitat for (one or more) fish species or ecosystems’, leading to its loss, is overfishing resulting in decreased availability of the function; then the catch of some species decreases or species become extinct; many species and ecosystems of which they were a part, in other words many functions, have indeed already been lost. The function ‘soil for cultivating crops’ may be damaged by unsustainable use of the function ‘supplier of timber’ of a forest, leading to loss of its function ‘regulator of the water flow’ and subsequent erosion; it may also be in conflict with itself, when unsustainable farming methods lead to erosion and salinization of the soil. The many functions of natural resources that threaten to get lost as a

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result of exhaustion of the resource are in competition with themselves; see Appendix. This competition of functions leads to partial or complete loss of function. Competing functions are by definition economic goods. If, at a given level of technology, use of function A is at the expense of use of function B, greater availability of function B will lead, one way or another, to reduced availability of function A; conversely, more of A will lead to less of B. An alternative will always have to be sacrificed (opportunity costs) and consequently both A and B are scarce - and consequently economic - goods. Here, ‘use’ obviously also includes passive use such as designation of an area as a nature reserve, which thereby excludes other uses, following recognition of the right of other species to exist; the sacrificed use, or sacrificed alternative, constitutes the opportunity cost. Competing environmental functions, defined as economic goods, form the theoretical backbone of the environmentally sustainable national income (eSNI) and its estimation. See Section 7. In this way the environment, and environmental losses, acquires a central place in economic theory, in contrast to an approach whereby these losses are viewed as external effects. The subject matter of economic theory can then be formulated as follows: the problem of choice with regard to the use of the scarce, alternatively applicable, dead and living matter of our physical surroundings for the satisfaction of classifiable wants. Or, very briefly: arranging the dead and living matter of the environment according to our preferences. This is argued in Hueting (1974/1980) and, more extensively, in Hueting (1992, 1995). One of the arguments can be stated succinctly as follows. In the literature external effects are defined, briefly, as unintended side-effects outside the market affecting third persons, nonmarket parties; for a more extensive definition, see Hennipman (1968). However, when a road is built through a nature reserve, or a sewer to a river, estuary or sea, and all citizens make equal use of the road or sewer, the same citizens nonetheless lose important functions, in part or in toto, and such decisions are often made intentionally, in full awareness of the consequences. The availability of environmental functions is the degree to which those functions can be used for a given end. This depends on two factors: one objective and measurable, the other subjective and not directly measurable. On the one hand, the availability of functions depends on the quality, quantity and spatial extent of environmental elements such as water and soil, which are largely amenable to measurement in physical units, and on the likewise measurable functioning of systems, including, specifically, ecosystems and life support systems, or in other words on the state of the environment. Through (over-) use of a certain function the state of the environment may be altered, leading to reduced availability of other functions or of the same function: competition between functions. Whether this happens, and to what extent, depends on the preferences of the economic subjects. The availability of functions is thus also dependent, on the other hand, on subjective preferences, which are not directly measurable. In Hueting (1974/1980) this is expressed in a system of coordinates with on the horizontal axis the availability of functions expressed in terms of a physical variables (units, parameters) and on the vertical axis the preferences and costs associated with restoration and maintenance of functions (see Section 4). In this way the relationship is established between subjectivist economic theory and the measurable physical environment, or ecology. Three categories of competition between functions are distinguished: spatial, quantitative and qualitative. Spatial competition occurs when the amount of space is inadequate to satisfy existing wants, or threatens to be so in the future. Worldwide severe competition exists between use of

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space for production of food, production of bio fuels, natural ecosystems and the survival of species, road building, building of houses, traffic and possibilities for children to play and discover their surroundings. Especially the function ‘space for the existence of natural ecosystems’ is threatened. Spatial competition is probably the main cause of species extinction, through loss and fragmentation of habitats. Everything points to this process continuing in accelerated tempo unless drastic measures are taken. Conservation of natural species is a key criterion for estimating the Sustainable National Income according to Hueting (see Section 7). In the case of quantitative competition, it is the amount of matter that is deficient or threatens to be so in the future. We are here concerned with natural resources such as oil, copper and groundwater, which are exhaustible and non-renewable on a human time scale or which cannot increase in quantity, such as water. In many regions of the world the quantity of ground and surface water is insufficient to meet the needs for both raining on agricultural crops and industrial processes and drinking water and the survival of species. With qualitative competition, it is always one and the same function, the function ‘waste dumping medium’, or much more accurately: ‘addition or withdrawal of species and matter’ that is in conflict with other possible uses such as ‘drinking water’, ‘physiological functioning of humans, plants and animals (breathing)’ and ‘habitat for species’. The introduction of agents into the environment (water, soil and air) or their withdrawal from it, in the course of a given activity, alters the quality of these environmental media, and as a result other uses of them may be disturbed or rendered impossible. Here, an ‘agent’ is defined as an abiotic or biotic element or amount of energy (in whatever form) introduced into or withdrawn from the environment that can cause loss of function. Thus, agents may be chemical substances, plants, animals, heat, ionizing radiation and so on. Qualitative competition includes pollution, disturbance of ecosystem by exotics and phenomena such as climate change. When using the concept of function, the only thing that matters in the context of environmental sustainability is that vital functions remain available. As for renewable resources, functions remain available as long as their regenerative capacity remains intact. Regeneration in relation to current use of 'non-renewable' resources such as crude oil and copper that are formed by slow geological processes is close to zero. Regeneration then takes the form of developing substitutes. The possibilities for this are hopeful; see Brown et al. (1998) and Reijnders (1996). So, economically speaking, there seems to be no essential difference between the two. Competition between functions is a manifestation of the finite nature of the environment, and to trace this competition in appropriate matrices is to expose the underlying conflicts. This has been done by Hueting (l974/1980). The conflict proves to lie almost entirely in the use of environmental functions for production and consumption, and growth thereof, in the here and now, at the expense of other desired uses and of future availability of environmental functions, including those functions necessary for production and consumption. In other words, the conflict boils down essentially to a question of sustainable versus unsustainable use of environmental functions. An elaboration for the use of the functions of a rainforest has been published by Hueting (1991). For a proper understanding of the economic aspects of the environment it is instructive to compare the concepts outlined above with the concepts traditionally used in economic theory. This is no more than a metaphorical exercise, however, as the two categories of concepts are ultimately incompatible. Thus, some functions of the physical surroundings can be seen as

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consumption goods. Examples include: ‘air for physiological functioning (breathing)’, ‘water as raw material for drinking water’ and ‘swimming water’. Other functions can be viewed as production means, such as ‘water for irrigating crops’ and ‘gene pool for breeding and modifying crops and livestock’. However, ‘normal’ consumption goods and production means have to be reproduced over and over again, while environmental functions remain, in principle, freely available. Only if they come to compete, with each other or with themselves, for example if certain thresholds are exceeded, does their continued availability require a sacrifice. Finally, what was termed ‘the non-manmade physical surroundings’ in Hueting (1974/1980) is now often referred to as ‘natural capital’. This, too, is instructive, but once again there is an anomaly: ‘normal’ capital goods wear out, but natural (or environmental) capital does not, in principle. These differences in terminology make no difference when it comes to the valuation method elaborated in Section 4. After all, capital goods derive their value from the value of the consumption goods they are used to produce, and thus ultimately from preferences for these goods. Similarly, environmental capital, or the physical surroundings, derives its value from the value of its possible uses, the environmental functions, and thus from preferences for these functions. The elimination measures are of course always aimed at conserving water, air, soil, ecosystems, and so on, and thus at natural capital as the vehicle of the functions.

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4. VALUATION OF ENVIRONMENTAL FUNCTIONS: A PRACTICAL SOLUTION FOR AN UNSOLVABLE PROBLEM The emergence of competition between functions marks a juncture at which functions start to fall short of meeting existing wants. Competing functions are by definition scarce and consequently economic goods, indeed the most fundamental economic goods humanity disposes of. In a situation of severe competition between functions, in which we live today, labour is not only reducing scarcity, and thus causing a positive effect on our satisfaction of wants, or welfare; but it is also increasing scarcity, thus causing a negative effect on welfare. The same holds for consumption. So today production not only adds value (viz. goods for consumption) but also nullifies value (by damaging environmental functions). The availability of functions, or, in terms of the System of National Accounts (SNA), their volume, decreases from ‘infinite’ (abundant with respect to existing wants) to finite, that is falling short with respect to existing wants. As a result, the shadow price of environmental functions rises, and with it their value, defined as price times quantity, from zero to an everhigher positive value. This rise in value reflects a rise in costs. To determine the extent of the loss of function, we must know the value of the function. Since environmental functions are collective goods that are not traded on the market, supply and demand curves have to be constructed. Without data on both preferences (demand) and opportunity costs (supply), determination of value is impossible. For, if a good is not wanted or if it’s acquisition requires no sacrifice, the economic value of that good equals zero and no problem of choice arises. It then is obviously not scarce, has by definition no economic aspect and falls consequently outside economics.

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The estimated costs of measures necessary to restore functions, that rise progressively per unit of function restored, can be seen as a supply curve, because it supplies the function. We call this the cost-effectiveness curve or the elimination cost curve, because it refers to measures that eliminate the pressure on the environment. Except in the case of irreparable damage, the elimination costs can always be estimated, so this curve can always be constructed. The measures include technical measures, direct shifts to environmentally benign production and consumption, development of alternatives for depletable resources such as oil and cupper, and family planning. See Appendix for the necessary pace of substitution of nonrenewables. Preferences for environmental functions (demand), on the contrary, can only partially be determined, since the possibilities for preferences for the current and future use of environmental functions to manifest themselves in market behavior are very limited (Hueting, 1974/1980). Therefore efforts have been made to trace these preferences by asking people how much they would be prepared to pay to wholly or partially restore lost environmental functions and to conserve them. Much research is being done on willingness to pay or to accept (contingent valuation). However, this method does not always provide reliable estimates for many reasons. 1. Information on the significance of environmental functions is deficient in many cases. This is especially so for the functions that determine the future quality of the environment. With respect to the functions of the life support systems there is often a question of the risk that interrupting complicated processes, for instance ecosystems and climate, may lead to serious overshoots and collapse, versus the chance that technologies not yet invented may cope with those risks. Many people may not be able to weigh these risks and chances, and thus to answer how much they are prepared to pay for avoiding them. According to the biological literature the possibility that overshoots and collapse may occur if the growth pattern of production (and population) is not changed constitutes the most important part of the environmental problem (see, for example, Odum 1971). If individuals are not aware of the importance of an environmental function, the survey method is pointless. 2. There is a considerable difference between saying that one is willing to spend money on something and actually paying for it. 3. The questioning method in fact tries to approach the value of a collective good as if it were a private marketable good (by trying to find some points on the demand curve). In a market the bidder knows fairly well what quality and quantity can be acquired by different bids. In a collective situation, however, this is not possible, because it is not known how much other people are going to bid. Without a considerable amount of additional research it is also not known how much money is required to attain different quality standards for the environmental functions. 4. In order not to make the questioning unjustifiably vague, some research on environmental accounting has to be done beforehand. For clear air, clean water, and so forth are not homogeneous goods from an economic point of view, as water and air have quite a few different economic functions. If the persons being questioned are to have a clear picture of the issues, they must be given information on the significance of the different functions, the consequences of their loss, and the measures and costs involved in their restoration. All together this constitutes a huge

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Roefie Hueting

5.

6.

7.

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8.

9. 10.

11. 12.

13.

amount of information, which would not be easy to survey. Although the willingness-to-pay method might be justified for one or two factors affecting the immediate living conditions of people asked, it is not a sound base for correcting national income. Much of the damage resulting from the loss of functions will take place in the future. No financial damage or compensation expenditures, as revealed preferences, can therefore arise in the present. Choosing a discount rate boils down to making an assumption about preferences and therefore does not resolve the problem; see Hueting (1991). Another example is that we cannot base ourselves on observed individual behaviour, given the working of the prisoners’ dilemma. People may be interested in the effects of their bids, together with the (unknown) bids of others, on, for instance employment levels and consumption patterns. For answering legitimate questions about this, scenario studies have to be elaborated, and the results have to be presented to the persons questioned. This hardly seems feasible. Again, what might be justified on a micro scale is most probably not justified on a macro scale. Asking people how much they are prepared to pay, suggests that conserving the environment always requires extra provisions that must be paid for. In quite a few cases, however, conservation is a matter of refraining from doing things rather than of doing them, and this saves rather than costs money. Thus not building a road through a mountainous area that is vulnerable to erosion is cheaper than building it, cycling is cheaper than driving, wearing a sweater and using an extra blanket is cheaper than raising the temperature, and confining the consumption of lettuce to the summer season is cheaper than eating it throughout the year. People who realize this may modify their answers because of such considerations. Some people will probably be convinced that it does not matter what they bid, because their bid will not influence environmental policy at all, and this conviction will influence their bid. Some people may think they have a “right” to a healthy and safe environment and will probably react accordingly by not making a bid at all. People will probably have their doubts about the participation of others (the Prisoner’s Dilemma from game theory) or prefer to wait and see (the Free Rider Principle from the theory of collective goods). Thus in developing countries, where the tropical rain forests are, the view is widespread, for a number of reasons, that people from the rich countries should pay for their conservation. In cases where the whole community is involved, the willingness-to–accept approach is pointless. For who is paying whom to accept the loss? The environment is an important collective good. But it is not the only one. Dikes, public administration and the army are too, while police and education have clear collective properties. To be sure of not exceeding budget restrictions, people also have to be questioned about how much they are prepared to pay for the other collective goods of the society. This hardly seems feasible. Again, what might be justified for one or two separate environmental agents on a micro scale may be impossible on a macro scale. The willingness-to-pay method also measures the consumer’s surplus. In national income the total value of the goods is found by multiplying the quantity of each good

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by its respective price and then adding together the resulting amounts. Using this procedure, the consumer’s surplus is not expressed in the level of national income. Thus, a doctor who saves a patient’s life creates a value that, whatever one may think about its exact size, is certainly higher than the value added recorded in national income. The intra-marginal utility of goods, which is ignored in national income, will approach an infinite value, because it includes the utility of the first unit of food, drink, and so forth. For this reason the results of willingness-to-pay research are not suitable to be used in conjunction with the figures of national income. An additional objection to incorporating the consumer’s surplus in the willingness-to-pay approach is that the results reflect the income distribution more directly than do the prices of market commodities; the differences between rich and poor in the weights of the “votes” become greater when the consumer’s surplus is included. The occurrence of differences in weights of “votes” is often defended by the argument that the contribution to the national package of goods and services by the rich is greater than by the poor: their incomes are higher because of the greater relative scarcity of their abilities. This argument is not valid with regard to the environment, because it is not produced by humanity. Because of the limitations mentioned above, the willingness-to-pay method does not present a firm enough basis for correcting national income for losses of scarce environmental functions. A correction based on this method may lead to inaccurate estimates of environmental decline. Consequently, it is not possible to construct a complete demand curve. Expenditure on compensation for loss of function and on restoration of physical damage resulting from loss of function, however, constitute revealed preferences for the availability of functions, so that some impression of these preferences can be obtained. One example is the additional measures for the production of drinking water as a result of the loss of the function ‘drinking water’ because of pollution (overuse of the function ‘water as dumping ground for waste’). Another example is the restoration of damage caused by flooding due to excessively cutting forests etc. (overuse of the function ‘provider of wood’ etc.) that consequently are losing their function ‘regulation of the water flow’. Because individual preferences can be measured only partially, shadow prices for environmental functions, which are determined by the intersection of the first derivatives of the constructed curves for demand and supply (see Figure 1), cannot be determined. Consequently, these shadow prices – and the value of environmental functions - remain unknown. This means that the correct prices for the human-made goods that are produced and consumed at the expense of environmental functions, and on which the NI is based, remain equally unknowable. However, to provide the necessary information, assumptions can be made about the relative preferences for environmental functions and produced goods. One of the possible assumptions is that the economic agents, individuals and institutions, have a dominant preference for an environmentally sustainable development. This assumption is legitimate since governments and institutions all over the world have stated support for environmental sustainability. Furthermore Hueting (1987), referring to the ecological risks by production growth, postulates: “Man derives part of the meaning of existence from the company of others. These others include in any case his children and grandchildren. The

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prospect of a safer future is therefore a normal human need, and dimming of this prospect has a negative effect on welfare.” The environmentally sustainable income (eSNI), described in Section 7, is based on the assumption of preferences for environmental sustainability. Another possible assumption is that the economy is currently on an optimal path that is described by the changes in the standard NI. So both the eSNI and the standard NI are fictitious in the context of what is at issue in economic theory and statistics, namely to provide indicators of the effect of our actions on our welfare. This holds true apart from the fact that measuring NI has smaller uncertainty margins than measuring eSNI. When assuming dominant preferences for sustainability, the unknown demand curves must be replaced by physical standards for sustainable use of the physical environment. The standards are scientifically determined and in this sense objective. They must, of course, be distinguished clearly from the subjective preferences for whether or not they should be attained. Examples are: the man-made rate of extinction of species should not exceed the rate at which new species come into being, for safeguarding the many functions of ecosystems; the emission of greenhouse gases has to be reduced by 70 to 80 % in order to let life support systems restore the climate; the rate of erosion of topsoil may not exceed the rate of formation of such soil due to weathering, for safeguarding the function: ‘soil for raising crops’. See also Appendix. sum of money per year per addition al unit of function

d

d'

s

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F

E

B

D

availability of standard for function in sustainable the year of use investigation

availability of env. function (in physical units)

Figure 1. Taken from Hueting (1974/1980). Translation of costs in physical units into costs in monetary units: s=supply curve or marginal elimination cost curve; d=incomplete demand curve or marginal benefit curve based on individual preferences revealed from expenditures on compensation of functions, and so on; d' = 'demand curve' based on assumed preferences for sustainability; BD = distance that must be bridged in order to arrive at sustainable use of environmental functions; area BEFD=total costs of the loss functions, expressed in money; the arrows indicate the way in which the loss of environmental functions recorded in physical units is translated into monetary units. The availability of the function (B) does not need to coincide with the level following from intersection point (E).

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From an economic perspective, sustainability standards approximate demand curves that are vertical in the relevant area of a diagram that has the availability of functions measured in physical units on the x-axis and the demand for functions and their opportunity costs on the yaxis. The shadow price for environmental functions – and their value – based upon the assumed preferences for sustainability then follows from the intersection of the vertical line and the marginal cost-effectiveness curve. In this manner the distance to sustainability, denoted in physical units on the x-axis, is translated into monetary units. See Figure 1, taken from Hueting (1974/1980), which shows the relationship between economy and ecology. Of course, bridging the gap requires a transition period. The greater the distance between the present economy and the desired more environmentally benign economy that has to be bridged, the higher the costs of the required set of elimination measures are, as Figure 1 shows. These measures, consisting of technical means to reduce the use of the environment, direct shifts to less environment-damaging products and, if necessary, birth control, are interacting with deliveries of all products, including services. So, when bringing these measures into practice, the interdependences between the producers, consumers and the environment make all commodity flows and prices change. For a correct approximation, such calculations have to be done by a general equilibrium model, which also generates the shadow prices for produced goods in a sustainable economy. The level of sustainable national income (see Section 7) follows from such a model as well.

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5. FIVE WAYS TO COMBAT MISLEADING INFORMATION ABOUT ECONOMIC GROWTH Based on the information described above, five ways can be distinguished to improve the current information about economic growth.

6. FIRST WAY: PUBLISH A SERIES NI’S EX ASYMMETRIC ENTRIES (ASYMS) ALONGSIDE THE STANDARD NI’S Producing is defined, in accordance with standard economic theory, as the adding of value. National income (NI) equals the sum of the values added. So NI measures - the fluctuations in the level of - production. It does so according to its definition and according to the intention of the founders of its concept to get an indicator for one of the factors influencing welfare - and a tool for quite a few other purposes. See Tinbergen and Hueting (1991/1992). (Nobelist Jan Tinbergen was one of the founders of the concept of NI and its quantification). As mentioned just now, producing is adding value. This value is added to the non-humanmade physical surroundings. Consequently, environmental functions (the most fundamental economic goods at human’s disposal) remain outside the measurement of standard NI. This is logical and easy to understand, because water, air, soil, plant and animal species and the life support systems of our planet are not produced by humans. So losses of functions, caused by

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production and consumption, are correctly not entered as costs. However, expenditures on measures for their restoration and compensation are entered as value added. This is asymmetric. These expenditures should be entered as intermediate, as they are costs. This asymmetry is sometimes defended by the remark that these expenditures contribute to welfare and generate income; see De Haan (2004) and Heertje (2006). This is of course self-evident, counting from the moment at which the loss of environmental functions and the consequential adverse effects have already occurred. However, the production factors, used for the measures, do not add any value counting from the moment that the functions were still available. With respect to that situation there is consequently no increase in (1) the quantity of final goods produced and (2) the availability of environmental functions. Opposite to the income earned with carrying into effect the measures there stays consequently no increase in production volume (= final goods produced) with respect to that situation. Income, to be spend on the market or to be transferred to public authorities, is a claim on goods and services produced by industries and public authorities, it is not a claim on the functions of the non-humanmade physical surroundings. By entering these expenditures as final instead of intermediate, the growth of production is overestimated, thus obscuring what is happening with both environment and production. The information about the development of production is improved by estimating an NI ex asyms alongside the NI. An NI ex asyms, apart from being useful in itself, is also important for the environmentally sustainable national income (eSNI) dealt with in Section 7. The eSNI is above all intended for gauging the distance between the achieved and the sustainable level of production in the course of time. Because expenditure on a number of elimination measures and a great deal of expenditure on repairing damage and on compensation measures are booked as contributions to the NI, NI is not a good yardstick of the (development of the) level of production. During a transition to the sustainable path the distance between NI and eSNI may increase as a result, while the gap between the sustainable and the present level of production (the NI ex asyms), which is what it is all about, decreases. Hence the gap that has to be bridged to achieve a sustainable level of production (the eSNI) is (NI ex asyms – eSNI) and not (NI – eSNI). See De Boer and Hueting (2010) for the formal mathematical details. With NI ex asyms we remain on the current development path. No changes in behaviour and changes in price ratios are simulated, as is the case with eSNI. So there is no change in the consumption and production package. The asyms can thus be simply deducted. By way of supporting this point it is useful to add: if expenditure on elimination, compensation and restoration of damage were entered as costs instead of value added, then one arrives at the same level NI ex asyms as in the case of deduction. The correct moment of comparison when entering elimination and compensation measures and restoration of damage may be in the same financial year or in an arbitrary year in the past; theoretically that makes no difference. Basically what it boils down to is that neutralising the effects of production growth on the environment must not be regarded as a contribution to the same growth. At the moment disruption in functions of the life support systems through, for example, the emissions of greenhouse gases (which are accumulating and are above the sustainability level), expenditure on elimination measures to reduce these emissions at home and abroad (by buying emission rights), expenditure on measures to compensate for the repercussions of loss of function such as construction of water reservoirs and the raising of

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dikes, and expenditure on repairing damage resulting from loss of function are partly in different financial years and partly in the same financial year. Disruption of the function ‘air for physiological functioning’ through intensive use of the function ‘air as medium to get rid of waste’, for one thing by traffic, and expenditure on medical help for CARA patients to compensate for the repercussions of this, largely take place in the same financial year. The same often applies to the loss of the recreational function of beaches through oil washed ashore and the cleaning up of the oil, a measure to repair the damage because this does not eliminate the cause which is the use of the oceans as a dumping ground for waste. Asyms are clearly in conflict with the original intention of the creators of NI as an indicator of the fluctuations in the level of the volume of production. Moreover asyms are important for the concept of environmentally sustainable national income (eSNI) dealt with in Section 7. It is therefore a good idea to publish a series of the NI minus asyms alongside the NI series.2

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7. SECOND WAY: PUBLISH A SERIES OF ENVIRONMENTALLY SUSTAINABLE NATIONAL INCOMES (ESNI) ALONGSIDE THE STANDARD NI’S TO INDICATE THE DISTANCE TO ENVIRONMENTAL SUSTAINABILITY Environmentally sustainable national income (eSNI) is defined as the maximal attainable production level by which vital environmental functions remain available for future generations, based on the technology available at the time. Thus the eSNI provides information about the distance between the current and a sustainable situation. The length of the period to bridge this distance, that is the transition period towards a sustainable situation, is limited only by the condition that vital environmental functions must not be damaged irreversibly. In combination with the standard national income (NI), the eSNI indicates whether or not the part of the production that is not based on sustainable use of the environment, is becoming smaller or greater. Because of the precautionary principle, future technological progress is not anticipated in the calculation of eSNI. When constructing a time series of eSNI’s, technological progress is measured after the event on the basis of the development of the distance between the eSNI and standard NI over the course of time. When this distance increases, society is drifting farther away from environmental sustainability, if this distance decreases, society is approaching environmental sustainability. The theory of and the necessary statistics for an eSNI have been worked on since the mid sixties. A first rough estimate of the eSNI for the world by Tinbergen and Hueting (1991/1992) arrives at roughly fifty percent of the production level of the world: the world income. Estimates for The Netherlands by a cooperation of Statistics Netherlands, the Institute of Environmental Studies and the Netherlands Environmental Assessment Agency also arrived at about fifty percent of the production level or national income of The Netherlands; see Verbruggen et al. (2001). This corresponds with the production level around 2

This exercise can be carried out relatively easily because we are talking about actual expenditure so that the NI ex asyms, unlike the eSNI, is on the same development path as the NI. At the time (1970 – 2000) there were those at Statistics Netherlands who were for and against the publication of a series NI ex asyms, and that is probably still the case. As long as the opponents have the upper hand the CE Delft would seem to be the appropriate institute to tackle the estimate of the asyms as a pilot project .

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1980. In view of the smaller size of the population, the consumption per capita was by that time substantially higher than fifty percent of the current level. In the period 1990-2005 the distance between NI and eSNI increased by thirteen billion euro or 10%. The methodology of the present calculation was proposed in 1992 by Hueting et al. (1992) and was developed further into the model approach published by Verbruggen et al. (2001) and Hueting and De Boer (2001). The necessary condition for sustainability is that environmental functions are maintained for future generations, at the lowest levels of availability that enables the physical elements of the environment, which are the carriers of the functions, to remain supporting these levels. This is the case when the sustainability standards – see Appendix – are met. The data of the cost of the measures to attain the standards and thus maintain vital functions, that rise progressively per unit of function restored (expressed in physical units, see Figure 1), are estimated in the way exposed in Section 4. The model yields an approximation of the eSNI. The model traces the consequences of (1) the reactions to the change in price ratios (environment burdening activities become relatively more expensive, whereas environmentally benign activities become relatively cheaper) and (2) direct shifts to environmentally less burdening activities. The change in price ratios can be elucidated as follows. It follows from Hueting (1981) and Hueting et al. (1992) that the bulk of national income growth is generated by industries that cause the greatest losses of environmental functions, both in production and in consumption. The increase in productivity in these industries, measured in terms of goods produced, is much greater than elsewhere in the economy, so the real prices of these products decrease strongly, and, with them, the price ratio between environmentally burdening and less burdening products. As a result, any shift to environmentally friendly products has a negative impact on the volume of national income; see Hueting et al. (1992). When, as in the simulation of environmentally sustainable income, the cost for attaining environmental sustainability are internalised in the prices of environment burdening products, the real prices of the latter increase, as does the price ratio between environmentally burdening and friendly products. The latter price ratios reflect the situation in an environmentally sustainable situation. Attaining environmental sustainability without a (drastic) change in price ratios is infeasible. The eSNI is the only indicator which (1) is directly comparable with standard NI because it is estimated in accordance with the conventions of the System of National Accounts (SNA), (2) relates the measurable physical environment (‘ecology’) with subjective preferences (economy) as shown in Figure 1, (3) provides the distance between the actual (NI) and sustainable (eSNI) production level in factor costs and (4) shows the development of this distance in the course of time and thus shows whether or not society is drifting further away from environmental sustainability defined as keeping vital environmental functions available for future generations. Therefore the eSNI is indispensable information for society and policy. A recent overview of the development of eSNI is given by Colignatus (2008).

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8. THIRD WAY: REFUTE THE FALLACY OF THE POLITICAL STATEMENT THAT PRODUCTION MUST GROW TO FINANCE SAFEGUARDING THE ENVIRONMENT

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The official policy of all countries in the world is that standard NI - production - must increase in order to create scope for financing environmental conservation, and thus attain sustainability. The theoretical mistake of this reasoning is shown by Hueting (1996). Of course, the future cannot be predicted. But the plausibility of the statement can be examined. On the grounds of the data discussed below the statement seems extremely unlikely. The author feels the opposite is more plausible for the following seven reasons. (1) Theoretically, the possibility cannot be excluded that growth of production and consumption can be combined with restoration and maintenance of environmental quality. However, such combination is highly uncertain and scarcely plausible. It would require technologies that simultaneously : (i) are sufficiently clean, (ii) do not deplete renewable natural resources, (iii) find substitutes for non-renewable resources, (iv) leave the soil intact, (v) leave sufficient space for the survival of plant and animal species and (vi) are cheaper in real terms than current available technologies, because if they are more expensive in real terms then growth will be reduced. Meeting all these six conditions is scarcely conceivable for the whole spectrum of human activities. Especially simultaneously realising both (i) through (v) and (vi), which is a prerequisite for combining production growth and conservation of the environment, is extremely difficult. Anyhow, technologies necessary for the combination of production growth and full conservation of the functions of the environment are not yet available. Anticipating the future availability of such technologies conflicts with the precautionary principle, and consequently with sustainability, which is, of course, certainly not the same as forecasting or not expecting technological progress. (2) An analysis of the basic source material of the Dutch national accounts shows that roughly one third of the activities making up standard NI (measured as labour volume) do not contribute to its growth. These activities include governance, the administration of justice and most cultural activities. Part of the services sector contributes moderately to the growth of NI, while the remaining one third contributes by far the largest part to the growth of production. Unfortunately, this latter third consists of activities associated with production and consumption that cause the greatest damage to the environment in terms of loss of nature and biodiversity (by use and fragmentation of space), pollution and depletion of resources. These activities include the oil and petrochemical industries, agriculture, public utilities, road construction and mining. These results are almost certainly valid for other industrialised countries and probably valid for developing countries; see Hueting (1981) and Hueting et al. (1992). (3) The burden on the environment as represented in standard NI equals the product of the number of people and the volume of the activities per person. Reducing this burden by decreasing population lowers growth or leads to a lower production level.

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Roefie Hueting (4) Applying technical measures has a negative effect on growth of production because they enhance real prices: more labour is needed for the same product. The research for the estimates of eSNIs has shown that environmental sustainability cannot be attained solely by applying technology. In addition, direct shifts, such as from car to bicycle and public transport, and from meat to beans, also are necessary. From point (2) above it follows that these shifts also reduce growth or lead to a lower production level. (5) A price rise resulting from internalising the costs of the measures which restore the environment means, like any price rise in real terms, a lowering of production growth. Depending on the situation, this decreases the production level. For a given technology, product costs will rise progressively as the yield (or effect) of environmental measures is increased. Of course, technological progress leads to higher yields. As production increases further, however, so must the yield of the measures increase in order to maintain the same state of the environment, while the fact of progressively rising costs with rising yields remains unaltered. (6) An unknown part of the value added in standard NI consists of asymmetric entering (see Section 6) and should therefore not be considered as a contribution to its volume, see Hueting (1974/1980). This part will increase considerably because of the expenditures on (1) measures to eliminate the origin of the climate problem (caused by damaging the functions of life support systems due to production growth) by reducing the emission of greenhouse gases and on (2) measures to compensate the effects of climate change, e.g. by building dikes and moving to higher elevations. (7) A sustainable production level with available technology is about fifty percent lower than the current level, both for the world: see Tinbergen and Hueting (1991/1992) and for the Netherlands: see Verbruggen et al. (2001). From this it follows that eSNI has to grow more than twice as fast as NI in order to reduce the distance between NI and eSNI. This seems to be an almost impossible task for environmental technology, which is the only means for increasing eSNI.

9. FOURTH WAY: CLARIFY WHY ENVIRONMENT DOES NOT CONFLICT WITH EMPLOYMENT UNDER LOGICAL CONDITIONS The proposition that to preserve the environment we must sacrifice employment is probably the major obstacle standing in the way of a sound environmental policy. This is because the proposition overlooks the simple fact that the possible uses or functions of the environment (including natural resources) are scarce goods which require the use of production factors for their restoration, preservation and substitution. Of these, labour is the most important. For example, in the Netherlands more than 80% of the Net Domestic Product is labour income (including mixed income - i.e. income of industries that goes to private households). In macroeconomic terms, labour is the dominant cost factor. A given amount of production and consumption requires more labour with environmental conservation than without. The extra labour required is used to maintain scarce environmental functions. 3 3

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This conclusion can be elucidated as follows. Human beings ultimately depend on three factors for survival and for the level of consumption that they want to attain:

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•

the possible uses, or functions, of their physical surroundings, the environment: water, air, soil, plant and animal species, space, and natural resources, including energy resources; • ‘hands and brains’ - in other words, labour, and because the brain steers the hands, it is ultimately human ingenuity that counts; • time. Of course, capital is also a production factor. But capital goods are manufactured by labour, using elements of our physical surroundings: the environment. Ultimately, the environment, labour and time are the factors with which humans have to make do in obtaining what they need. The environmental problem can be conceived as a process involving the steady substitution of time, or working hours, through depletion of the environment. For example, spraying herbicides requires less time than manual weeding. The point made in italics above can therefore be reformulated as follows: given the technology available at a given time, it takes more time, that is working hours, to attain a certain goal without depleting the environment than if the environment is depleted. There is a continuous exchange between the time spent on work with that on leisure. Working hours are reduced either directly or by longer holidays and part-time work. On the other hand, there is an increase in working hours owing to the participation of women, and all kinds of small jobs on the side. Leisure and working hours can be substituted 4 once a basic level of self-support has been reached. So the point can again be reformulated as follows: attaining a certain goal requires more labour with environmental conservation than without.5 Travel provides a clear example of the exchange between time and the environment, both in production and consumption, and also of the potential for substituting time for work by time for consumption. A newspaper reporter can interview three international ‘personalities’ a week by travelling by airplane, and perhaps one by taking the boat or train. The same holds true for consumption: we can reach more distant places if we travel in ways that burden the environment than if we do so in environmentally friendly ways. As a society, 6 we have the following three choices: •

First choice: From this day on we take the train to a nearby resort, instead of taking a plane halfway round the world to Bali. This means a lower level of welfare acquired from goods produced, because the new consumption pattern differs from revealed preferences. It also means a lower real national income, because activities with a

4

The degree of substitution and its direction obviously depend on preferences. Decisions on this point can usually be made individually. 5 Whatever goal, whether travelling or producing meat. 6 Environmental functions are collective goods. Individual decisions are subject to the prisoner's dilemma. Within a given structure, one puts oneself at great disadvantage while the desired effect is estimated to be negligibly small because one doubts whether others will join the effort. This is why a choice can only be made collectively.

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•

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capacity for producing a volume of goods that has increased to fabulous heights in recent decades are replaced by activities for which this capacity has increased only modestly, or not at all (see Section 8). Second choice: We continue going to Bali, but we do so by train and boat. This means an increase in travel time, less time for work and consequently lower consumption. A lower volume of national income accrues due both to the lower labour productivity of the transporters and to shorter working hours for the traveller. Third choice: We continue flying to Bali and accept the inherent loss of the environment.

With the current state of technology it is impossible to realize existing levels of production and consumption sustainably.7 As long as this is the case, we can only increase our production and consumption (per time unit) at the expense of the environment (see Section 3 and 8). The extra labour needed to save the environment is either directly or, on balance, the result of environmental protection. Clean production and consumption require provisions and adaptations of all kinds. Examples include cleaning industrial or household waste water, integrated pest control in agriculture, sustainable exploitation of forests, and prevention of noise nuisance. Such provisions and adaptations require more labour directly. In the case of activities that burden the environment being replaced by environmentally less burdensome activities, there is always a positive balance of additional labour and saved labour. Besides travel (see above) packing is a clear example. Disposable packaging and cutlery were introduced to reduce labour input in order to increase labour productivity. However, the ensuing loss of scarce environmental functions is not taken into account in the calculation of this productivity. If we buy eggs in a basket, milk in a jug and take-away Indonesian food in a rantang, we will certainly cause some loss of employment in the packaging industry, but at the same time we create many more jobs in the service sector. This too results in a decrease in labour productivity: the same goal is reached with more working hours and more consumer time. In the past, the price mechanism forced out labour at the expense of the environment because the environment falls outside this mechanism. This labour will be drawn in again when we start taking the environment into account in whatever form by ‘internalising’ it (again, given the available technology). The absurdity of a perceived conflict between the environment and employment becomes particularly evident when we trace its consequences. If conservation of the environment were to be achieved at the expense of employment, then ‘clean’ production and consumption should require less time than ‘dirty’ production and consumption. Because labour is the dominant cost factor, as explained above, clean production would then be cheaper. From this it follows that there would then be no environmental problem! Everyone would then switch to these cleaner, cheaper production methods, forced to do so by the market. Thus, if merely one company were to switch to clean production, the rest would have to follow suit in order not to be priced out of the market. The situation is presented upside down: the opposite of what we are being told is true. There is an environmental problem because clean production creates structurally more 7

This appears from the study on sustainable national income described in Section 7.

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employment than dirty production. This makes clean products more expensive, and this is why we produce and consume in a way that burdens the environment. 8 The environment is a collective good, and decisions about it can only be made collectively. If one company switches to production methods that meet national or global sustainability standards, while others do not follow suit, then higher costs will price that company out of the market, and disemploy its employees. Therefore, the logical conditions under which regaining the availability of environmental functions that have become scarce goods creates rather than destroys employment must be made binding for the whole economy. Of the necessary preconditions the following are the most obvious:

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1. Income has to be reduced in proportion to the costs of the measures required to conserve the environment. This precondition is completely logical. The extra labour required to restore and conserve scarce environmental functions is deployed to acquire non-market goods. Since income is nothing but a claim to produced goods (the sum of incomes equals the sum of goods produced), environmental measures come down to a reduction of (the growth of) the wage base. This outcome corresponds with an extremely simple datum. A good is scarce if one needs to sacrifice something else that one would like to have in order to acquire it. With scarce goods it therefore holds that more of the one entails less of the other. Thus, ceteris paribus (including the technology available at a given moment), more environment means less production and vice versa. The conflict is therefore apparently between the environment and production or its growth, rather than between the environment and employment. 2. Other countries must take similar measures to the same degree. This precondition is logical too, because otherwise firms from countries without protection measures can compete domestic industries out of the market. It is difficult if not impossible to test the effects of the introduction of these conditions empirically. The environmental measures taken to date are marginal in relation to what has to be done to arrive at a sustainable use of the environment. Most measures only slow down the rate of deterioration, owing to the persistent and cumulative character of the burden. No government in the world accepts the unavoidable truth that, given the available technology, more environment means less production (and vice versa); so nowhere is reducing the wage rate taken in consideration. However, the introduction of the necessary preconditions can be simulated and their effects can be tested with the aid of an econometric model. This has been done in the CEscenario (Potma et al., 1983). A summary in English is given in Hueting (1987). In this study two contrasting scenarios are elaborated, one with business as usual and one giving priority to saving the environment and resources, be it not up to environmental sustainability . All 8

The point is whether or not we want to 'pay' for environmental conservation in the form of re-allocating production factors for the implementation of technical provisions or in the form of a direct shift from environmentally burdening to environmentally friendly activities. Examples: from car to bicycle, from a lot of meat to a little meat plus beans. There is no way to establish unambiguously what sacrifices we are prepared to make to preserve the environment (see Section 4).

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variables that are not relevant to the problem are kept the same. In this way the effects of environmental protection on employment and production are isolated. In the environment scenario, wages are reduced in proportion to the costs of the measures taken, but similar measures in other countries are not assumed. Still, the outcome of this model study confirms what can be expected on the grounds of simple analysis: unemployment decreases 9 and production growth is checked (if the outcome of a model is not in conformity with the underlying theory, one of the two has to be reconsidered). One of the underlying assumptions of the model study is that the demand for goods and services produced remains fully intact. For example, people have been travelling from time immemorial; they will not stay at home if car and air traffic decreases; they will go by train, boat or bicycle, even though they do not get as far per unit of time; the revealed preference for travel will not suddenly disappear. The enormous concern voiced by governments and industry about environmental issues would lead one to expect major encouragement of research on the logical conditions under which two major issues of our time - unemployment and the environment - neutralize rather than reinforce one another. But nothing could be further from the truth. The above-mentioned CE-scenario has been completely ignored. Openly admitting the above obvious fact and creating the logical conditions under which the problems of unemployment and the environment neutralize one another would lead to a structural drop in labour productivity. This certainly checks the growth of production as measured in national income, and probably leads to a lower production level. With this conclusion we have arrived at the heart of the environmental problem - growth of production (see Section 8).

10. FIFTHS WAY: SHOW THE WRONGNESS OF THE STATEMENT THAT ENVIRONMENTAL CONSERVATION IS UNPAYABLE We would love to save the environment, but it is too expensive. This statement may not be the most dangerous one, compared with the wrong statements mentioned above, but it is certainly the most hypocritical. All fundamental solutions for safeguarding the environment are clearly much cheaper 10 than continuing the process that is threatening life on this planet. For example: travelling by bicycle is much cheaper than driving the same distance by car. Heating one room, in combination with a sweater and an extra blanket, is much cheaper than heating the entire house. A vacation by boat or train is cheaper than a holiday flight. A diet combining some meat and beans is cheaper than eating lots of meat. Winter vegetables in winter are cheaper than summer vegetables in winter. Raising two children is cheaper than raising six.

9

Of course, seasonal, frictional and business-cycle unemployment are not influenced, nor the unemployment caused by the fact that labour productivity is lower than the legal minimum wage. 10

Cheaper in the ordinary everyday meaning of the word—that is, in the sense that less input of production factors is required. Compare footnote 8. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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The burden on the environment is determined by the number of people, the amount of activity per person, and the nature of this activity. Because activities with little or no impact on the environment can be expanded, the shift to environmental sustainability comes down to adapting the number of individuals of our species and the kind of activities we engage in to the carrying capacity of our planet. This adaptation is extraordinarily cheap. Of course, there is an economic sacrifice to be made; otherwise there would be no environmental problem. Most of us would love to make unrestricted use of the private car, are mad about eating meat, and prefer to have sex without a pill or condom. But if we unlink our credo of progress from the growth of our consumption, there is no reason at all to panic. In the first place, shifting to sustainability will not damage our health. On the contrary, environmentally-friendly activities are usually healthier than those that harm the environment. Second, a sustainable level of activity by no means implies a return to the Middle Ages, as often claimed. Global production and consumption will have to be halved in order to attain sustainable levels (see Section 7), thus to repay our debt to future generations. In the long term NI doubles every 25 years. Were living conditions in 1985 worse for most of the people in the world than they are now? A sustainable level of activity will be higher than that of 25 years ago.

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11. APPENDIX ABOUT STANDARDS In establishing sustainability standards, as the basic point of departure is taken the natural regeneration capacity of the environment: as long as this remains intact, environmental functions will remain available. The following examples illustrate how this quantity and the acceptable, that is sustainable burden can be established. It can, for instance, be established that the rate of erosion of topsoil may not exceed the rate of formation of such soil due to weathering. Similar consumption standards can be set for other natural resources. With respect to how sustainability relates to species, then, the standard holds that the rate of human-induced extinction should not exceed the rate at which new species come into existence. This boils down to preserving all the species still alive today, for it is assumed that during the past several thousand years conditions have been such that, leaving aside drastic human intervention for the moment, the number of new species must certainly have at least equalled the number of species lost to extinction (Raup, 1986; Hawksworth, 1995). However, in contrast to the situation prior to human intervention, the rate at which natural species are becoming extinct is today at least a factor 10000 higher than the rate at which new species are evolving (Raup, 1986). There is obviously a level, defined as a number of individuals of a species, below which the species is threatened with extinction; arriving below that level is unsustainable, remaining above that level is sustainable. Together with the condition that harvesting a species should not disrupt the ecosystem of which it forms a part (see Odum, 1971), this yields the sustainability standard for the species. In the absence of drastic human intervention, the quantity and quality of renewable natural resources such as groundwater or biomass (including wood) generally show a substantial degree of constancy. In the absence of human intervention, our renewable physical surroundings is thus characterized by a substantial degree of constancy or even increase.

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With regard to pollution, too, criteria can be established (Hueting and Reijnders, 1996, 1998). Acid precipitation, for example, should not exceed the neutralizing capacity of the soil. Likewise, there should be no exportation of risks to future generations through pollution of groundwater that is to serve as a source of drinking water for those generations. In many cases, the accompanying environmental burden can be determined with great accuracy. There is a wealth of data on the rate at which new fertile soil is naturally formed and on the neutralizing capacity of natural soils, and these data enable a precise indication to be given of the admissible environmental burden due to erosion and acid rain (Reijnders, 1996). In other cases we have insufficient knowledge to make firm pronouncements. For example, at present we can do no more than give a rough indication of the conditions under which plant and animal species are able to survive (Hawksworth, 1995; Den Boer, 1979). On the basis of the best available global circulation models it can be calculated that worldwide emissions of carbon dioxide must be reduced drastically to achieve stabilization of the global warming process, but an exact percentage cannot be given (de Boer, 1996). Similarly, shortcomings in our toxicological knowledge mean that we cannot fully analyse the risks associated with polluted groundwater. However, this does not detract from the fact that improved scientific knowledge can lead to a more precise establishment of standards for sustainability. All in all, it is feasible to establish scientifically the environmental burden that is ‘admissible’ on the basis of the objective of sustainability. Hueting and Reijnders (1999) describe how the precautionary principle can be employed if there are uncertainties and inadequate knowledge in the context of sustainability. In the case of very slowly forming natural resources such as crude oil and copper, which are to all intents and purposes non-renewable, ‘regeneration’ can take three forms: efficiency improvements, recycling and, over the longer term, substitution of one form of environmental element by another that can provide the same functions. Familiar examples of substitution include solar power and glass fibre for crude oil and copper wire, respectively. This can be expressed as follows in a numerical value. Sustainability of non-renewable natural resources means that in a given period only as much may be withdrawn from the stock as substitutes for the resource are expected to be developed in the long run as well as new potential for recycling and conserving the resource (improvement of efficiency). In this way the functions of a resource available in the year of investigation are maintained at the same levels in the future. In practice this can be worked out by, for instance, taking from a period in the past the quantity of possible uses (for example heating, transportation, and so on expressed in effective energy) that has become available through efficiency improvement, substitution and recycling and then assuming that the relative rates of efficiency improvement, substitution and recycling will be the same in the future.11 There follows from this a maximum permissible annual rate of extraction that can be used as a sustainability standard. In a formula: e(t0)≤r(t0).S(t0), in which e(t0) is the extraction rate in year t0, r(t0) the relative rate (or rate coefficient) of reduction of consumption of the resource (resulting from substitution, and so on) at a constant level of activities, and S(t0) the stock in year t0 (Tinbergen, 1990). 11

This involves an assumption about technological progress in the fields of substitutes and recycling. This exception to the point of departure that the estimation should be based on the technology that is operational in the year of investigation, or shortly thereafter, is the only way to arrive at a sustainability standard for nonrenewable resources. The only other option, to pass on stocks untouched to future generations, is unfeasible and also makes no sense, because this would then have to be carried through ad infinitum.

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This formula is applied at the global level. Standards for individual countries can be subsequently derived by applying the general rule that a country's share in meeting the global standard should be equal to its share in total extraction. In practice, the factor r(t0) is determined mainly by efficiency improvements, as substitution and recycling have still made only a very minor contribution in recent years. The aforementioned assumption that the line recording use of the resource in the past can be continued into the future with, basically, a constant annual rate of efficiency improvement, implies that as time progresses the same material output can be achieved at a fraction of current resource use. In a study on the development of energy efficiency, Tinbergen (1990) found a practical value of 1.67 per cent for this improvement rate. From this it follows that in 60 years' time the present level of production can be achieved with 37 per cent and in 315 years' time with 0.5 per cent of current fossil fuel consumption: S(3l5)= (1-0.0167)315 X S(0) = 0.005 X S(0). Such enormous efficiency improvements (63 per cent and 99.5 per cent, respectively) seem rather unlikely. In the context of sustainability, 315 years is a very short time. The probability that humankind will sooner or later have to manage without the functions of the non-renewable natural resources, if no substitutes are found, is comparable to the certainty that humankind will sooner or later have to manage without the functions of the soil in those areas where the degree of erosion is higher than the rate of soil formation. Because efficiency improvements alone are thus inadequate to achieve sustainability, it has been proposed in the theory behind the calculation of eSNI, that additional measures must be taken for the development of substitutes (Tinbergen and Hueting, 1991). We here adopt this proposal, applying the following procedure. For each resource, statistical data are used to establish the rate at which substitution (the ultimate solution) has taken place over the past 10 to 20 years and the annual cost this has entailed. It is then calculated how long it would take, at this rate, to completely replace the resource (1). Next, it is calculated how long it will take for the resource to be depleted, at the current level of production (2). Then (1) divided by (2) yields a rough approximation of the required ‘acceleration factor’ for the development of substitutes in time for them to replace the functions of the resource when it is depleted. This factor multiplied by the statistically established annual cost of substitute development yields the sum that needs to be reserved for this purpose. The figures thus found can be no more than rough estimates, of course. In the context of non-renewable natural resources, though, this is an approach that does justice to the principle of sustainability, which is the point of departure of our estimates. Our approach would be comparable with that of Solow (1974), Hartwick (1977, 1978) and others, if the latter were to exclude unfeasible substitution of renewable resources by other resources and by capital (see below), that is if they were to abandon their faith in the extreme areas of formal production functions. When using the concept of environmental function, the only thing that matters in the context of sustainability is that vital functions remain available. What does the conservation of vital functions imply for the distinction between renewable and non-renewable resources and for the distinction between strong and weak sustainability? As for renewable resources, functions remain available as long as their regenerative capacity remains intact. Regeneration in relation to current use of ‘non-renewable’ resources such as crude oil and copper that are formed by slow geological processes is close to zero. ‘Regeneration’ then takes the form of efficiency improvement, recycling and, in the final instance, developing substitutes (see above). The possibilities for this are hopeful (Reijnders,

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1996; Brown et al., 1998). So, economically speaking, there seems to be no essential difference between the two types of resource: sustainability is attained if their functions remain available. Advocates of ‘weak sustainability’ take the line that all elements of the environment can ultimately be substituted by man-made alternatives, implying that restoration of lost elements can be postponed in anticipation of cheaper substitutes provided by future technologies. However, the life support systems of our planet (see Section 3), on which a number of vital functions depend, are not substitutable at all (Lovelock, 1979; Roberts, 1988; Goodland, 1995; Reijnders, 1996). The same holds for most of the functions of natural ecosystems, especially in the long term (see, for example, the remark on the function of ‘gene pool’ in Section 3). Consequently, there can be no such thing as ‘weak sustainability’ for the functions of these systems. Advocates of ‘strong sustainability’ hold it to be impossible for humanity to substitute many of the elements of the natural environment. In its strictest form, however, this implies that stocks of non-renewable resources should remain fully intact, an unrealistic aim. Consequently, strong sustainability for non-renewable resources seems to be impossible. In conclusion, there seems to be only one kind of sustainability, whereby non-renewable resources must gradually be substituted by other elements of our physical surroundings in order to guarantee the availability of functions, and substitution of a large class of renewable resources is impossible, particularly life support systems, including ecosystems. The question is often asked whether sustainability standards should be applied locally or globally. This depends on the scale at which the functions in question should be substituted. For instance, preservation of the function ‘soil for growing crops’ requires local application of the standard for erosion (the erosion rate may not exceed the soil formation rate; see above), because exceeding the standard at one place cannot be compensated by remaining under this standard elsewhere. Crude oil, on the other hand, is a global resource, so in this case the sustainability standard, effectuated through efficiency improvement and substitute development, should be applied worldwide.

12. CONCLUSION AND RECOMMENDATION The arguments given above lead to the following conclusion and recommendation. 1. Our planet is threatened by a wrong belief in a wrongly formulated growth. 2. The NIs (or GDPs) in all countries should be supplemented by a series of NIs without asyms and a series of eSNIs, alongside the standard NI, in order to improve the information.

REFERENCES Brown LR, Flavin C and French H. State of the World 1998. W.W. Norton, New York, 1998. Brundtland GH et al (World Commission on Environment and Development). Our Common Future. Oxford University Press, Oxford, 1987. Daly H. Toward a Steady State Economy. Freeman, San Francisco, 1973.

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De Boer B. Calculation of sustainable national income in the Netherlands: some results. Paper prepared for the workshop Valuation Methods for Green National Accounting: a Practical Guide, organized by The World Bank, U.N. Statistical Office and Ecological Economics. Washington, D.C., 20- 22 March 1996. De Boer B, Hueting R. Relatie NI ex asyms en mDNI (Relation NI ex asyms and eSNI). Website sni-hueting.info, 2010. Den Boer PJ. Het overleven van soorten. Intermediair 15 (48):7-13, 1979. De Haan M. Accounting for goods and for bads. Statistics Netherlands, 2004. Goodland R. The concept of environmental sustainability. Aun. Rev. Ecol. Syst. 26, p.1-24, 1995. Hartwick JM. Intergenerational equity and the investing of rents from exhaustible resources. American Economic Review 66: 972-974, 1977. Hartwick JM. Investing returns from depleting renewable resource stocks and intergenerational equity, Economics Letters 1: 85-88, 1978. Hawksworth DL (ed.). Biodiversity, Measurement and Estimation. Chapman & Hall, London, 1995. Heertje A. Echte economie. P.138. Valkhof Pers, Nijmegen, 2006. Hennipman P. Economisch motief en economisch principe. Amsterdam, 1940. Hennipman P. Nut, nuttigheid en objectieve gebruikswaarde. De Economist:433-438, 1943. Hennipman P. Doeleinden en criteria. Theorie van de economische politiek. Leiden, 1962. Hennipman P. De externe effecten in de hedendaagse welvaartstheorie. Economisch-Statistische Berichten, 20 March 1968. Hennipman P. Welfare economics and the theory of economic policy. Hartnolls, Cornwall, 1995. Hueting R. Functions of Nature: Should Nature Be Quantified? World Wildlife Fund, London, 1969. Hueting R New Scarcity and Economic Growth: More Welfare Through Less Production? Dutch edition: Agon Elsevier, Amsterdam, 1974 - English edition, North-Holland Publishing Company, Amsterdam, New York, Oxford, 1980 Hueting R. Some Comments on the Report A Low Energy Strategy for the United Kingdom, compiled by Leach G. et al. for the International Institute for Environment and Development. Paper prepared for the working party on Integral Energy Scenarios, Den Haag, 1981. Hueting R. An Economic Scenario That Gives Top Priority to Saving the Environment. Ecological Modelling 38 (1/2): 123-140, 1987. Hueting R. The Brundtland Report: A Matter of Conflicting Goals. Ecological Economics 2: 109-117, 1990. Hueting R. The Use of the Discount Rate in a Cost-Benefit Analysis for Different Uses of a Humid Tropical Forest Area, Ecological Economics 3 (1): 43-57, 1991. Hueting R. The Economic Functions of the Environment. In: P. Ekins and M. Max-Neef (eds), Real-Life Economics, Routledge, London and New York, 1992. Also published in: L.L.Boyer (ed.), Proceedings of the 5th International Conference on Underground Space and Earth Sheltered Structures, Delft University Press, Delft, 1992. Hueting R. The economic functions of the environment - valuation of environmental effects. Evaluation of Environmental Effects of Transport, Report of an International Roundtable

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organised by PTRC Education and Research Services Ltd., The Hague, 19-20 June 1995. London, 1995. Hueting R. Three Persistent Myths in the Environmental Debate. In: Ecological Economics 18: 81–88, 1996. Hueting R, Bosch P, De Boer B. Methodology for the Calculation of a Sustainable National Income. Statistics Netherlands, Statistical Essays, M 44, The Hague, SDU Publishers, 1992. Also published as WWF International report, Gland, Switzerland, June 1992. Hueting R, Reijnders L. Duurzaamheid is een objectief begrip. Economisch-Statistische Berichten: 425-427, 1996. Hueting R, Reijnders L. Sustainability is an Objective Concept. Ecological Economics 27 (2): 139-147, 1998. Hueting R, Reijnders L. Uncertainty and Sustainability. Ecological Economics 29(1): 9-11, 1999. Hueting R, De Boer B. Environmental Valuation and Sustainable National Income According to Hueting. Van Ierland E. C. et al., editors. Economic Growth and Valuation of the Environment: A Debate, pp. 17–77. Edward Elgar, London, 2001. IUCN. The World Conservation Strategy. Gland (Switzerland), WWF/IUCN, 1980. Kapp KW. The Social Costs of Private Enterprise. Cambridge (Mass.), 1950 Lovelock JE. Gaia, A New Look at Life on Earth. Oxford University Press, Oxford, 1979. Mill JS. Principles of Political Economy, p. 452 et seq.. London (First edition 1862), 1876. Odum EG. Fundamentals of Ecology, 3rd edn, Philadelphia (Penn.), p.223 et seq., 1971. Potma TG, Becht HY, Hueting R and Zijlstra GJ. Het CE Scenario, een realistisch alternatief. Centrum voor Energiebesparing. Delft, 1983. Raup DM. Biological Extinction in Earth History. Science 231:1528-33, 1986. Reijnders L. Environmentally Improved Production Processes and Products, Kluwer Scientific Publishers, Dordtrecht, 1996. Robbins L. An essay on the Nature and Significance of Economic Science, 2nd ed, London (1st ed 1932), 1952. Roberts F. Modern Cassandras. Resource Policy, 14: 306-7, 1988. Rosenstein-Rodan PN. Grenznutzen. Handwörterbuch der Staatswissenschaften, 4. Auflage, Vierter Band, Jena, p. 1195 et seq, 1927. Solow RM. Intergenerational equity and exhaustible resources. Review of Economic Studies: 29-45, 1974. Tinbergen J. Bepalen van omslagpunt is van essentieel belang, NRC-Handelsblad, 16 October 1990. Tinbergen J, Hueting R. GNP and Market Prices: Wrong Signals for Sustainable Economic Success that Mask Environmental Destruction. Goodland R, Daly H, El Serafy S, Von Droste B, editors, Environmentally Sustainable Economic Development: Building on Brundtland. United Nations Educational, Scientific and Cultural Organization, Paris, 1991. Also published in: Goodland R et al., editors. Population, Technology and Lifestyle, The Transition to Sustainability. Island Press, The International Bank for Reconstruction and Development and UNESCO, Washington, D.C., 1992. Also published in: Goodland R et al., editors. Environmentally Sustainable Economic Development: Building on Brundtland. Environment Working Paper No 46, The World Bank, Washington, D.C., 1991.

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Verbruggen H., Dellink RB., Gerlach R., Hofkes MW, Jansen HMA. Alternative Calculations of a Sustainable National Income for the Netherlands According to Hueting. Van Ierland EC et al., editors, Economic Growth and Valuation of the Environment: A Debate. Pp. 275–312, Edward Elgar, London, 2001.

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In: Theories and Effects of Economic Growth Editor: Richard L. Bertrand, pp. 31-51

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Chapter 2

COHESION, GROWTH AND DEVELOPMENT SINCE THE INDUSTRIAL REVOLUTION Espen Moe NTNU Social Research AS, Norwegian University of Science and Technology

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ABSTRACT The chapter focuses on the relationship between cohesion and economic growth and development. Theoretically, I combine Joseph Schumpeter and Mancur Olson. Structural economic change is what makes a state grow in the long term. However, policies of structural change are politically risky as they create redistributive effects and are fought by vested interests. I suggest that cohesion stimulates growth by making it politically safer for decision-makers to pursue policies of structural change. Paired comparisons between Britain, France, Germany, the US and Japan during five core industries and five time periods since the Industrial Revolution provides a tentative qualitative test.

INTRODUCTION Cohesion is about what holds a country together. It is about trust and legitimacy – between the people and the institutions of government, and within the state itself. It seems obvious that this should impact upon a country’s potential for long-term economic growth and development. But the links are only poorly understood. This chapter suggests a mechanism through which cohesion affects growth and development. In this chapter, cohesion is defined as what makes it possible for policymakers to pursue politically risky and difficult policies. It is what makes it possible to pursue policies of structural economic change and what makes it possible for political decision-makers to go against vested interests. The overall framework combines Joseph Schumpeter and Mancur Olson. From Schumpeter comes the onus on structural economic change as the main engine of long-term growth. Olson’s contribution is the emphasis on vested interest groups, and how

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they often have the ability to prevent structural change. Policies pursuing structural change are politically risky, as they always entail both winners and losers. The losers have typically had years to acquire economic and political influence. Crossing them comes at a political cost. Hence, this chapter suggests that only during periods of cohesion will a state exhibit the willingness and the ability to pursue politically risky economic and industrial policies at the expense of vested interests. And consequently, in the long-term only cohesive states will grow and prosper. In the following I provide a brief sketch of the theoretical argument and methodology. The empirical section provides evidence from five core industries over five periods of structural economic change – cotton textiles, iron, chemicals, automobiles, and ICT-related industries. While cohesion is no easily defined concept, the empirical section demonstrates its usefulness, suggesting that it plays an important role in explaining long-term growth and development.

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THE THEORETICAL FRAMEWORK The focus of this chapter is on Schumpeterian growth, that is, economic growth based on technological innovation, knowledge, and human capital. Schumpeter adopted the Russian economist Kondratieff’s view of the world economy as going through successive waves of industrial revolutions of empirically 50-60 years each. While too deterministic a view, there is more than a rough consensus that through historical epochs, certain core industries and technologies have been particularly important for a country’s growth and prosperity.1 Schumpeter views the economy as going through long-term economic cycles, driven by growth in one or a few core industries. When these industries saturate, the economy drifts into structural depression ultimately resolved only when (or if) new growth industries provide the economy with new industrial engines. Depression leads to the destruction of old firms and industries, but also to the creation of new ones. Hence, the world economy goes through ‘waves of creative destruction’ (Schumpeter 1934; 1942). Structural change routinely meets with resistance from vested interest groups.2 Hence, new promising industries may find themselves constrained by old and established industries using their influence to sway policy-decisions in their favor. This is Mancur Olson’s (1982) contribution. Olson does not focus specifically on technology and has no cyclical understanding of the economy. Also, despite its long-term pretensions, his theory is static rather than dynamic. Yet, his argument neatly applies to Schumpeter. Technologies come and go, and industries and vested interest groups come and go with them. When technological 1

A number of scholars identify the same core industries. Freeman & Perez (1988:50pp) single out five ‘technoeconomic paradigms’ of 50-60 years each since the Industrial Revolution, based on cotton textiles, iron, steel, electric industry (including chemicals), oil and consumer durables, and computers and microelectronics. See also Bairoch (1982), Gilpin (1987), Hobsbawm (1969), Landes (1998), Modelski & Thompson (1996), Rostow (1978). 2 There will always be vested interests resisting change. New knowledge displaces existing skills and technological change means losses for those who have invested heavily in the old technology. Hence, obstacles to obstruct innovation are routinely set up: 1) Outright physical resistance. 2) Laws and regulations restricting the implementation of new technologies. 3) Lobby groups seeking to shield themselves through favorable treatment (Mokyr 1990).

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change is allowed to take place, Olson’s silting up of institutional rigidities will not occur. When the process of creative destruction is blocked, it will. This provides for a role for the state akin to a balancing act. It needs to prevent technological progress from creating the forces that will eventually destroy it, i.e. preventing vested interests from seizing control over economic policy-making. It allows for a state to promote and protect new technologies and industries while young and vulnerable. But if promotion and protection is allowed to persist, vested interests have again been granted economic and political influence. Towards the end of a technology or an industry’s product cycle, it is important not to support it, as it will impede upon structural change and harm the chances of future success in other industries. The state should prevent industries from eventually becoming so powerful that a few decades down the line, they themselves have acquired the political and economic influence to prevent further structural economic change. Hence, economic success can easily breed failure. If a country invests heavily in one set of industries, these investments cannot necessarily be translated into new industries based on other technologies. And the bigger the difference between old and new, the bigger the chance that the dominant power of the past will not be equally dominant in the future.

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Cohesion: Political Consensus and Social Cohesion The suggestion made here is that the key to whether or not a state can successfully control its vested interests is cohesion. The more cohesive the state, the greater the chance of preventing vested interests from gaining control, and the greater the chance that the state will prosper. The cohesion argument falls within a strand of theorizing that points to the importance of good governance. It is related to arguments about trust and legitimacy. For short, societies characterized by a high degree of trust and legitimacy have a higher likelihood of accomplishing long-term growth and development. To the OECD (2001a:39p), societies founded on networks of trust and cooperation help realize human potential. World Values Surveys regularly show the Nordic countries – among the wealthiest countries on the planet – to have the highest levels of trust in the world (Dayton-Johnson 2001:4). This increases stability, reduces tension, strengthens links between societal actors, reduces transaction costs, releases creative potential, etc. Cohesion can be thought of as the bonds that hold a country together. Knutsen (1999:168) emphasizes how a country can be supremely strong as a power, but weak as a state. The Soviet Union was fraught with corruption, instabilities, a stalling economy, and a population less than convinced as to the virtues of the system. Even if both were supremely strong powers, only the US was strong as a state. Holsti (1996:104pp) talks about the importance of a perceived social contract between the citizens. Dayton-Johnson defines social cohesion as the degree of interconnectedness and trust among a group of people, referring to “a community of shared values, shared challenges and equal opportunity” (Dayton-Johnson 2001:8, 35, 59). Focusing on the political dimension of cohesion, Putnam (1995) laments what he sees as a decrease in social capital in the US over the past four decades, whereas Fukuyama (1995) in Trust focuses on the functional and microeconomic role of cohesion – successful economies are economies with a high degree of trust. In The Great Disruption

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(1998) he suggests that trust evaporates more easily in times of structural change, when society is at its most vulnerable. However, we do need a mechanism through which cohesion can affect growth and development. In the foreword to Chang’s volume on institutional change Nayyar (2007) laments how economists treat institutions as they have technology; as a black box. Swilling and Annecke (2010) suggest that innovation be divided into three: Technological and institutional innovations (the obvious ones). But they also add relational innovations – innovations in relational patterns creating solidarity and cohesion, managing cooperation, creating democratic engagements necessary for change on the two other levels. This brings up two points. First, institutions are still poorly understood, even if they now belong to the regular academic language. Examining the historical record, tracing how they have worked in different settings is paramount. Second, the realization that there are basic underlying societal patterns that determine the ease with which changes to different structures can be pursued. Depending on definitional preferences, cohesion could be both an institution (in the Northian sense), and it could serve as a relational innovation, affecting the ease with which for instance institutions can be changed. While siding with the latter here, most importantly, cohesion must not become a black box. Thus, the following attempt at outlining a mechanism that even in a short chapter may illustrate the fruitfulness of the approach. De Long (2001:139p) provides a clue. One might think that long-term growth was among the state’s main priorities. Yet, politics consists of a myriad of minor and seemingly trivial decisions. Before decisions can be made on large-scale, abstract and overarching issues, countless minor concerns have to be satisfied. Hence, technological change and long-term growth are concerns mainly of high-flying rhetoric, with a focus often decidedly short-term. This is true of present-day democracies as it was of past authoritarian regimes where military issues would normally take primacy. Consequently, the likelihood that the state will pursue policies that seriously harm the most powerful vested interests is modest. A truism of the social sciences is that a regime’s most immediate concern is its own survival. The likelihood of survival diminishes radically when controversial decisions with grave redistributive effects are made. The likelihood that the state will pursue policies of structural economic change without solid backing either in parliament or the people is small. These are decisions that are typically only made in a political environment characterized by high cohesion. Cohesion applies both to the state itself and to the overall population, hence the need to split the notion in two. Political consensus applies to the ruling elites, social cohesion to the people. The result of both political consensus and social cohesion is less leverage for vested interests to exploit footholds and fragmentation within the polity. Hence, as defined in this chapter, cohesion specifies a concrete causal mechanism to help us assess the validity of the argument, even though the variable is difficult to operationalize. To spell the implications out clearly: 1) A lack of political consensus and/or a lack of social cohesion in the people make it easier for vested interests to pursue their own interests: A lack of political consensus makes it easier to exploit differences of opinion between different parties or decision-makers. A lack of social cohesion makes it more risky for political parties or other decision-makers to pursue policies with large redistributive effects. 2) Political consensus and/or social cohesion in the population make it easier to promote structural economic change, that is, decisions in the interest of society at large, at the expense of vested interests: Political consensus makes it more difficult for vested interests to secure favorable regulations and it makes it less risky for political parties or other decision-makers to pursue policies with potentially large

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redistributive effects. Social cohesion makes it less risky for political parties or other decision-makers to pursue policies with redistributive effects.3

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METHODOLOGY Cohesion is obviously not the sole relevant variable. The Schumpeterian-Olsonian framework contains numerous variables (most notably vested interests). This chapter however seeks to hone in on cohesion. The variable is not easily quantifiable. Also, the quality of data deteriorates dramatically when going back in time. This is also a problem when making comparisons between countries and industries for different time periods. Hence, the qualitative approach of this chapter. And hence, the ambition lies in demonstrating the potential of an often neglected or causally mis-specified variable rather than offering an explanation of growth to rival every other. For political consensus, I am looking at broad consensus amongst the ruling elites – typically government and parliament – as to the major economically and industrially relevant political issues. However, also when looking at less than democratic regimes, the ruler always relies on implicit political alliances in order to remain in power and to implement policies. Thus, “ruling elites” is a fluid notion (often including the nobility), with different groups typically functioning as informal checks and balances. Who constitutes the ruling elites is not an a priori given.4 Social cohesion can be thought of as the bonds that hold a country together. Again, operationalization is difficult. However, there is little doubt that numerous governments have played on feelings of nationalism, identity, and external threats in order to mold the populace and “manufacture” cohesion. There are data on the overall level and severity of riots, and for the present, survey data on trust. Ultimately I have had to make overall assessments as to the general level of social cohesion in the people based on the historical literature, the evidence of trust, and the record of politically directed unrest and turbulence in the population. As the data are only loosely defined, I have shied away from controversy, relying on interpretations that the overwhelming majority of scholars should agree upon.5 I look at a total of nine cases for five different time periods and industries, combining the comparative and the historical method. With one exception, I juxtapose one positive and one negative case for each time period and industry, employing Mill’s (1904 [1843]) Method of Indirect Difference. Combined with the historical method, this creates a foundation for drawing causal inferences about the co-variations discovered through the comparative

3

1) This says nothing about how social cohesion arises. The concern here is with its strength, not on how it came to be that way. 2) Consensus does not by necessity lead to technological change, growth and development. Consensus might easily center around the “wrong” choices, as can be seen in the empirical section. However, consensus and cohesion increase the chance that such transitions will be made. 4 This is along the lines of North, Wallis & Weingast (2007), where elites are defined simply as those who share power in the dominant coalition. 5 Reliable data on social cohesion are harder to find than for political consensus. Data on consensus refer to a small group of people, and is easier to track. Also, there is more data on the ruling classes than on the people. Finally, because of access to voting records etc., more easily operationalizeable data exists for consensus. Thus, some of the cases focus more on consensus than on social cohesion.

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method. For a far more extensive treatment, methodologically and empirically, I refer the reader to Moe (2007). I look at five periods of structural change and industries: late 18th to early 19th century cotton textiles, early-to-mid 19th century iron, late 19th to early 20th century chemical industry, early-to-mid 20th century automobile industry, and late 20th century ICT-based industries. I compare the lead economy with another great power that fared distinctly worse. Hence, for cotton textiles and iron, I juxtapose British success and French relative failure, for chemicals, German success vs. British misery, and for ICTs US success and Japanese failure. The exception is the car industry, where I only look at the US. The argument could be made that such a design allows for growth to be causing cohesion and not the other way around. Yet, by focusing on periods of structural change rather than overall economic growth, and on how cohesion impacts upon processes of structural change through political decision-making, causality is clearly unidirectional. If anything, the theoretical expectation if causality were to run instead from structural change to cohesion would be the opposite. Structural change tends to threaten cohesion (e.g Fukuyama 1998). The design ensures variation on the dependent variable, for each time period and for the whole chapter. This is no conclusive test, both because cohesion is loosely defined and because space constraints severely limit the empirical material included. Yet, the values on the dependent variable systematically match the values on the independent variable and are supported by the historical narrative. Regardless of the tentative nature of the findings, the chapter shows the variable’s potential, supporting the proposition that cohesion is vital in understanding long-term growth and development, suggesting the importance of further theoretical and empirical effort.

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COHESION AND ECONOMIC GROWTH AND DEVELOPMENT Cotton Textiles No industry is more closely tied to the Industrial Revolution than cotton textiles. A series of British innovations (spinning Jenny (1764), water frame (1769), mule (1779)) increased productivity to the extent that by the end of the 18th century, a mule would produce 200-300 times more than a normal spinning wheel (Brose 1998:36; Landes 1969:85; Mokyr 1999:21p). Cotton textiles accounted for 40% of British exports, and while roughly equal to France prior to the French Revolution, by the end of the Napoleonic Wars, British raw cotton consumption was four times that of France (Hudson 1992:183; Modelski & Thompson 1996:99). Towards the mid-18th century, Britain did not seem socially cohesive. Between 1758 and 1780, the number of arrests and casualties in ‘contentious gatherings’ steadily increased (Pugh 1999:23p, 38pp; Tilly 1995:10,92,419pp).6 The 1780s saw waves of radicalism, movements for parliamentary reform and suffrage, and the anti-Catholic Gordon riots (Pugh 1999:22; Melton 2001:40). It seriously threatened to impede on industrialization. Britain 6

This is partly due to the French Revolution triggering levels of repression not seen in Britain since the civil war. Revolutionary inspired movements were closed down and mass-membership affiliations held under tight control. Meetings with more than 50 people were banned. Speaking or writing in criticism of the constitution was prohibited and habeas corpus temporarily suspended (Pugh 1999:23p,38pp; Tilly 1995:10,419pp).

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faced widespread resistance against new machinery, with numerous attacks against sawmills, spinning Jennies and power looms (Hobsbawm 1969:67; Mokyr 1990:256pp; 2002:265p; Morgan 1999:46; Pugh 1999:46). Yet, the era also saw the forging of a British identity, primarily through war (Colley 1992). Knutsen (1999:107) writes that much of the 18th century had seen “a robust social consensus anchored in a distinct and relevant political mythology…forged on the anvil of large-scale war…this consensus rendered England self-confident, productive and strong.” Hence, the record on social cohesion seems mixed. More important was the way in which the British state dealt with riots, actively preventing industrialization from being nipped in the bud. Political consensus increased markedly as the late 18th century saw the coming together of British ruling elites. Struggles became personal rather than political. The number of contested elections shrank. A rapid fusing of English, Welsh, Scottish and Irish elites through marriage and inheritance resulted in a genuinely British ruling class (Colley 1992:167). Distinctions between Tories and Whigs blurred, with party loyalty often a matter of family tradition, but with both parties unanimously and staunchly pro-industry (Pugh 1999:15pp; Root 1991). That the locus of early British industry was the countryside benefited the landlords as technological change yielded a sharp increase in real estate values in industrializing and mining regions (Freeman & Louça 2001:166; Mokyr 2002:268p; Pugh 1999:17; Melton 2001:33p). The pro-industry stance meant that riots were violently suppressed. Tampering with bridges and mines was made a capital offense. Petitions to ban new technology were summarily and persistently rejected by Parliament. Ancient statutes and regulations were removed. Labor organizations were declared illegal if perceived to be threatening the advance of technology (Colley 1992; Freeman & Louça 2001:178; Mokyr 1990; 2002; Morgan 1999). Also worth noting is the increase in cohesion towards the very end of the century, among other things due to the French Revolution and the Napoleonic Wars. From the 1760s to the 1780s, the British ruling class was increasingly unpopular.7 1789 gave it the break it needed with respect to clamping down on potential opposition, industrial resistance and to reforming and legitimizing itself, which it duly did. The outcome was a ruling class with far more authority and legitimacy now heading a Britain much more stable in social and industrial terms, coming down decisively on the side of new manufacturing industry (Colley 1992). Hence, the wars affected cotton textiles through social cohesion, by cementing national identity.8 Notably, most cases of industrial unrest occurred either prior to or after this period. The Revolution caused enormous stir and nervousness in the ruling class, but there was scant evidence of pro-Frenchness or revolutionary activity in Britain following the Revolution. Britain had few problems recruiting people for military duty, and volunteering was unaffected by social class.9 As crisis arose, Britain had reservoirs of latent cohesion in its populace to draw upon (Best 1982:132p; Colley 1992:287; Evans 1983:81). Between 1789 and 1815, cotton 7

Colley writes (1992:152): “…everyone in the British Establishment had his hand in the till, advanced his own male and female relations and was closely related by blood or marriage to everyone else in high office.” The landed class was seen as parasitic, distinct from the king. 8 Also, the lack of technology diffusion across the Channel during the wars prevented France from catching up in technological terms, which overall was probably the more important effect. 9 The ones most reluctant to volunteer were peasants from remote, rural areas, and not industrial workers. In seven rural counties, 22% of all men volunteered. In contrast, in 11 counties dominated by trade and industry, the volunteer rate was 35% (Colley 1992:298).

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textiles flourished as international turmoil moved the focus elsewhere. Attacks on machinery dwindled and resistance against new technology subsided (Colley 1992:293pp). The French Revolution and the Napoleonic Wars became simultaneously crisis point and salvation. France also saw massive resistance against new technology, particularly in cotton textiles.10 But in France, the social fabric was breaking down rather than being rebuilt and cohesion markedly lower than in Britain. There was growing recognition that the king was not above the nation. Enlightenment criticism emphasized individual rights, and a public sphere was developing. The discourse switched ever more towards issues like government reform, the elites to an ever greater extent dissociating from the state (Collins 1995:223pp; Furet 1995:16; Roche 1998:441pp). It was far harder to give grievances a clear institutional expression than in Britain. In Britain, Parliament would always on some level be responsive to the nation – public opinion had an institutional locus (Melton 2001:62). The absence of a French locus gave the term “public opinion” a distinct elusiveness. Very few French 18th century periodicals carried actual political news. France did not even have a daily newspaper until the final quarter of the 18th century (Colley 1992:41).11 Instead, what passed for journalism was court gossip, slander, defamation and scandal, which should not be underestimated in a world where personalities counted more than politics and where politics occurred at the royal court. With censorship, police, and booksellers’ guilds imposing strong constraints on publishing, the general public had little knowledge about politics beyond the underground literature specializing in court rumors, gossip and scandals (Darnton 1982:vi,203p). Thus, the rise of a public sphere actually undermined social cohesion. In France, every famine triggered suspicion of government involvement, as in food shortages being created for personal enrichment. In 1789 in Britain, hundreds of popular demonstrations and addresses congratulated George III on recovering from illness. In France, the king was soon staring at execution (Evans 1983:185; Knutsen 1999:110; Melton 2001). This was a state that could not rely on any groundswell of cohesion once the going got rough. The state provided no consistent take on industrialization, in part because it was weak, but also because the ancien regime’s vacillating attitude towards new technology. The lack of social cohesion was matched by an absence of political consensus in the elites, for instance on structural reform. One might think an absolutist monarchy easily able to pursue change. And granted, French monarchs did seek technological and industrial progress through technology diffusion, industrial espionage, government prizes and pensions (Magnusson 2009; Mokyr 2002). Yet, the king was reliant on alliances that put obvious confines on his power. And these made it hugely difficult to do anything about the economic structure itself. Government perpetuated huge structural budget deficits and hampered growth, but reform met with fierce resistance. Opposition from nobility, Church and guilds made tax reform impossible, despite being crucial. Attempts at introducing a property tax and abolishing trade guilds (1776) created large-scale tension, clergy, nobility, magistrates, craftsmen, merchants and urban people all uniting against it. For structural reform, the king would have to side against the 10

Although because of the endemic level of riots all over France towards the end of the century, it is hard to know to what extent riots were directed against technology or against the regime. 11 The Journal de Paris, established in 1777 (Colley 1992:41). Only a handful of dailies existed in France (Unwin & Unwin 1994:432). In contrast, in 1746 London alone had 18 newspapers, the first established in 1702. Among the reasons why we have more data on British unrest, is the abundance of newspapers reporting on such events.

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forces from which he normally derived his support, and with forces towards which his traditional support would be downright hostile. Social cohesion was not strong enough for French kings to jeopardize the power alliance that they had with the privileged classes to seek support from reform-minded bourgeoisie and the lower classes. And a complete lack of political consensus made it impossible to implement structural reform. The state could neither whole-heartedly support industrialization nor push structural reform. Riots, against the state and against new machines and technology provided a hostile business environment. The end result was revolution (Furet 1995:51p; Hoffman & Rosenthal 2000; Mokyr 1990:258p; 2002:270; Price1993:71,139; Wright 1995:9, 34pp). The Napoleonic Wars exacerbated the problems. The cotton industry was lagging behind even before the wars. By the time of peace, Britain’s lead was insurmountable.

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Iron The second major early industry was iron. Many of the breakthroughs stem from the same period as breakthroughs in cotton textiles, but it was not until after the Napoleonic Wars that iron became the engine of the economy. Also, from the 1830s, the links with coal, steam power and railroads made iron ever more important, providing Western European economies with a crucial mid-19th century boost. The pro-industrial consensus of the British ruling elites held until the end of the Napeoleonic Wars. The most contentious economic policy issue of the day was the Corn Laws, introduced in 1815 in response to pressure from landed interests, and repealed in 1846. The immediate benefit of repeal was the provision of abundant and inexpensive food, alleviating hunger and preventing dissent. This was a case of landed vs. manufacturing interests, landed interests controlling the state and blocking change by for all practical purposes imposing a steep tax on workers and manufacturers by putting a minimum price tag on wheat, channeling resources away from productive sectors like iron (Hobsbawm 1969:120; Judd 1996:58pp; Pugh 1999:101).12 Whig governments were pro-industry, but there was no political consensus on repeal. At the same time, their reform hunger drove vested interests into the arms of the Tories (Bairoch 1993:21; Chang 2002:23; Lloyd-Jones 1990:598; Lloyd-Jones & Lewis 1998:49p; Pugh 1999:52). Thus, repeal required the consensus of Whigs and Tories. The mid-1830s economic crisis put free trade back on the political agenda. Cotton textiles could no longer serve as the engine of the economy, but vested interests were preventing new industries from replacing it, among other things by placing artificial restrictions on the expansion of markets. The 1837-42 crisis brought falling profits and rising unemployment. Iron and coal was hit particularly hard. To future PM Robert Peel (1841-46) this was a crisis of artificial trade barriers and underconsumption, thus caused by the Corn Laws. Only a conservative government, itself part of the vested agricultural interests, would be strong enough to go against the same interests (Lloyd-Jones 1990:599; Lloyd-Jones & Lewis 1998:51pp; McLean 1990:280; Pugh 1999:63).13 12

Regressions suggest that the Corn Laws raised living costs by 8-14% (1820-45) and that repeal could have raised real wages by 12.3-23.3% (Lindert 2003:329; O’Rourke 1994:133). 13 Robert Peel established an agenda in which repeal became the next logical step: Lowering import duties, 1842 and 1845; reintroduction of income tax, 1842; Bank Act, 1844. Further, the 1845-46 Irish potato famine made Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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That policies of structural change are risky is illustrated by the fact that it led to the Tories splitting, with two thirds of the party voting against repeal. Yet, a full third of Tory MPs, in a Parliament where 80% of the MPs belonged to the landed classes, actually voted for a repeal they had voted massively against only four years earlier (McKeown 1989:356; Pugh 1999:69p). But there were other problems. Social cohesion had dropped dramatically, and by 1832 Britain was on the brink of social revolution. Quoting Hobsbawm (1969:72): “At no other period in modern UK history have the common people been so persistently, profoundly and desperately dissatisfied.” Yet, while France underwent two revolutions and a coup d’etat, Britain opted for reform. Protest and dissent was channeled into institutionalized forms, with the 1832 franchise extension key.14 Post-1832 British regimes could rely on an increasing groundswell of cohesion, and policy-making could be pursued without fear of revolution. While unrest lasted throughout the 1840s, ending in 1848 when the government countered a Chartist rally by recruiting 100,000 volunteers, the 1840s saw a social calm re-impose itself (Pugh 1999:59pp). The potentially revolutionary middle class of 1832 had come down on the side of the traditional elites, for social and political stability. In 1848, with Europe plagued by revolutionary rebellions, Britain saw no reaction (Evans 1983:218; Hobsbawm 1969:77; Pugh 1999:48pp,71p; Tilly 1995:163). There was something peculiarly British to it. Contentious issues were resolved within the existing system. A parliament dominated by landowners moved towards free trade and incorporated the middle classes into the power structure while the rest of Europe was on fire. And problems were settled within the confines of the institutional structure, without Parliament falling prey to vested interest pressure. While not supremely strong in either consensus or cohesion, Britain was still far better endowed than most. A complete lack of cohesion explains the inability to curb vested interests in France. This seriously hampered the development both of a modern iron industry and of the railroad network so vital for the iron industry. Governments had little leverage. Bourbon (1815–30) and July Monarchy (1830–48) administrations were weak. Staying in power without triggering revolution was hard enough without challenging vested interests too. Also, the interests of the ruling elites often overlapped with those of the most powerful vested interests, or were even part of the same interests. While France underwent periods of stability, in crisis there was no groundswell of cohesion to uphold the regime (Price 1993:160pp; Trebilcock 1981:187; Wright 1995:146p). To the extent that consensus did exist, this was a consensus about preserving the status quo, not change. The power balance among the ruling elites was tenuous. 1830-40 was permanently unstable, with government ministries averaging less than a year. When the king garnered support, it was from the right, that is, from those the least interested in change. Hence, the 1840-48 Guizot administration was strong, but committed to not rocking the boat (Price 1993:168). Furthermore, Guizot’s strength derived from extensively employing personal side-payments to secure support, offering Deputies in the Chamber government bureaucrat positions while still being Deputies. At the most extreme, a third of the Deputies

the consequences of high grain prices extremely obvious (Bairoch 1993:21; Hoppen 1998:93,127pp; McKeown 1989:365; Pugh 1999:38p,69,91). 14 The 1832 Reform Act doubled the size of the franchise to roughly 18% of adult males. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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also had salaried government posts, making the bureaucracy a very heavy vested interest (Wright 1995:113). The result was an inability, and often an unwillingness, to pursue structural change. The railroad bureaucracy could easily block attempts at railroad reform, which meant that France did not get a proper railroad network until the 1852 coup d’etat of Louis-Napoleon (Smith 1990). The iron industry was also hampered by a very inconsistent pattern of import tolls. France was in short supply of coal for iron-smelting, and completely dependent on imports. But mining interests managed to push through import tolls on coal, thus imposing a steep tax on French iron, which was probably the European iron industry most desperately in need of coal (Trebilcock 1981:187). And pressure from vested interests in metallurgy led to the promotion of wood for iron-smelting so as not to go against the interests of charcoal ironproducers, for all practical purposes an explicit sheltering of the most archaic part of the industry (Trebilcock 1981:186p; Wright 1995:147p).15 With respect to social cohesion, what stood out was how vulnerable the country seemed. Economic crises were instrumental in bringing down the Bourbon Monarchy, the July Monarchy and the Second Republic, illustrating the lack of leverage of regimes deficient in legitimacy. With the support of core groups withdrawn, the regime had no reserves of social cohesion to fall back on. Not even a democracy could muster much support. The Second Republic was undermined by the 1848-51 economic crisis, yielding a “shock-like decline in industrial production” (Berger & Spoerer 2001:293p,319), paralyzing railroad construction and wreaking havoc on coal and iron.16 Riots prolonged and intensified the crisis (Price 1993:176; Wright 1995:126pp,151). In 1851, as Louis-Napoleon brought down the republic, there was little resistance. During economic crisis, the tenuous balance holding France together simply ceased to exist (Cameron & Neal 2003:234; Furet 1995:351,380pp; Price 1993:168p; Wright 1995:109p). The lack of social cohesion meant that preventing revolution was always the main concern. In crisis, there was no shared vision that disagreements be resolved through peaceful means and institutional channels. There was no widespread belief that the regime cared about the people. Any famine or economic downturn resulted in crisis. Consequently, governments were left with very little leverage in policy-making. And hence, no structural change was pursued, the industry left to fend for itself (Furet 1995:386; Price 1993:160pp; Wright 1995:147).

Chemicals The late 19th century saw major structural change in the guise of a host of new knowledge-intensive industries. Among these, the chemical industry best signals the waning of Britain as a dominant power and the rise of Germany. In 1850, Britain had the largest chemical industry in the world, and in 1856 invented the first synthetic dye. Yet, almost all 15

The exception was Napoleon III (or Louis-Napoleon until his coup d’etat), who had more autonomy than any French ruler since Bonaparte. This enabled him to go against vested interests on tariffs, railroad construction and financial reform, proving beneficial to iron and the overall economy. Consensus was achieved, but by removing the opposition. Yet, in the 1860s it became clear that the consensus behind his coup depended on tacit power alliances that now seriously constrained him. 16 Coal production dropped 20%, iron production 30% (Cameron & Neal 2003:234).

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subsequent inventions were German. By the end of the century, the German share of synthetic dyes was 85-90%. As the first science-based industry, chemicals had different requirements than traditional industry, primarily regarding patenting and education. Also, as a new British industry facing stiff foreign competition, free trade was no advantage, especially not when confronted with rising tariff barriers abroad. However, an absence primarily of political consensus made it very hard to pursue policies of structural change. And with the franchise extensions of the late 19th century, political elites, primarily on the right, sought to manufacture social cohesion by emptying the domestic political sphere of controversial content, relying on Queen, country and imperial rhetoric, for all practical purposes gridlocking economic policy-making. There was no consensus on education reform. The Liberal Party favored reform, but had to placate the contradictory interests of the Church of England and the Nonconformists (Hoppen 1998:598p; Lindert 2003:330; Pugh 1999:101). The Conservative Party was against. First they could not see why it mattered – in the past it had not. Second, they were afraid of awakening the masses. Third, it would cost massive amounts of money. Finally, aristocratic interests considered technology as beneath the universities. Scientific pursuit was a gentlemanly activity, separate from industry. Hence, reform was late, watered down and cheap. And hence, England (Scotland had its own policies) failed to churn out a sufficient amount of experts for the new industries, chemicals in particular (Evans 1983:324; Hoppen 1998:597pp; Landes 1969:344p; 1998:290; Lindert 2003:330; Mokyr 1990:199). An unorganized chemical industry, lacking in high-skilled and prestigious experts, was unable to push for patent reform. It was also countered by a powerful textile industry and by traders (Murmann 2003:187pp). Further, protectionism was associated with high food prices, starvation and the selfish interests of the landed aristocracy. The major new voter groups of 1867 were pro-free trade. That the staunchly free-trade Liberals dominated politics made tariff reform impossible to such an extent that the Conservatives shunned the issue even when in power. Even with British industries struggling and the economy in decline, when raised in 1906, the tariff issue scored the Liberals a landslide win, killing any notion of reform (Judd 1996:150,187pp; Klug 2001:221; Pugh 1999:115,145). To the extent that consensus existed, it was one of preserving the rapidly more obsolescent status quo, not structural change. Towards the end of the century, issues of social cohesion became relevant. The 1884-85 election reform enfranchised over 60% of the male population. To woo the lower classes, the Conservative Party consciously sought to manufacture cohesion by taking controversy out of politics by shifting the focus away from problems at home. Hence, economic and industrial politics disappeared off the scene. Against a radical Liberal Party, the Conservatives put up a staunch defense of private property, against radicalism, Irish nationalism and socialism. They courted the trade unions, and rejected the puritanism of the liberals on alcohol. Above all, they became the party of patriotism, Imperial ambition, and of British superiority. Previous decades had been about domestic politics; free trade, reform and retrenchment. The future was about external threats – colonial rivalry, naval race, invasion threats. The enthusiasm shown for the Empire by ordinary citizens, ensured that late 19th century British politics would to a great extent focus on Imperial endeavors rather than schooling, patents and trade issues (Hoppen 1998:649; Pugh 1999:107pp,129pp). If this was cohesion, it was a nervous and jingoistic cohesion, crafted so as to take focus away from the real, and politically far more tenuous, problems of the country.

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In Germany, the ability to pursue economic policy unhindered by vested interests cannot easily be ascribed to cohesion. As in Britain, cohesion was manufactured by emptying politics. The Kaiser’s Weltpolitik, while reflecting his own delusions of grandeur, was also an attempt to draw attention away from arch-conservative Junkers, breakneck industrialization, social unrest, a rising Social Democratic Party, and a growing working class. It worked, the middle classes identifying themselves with Germany, taking pride in foreign policy, and also the working class partially following suit. Yet, many argue that the growing tensions would never be resolved within the existing framework, World War I essentially coming to the rescue. It illustrates the problems faced by German chancellors, with foreign policy diversions creating cohesion and taking the focus off domestic issues (Fulbrook 1992:117,140pp; Schulze 1998:118pp,173pp; Stürmer 2002:45; Tipton 2003:90,159pp,186; Wehler 1985:57pp,89p,102pp,137,177). At first glance, consensus was also low. Bismarck ran Germany on a day-to-day basis, avoiding political alliances, seeking to balance diverging interests, switching overnight from free-trade to protectionism because of a need for allies. Thus, economic problems were subordinate to political problems. While skillful in manufacturing alliances, much of his maneuvering was essentially just maneuvering. He did not oppose modernization or industrialization, but also had no commitment to it. Success consisted of striking a precarious balance between powerful social forces, preserving some sort of uneasy status quo. As the socialists rose, the lack of consensus became ever more obvious (Rogowski 1989:40; Tipton 2003:159pp; Wehler 1985:57pp). Yet, consensus thrived on another level. The bureaucracy was manned by highly educated experts supportive of science and industry and responsive to the needs of chemicals in particular. When German industries pushed for a patenting system, chemicals was explicitly taken into consideration. A vocal and united lobbying effort secured the dye industry a special clause, with chemical firm BASF even involved in the actual formulation of the law (Freeman & Soete 1999:90; Murmann 2003:187; Murmann & Landau 1998:42). Murmann (2003:167) attributes particular significance to Friedrich Althoff, who between 1882 and 1907 handled all appointments at Prussian universities and technical universities. His beliefs in the importance of scientific and technological research and education made him an invaluable ally whenever the dye industry lobbied for educational facilities. The relationship between Althoff and the Verein deutscher Chemiker was close. The dye industry also had excellent access to the Prussian Landtag, where one of the Bayer directors had a seat, which he used to fight for education spending and the dye industry in general. He was also a close friend of the Prussian finance minister and of Althoff, and could easily coordinate initiatives with key players. Hence, while not articulated by Bismarck, a strong pro-industry consensus did exist, as the bureaucracy consciously responded to the needs of new industry. Also, among the reasons why vested interests could not dominate German politics was that these interests were far weaker than in Britain, and that the new and rising industries were stronger, better organized, could draw upon more experts, and consequently were far better at gaining the ear of policymakers (Freeman & Soete 1999:90; Murmann 2003:167; Murmann & Landau 1998:40; Schulze 1998:183). Also, occasionally industrially beneficial policies were initiated for military, not economic reasons, as was partially the case with the education system (Kindleberger 2000:122; Landes 1969; Lenoir 1998:23p; Lindert 2003:332p). Still, German

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success to a major extent stemmed from a consensus within the state as to the importance of the new industries.

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The Automobile Industry Of the five industries, the automobile industry is the exception. It had a massive economic impact at a time when old industries were stagnating. The major breakthrough – mass production – had revolutionary effects.17 However, this was a process technology, not a product technology. It primarily allowed for faster and cheaper production. Success depended less on technological sophistication than on bringing fairly familiar technologies as cheaply as possible to the market. Success was Smithian, depending on demand, access to capital, and market size, rather than Schumpeterian. For this reason, I look only briefly at one country – the US, accounting for 70-90% of the world’s pre-World War II production (Modelski & Thompson 1996:102). This is probably the industry where consensus and cohesion was the least important. Granted, a political consensus did emerge, going against the vested interests of traditional US industries. The Republicans left their protectionist platform in 1928, and in 1932, Democratic president-to-be Franklin D. Roosevelt came down on the side of free-trade. By 1936, consensus was decisively in favor of capital-intensive industry (i.e. car-manufacturing) (Ferguson 1984; Hiscox 2002). However, at this stage the US car industry had reigned supreme for a couple of decades already. Thus, this was hardly what triggered growth in the first place. Granted, during the 1920s, infrastructure developments fueled growth in the car industry. Laissez-faire presidents persistently reduced public expenditures, but not for road construction. No industry employed more men or spent more money. By 1929, total expenditures on roads and streets (local, state and federal) amounted to $2 billion a year, or a full 2% of GNP, behind education only in terms of public expenditures (Atack & Passell 1994:578; Brinkley 2003:333p; Moss 1995:138). While modest by today’s standards, to quote Leuchtenburg (1993 [1958]:184): “Road building gave the auto industry a larger government subsidy than railroads received in their entire history”. This would have been impossible if not for a change in the overall consensus, signaled by the rise of the Progressive party by the turn of the century and the influx of progressivist ideas with both Democrats and Republicans. Also, strongly pro-business governments provided the industry with highly favorable conditions. During the Republican administrations of Harding (1920-23) and Coolidge (192328), Secretary of Commerce (later president) Hoover stimulated big business by encouraging trade associations, information sharing, and acting as a “clearing-house for information on business opportunities abroad” (Heilbroner & Singer 1994:133; Rae 1984:69). Investments and profits soared. Attitudes towards the car were overwhelmingly positive, with industrialists like Henry Ford rising to folk hero status, and others like Chrysler, Durant, Willys and Nash not far behind (Moss 1995:142; Parrish 1994:52; Rae 1984:69). Yet, while infrastructure and favorable regulations may have fueled this growth, it hardly sparked it in

17

Reducing the assembly time of a T-Ford by 88%, from 12h30m to 1h32m (Brinkley 2003:153).

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the first place. At this time, the US car industry was already by far the world’s largest. Consensus and cohesion contributed, but Smithian arguments hold more explanatory power.

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Information and Communication Technology (ICT) Industries This final section must be somewhat speculative, as ICT developments are still very much on-going. Also, a distinction must be made between manufacturing of ICT equipment and the services employing such equipment. ICT manufacturing has exhibited stellar productivity growth, but is too small a sector to have a big impact on the economy. Instead, the main impact stems from its application in the ICT using services, which account for more than a quarter of GDP. Hence, far above average productivity growth rates in this sector has considerably increased overall growth. This is where the US has leapt ahead (van Ark & Inklaar 2003:11; van Ark, Inklaar & McGuckin 2003:17; Yusuf & Evenett 2002:105). In ICT manufacturing, the US and Japan are both winners. But in utilizing ICTs in the services, the US is a success and Japan a laggard.18 For the past decades, US politics has not looked consensual at all. But through the presidencies of Carter, Reagan, Bush and Clinton, certain policies have gone through unhindered by vested interests. With respect to deregulation and liberalization, political consensus has been strong, and presidents from different parties have taken on each others’ legacies. While the current economic crisis suggests that deregulation and liberalization have gone too far, by the late 1970s Western economies were bogged down by inefficiencies and rigidities. Pressure built in favor of deregulation, tax cuts and liberalization. Jimmy Carter started the process. Ronald Reagan continued it, latching onto Margaret Thatcher’s ideas. Controversial at first, by the end of the Cold War even former socialist countries subscribed to what had become a neo-liberal economic orthodoxy. Eight years of Reagan moved large amounts of economic decision-making powers from politicians to the market (Castells 2000a:138; Friedman 2000:104p; Knutsen 1999:288; Krugman 1994:69pp,78; Micklethwait & Woolridge 2004:88). The pervasiveness of the new orthodoxy can be seen with Reagan’s successors. Democrats and Republicans agreed on removing business regulations, cutting welfare programs, deregulating S&L banks, etc. Bill Clinton, who explicitly declared to reverse 12 years of Republican policies, continued and extended on it, declaring “the end of welfare as we know it” and “the end of big government”. Friedman (2000:106) portrays the differences between Clinton and Bob Dole during the 1996 presidential election as slight. They both acknowledged being subject to international capital-flows and that deviating far from the preferences of international investors would unduly harm the economy. There was broad agreement on low tariffs, removing foreign investment restrictions, removing quotas and domestic monopolies, increasing exports, deregulating capital markets, opening banking and telecommunication systems to private ownership and competition. Clinton extended deregulations to the international economy and became one of the world’s foremost

18

For this chapter I emphasize consensus, as the differences on cohesion seem unimportant with respect to the growth of ICT-based industries and services.

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promoters of an open international, liberal economic world order. Here, he relied on bipartisan consensus (Castells 2000a:140pp; Rosecrance 1999:146). The consequence was a US that more easily took advantage of new technologies, as computers, fax machines, printers, voice recognition software and other technologies greatly improved the quality of US services and manufacturing (Rosecrance 1999:145). A lack of political consensus is the reason why vested interests, or an “iron triangle” of politicians, bureaucrats and special interests, have been so powerful in Japan. True, the LDP reigned supreme for four decades, their policies carried out in parliament without much opposition. However, before branding this consensus, beware that the government has typically been under strict Party control, with politics conceived by the Party, in conjunction with the bureaucracy and vested interests. Bills and budgets require instruction of and final approval by the Party. PMs come and go, controlled by leaders behind the scenes, people devoted to the status quo rather than reform. It is behind the scenes that we have to look for consensus (Castells 2000b:225pp; Grimond 2002; Sakakibara 2003:47pp). Quoting Grimond (2002): “Its [LDP] two main purposes – rent-seeking and self-perpetuation through electoral success – have both flourished under the status quo. Almost every interest-group imaginable is represented within its ranks, and it takes care to look after them.” LDP predominance has rested on a coalition of interests and factions organized around the LDP and rigged by corruption. Hence, LDP leaders have rarely been pro-reform. Japan is a nation of small shopkeepers. These are the backbone of Japanese retailing and the backbone of the LDP (Lewis 2004:46p; Sakakibara 2003:138p). Regulations are responsible for the low level of productivity in the non-export sectors, but reform would have put thousands of firms out of business and hundreds of thousands out of work. This is not easily implemented in a system with as strong vested interests as the Japanese. Cuts in the labor force have been marginal, with no major restructuring of business (Gilpin 2000:281; Gordon 2003:327; Grimond 2002). Services has given rise to enormous amounts of bad bank loans. It is within services that we find what The Economist (2004:81) labels “‘zombies’ – companies that are competitively dead, but sustained by their banks, continue to walk the Earth and give healthier firms nightmares.” A more genteel economy than the US, it is also less efficient at creative destruction and less well adapted to structural change. Emphasis has been on safeguarding the weak (Castells 2000a:191; Friedman 2000:60; Fukuyama 1995:165; Gilpin 2000:282; Grimond 2002). With politics shaped by the iron triangle, it has been exceedingly hard to muster the consensus to go against these interests. Blocking deregulation, liberalization and the opening up of Japan to an integrated, global economy, those sectors that have had the potential to utilize ICTs the most (banking and finance) have been deprived of the opportunity and incentive to, falling far behind the US (Gilpin 2000:280; Gordon 2003:325; Rosecrance 1999:124). To the extent that there has been a Japanese political consensus, this has been a consensus about preserving the status quo, not one of structural change. This may even have served Japan well during a period of structural stability and catch-up in mass production export industries. During times of structural change, it has become a liability. Granted, economic and political reform has been on the agenda since at least 1985, and former PM Junichiro Koizumi built his political platform around reform, at least heightening the focus around the need for reform (Aoki 1995:xii; Emmott 2005; Fukushima 1996:58pp; Gordon 2003:321pp; Grimond 2002; OECD 2001b:13,53). Still, there is little doubt that the lack of consensus around reform has made it far harder to benefit from ICT-based growth than in other countries.

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CONCLUSIONS Cohesion is no neat and easy variable. However, it is theoretically interesting, and it would be a shame not to look into the potential relationship between cohesion and growth, just because it is hard to put to a rigorous test. The chapter suggests a relationship: Policies of structural change are politically risky, and countries that are cohesive stand the best chance of pursuing such policies. This is illustrated by all cases, with the partial exception of the car industry. It is not that they are all characterized by political consensus and social cohesion, or conversely the lack of both. But in each of the cases, at least one of the two provided a powerful stimulus to or a strong block against structural economic change. In Britain, consensus rather than cohesion secured the early Industrial Revolution, even if social cohesion rose markedly and certainly contributed. In the mid-19th century, renewed social cohesion guaranteed stability for governments to carry out risky policies without the fear of revolution so prevalent on the other side of the Channel. In France a lack of both made structural change impossible, because it was blocked by powerful vested interests and because there was no groundswell of social cohesion to rely upon whenever economic crisis occurred. The only moderately strong French regime since Napoleon Bonaparte, was the Second Empire of Napoleon III. It was also the first French regime with the power and willingness to go against vested interests since Bonaparte. In Germany, a lack of social cohesion was countered by a strong pro-industry administrative political consensus. Yet, in Britain, no structural change was possible – because the political consensus favored the status quo and because social cohesion was dropping to such an extent that it had to be manufactured by emptying politics of all substance and replacing it with Imperial rhetoric of Queen, country and colonies. Both modern-day US and Japan have been fairly high on social cohesion. Here, the difference lies in the level of consensus. Whereas in the US liberalization and deregulation have been bipartisan issues, the Japanese “iron triangle” has efficiently blocked similar policies. The car industry only vaguely conforms. Indeed, political consensus and social cohesion do apply, but primarily at a time when the industry had already become the world’s largest. This was a case of Smithian rather than Schumpeterian growth, hence dependent on demand, market size, and access to capital rather than technological sophistication. For a variable as loosely defined as cohesion, we cannot expect history to play itself out in the exact same way across different industries and time periods. What we can expect, and what we see, is a loose pattern. We see something that is certainly an important component to growth and development, even if there may be uncertainty about exactly how it manifests itself and what the exact mechanisms are. This chapter suggests that one relevant mechanism has to do with the state’s ability to pursue policies of structural change. The empirical evidence bears this out. It suggests a mechanism where success is never final, but has to be created and re-created. And where success might breed failure as easily as success. This is exactly where cohesion has the potential to make a difference.

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REFERENCES Aoki, M. (1995). Information, Corporate Governance, and Institutional Diversity. Oxford: Oxford University Press. Ark, B. van, & Inklaar, R. (2003). ICT Production and Use in Germany, Japan and the United States. http://www.eco.rug.nl/medewerk/inklaar/papers/ictgermanyjapan.pdf. Ark, B. van, Inklaar, R., & McGuckin, R. H. (2003). ICT and Productivity in Europe and the United States. http://www.eco.rug.nl/medewerk/inklaar/papers/ictdecompositionrev2.pdf. Atack, J.& Passell, P. (1995). A New Economic View of American History from Colonial Times to 1940. New York: W.W. Norton. Bairoch, P. (1982). International Industrialization Levels from 1750 to 1980. The Journal of European Economic History 11, 2, 269-333. Bairoch, P. (1993). Economics & World History. Chicago: University of Chicago Press. Berger, H., & Spoerer, M. (2001). Economic Crises and the European Revolutions of 1848. The Journal of Economic History, 61, 2, 293-326. Best, G. (1982). War and Society in Revolutionary Europe. Bungay: Fontana. Brinkley, D. (2003). Wheels for the World. New York: Viking. Brose, E. D. (1998). Technology and Science in the Industrializing Nations. New Jersey: Humanities Press. Cameron, R., & Neal, L. (2003). A Concise Economic History of the World. Oxford: Oxford University Press. Castells, M. (2000a). The Rise of the Network Society, The Information Age. Malden: Blackwell. Castells, M. (2000b). End of Millennium, The Information Age. Malden: Blackwell. Chang, H.-J. (2002). Kicking Away the Ladder. London: Anthem Press. Colley, L. (1992). Britons: Forging the Nation 1707-1837. London: Yale University Press. Collins, J. (1995). The State in Early Modern France. Cambridge: Cambridge University Press. Darnton, R. (1982). The Literary Underground of the Old Regime. Cambridge: Harvard University Press. Dayton-Johnson, J. (2001). Social Cohesion and Economic Prosperity. Toronto: James Lorimer. De Long, J. B. (2000). Overstrong Against Thyself. In M. Olson, & and S. Kähkönen (Eds.), A Not-So-Dismal Science, (pp. 138-167). Oxford: Oxford University Press. Economist, The (2004). Dead firms walking. September 25th-October 1st 2004, 8394(372), 81. Emmott, B. (2005). The Sun Also Rises. The Economist, Oct 6 2005. http://www.economist. com/surveys/displaystory.cfm?story_id=E1_QQVQNQQ. Evans, E.J. (1983). The Forging of the Modern State. Harlow: Longman. Ferguson, T. (1984). From Normalcy to New Deal. International Organization, 38, 41-94. Freeman, C., & Louçã, F. (2001). As Time Goes By. Oxford: Oxford University Press. Freeman, C., & Perez, C. (1988). Structural Crisis of Adjustment, Business Cycles and Investment Behaviour. In G. Dosi, C. Freeman et al. (Eds.), Technical Change and Economic Theory (pp. 38-67). London: Pinter Publishers. Freeman, C., & Soete, L. (1999). The Economics of Industrial Innovation, Cambridge: MIT Press.

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Friedman, T. (2000). The Lexus and the Olive Tree. New York: Anchor Books. Fukushima, K. (1996). The Revival of ‘Big Politics’ in Japan. International Affairs, 72, 1, 53-72. Fukuyama, F. (1995). Trust. New York: Free Press. Fukuyama, F. (1998). The Great Disruption. New York: Free Press. Fulbrook, M. (1992). A Concise History of Germany. Cambridge: Cambridge University Press. Furet, F. (1995). Revolutionary France 1770-1880. Oxford: Blackwell. Gilpin, R. (1987). The Political Economy of International Relations. Princeton: Princeton University Press. Gilpin, R. (2000). The Challenge of Global Capitalism. Princeton: Princeton University Press. Gordon, A. (2003). A Modern History of Japan. Oxford: Oxford University Press. Grimond, J. (2002). A Survey of Japan. The Economist, April 18th 2002. http://www. economist.com/surveys. Heilbroner, R., & Singer, A. (1994). The Economic Transformation of America Since 1865. Fort Worth: Harcourt Brace. Hiscox, M. J. (2002). International Trade & Political Conflict. Princeton: Princeton University Press. Hobsbawm, E.J. (1969). Industry and Empire. London: Penguin. Hoffman, P., & Rosenthal, J.-L. (2000). New Work in French Economic History. French Historical Studies, 23, 3, 439-453. Holsti, K. J. (1996). The State, War, and the State of War. Cambridge: Cambridge University Press. Hoppen, K. T. (1998). The Mid-Victorian Generation. Oxford: Oxford University Press. Hudson, P. (1992). The Industrial Revolution. London: Edward Arnold. Judd, D. (1996). Empire. New York: Basic Books. Kindleberger, C. P. (2000). Comparative Political Economy. Cambridge: MIT Press. Klug, A. (2001). Why Chamberlain Failed and Bismarck Succeeded. European Review of Economic History, 5, 219-250. Knutsen, T. (1999). The Rise and Fall of World Orders. Manchester: Manchester University Press. Krugman, P. (1994). Peddling Prosperity. New York: Norton. Landes, D. (1969). The Unbound Prometheus. New York: Cambridge University Press. Landes, D. (1998). The Wealth and Poverty of Nations. New York: W.W. Norton. Lenoir, T. (1998). Revolution from above. The American Economic Review, 88, 2, 22-27. Leuchtenburg, W. E. (1993). The Perils of Prosperity, 1914-1932. Chicago: University of Chicago Press. [1958] Lewis, W. W. (2004). The Power of Productivity. Chicago: University of Chicago Press. Lindert, P. H. (2003). Voice and Growth. The Journal of Economic History, 63, 2, 315-350. Lloyd-Jones, R. (1990). The First Kondratieff. Journal of Interdisciplinary History, 20, 4, 581-605. Lloyd-Jones, R., & Lewis, M. J. (1998). British Industrial Capitalism since the Industrial Revolution. London: UCL Press. McKeown, T. J. (1989). The Politics of Corn Law Repeal and Theories of Commercial Policy. British Journal of Political Science, 19, 3, 353-380.

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McLean, I. (1990). ‘The Politics of Corn Law Repeal’: A Comment. British Journal of Political Science, 20, 2, 279-81. Magnusson, L. (2009). Nation, State and the Industrial Revolution. New York: Routledge. Melton, J. van Horn (2001). The Rise of the Public in Enlightenment Europe. Cambridge: Cambridge University Press. Micklethwait, J., & Woolridge, A. (2004). The Right Nation. New York: Penguin. Mill, J. S. (1904). A System of Logic. London: Longman’s. [1843] Modelski, G., & Thompson, W. R. (1996). Leading Sectors and World Powers. Columbia: University of South Carolina Press. Moe, E. (2007). Governance, Growth and Global Leadership. Aldershot: Ashgate. Mokyr, J. (1990). The Lever of Riches. Oxford: Oxford University Press. Mokyr, J. (1999). Editor’s Introduction. In J. Mokyr (Ed.), The British Industrial Revolution (pp. 1-127). Boulder: Westview Press. Mokyr, J. (2002). The Gifts of Athena. Princeton: Princeton University Press. Morgan, K. (1999). The Birth of Industrial Britain. London: Longman. Moss, G. D. (1995). The Rise of Northern America. Upper Saddle River, NJ: Prentice Hall. Murmann, J. P. (2003). Knowledge and Competitive Advantage. Cambridge: Cambridge University Press. Murmann, J. P., & Landau, R. (1998). On the Making of Competitive Advantage. In A. Arora, R. Landau, & N. Rosenberg (Eds.), Chemicals and Long-Term Economic Growth (pp. 27-70). New York: John Wiley & Sons. Nayyar, D. (2007). Foreword. In H-J. Chang (Ed.), Institutional Change and Economic Development (pp. xvii-xx). New York: United Nations University Press. North, D. C., Wallis, J. J., & Weingast, B. (2007). A Conceptual Framework for Interpreting Recorded Human History. Working Paper 75, Mercatus Center, George Mason. OECD (2001a). The Well-being of Nations. Centre for Educational Research and Innovation. Paris: OECD. OECD (2001b). OECD Economic Surveys: Japan. Paris: OECD Publications. Olson, M. (1982). The Rise and Decline of Nations. London: Yale University Press. O’Rourke, K. (1994). The Repeal of the Corn Laws and Irish Emigration. Explorations in Economic History, 31, 120-138. Parrish, M. E. (1994). Anxious Decades. New York: W.W. Norton. Price, R. (1993). A Concise History of France. Cambridge: Cambridge University Press. Pugh, M. (1999). Britain Since 1789. New York: St. Martin’s Press. Putnam, R. (1995). Bowling Alone. Journal of Democracy, 6, 1, 65-78. Rae, J. B. (1984). The American Automobile Industry. Boston: Twayne. Roche, D. (1998). France in the Enlightenment. Cambridge: Harvard University Press. Rogowski, R. (1989). Commerce and Coalitions. Princeton: Princeton University Press. Root, H. (1991). The Redistributive Role of Government. Comparative Studies in Society and History, 33, 2, 338-369. Rosecrance, R. (1999). The Rise of the Virtual State. New York: Basic Books. Rostow, W. W. (1978). The World-Economy. London: Macmillan Press. Sakakibara, E. (2003). Structural Reform in Japan. Washington DC: Brookings Institution Press. Schulze, H. (1998). Germany: A New History. Cambridge: Harvard University Press.

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Schumpeter, J. (1934). The Theory of Economic Development. Cambridge: Harvard University Press. Schumpeter, J. (1942). Capitalism, Socialism and Democracy. New York: Harper Torchbooks. Smith, C., Jr. (1990). The Longest Run. The American Historical Review, 95, 3, 657-692. Stürmer, M. (2002). The German Empire. Modern Library, New York. Swilling, M., & Annecke, E. (2010). Just Transitions: Exploring Sustainability in an Unfair World. Cape Town: University of Cape Town Press. Tilly, C. (1995). Popular Contention in Great Britain. Cambridge: Harvard University. Tipton, F. B. (2003). A History of Modern Germany Since 1815. Berkeley: University of California Press. Trebilcock, C. (1981). The Industrialization of the Continental Powers. London: Longman. Unwin, G., Unwin, P. S., et al. (1994). Publishing. In R. McHenry, & Y.C. Hori (Eds.), The New Encyclopædia Britannica, (vol 26, pp. 415-449). Chicago: Encyclopædia Britannia Inc. Wehler, H.-U. (1985). The German Empire 1871-1918. New York: Berg. Wright, G. (1995). France in Modern Times. New York: W.W. Norton. Yusuf, S., & S. J. Evenett (2002). Can East Asia Compete? Washington DC: World Bank and Oxford University Press Copublication.

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Chapter 3

WORLDWIDE RANKINGS IN ECONOMIC GROWTH: AUTHORS, INSTITUTIONS AND PUBLICATION TRENDS DURING 1992-2002 Vicente German-Soto∗ Facultad de Economía, Universidad Autónoma de Coahuila Unidad Camporredondo, Edificio “E”, Planta Baja. C.P. 25280, Saltillo, México

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ABSTRACT Economic growth is a highly important area for economists, governments and society. However, how much have we learned? Which individuals have more investigations? What journals made more contributions to economic growth? Which theoretical model is the most empirically tested? How is the hall of fame of economic growth institutions integrated? The aim of this chapter is to build a bibliographic analysis and offer a viewing of the current state of investigation of economic growth. Empirical work is based on 30 leading journals in Economics and database covers eleven years (1992-2002). As a result, I offer rankings of journals, individuals, institutions and countries. It is observed that the theoretical analysis dominated the merely empirical one in the economic growth field, while the endogenous theory had more publications than the exogenous theory. Also, I estimate a Logit model to try to explain the authors’ decision on the model used to analyze economic growth and its determinants. I think these rankings and trends highlighted by economic growth are a helpful guide to graduate students, faculty members, and academics, and also to measure the relevance of this topic.

INTRODUCTION The 1990s were characterized by a great quantity of studies on economic growth. This tendency was mainly driven by two factors: new mathematical models of the growth process ∗

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and the construction of new data sets. As a result, economic growth was conducted to an excellent position in the circles of academic discussion and it was so in the journals with a high ranking in Economics. However, this explosive expansion made it difficult to understand the current state of investigation and so did the bibliographical analysis. In this sense, I sought to answer some important questions such as How much have we learned up to this moment?, Whose contributions have been the most outstanding?, Which countries concentrate the greatest efforts?, and Which methods and variables have been most often used in investigations? I offer a consistent bibliographic perspective of both qualitative and quantitative changes in the economic growth field reviewing scientific publications of the main journals in Economics. I worked on the basis of a sample of leading journals in Economics. If I found that ‘economic growth’ was being discussed quite often in the most important journals, then I would have enough evidence for its relevance to Economics nowadays. The empirical investigation is based on 30 specialized journals in Economics and the database covers a period of eleven years, from 1992 to 2002. In addition, it considers the traditional rankings commonly offered in this kind of essays about authors, institutions and countries. Actually, bibliographical analysis practice is much extended. Some examples are Chung and Cox (1990), in Finance; Figlio (1994), about Empirical Economics; van den Bergh and Button (1997), in Urban Economics and Transportation; Baltagi (1998 and 2003), in Econometrics; Anselin, Rey and Talen (2000), Rey and Anselin (2000) and Dundorf et al. (2002) in Regional Science; Nijkamp and Poot (2002), about the wage curve, among others. Most of these surveys are concentrated in the publication patterns of the economists. For instance, Sauer (1988) introduced a consistent empirical analysis of the 140 academic economists associated to 7 of the 40 U.S. departments with the best ranking. Bairam (1994) reported a list of 30 institutions with the highest number of pages published in the top five journals of Economics. Lucas (1995) analyzed the ranking of the 733 economists that participate in Canadian universities. Scott and Mitias (1996) built up a ranking of the U.S. Economics departments and they made an average of the investigations concentrated in each department. Sarafoglou and Haynes (1996) analyzed the productivity of the Swedish university. Dusansky and Vernon (1998) evaluated the U.S. Economics departments using eight different rankings and four different methodologies. Elliot, Greenaway and Sapsford (1998) reported and discussed the results derived from the investigation of the national composition of contributors to the leading Economics journals in U.S. and Europe. Kalaitzidakis, Mamuneas and Stengos (1999) came along with a ranking of the European economic institutions as well as some countries based on the publications of a group of 10 journals of Economics from 1991 to 1996. Another work that focused on the patterns of specialization of the European scientific centers based on the bibliometrical indicators was the one made by Wichmann and Schwarz (1999). They also analyzed the strengths of the investigations of European scientific centers. Some other authors have discussed the ranking of one specific subject. For example, Colander (1989) studied some recent contributions to Economics from the idea of bringing some information to the non-specialists on what was being done in Economics. Isserman (1995) researched the future of regional science. Cribari-Neto, Jensen and Novo (1999) presented a ranking of institutions and investigators specialized in Econometric Theory from 1986-1996. Isard (1999) investigated some aspects of Physics and Chemistry to suggest possible parallel relationships in regional science. Rey and Anselin (2000) introduced an

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edition of the annual regional science rate. Also within the regional scope, Dundorf et al. (2002) built rankings of citations, authors and evaluators of the Regional Studies journal for the period 1981–2002. Baltagi (2003) updated the rankings by Hall (1990) and Baltagi (1998) about Econometrics; and Suriñach et al. (2003) offered the rankings of Urban and Regional Economics. Others have criticized the methods applied to the creation of several rankings. Beed and Beed (1996) discussed the limitations of the techniques elaborated to measure the quality of the publications. Different aspects of the classic ranking of institutions have also been investigated. For example, Frey and Eichenberger (1993) analyzed the differences between America (U.S. and Canada) and Europe (West) regarding their conception of Economics, how they practiced it and how professionals behaved. They found specific outstanding differences. Strathman (1992) made an overhaul of the theoretic, methodological and empirical investigations in regional science. Laband and Piette (1994) updated the database of Liewowitz and Palmer (1984) to investigate the variation of the Economics journals market in the period 1970-1990. They also examined the incursion of new journals and the changes throughout the period. Hondgson and Rothman (1999) examined the data of authors and publishers of 30 journals with the best ranking in Economics and found a high level of geographical concentration of publishers and authors. Collins, Cox and Stango (2000) introduced the data of publications for 50 programmers recently graduated with PhD in Economics and found that the product of publication was highly concentrated among the leading graduated programmers. The present investigation follows the studies commented above although it distinguishes them because the rankings made and analyzed here refer to a specific Economics field not previously considered in the bibliometric literature: economic growth. Among the specific objectives suggested in the current investigation are to measure and quantify the relevance of the topic ‘economic growth’ to Economics. On the other hand, I tackle an analysis of the main variables used to explain economic growth in order to infer the trends and patterns of publication in this area. These two exercises appear as innovative contributions compared to other studies of this nature. The chapter is structured in five sections. In this first section I have commented the introduction. The methodological description of the bibliographic analysis and the journal selection are put forward in the second section. Next, I present the obtained results of the different rankings. The following section explains the main trends in economic growth. Finally, conclusions are detailed in the last section.

METHODOLOGY AND DATABASE The method followed here is supported by four essential aspects: (1) the criteria used to select the group of journals and the time period; (2) the criteria for the article selection and measurement of the scientific production; (3) the used statistic techniques; and finally, (4) one set of aspects linked to the profile of the variables investigated by the authors.

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Journals Selection and the Time Period

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The definition of the most influential journals in Economics is based on the report of journals citation given by the Institute for Scientific Information (ISI).1 This report has two editions: mathematic sciences and social sciences. For each edition, diverse categories are specified like Economics, Law, Biology, Chemistry, among others. I used the ‘social sciences’ edition for year 2002 and the “Economics” category. Thus, I obtained the information from 166 journals, which I arranged from the highest to the lowest impact factor index.2 These selected journals share common objectives such as publishing investigations of high quality, but many of them are specialized in scientific publications of a field very different from economics, for example Journal of Human Resources, National Tax Journal, Energy Journal, and Insurance Mathematics Economics, where Economics only plays a peripheral role in their discussions. Since my purpose is to determine the relative importance of economic growth within economic science, I applied a filter with the aim of selecting journals more linked to economic science. This implied to accept only 76 journals. This sample of journals published articles from very diverse perspectives: theoretical, applied, empirical, regional, national or international. So, I based my investigation on 30 of these journals. On the other hand, the time period of analysis was decided as follows. I started in 1992 and finished in 2002. The start year was inspired by the influential work of Mankiw, Romer and Weil (1992) since I believe it as a renewal of the neoclassic current and its controversy on convergence. The finish year was selected by operative reasons because, when I started this project, 2003 had not finished yet. Moreover, in this way I could give empirical evidence for the huge increase of the scientific production of economic growth in the nineties.

Selection and Measurement of the Scientific Production I used direct sources of information available in printed version, mainly. This was a good method of identification (although it required much effort and time). Another used technique was the consulting of journals on-line. Also the JEL classification and the keywords were a great guide, although they were used neither by all journals nor for all the years of the sample. Another important matter was that I just considered the ‘articles’ section of the journals. That means that I did not consider sections such as Lectures, Features, Symposiums, Comments and Discussions, Review of Books, among others. Special editions, Conferences or Congresses were not included either. The idea was to estimate the allowed space to economic growth in comparison to other subjects in Economics. Following the tradition in other studies I standardized the journals taking into account the number of characters per page of the American Economic Review as a measure base = 1, and 1 2

This institute presents the most important worldwide publications based on different ratings of qualification like the impact factor, citations, and published articles, among others. The impact factor is a measure of the frequency with which the “average article” in a journal has been cited in a particular year or period. It is calculated as the ratio between citations and recent citable items published. Thus, the impact factor of a journal is calculated by dividing the number of current year citations to the source items published in that journal during the previous two years.

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so making an appropriate comparison of pages. Some other authors considered similar methods of standardization, such as Sauer (1988), Figlio (1994), Bairam (1994), Scott and Mitias (1996), Dusansky and Vernon (1998), and Kalaitzidakis, Mamuneas and Stengos (1999), among others. They argued that this journal had not had changes in the format of its edition during the period of study, which turned out to be practical to make comparisons. The standardization process included the traditional method applied to other studies of the same nature consistent with the average number of characters published in one page of the respective journal with the numeraire set equal to 1 for an American Economic Review page. Because of the heterogeneity of the format of the journals, the average of characters contained in one normal line was counted for each journal and then it was multiplied by the number of lines in one normal page.3

Statistic Techniques

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Most works about bibliographical analysis considered that the state-of-the-art had to be supported by quantitative techniques with the purpose of giving vigor and support to the analysis. In this sense, I applied both descriptive and causal analyses. Within the descriptive analysis, I used graphics, tables of relative and accumulated frequency and the counts of observations that allowed me to set a ranking of the analyzed variables, the central trend of the effects and its statistic signification. The causal analysis consisted of a valuation of variables on a kind of dichotomy quantification with the purpose of capturing the impacts and trends in economic growth. The main tool in this section is the use of a logistical regression model.

Variables: Profile and Definition A first set of investigated variables per article included journal’s name, authors, institutes, countries, number of pages, period of analysis and variables considered in each paper. From each journal I counted the total of pages and articles published each year in normal articles as well as the articles linked to economic growth. In this way I estimated the economic growth share in comparison with the rest of themes in Economics. Thus, I obtained an impact index for economic growth and its relative importance during the time. Following the tradition, in the case of n joints authors, each author received 1/n of the publication credit. In the case that one author had m affiliations, each affiliation received 1/m of the publication credit given to that author. This method was implemented by Sauer (1988), among others, who, by using a regression equation with the economist wage as a dependent variable, found that the economic value of the articles followed such rule. For the country variable I considered the geographical place of the institutional affiliation of the author. In addition, I studied the analysis period of the articles as long as they included an empirical exercise. If one article included two or more periods, then an exhaustive

3

One normal page (and one normal line) does not contain graphs, tables, equations or any other type of special symbols. Therefore, it consists of letters only.

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consideration was implemented to choose the most important.4 A similar process was used to detect the variables objects of the study when the hypothesis was not explicit in the work. However, most of the articles showed periods and variables explicitly. An overwhelming majority of articles linked a specific variable with rates of growth, making the work a lot easier. I picked up a second group of variables: type of investigation (empirical, theoretical or both), type of countries (developed, developing, or both), model (endogenous, exogenous and TFP5), and finally, the geographical scope of the study (regional, national or international).

BASIC RESULTS During the period 1992-2002, 12,825 articles were published in 280,351 pages (218,715 standardized pages) in the 30 journals. Table 1 shows that during those 11 years there was a total of 948 articles on economic growth attributed to 1,570 authors with a total of 16,686 standardized pages. The economic growth share was 7.39%, in terms of published articles, and 7.63% regarding standardized pages. The year with the highest levels of production on economic growth as regards standardized pages was 1996 with 2,268 pages, followed by 1997 with 1,781, and then 2000 (1,708) and 1999 (1,684), whereas the data about the number of articles pointed out that 1996 was also the one with the highest production with 134, followed by 1997 (101), 1998 (95) and 1995 (92). In general, the scientific production on economic growth in these 30 journals had the following conduct: an increasing tendency during the first years, a maximum limit (in 1996) and finally a decreasing tendency, but with a higher mean than at the beginning. Figure 1 shows this description.

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A. Articles 160 140 120 100 80 60 40 20 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Figure 1. Continued on next page. 4

This process implied to seek, in the problem, the objectives, the hypothesis and the conclusions, that period directly linked to the main objective of the article. 5 Total Factor Productivity. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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B. Number of pages 2.500,0 2.000,0 1.500,0 1.000,0 500,0 0,0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: own estimations.

Figure 1. Scientific production on economic growth, 1992-2002.

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I think that scientific production on economic growth was highly influenced by the resurgence of the neoclassical theory. The Mankiw, Romer and Weil (1992) article maybe encouraged discussions among scientists and increased publications in the journals. On the other hand, this behavior could not be due to the natural result of the economic scientific trend itself, because, whereas economic growth evolved forming a bell-shaped curve, economic science made it print a positive trend, lightly increasing over the time. Figure 2 illustrates this aspect.

A. Articles 1.300,00 1.250,00 1.200,00 1.150,00 1.100,00 1.050,00 1.000,00 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Figure 2. Continued on next page.

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B. Number of pages 23.000,0 22.000,0 21.000,0 20.000,0 19.000,0 18.000,0 17.000,0 16.000,0 15.000,0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source: own estimations.

Figure 2. Evolution of the scientific production in Economics, 1992-2002.

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Some basic statistics about authors, articles, pages and the conversion factors are reported in Table 1 –a shortened form of the journals name is offered in parentheses. This ranking (based on the impact factor index) and the information contained in our database allow us to answer a variety of questions. 1. What journals made more contributions about economic growth? Over the period 1992-2002, 948 articles on economic growth were published in these thirty journals. 10.76% of these articles were published by JEG, followed by JDE (7.49%), JED&C (6.75%), JME (6.54%), WD (6.33%), QJE (4.85), AER (4.85%), IER (4.64%), and EER (3.59%). Meanwhile, out of the total of standardized pages published on economic growth, 12.40% were published by JEG, followed by the journals JDE (8.28%), JME (6.77%), JED&C (6.27%) and AER (5.8%), among the most important ones. These journals may be considered as the main outlets for the economic growth area. 2. What is the distribution of the economic growth publications as regards empirical and theoretical analyses? Out of the total of published articles, 41.35% belonged to the pure theoretical field, 32.06% were for the empirical analysis and 26.48% included both theoretical and empirical analyses. 3. What is the distribution of publications on economic growth according to the type of country? Out of the 948 articles published on economic growth, only 570 included an application with empirical data, this quantity is about 60% of the articles. From this amount, 39.5% (225 articles) corresponded to developed countries, 26.5% (151 articles) to developing countries and 34% (194 articles) contributed with studies for both developed and developing countries. 4. What is the distribution of articles in economic growth according to the type of model? Out of the total of publications, 33.12% (314 articles) were classified under the endogenous growth theory, 23% (218 articles) under the exogenous growth

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6.

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7.

8.

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theory and only 5.48% used TFP methodology. The remaining articles (38.2%) used a different model. What is the distribution of publications about economic growth by geographical scope? Out of the total of publications on economic growth, only 586 articles were counted in some of the following three scopes: regional, national or international. From this amount, 339 articles (57.85%) corresponded to the international level, 180 (30.72%) to the national level and only 67 (11.43%) to the regional level in this sample of journals. What journals made more contributions as far as the empirical and theoretical analyses are concerned? For empirical work, the journals with the highest quantity of articles were WD with 54 articles (17.76%) and QJE with 20 articles (6.58%), while with 19 articles (6.25%) there were three journals: JEG, TWBER, and JDE. Following this ranking, we find CamJE with 18 articles (5.92%), OREP with 16 (5.26%), JME with 15 (4.93%), AER with 13 (4.28%), among others. Concerning theoretical work, the major contributions corresponded to JED&C with 50 articles (12.76%), followed by JEG with 49 (12.5%), IER with 39 (9.95%), JDE with 28 (7.14%), JME with 26 (6.63%), OEP with 22 (5.61%), and with 20 articles (5.1%) there are JIE and JPubE. For both theoretical and empirical studies, the most oustanding were JEG with 34 articles (13.55%), JDE with 24 (9.56%), AER with 23 (9.16%), JME and RESta with 21 each one (8.37%), JAE with 13 (5.18%), EER with 12 (4.78%), QJE and JED&C with 11 each (4.38%) and JPE with 9 (3.59%). What journals made more contributions according to the type of country? In developing countries, the journals with the highest number of articles were WD with 42 (27.81%), JDE with 25 (16.56%), TWBER with 12 (7.95%), JEG with 8 (5.3%), JEP with 7 (4.64%), while JME, RESta and TWE published 6 articles (3.97%) each one. In developed countries, the journals with more contributions were RESta with 24 articles (10.67%), JPE with 15 (6.67%), EER with 13 (5.78%), JAE with 12 (5.33%), OREP with 11 (4.89%), CanJE with 10 (4.44%), QJE and CamJE with 8 each one (3.56%), BPEA with 7 (3.11%), among others. Concerning the journals with more publications for both developed and developing countries, we have JEG with 32 articles (16.49%), QJE with 20 (10.31%), AER with 17 (8.76%), WD and JDE with 16 each one (8.25%), JME with 14 (7.22%), TWBER with 10 (5.15%), JAE with 7 (3.61%), NBER M.A., OREP and OEP with 6 each one (3%). What journals had more publications by type of model? Out of the total of articles on endogenous growth, the journals with the highest contributions were JED&C with 34 (10.83%), JEG with 32 (10.19%), JME with 29 (9.24%), JDE with 27 (8.60%), IER with 21 (6.69%), JPE with 20 (6.37%), JIE with 19 (6.05%), EER with 16 (5.10%). QJE, AER and JPE made 13 contributions each one (4.14%), while OEP, CanJE and Economica made 12 contributions each one (3.82%). For exogenous models, JEG had the highest number of publications with 33 (15.14%). Next, JME with 17 (7.80%), AER with 16 (7.34%), QJE with 15 (6.88%), WD with 14 (6.42%), JDE with 12 (5.50%), JEL and EER with 12 articles each one (4.59%), CanJE with 9 (4.13%), JPE and RESta with 7 each one (3.21%), BPEA and JED&C with each one (2.75%).

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Table 1. Data summary, 1992-2002 Journal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Journal of Economic Literature (JEL) Quarterly Journal of Economics (QJE) Journal of Economic Perspectives (JEP) Brookings Papers on Economic Activity (BPEA) Econometrica NBER Macroeconomics Annual (NBER M.A.) Economic Geography (EG) American Economic Review (AER) Journal of Political Economy (JPE) Journal of Economic Growth (JEG) Journal of International Economics (JIE) The World Bank Economic Review (TWBER) Journal of Monetary Economics (JME) The Review of Economics Studies (REStu) The Economic Journal (EJ) Journal of Econometrics (JoE) Review of Economics and Statistics (RESta) World Development (WD) Journal of Public Economics (JPubE) Journal of Applied Econometrics (JAE) The World Economy (TWE) Journal of Economic Dynamics & Control (JED&C) European Economic Review (EER) Oxford Review of Economic Policy (OREP) Cambridge Journal of Economics (CamJE) Oxford Economic Papers (OEP) Journal of Development Economics (JDE) Canadian Journal of Economics (CanJE) International Economic Review (IER) Economica Total

ource: Own statistics.

N. of Authors 16 76 14 26 13 16 15 84 62 170 45 44 103 36 38 30 59 108 46 33 11 100 51 26 33 46 112 50 69 38 1.570

N. of Articles 11 46 9 14 8 10 10 46 31 102 27 24 62 19 19 16 32 60 27 19 10 64 34 18 26 33 71 31 44 25 948

Normal Pages 372 1395 172 813 201 497 224 970 832 2501 595 608 1445 419 378 397 338 875 628 323 174 1546 717 337 523 626 1690 539 952 452 21.539

Stand. Pages 291,8 741,9 123,9 460,6 142,3 311,2 196,0 970,0 523,4 2068,8 428,5 431,7 1128,9 353,3 280,6 268,5 432,4 920,8 525,3 294,4 120,9 1045,5 472,3 351,0 456,3 467,3 1382,4 397,2 751,3 348,3 16.686

Conv. Factor 0,784 0,532 0,720 0,567 0,708 0,626 0,875 1,000 0,629 0,827 0,720 0,710 0,781 0,843 0,742 0,676 1,279 1,052 0,836 0,911 0,695 0,676 0,659 1,042 0,873 0,747 0,818 0,737 0,789 0,771

Impact Factor 4,312 3,941 3,058 3,045 2,737 2,667 2,455 2,052 2,011 2,000 1,607 1,310 1,272 1,194 1,134 1,106 1,085 1,056 1,013 0,970 0,744 0,738 0,726 0,723 0,688 0,653 0,632 0,59 0,563 0,464

Worldwide Rankings in Economic Growth

63

Ranking of the Journals The ranking of the journals is shown in Table 1, 2 and 3. Table 1 takes into account the impact factor. The ranking in Table 2 is based on the total of standardized pages about economic growth. Journal of Economic Growth (JEG) is the top ranked journal in economic growth over the period 1992-2002 with 2,068 pages. Other journals in this ranking are JDE (1382 pages), JME (1,129 pages), JED&C (1045 pages), AER (970 pages), and WD (921 pages). Table 2. Ranking of journals by economic growth publications based on standardized page counts, 1992-2002

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Rank.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Journal

Journal of Economic Growth Journal of Development Economics Journal of Monetary Economics Journal of Economic Dynamics & Control American Economic Review World Development International Economic Review Quarterly Journal of Economics Journal of Public Economics Journal of Political Economy European Economic Review Oxford Economic Papers Brookings Papers on Economic Activity Cambridge Journal of Economics The Review of Economics and Statistics The World Bank Economic Review Journal of International Economics Canadian Journal of Economics The Review of Economics Studies Oxford Review of Economic Policy Economica NBER Macroeconomics Annual Journal of Applied Econometrics Journal of Economic Literature The Economic Journal Journal of Econometrics Economic Geography Econometrica Journal of Economic Perspectives The World Economy

Stand. Pages 2.068,8 1.382,4 1.128,9 1.045,5 970,0 920,8 751,3 741,9 525,3 523,4 472,3 467,3 460,6 456,3 432,4 431,7 428,5 397,2 353,3 351,0 348,3 311,2 294,4 291,8 280,6 268,5 196,0 142,3 123,9 120,9

Source: Own statistics.

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N. of articles 102 71 62 64 46 60 44 46 27 31 34 33 14 26 32 24 27 31 19 18 25 10 19 11 19 16 10 8 9 10

N. of authors 170 112 103 100 84 108 69 76 46 62 51 46 26 33 59 44 45 50 36 26 38 16 33 16 38 30 15 13 14 11

64

Vicente German-Soto

For the 30 considered journals throughout the period from 1992 to 2002, the rank of contributions is located between 120 pages published by TWE and the 2,068 by the journal in the first place of the ranking (JEG). We can distinguish that only four journals exceeded the quantity of 1,000 pages: JEG, JDE, JME and JED&C. However, there is a notable difference of almost 700 pages between the first and second place of this ranking. Whereas at the bottom of Table 2 we can notice four journals with a contribution of less than 200 pages during the period of study: TWE, JEP, Econometrica and EG. By number of standardized pages, Table 2 can turn out useful to indicate which journals gave more space to economic growth in comparison to the rest of subjects of Economics. Table 3 brings the journals ranking based on the number of articles published during 1992-2002. The results are very similar and there is only a slight change regarding the ones shown in Table 2. Table 3. Ranking of journals by economic growth publications based on article counts, 1992-2002

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Rank.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Journal

Journal of Economic Growth Journal of Development Economics Journal of Economic Dynamics & Control Journal of Monetary Economics World Development American Economic Review Quarterly Journal of Economics International Economic Review European Economic Review Oxford Economic Papers The Review of Economics and Statistics Journal of Political Economy Canadian Journal of Economics Journal of Public Economics Journal of International Economics Cambridge Journal of Economics Economica The World Bank Economic Review The Review of Economics Studies Journal of Applied Econometrics The Economic Journal Oxford Review of Economic Policy Journal of Econometrics Brookings Papers on Economic Activity Journal of Economic Literature NBER Macroeconomics Annual Economic Geography The World Economy Journal of Economic Perspectives Econometrica

Stand. Pages 2.068,8 1.382,4 1.045,5 1.128,9 920,8 970,0 741,9 751,3 472,3 467,3 432,4 523,4 397,2 525,3 428,5 456,3 348,3 431,7 353,3 294,4 280,6 351,0 268,5 460,6 291,8 311,2 196,0 120,9 123,9 142,3

Source: Own statistics. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

N. of articles 102 71 64 62 60 46 46 44 34 33 32 31 31 27 27 26 25 24 19 19 19 18 16 14 11 10 10 10 9 8

N. of authors 170 112 100 103 108 84 76 69 51 46 59 62 50 46 45 33 38 44 36 33 38 26 30 26 16 16 15 11 14 13

Worldwide Rankings in Economic Growth

65

The JEG journal remains as leading journal also in this classification with 102 articles on economic growth. Other journals are JDE (71 contributions), JED&C (64 contributions), JME (62 articles), WD (60 contributions), AER and QJE (with 46 each one), and IER (with 44 articles). The last column in Table 3 contains information about the number of authors that studied economic growth. A trend to publish two or more authors was appreciated because of the relationship of 2 to 1 as regards number of authors and published articles in almost every journal. I also measured the relative importance of economic growth (in terms of allowed space) in the normal content of the 30 journals. Table 4 provides the ranking based on this measure.

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Table 4. Ranking of journals by dedicated space to economic growth publications, 1992-2002 Rank. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Journal Journal of Economic Growth NBER Macroeconomics Annual The World Bank Economic Review Journal of Development Economics Brookings Papers on Economic Activity Journal of Economic Dynamics & Control Journal of Monetary Economics Cambridge Journal of Economics Quarterly Journal of Economics Oxford Economic Papers International Economic Review American Economic Review European Economic Review Economica Journal of Applied Econometrics Journal of Political Economy Oxford Review of Economic Policy Journal of International Economics Journal of Economic Literature Economic Geography The Review of Economics and Statistics Canadian Journal of Economics The Review of Economics Studies World Development The Economic Journal Journal of Public Economics Journal of Economic Perspectives The World Economy Journal of Econometrics Econometrica

% 89,19 17,23 14,87 14,81 13,43 12,55 12,10 10,10 9,50 9,27 8,57 8,48 7,51 7,47 6,73 6,01 6,00 5,65 5,40 5,36 5,34 4,91 4,69 4,52 4,33 3,86 3,52 2,51 1,79 1,48

Source: Own statistics.

The relative importance rate was made by dividing the total of standardized pages (per journal) assigned to the topic of economic growth by the total of standardized pages (per journal) from the normal content of each journal during the period of 1992-2002. The first Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

66

Vicente German-Soto

position corresponded to JEG with nearly 90% of its pages dedicated to economic growth. It can also be observed that eight influential journals dedicated more than 10% of the standardized pages to the discussion about this economic topic.

The Institutions’ Hall of Fame Table 5 shows the ranking of the first 197 academic institutions with a contribution higher than 18 pages to the economic growth field during 1992-2002. These institutions were ranked by using the number of standardized pages published by individuals associated to those institutions. In the last column, I also included the total of authors that published for that institution during 1992-2002. A variety of comments illustrated by this ranking outstands. Table 5. Ranking of institutions by economic growth publications, 1992-2002

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Rank.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Institute

The World Bank Harvard U. NBER MIT U. of Chicago CEPR IMF U. of Washington London School of Economics Duke U. Stanford U. U. of California, L.A. Princeton U. Columbia U. Brown U. U. of Pennsylvania New York U. U. of Houston Yale U. F.R.B Richmond U. of California, Berkeley U. of Wisconsin Tilburg U. Cornell U. Tel-Aviv U. Hebrew U. U. of Virginia U. of Rochester F.R.B Minneapolis U. of Michigan U. of California, San Diego

Counts of Stand. pages 766,06 651,15 454,46 445,35 364,70 348,03 332,61 278,20 233,10 231,40 204,27 193,67 192,60 191,30 188,85 170,77 167,42 164,90 162,97 162,88 158,30 142,60 137,83 134,60 134,44 127,99 127,18 117,65 117,02 116,40 112,65

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N. of articles 41,52 29,00 26,87 22,20 17,62 19,89 17,97 15,17 11,50 10,25 10,57 8,48 8,17 8,42 9,34 9,43 9,89 10,08 7,67 8,73 6,67 7,33 7,62 7,92 8,35 6,83 7,23 5,23 6,37 7,25 6,58

N. of authors 74,33 50,33 38,67 35,83 30,00 30,50 29,00 23,00 15,00 11,50 18,33 15,17 12,00 11,83 22,67 22,33 18,67 15,00 11,83 11,33 9,33 14,00 15,00 13,00 15,00 13,17 12,33 10,67 10,83 8,50 10,00

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Worldwide Rankings in Economic Growth

Rank.

Institute

32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83

Ohio State U. Universidad Autónoma de Barcelona U. of Toronto U. of British Columbia Boston U. U. of South Carolina U. of Cambridge U. of Florida U. of Maryland Universidad Pompeu Fabra Georgetown U. Michigan State U. Erasmus U. F.R.B Philadelphia U. of Minnesota Hong Kong U. of Science and Tech. Australian National U. Southern Methodist U. Chinesse U. Hong Kong Tufts U. U. of Oxford U. of Manchester U. College Dublin ITAM Arizona State U. Université de Paris I Universidad of Chile Northwestern U. U. of Notre Dame U. of Iowa Stockholm School of Economics Bank of England Northern Ireland Economic Research Centre Harvard Inst. for Int. Dev. U. of Illinois U. of Texas-Austin OECD Academia Sinica Federal Reserve Board, Washington F.R.B New York U. of Iceland Stockholm U. National Inst. for Economic and Social Research CERAS Indiana U. Vandervilt U. Tohoku U. Board of Governors of the F.R.S. Catholic U. Rio de Janeiro Brookings Institutions U. College London Pennsylvania State U.

Counts of Stand. pages 112,40 100,07 97,10 95,30 92,45 92,40 86,65 82,50 80,52 76,60 75,15 74,72 74,58 74,34 74,19 72,74 71,60 70,93 69,56 68,80 68,80 68,50 68,20 67,00 65,29 64,46 63,00 62,44 62,30 62,00 60,80 59,37 59,00 57,50 55,40 54,55 54,45 53,00 52,73 52,65 51,75 51,35 51,20 51,00 50,10 49,90 46,84 46,60 45,67 45,48 44,96 44,54

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N. of articles 8,17 4,50 4,67 5,50 4,70 4,00 4,33 5,50 3,40 4,00 3,75 4,50 4,42 4,00 3,03 4,17 4,33 4,00 3,92 3,50 3,17 4,33 4,50 3,50 3,00 5,00 3,92 2,94 3,75 4,17 3,17 3,25 1,50 2,83 4,33 2,83 2,50 3,70 3,00 2,00 2,50 2,50 3,00 3,70 2,83 2,33 2,50 2,53 3,00 1,42 1,77 2,75

N. of authors 11,00 6,00 6,50 8,00 7,50 5,00 9,50 9,00 7,50 5,50 8,50 7,00 7,67 7,00 5,33 7,50 5,50 6,00 8,00 5,50 5,33 6,50 5,00 6,00 3,00 5,00 6,00 5,17 6,00 7,00 5,50 4,00 1,50 3,50 7,50 5,33 5,00 6,00 4,00 3,50 4,83 4,17 2,00 4,50 4,50 3,00 3,00 5,50 5,00 3,50 3,00 7,00

68

Vicente German-Soto Table 5. Continued

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Rank.

84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131

Institute

INSEAD U. of Pittsburgh Ben-Gurion U. Queen's U. Inter-American Dev. Bank Trinity College U. of Ottawa Lancaster U. Korea U. U. of Albany U. of Sussex U. of California, Santa Cruz U. of Missouri-Columbia U. of Nottingham U. of Western Ontario U. of Tokyo F.R.B. Atlanta Universidad Carlos III de Madrid U. of Victoria U. of Connecticut U. of Massachusetts European U. Inst. Graduate Inst. of Int. Studies U. of New South Wales Canadian Inst. for Advanced Research National U. of Singapore Hertford College Carleton U. Hitotsubashi U. U. of Amsterdam U. of Kent U. of Melbourne U. of London Indian Statistical Inst. Oxford U. Southampton U. U. of Helsinki U. of California, Davis U. of Alabama Claremont Graduate U. Northern Illinois U. Southern Illinois U. U. of Colorado Overseas Dev. Inst. State U. of New York Florida State U. CNRS Louisiana State U.

Counts of Stand. pages 44,33 44,30 43,18 43,15 43,06 42,75 42,60 42,31 42,25 41,70 41,50 41,20 41,20 40,85 40,81 40,50 40,46 40,05 38,65 38,60 38,60 38,45 37,74 37,50 36,98 36,90 36,75 36,59 36,03 35,38 34,80 34,80 34,43 33,94 33,23 32,90 32,00 30,95 30,60 30,31 30,20 29,86 29,75 29,43 29,43 29,10 28,90 28,80

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N. of articles 3,00 2,17 2,50 2,50 3,12 2,78 2,50 3,00 2,25 2,00 2,00 2,00 3,00 2,50 2,75 2,83 2,00 2,70 2,50 2,50 2,50 3,00 2,58 3,00 2,20 2,03 1,83 2,50 2,00 2,33 2,33 1,83 2,00 1,50 2,33 2,00 2,67 1,62 3,33 0,67 2,00 1,75 1,58 2,00 1,75 2,17 2,33 1,58

N. of authors 3,00 5,00 3,33 4,00 5,00 4,00 3,00 6,00 3,50 1,00 3,00 3,00 4,00 5,50 5,33 4,00 3,00 4,50 4,50 4,00 4,00 2,00 3,67 3,00 4,49 2,17 2,00 5,00 3,00 3,83 4,00 3,00 2,83 2,00 3,50 2,00 3,50 4,00 4,00 2,00 4,00 4,00 1,00 3,00 4,00 4,50 2,50 3,00

Worldwide Rankings in Economic Growth Rank.

132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157

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158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179

Institute

Northeastern U. Purdue U. U. of Mississippi F.R.B Dallas Fedesarrollo, Colombia U. of the West Indies College of William and Mary U. of Oregon Griffith U. Bilkent U. U. of Cyprus Goldman Sachs and Co. Dartmouth College F.R.B San Francisco U. of Edinburgh Simon Fraser U. CEPREMAP Clemson U. U. of Essex DELTA Vassar College Göteborg U. GREQAM U. of York F.R.B Cleveland Rutgers U. Département et Laboratoire D'Economie Théoriquee and Appliquée U. of Ilorin Inst. of Dev. Studies, Falmer U. of Dundee Smith College U. of California, Riverside U. of Leicester Université Laval Nuffield College Central Bank of Ireland Hoover Institution Hamilton College U. of Miami Université d'Evry-Val d'Essonne Rusell Sage Foundation Universidad de Alicante Iowa State U. Universitá Commerciale L. Bocconi U. of Munich Occidental College, L.A. Ramapo College of New Jersey Universitá di Roma 'La Sapienza'

69

Counts of Stand. pages 27,70 27,40 27,20 27,10 27,00 27,00 25,80 25,60 25,30 25,27 25,20 25,15 25,12 24,75 24,60 24,55 24,53 24,50 24,45 23,95 23,90 23,85 23,78 23,20 23,16 23,15

N. of articles 1,33 1,50 2,00 1,33 1,00 1,00 1,50 1,33 1,00 1,33 1,79 1,33 2,00 2,00 2,00 1,33 2,20 1,00 2,00 2,33 1,75 1,33 1,28 1,83 0,67 1,33

N. of authors 2,00 1,50 2,00 2,50 2,00 1,00 3,00 3,00 1,00 3,00 0,83 3,00 3,00 4,00 3,00 1,50 2,67 1,00 3,00 2,83 5,00 1,50 2,83 2,00 2,00 1,50

22,90

1,00

2,00

22,90 22,70 22,30 22,10 22,10 22,05 21,90 21,87 21,80 21,71 21,60 21,50 21,50 21,30 21,00 20,80 20,70 20,60 20,00 20,00 20,00

1,00 1,00 1,58 1,00 1,50 1,18 1,00 1,50 1,00 1,23 1,00 1,00 1,00 1,00 1,00 1,00 0,60 1,00 1,00 1,00 3,00

1,00 1,00 3,00 1,00 3,00 2,83 1,00 1,83 1,00 0,50 2,00 1,00 1,00 1,00 2,00 2,00 2,00 1,00 2,00 1,00 1,50

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Vicente German-Soto Table 5. Continued

Rank.

180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197

Institute

Georgia State U. National Chengchi U. U. of Guelph Baylor College of Medicine Dalhousie U. Universidad Pública de Navarra U. of Akron U. of Copenhagen Yokohama National U. U. of New Hampshire European Bank for Reconstruction and Dev. Université de Montréal New School for Social Research U. of Hong Kong Sveriges Riksbank Fordham U. U. of Groningen U. of Tuebingen

Counts of Stand. pages 19,85 19,70 19,70 19,60 19,50 19,50 19,20 19,16 19,00 18,90 18,75 18,70 18,40 18,40 18,20 18,00 18,00 18,00

N. of articles 1,33 1,00 1,48 1,00 1,50 1,00 2,00 1,00 1,00 1,00 1,03 1,33 0,83 1,50 1,00 1,00 1,00 1,00

N. of authors 2,00 1,00 3,00 1,00 2,00 1,00 4,00 2,33 1,00 2,00 2,00 1,50 2,00 2,50 1,00 2,00 1,00 1,00

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Source: Own statistics.

The World Bank institution dominated the first place with 766 pages. It is followed by Harvard U. (651)35, NBER Institute (454), and MIT (445), while in the 5th and 6th place we have U. of Chicago (364.7) and CEPR (348). In this same order, we have IMF (332.6), U. of Washington (278.2), London School of Economics (233.1), Duke U. (231.4) and Stanford U. (204.7). These first 11 institutions contributed to the production about economic growth with 200 or more pages each one. However, the gap between the first and second place is superior to 100 pages, whereas the distance between the second and third place is nearly 200 pages. For the rest it is possible to appreciate minor dispersions among institutions. The ranking in Table 5 offers a perspective about the global concentration of the published pages on economic growth. There were 497 centers involved in the scientific production about economic growth, but only 11 overtook the 200 pages and 22 were between 100 and 200 pages. In general, it can be noticed that only 33 overtook the 100 pages published, only 43 did it in a range between 50 and 100 pages, and 103 institutions published between 20 and 50 standardized pages. This ranking shows that only 197 institutions participated with a production higher than 18 pages, while there were 300 with 18 or less pages. This means that 25% of the published pages on economic growth belonged to 2% of the institutions (a quantity of 10 institutions). Besides, 50% of the published pages about economic growth were generated by nearly 8.5% of the institutions (a quantity of 42 institutions). On the other side, we have that 60% of the institutions (300 institutions with 18 or less pages each one) barely gave almost 16% of the published pages about this topic.

35

In parenthesis number of pages that were published.

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71

Also, I introduce the institutions ranking by the number of published articles. This information is shown in Table 6 for the first 132 institutions with an individual contribution of 2 or more articles on economic growth during 1992-2002. Again, in this classification, The World Bank institution obtains the first place with a number of 41.5 articles. Harvard U., NBER, MIT and CEPR occupy second, third, fourth and fifth position with 29, 26.8, 22.2 and 19.9 articles, respectively. Continuing in this order, we have IMF (17.9), U. of Chicago (17.6), U. of Washington (15.2), London School of Economics (11.5) and Stanford U. (10.6). These first 10 institutions contributed with 22.4% of the total of published articles.36 Table 6. Ranking of institutions based on the number of articles on economic growth, 1992-2002 Rank.

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 36

Institute

The World Bank Harvard U. NBER MIT CEPR IMF U. of Chicago U. of Washington London School of Economics Stanford U. Duke U. U. of Houston New York U. U. of Pennsylvania Brown U. F.R.B Richmond U. of California, L.A. Columbia U. Tel-Aviv U. Ohio State U. Princeton U. Cornell U. Yale U. Tilburg U. U. of Wisconsin U. of Michigan U. of Virginia Hebrew U. U. of California, Berkeley U. of California, San Diego F.R.B Minneapolis U. of British Columbia

Counts of Stand. pages 766,06 651,15 454,46 445,35 348,03 332,61 364,70 278,20 233,10 204,27 231,40 164,90 167,42 170,77 188,85 162,88 193,67 191,30 134,44 112,40 192,60 134,60 162,97 137,83 142,60 116,40 127,18 127,99 158,30 112,65 117,02 95,30

In parentheses, the number of articles that were published.

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N. of articles 41,52 29,00 26,87 22,20 19,89 17,97 17,62 15,17 11,50 10,57 10,25 10,08 9,89 9,43 9,34 8,73 8,48 8,42 8,35 8,17 8,17 7,92 7,67 7,62 7,33 7,25 7,23 6,83 6,67 6,58 6,37 5,50

N. of authors 74,33 50,33 38,67 35,83 30,50 29,00 30,00 23,00 15,00 18,33 11,50 15,00 18,67 22,33 22,67 11,33 15,17 11,83 15,00 11,00 12,00 13,00 11,83 15,00 14,00 8,50 12,33 13,17 9,33 10,00 10,83 8,00

72

Vicente German-Soto Table 6. Continued

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Rank.

34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75

Institute

U. of Rochester Université de Paris I Boston U. U. of Toronto Universidad Autónoma de Barcelona Michigan State U. U. College Dublin Erasmus U. Australian National U. U. of Cambridge U. of Manchester U. of Illinois Hong Kong U. of Science and Tech. U. of Iowa U. of South Carolina F.R.B Philadelphia Southern Methodist U. Universidad Pompeu Fabra Chinesse U. Hong Kong Universidad of Chile U. of Notre Dame Georgetown U. Academia Sinica CERAS Tufts U. ITAM U. of Maryland U. of Alabama Bank of England U. of Oxford Stockholm School of Economics Inter-American Dev. Bank U. of Minnesota Arizona State U. Federal Reserve Board, Washington INSEAD U. of Missouri-Columbia European U. Inst. U. of New South Wales Universitá di Roma 'La Sapienza' National Inst. for Economic and Social Research Catholic U. Rio de Janeiro

Counts of Stand. pages 117,65 64,46 92,45 97,10 100,07 74,72 68,20 74,58 71,60 86,65 68,50 55,40 72,74 62,00 92,40 74,34 70,93 76,60 69,56 63,00 62,30 75,15 53,00 51,00 68,80 67,00 80,52 30,60 59,37 68,80 60,80 43,06 74,19 65,29 52,73 44,33 41,20 38,45 37,50 20,00

N. of articles 5,23 5,00 4,70 4,67 4,50 4,50 4,50 4,42 4,33 4,33 4,33 4,33 4,17 4,17 4,00 4,00 4,00 4,00 3,92 3,92 3,75 3,75 3,70 3,70 3,50 3,50 3,40 3,33 3,25 3,17 3,17 3,12 3,03 3,00 3,00 3,00 3,00 3,00 3,00 3,00

N. of authors 10,67 5,00 7,50 6,50 6,00 7,00 5,00 7,67 5,50 9,50 6,50 7,50 7,50 7,00 5,00 7,00 6,00 5,50 8,00 6,00 6,00 8,50 6,00 4,50 5,50 6,00 7,50 4,00 4,00 5,33 5,50 5,00 5,33 3,00 4,00 3,00 4,00 2,00 3,00 1,50

51,20

3,00

2,00

45,67

3,00

5,00

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Rank.

77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120

Institute

Northwestern U. Harvard Inst. for Int. Dev. Indiana U. U. of Tokyo U. of Texas-Austin Trinity College Pennsylvania State U. U. of Western Ontario Universidad Carlos III de Madrid U. of Helsinki Graduate Inst. of Int. Studies Board of Governors of the F.R.S. OECD Tohoku U. Queen's U. U. of Ottawa U. of Victoria U. of Connecticut U. of Massachusetts U. of Exeter Ben-Gurion U. U. of Nottingham Carleton U. U. of Iceland Stockholm U. Vandervilt U. U. of Amsterdam U. of Kent Oxford U. CNRS DELTA Korea U. Canadian Inst. for Advanced Research CEPREMAP U. of Pittsburgh Florida State U. National U. of Singapore F.R.B New York U. of Albany U. of Sussex U. of California, Santa Cruz F.R.B. Atlanta Hitotsubashi U. Southampton U.

Counts of Stand. pages 62,44 57,50 50,10 40,50 54,55 42,75 44,54 40,81 40,05 32,00 37,74 46,60 54,45 46,84 43,15 42,60 38,65 38,60 38,60 9,70 43,18 40,85 36,59 51,75 51,35 49,90 35,38 34,80 33,23 28,90 23,95 42,25 36,98 24,53 44,30 29,10 36,90 52,65 41,70 41,50 41,20 40,46 36,03 32,90

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N. of articles 2,94 2,83 2,83 2,83 2,83 2,78 2,75 2,75 2,70 2,67 2,58 2,53 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,50 2,33 2,33 2,33 2,33 2,33 2,33 2,25 2,20 2,20 2,17 2,17 2,03 2,00 2,00 2,00 2,00 2,00 2,00 2,00

N. of authors 5,17 3,50 4,50 4,00 5,33 4,00 7,00 5,33 4,50 3,50 3,67 5,50 5,00 3,00 4,00 3,00 4,50 4,00 4,00 1,00 3,33 5,50 5,00 4,83 4,17 3,00 3,83 4,00 3,50 2,50 2,83 3,50 4,49 2,67 5,00 4,50 2,17 3,50 1,00 3,00 3,00 3,00 3,00 2,00

74

Vicente German-Soto Table 6. Continued Rank.

122 123 124 126 127 128 129 130 131 132

Institute

Overseas Dev. Inst. U. of Mississippi Dartmouth College U. of Edinburgh U. of Essex U. of Akron U. College of Gävle Illinois State U. U. of Calgary U. of London

Counts of Stand. pages 29,43 27,20 25,12 24,60 24,45 19,20 17,40 16,80 16,50 34,43

N. of articles 2,00 2,00 2,00 2,00 2,00 2,00 2,00 2,00 2,00 2,00

N. of authors 3,00 2,00 3,00 3,00 3,00 4,00 2,00 2,00 2,00 2,83

Source: Own statistics.

We can see that only 4 institutions (less than 1%) exceeded the 20 articles published on economic growth during the 11 years consulted. This quantity represents a less than 12.6% concentration. We can also observe that only 12 research centers exceeded the 10 publications individually.

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The ‘Hall of Fame’ of the Economic Growth Authors Table 7 picks up the list of the first 154 individual contributors of economic growth articles to the 30 journals from 1992 to 2002. These authors were classified by using the number of standardized published pages on economic growth in the 30 journals in this period of 11 years. The institutional affiliation is the one aforementioned by the author in the case when such author pointed out just one institution. In the case of authors with multiple affiliations, the procedure came in two forms. First, it was necessary to go to Coupé’s (2003) work, where the ranking of the first 1,000 economists were reported. He proposed as an institutional affiliation the one maintained by the author in the year 2000. I used that list to decide here the affiliation of authors contained in this work. Second, for the non contained cases in Coupe´s list, I used the affiliation of the most recent article or the best-known affiliation of the author. Table 7 shows that the first position is dominated by Turnovsky, S. (U. of Washington) with 193.7 standardized pages published about economic growth. It is followed by Easterly, W. (World Bank, 181.3), Peretto, P. (Duke U., 137.7), Jones, Ch. (Stanford U., 131.3), and Barro, R. (Harvard U., 129.2), in the top five. Continuing this order, we have Sala-i-Martin, X. (Columbia U., 119.6), Levine, R. (U. of Minnesota, 111.3), Acemoglu, D. (MIT, 108.6), McDermott, J. (U. of South Carolina, 92.4), and Smith, B. (U. of Texas-Austin, 92). 37 The economic growth publications registered 1,010 different individual authors. Table 7 contains the ranking of those who contributed with more than 25 pages, individually. The production in terms of standardized pages of these 154 authors (about 15% of the total) was of 7,368 (nearly 44%). Meanwhile, the remaining 85% contributed with the 56% of the pages.

37

In parentheses, we have institutional affiliation and standardized pages, respectively.

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Table 7. Ranking of individuals by economic growth publications based on standardized pages counts, 1992-2002

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Rank. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

Author

Turnovsky, Stephen J. Easterly, William Peretto, Pietro F. Jones, Charles I. Barro, Robert J. Sala-i-Martin, Xavier Levine, Ross Acemoglu, Daron McDermott, John Smith, Bruce D. Aghion, Philippe Howitt, Peter Rodrik, Dani De Gregorio, José Bénabou, Roland Galor, Oded Temple, Jonathan R.W. Young, Alwyn Ben-David, Dan Glomm, Gerhard Quah, Danny T. Thompson, Peter Ravallion, Martin Martin, Philippe Smulders, Sjak Lloyd-Ellis, Huw Hendricks, Lutz Zhang, Jie Weinberg, Bruce A. Pritchett, Lant Segerstrom, Paul S. Oulton, Nicholas Eicher, Theo S. Lee, Jong-Wha Durlauf, Steven N. Edwards, Sebastian Sachs, Jeffrey D. Tornell, Aaron Jorgenson, Dale W. Perotti, Roberto Crafts, Nicholas Tamura, Robert Klenow, Peter J.

Affiliation

U. of Washington World Bank Duke U. Stanford U. Harvard U. Columbia U. U. of Minnesota MIT U. of South Carolina U. of Texas-Austin U. College London Ohio State U. Harvard U. IMF Princeton U. Brown U. Hertford College MIT Tel Aviv U. Michigan State U. London School of Economics U. of Houston World Bank The Graduate Inst. of Int. Studies Tilburg U. U. of Toronto Arizona State U. U. of Windsor Brown U. World Bank Stockholm School of Economics Bank of England U. of Washington Korea U. U. of Wisconsin-Madison U. of California, L.A. Harvard U. Harvard U. Harvard U. Columbia U. London School of Economics U. of Iowa U. of Chicago

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N. of articles 9,83 8,58 6,50 7,50 6,83 5,83 4,83 4,67 4,00 4,17 4,42 5,58 4,00 4,33 3,00 4,50 4,00 4,00 5,00 5,50 3,50 4,00 5,00 4,33 3,50 2,50 3,00 3,67 0,33 3,25 3,00 3,50 4,00 3,33 4,00 3,00 1,50 2,50 1,50 2,50 3,00 3,00 3,00

Stand. Pages 193,70 181,30 137,70 131,30 129,20 119,60 111,30 108,60 92,40 92,00 91,60 88,10 87,40 85,80 84,30 83,30 80,40 79,60 76,10 75,70 73,40 72,60 69,90 67,20 66,70 66,50 65,30 65,30 64,60 63,80 63,70 63,50 63,10 62,80 61,90 61,40 58,80 58,50 58,40 58,30 57,30 55,60 55,10

76

Vicente German-Soto Table 7. Continued

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Rank. 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87

Author

Affiliation

De la Fuente, Angel U. Autonoma de Barcelona Saint-Paul, Gilles U. Pompeu Fabra Pesaran, M. Hashem U. of Cambridge Azariadis, Costas U. of California, L.A. Gudgin, Graham Northern Ireland Economic Research Centre Krener, Michael MIT Ortigueira, Salvador ITAM Bertola, Giuseppe Universitá di Torino Bovenberg, A. Lans Tilburg U. Pereira, Alfredo M. College of William and Mary Tsiddon, Daniel Tel Aviv U. Devereux, Michael B. U. of British Columbia King, Robert G. U. of Virginia Foster, Andrew D. Brown U. Mountford, Andrew Southampton U. Rosenzweig, Mark R. U. of Pennsylvania Pecorino, Paul U. of Alabama Laitner, John U. of Michigan Kim, Se-Jik IMF Ravikumar, B. U. of Virginia Evans, Paul Ohio State U. Rebelo, Sergio T. U. of Rochester De Long, J. Bradford U. of California, Berkeley Rauch, James E. U. of California, San Diego Santos, Manuel S. U. of Minnesota Twin Cities Krusell, Per U. of Rochester Kelly, Morgan U. College Dublin Zou, Heng-Fu World Bank Stokey, Nancy L. U. of Chicago Rodríguez-Pose, Andrés U. of Chicago Lane, Philip R. Trinity College Bleaney, Michael F. U. of Nottingham Zilibotti, Fabrizio London School of Economics Dinopoulos, Elias U. of Florida Prescott, Edward C. F.R.B. of Minneapolis Quadrini, Vincenzo Duke U. Mendoza, Enrique G. Duke U. Helpman, Elhanan Harvard U. Zilcha, Itzhak Tel Aviv U. Campbell, John Y. Princeton U. Vamvakidis, Athanasios IMF Roubini, Nouriel Yale U. Ventura, Jaume MIT Dignan, Tony Coopers and Lybrand

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N. of articles 2,00 4,50 2,00 2,00 1,00 2,75 2,17 3,00 2,00 2,50 3,50 3,00 2,00 2,08 3,00 2,08 4,00 3,00 2,50 3,50 4,00 1,83 2,00 2,50 2,67 2,33 3,50 2,33 3,50 3,00 2,00 2,17 1,50 2,00 2,00 1,33 1,33 1,67 2,50 1,00 2,00 1,75 2,00 1,00

Stand. Pages 54,90 53,90 52,30 51,90 47,90 47,30 47,30 46,90 46,90 46,70 46,20 46,00 45,90 45,20 45,20 45,20 44,80 44,70 44,10 44,10 43,80 42,40 41,90 41,60 41,20 41,10 40,60 40,30 40,00 39,90 39,40 36,50 36,40 36,10 36,00 36,00 35,60 34,90 34,60 34,40 34,10 34,00 33,40 33,30

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Worldwide Rankings in Economic Growth Rank.

Author

88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134

Besley, Timothy Ireland, Peter N. Bernstein, Jeffrey I. Chatterjee, Satyajit Fischer, Stanley Gylfason, Thorvaldur Rangazas, Peter C. Datt, Gaurav Goodfriend, Marvin Harberger, Arnold C. Ríos-Rull, José-Víctor Mankiw, N. Gregory Moav, Omer Page, John Bencivenga, Valerie R. Manuelli, Rodolfo E. Rodríguez, Francisco Cozzi, Guido Dolmas, Jim Duffy, John Wall, Richard A. Robinson, James A. Fatás, Antonio Glaeser, Edward L. Taylor, M. Scott Kalemli-Ozcan, Sebnem Romer, Paul Corriveau, Louis G. Sarte, Pierre-Daniel Bernard, Andrew B. Kaganovich, Michael Justman, Moshe Morrison, Catherine J. Rao, J. Mohan Verdier, Thierry Yanagawa, Noriyuki Caballé, Jordi Ishikawa, Jota Osang, Thomas Potter, Simon M. Dutt, Amitava Krishna Fogel, Robert W. Northover, Patricia Olivier, Jaques Waverman, Leonard Caselli, Franceso Redding, Stephen

Affiliation

London School of Economics F.R.B. of Richmond Carleton U. F.R.B. of Philadelphia MIT U. of Iceland Indiana U. World Bank F.R.B. of Richmond U. of California, L.A. U. of Pennsylvania Harvard U. Hebrew U. The World Bank U. of Texas-Austin U. of Wisconsin-Madison U. of Maryland New York U. Southern Methodist U. U. of Pittsburgh U. of Tuebingen U. of California at Berkeley INSEAD Harvard U. U. of British Columbia U. of Houston Stanford U. U. of Ottawa F.R.B. of Richmond MIT Indiana U. Ben-Gurion U. Tufts U. U. of Massachusetts ENS U. of Tokyo Universitat Autonoma de Barcelona Hitotsubashi U. Southern Methodist U. U. of California, L.A. U. of Notre Dame U. of Chicago U. of the West Indies National U. of Singapore Harvard U. Harvard U. London School of Economics

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77 N. of articles 1,50 3,00 2,50 1,50 1,50 1,33 2,00 2,00 1,50 1,00 1,33 1,67 1,33 1,00 1,67 1,30 1,00 2,00 2,00 1,30 0,50 1,20 2,00 1,90 2,00 1,30 1,30 2,00 1,50 2,00 1,50 1,50 1,50 1,50 1,50 2,00 1,50 1,50 1,50 1,50 2,00 1,00 1,00 1,50 0,50 1,30 1,00

Stand. Pages 33,20 33,10 33,00 32,90 32,90 32,90 32,80 32,50 32,10 32,00 32,00 31,90 31,90 31,90 31,70 31,70 31,50 31,40 31,20 31,10 31,10 30,80 30,40 30,40 30,30 30,20 30,10 29,30 29,30 29,10 29,10 29,00 28,50 28,30 28,00 28,00 27,60 27,50 27,50 27,30 27,10 27,00 27,00 26,90 26,90 26,80 26,80

78

Vicente German-Soto Table 7. Continued

Rank. 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154

Author

Slemrod, Joel Ranis, Gustav Steger, Thomas M. Stiroh, Kevin J. Lavoie, Marc Summers, Lawrence H. Marquis, Milton H. Nordhaus, William D. Mino, Kazuo Muniagurria, María E. Collier, Paul You, Jong-Il Durham, J. Benson Knack, Stephen Carlino, Gerald A. Daniels, Peter L. Stanners, W. Ades, Alberto F. Marrewij, Charles van Mulligan, Casey B.

Affiliation

U. of Michigan Yale U. U. of Greifswald F.R.B. of New York U. of Ottawa U.S. Department of the Treasury Board of Governors of the F.R.S. Yale U. Tohoku U. U. of California, Santa Cruz World Bank U. of Notre Dame Columbia U. U. of Maryland F.R.B. of Philadelphia Griffith U. (sin afiliación) Goldman Sachs & Co. Erasmus U. Rotterdam U. of Chicago

N. of articles 1,00 1,30 2,00 0,50 1,00 1,25 2,00 1,00 1,50 1,50 1,00 1,50 1,00 1,25 1,50 1,00 1,00 1,50 1,50 1,00

Stand. Pages 26,60 26,50 26,40 26,40 26,20 26,20 26,10 26,10 25,90 25,90 25,70 25,70 25,60 25,50 25,40 25,30 25,30 25,20 25,00 25,00

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Source: Own statistics.

We can see that the first 10 authors in Table 7 published almost 1,300 pages jointly, around 8% of the total. In general, there were 8 authors with more than 100 pages produced in the period of 11 years, 39 authors whose production ranged between 50 and 100 pages, 107 authors were in the 25-to-50-page range, 404 made it for the 10-to-25-page range and, finally, 452 had contributions of less than 10 standardized pages. I also reveal the authors ranking in terms of the number of articles. This information is shown in Table 8 for the first 147 authors with more than 1.5 published articles. There are small differences concerning the results obtained by the ranking of standardized pages in Table 7. The first place is taken by Turnosvky, S. (U. of Washington) with 9.83 articles. The list goes on as follows: Jones, Ch. (Stanford U., 7.5), Barro, R. (Harvard U., 6.83) and Peretto, P. (Duke U., 6.5), in the top five of the list. They are also the authors with more than six published articles. For position 6 through 10 we have Sala-i-Martin, X. (Columbia U., 5.83), Howitt, P. (Ohio State U., 5.58), Glomm, G. (Michigan State U., 5.5), Ben-David, D. (Tel-Aviv U., 5), and Ravallion, M. (World Bank, 5). These first 10 authors of the classification are also the ones who contributed with 5 or more articles in the field of economic growth. In addition, Table 8 offers the position of authors in the ranking of standardized pages. The supreme positions of Turnovsky, S. (U. Washington) and Easterly, W. (World Bank) do not vary; while Jones, Ch. (Stanford U.) upgrades one position from the fourth place in Table 7 to number 3 in Table 8. Likewise, Barro, R. (Harvard U.) goes from the fifth to the fourth place, but Peretto, P. (Duke U.), loses two positions in this classification by going from the third place to the fifth, while Sala-i-Martin, X. (Columbia U.) keeps the sixth position in both

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79

tables. Other authors upgrade substantially, like Howitt P. (Ohio State U.), by going from the twelfth to the seventh place; Glomm, G. (Michigan State U.), who upgrades 12 places by moving from position 20 to position 8; Ben-David, D. (Tel-Aviv U.), from 19 to position 9; and finally, Ravallion, M. (World Bank), who goes up from position 23 to position 10, among the most outstanding in Table 8. Table 8. Ranking of individuals by economic growth publications based on the number of articles, 1992-2002

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Rank. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Author

Turnovsky, Stephen J. Easterly, William Jones, Charles I. Barro, Robert J. Peretto, Pietro F. Sala-i-Martin, Xavier Howitt, Peter Glomm, Gerhard Ben-David, Dan Ravallion, Martin Levine, Ross Acemoglu, Daron Galor, Oded Saint-Paul, Gilles Aghion, Philippe De Gregorio, José Martin, Philippe Smith, Bruce D. McDermott, John Rodrik, Dani Temple, Jonathan R.W. Young, Alwyn Thompson, Peter Eicher, Theo S. Durlauf, Steven N. Pecorino, Paul Evans, Paul Zhang, Jie Quah, Danny T. Smulders, Sjak Oulton, Nicholas Tsiddon, Daniel Ravikumar, B. Kelly, Morgan Stokey, Nancy L. Weil, David N.

Stand. Pages

Affiliation

N. of articles

Counts

Rank.

U. of Washington World Bank Stanford U. Harvard U. Duke U. Columbia U. Ohio State U. Michigan State U. Tel Aviv U. World Bank U. of Minnesota Twin Cities MIT Brown U. U. Pompeu Fabra U. College London IMF The Graduate Inst. of Int. Studies U. of Texas-Austin U. of South Carolina Harvard U. Hertford College MIT U. of Houston U. of Washington U. of Wisconsin-Madison U. of Alabama Ohio State U. U. of Windsor London School of Economics Tilburg U. Bank of England Tel Aviv U. U. of Virginia U. College Dublin U. of Chicago U. of Basel

9,8 8,6 7,5 6,8 6,5 5,8 5,6 5,5 5,0 5,0 4,8 4,7 4,5 4,5 4,4 4,3 4,3 4,2 4,0 4,0 4,0 4,0 4,0 4,0 4,0 4,0 4,0 3,7 3,5 3,5 3,5 3,5 3,5 3,5 3,5 3,3

193,7 181,3 131,3 129,2 137,7 119,6 88,1 75,7 76,1 69,9 111,3 108,6 83,3 53,9 91,6 85,8 67,2 92,0 92,4 87,4 80,4 79,6 72,6 63,1 61,9 44,8 43,8 65,3 73,4 66,7 63,5 46,2 44,1 40,6 40,0 7,6

1 2 4 5 3 6 12 20 19 23 7 8 16 45 11 14 24 10 9 13 17 18 22 33 35 60 64 28 21 25 32 54 63 70 72 697

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80

Vicente German-Soto Table 8. Continued

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Rank. 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79

Author

Lee, Jong-Wha Pritchett, Lant Bénabou, Roland Hendricks, Lutz Segerstrom, Paul S. Edwards, Sebastian Crafts, Nicholas Tamura, Robert Klenow, Peter J. Bertola, Giuseppe Devereux, Michael B. Mountford, Andrew Laitner, John Rodríguez-Pose, Andrés Ireland, Peter N. Krener, Michael Santos, Manuel S. Lloyd-Ellis, Huw Tornell, Aaron Perotti, Roberto Pereira, Alfredo M. Kim, Se-Jik Rauch, James E. Zilcha, Itzhak Bernstein, Jeffrey I. Krusell, Per Zou, Heng-Fu Ortigueira, Salvador Bleaney, Michael F. Rosenzweig, Mark R. Foster, Andrew D. De la Fuente, Angel Azariadis, Costas Bovenberg, A. Lans King, Robert G. De Long, J. Bradford Lane, Philip R. Dinopoulos, Elias Prescott, Edward C. Vamvakidis, Athanasios Ventura, Jaume Rangazas, Peter C. Datt, Gaurav

Stand. Pages

Affiliation

N. of articles

Counts

Rank.

Korea U. World Bank Princeton U. Arizona State U. Stockholm School of Economics U. of California, L.A. London School of Economics U. of Iowa U. of Chicago Universitá di Torino U. of British Columbia Southampton U. U. of Michigan U. of Chicago F.R.B. of Richmond MIT U. of Minnesota Twin Cities U. of Toronto Harvard U. Columbia U. College of William and Mary IMF U. of California, San Diego Tel Aviv U. Carleton U. U. of Rochester World Bank ITAM U. of Nottingham U. of Pennsylvania Brown U. U. Autonoma de Barcelona U. of California, L.A. Tilburg U. U. of Virginia U. of California, Berkeley Trinity College U. of Florida F.R.B. of Minneapolis IMF MIT Indiana U. World Bank

3,3 3,3 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 3,0 2,8 2,7 2,5 2,5 2,5 2,5 2,5 2,5 2,5 2,5 2,3 2,3 2,2 2,2 2,1 2,1 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0

62,8 63,8 84,3 65,3 63,7 61,4 57,3 55,6 55,1 46,9 46,0 45,2 44,7 39,9 33,1 47,3 41,2 66,5 58,5 58,3 46,7 44,1 41,6 34,6 33,0 41,1 40,3 47,3 36,5 45,2 45,2 54,9 51,9 46,9 45,9 41,9 39,4 36,1 36,0 34,1 33,4 32,8 32,5

34 30 15 27 31 36 41 42 43 51 55 58 61 73 89 49 68 26 38 40 53 62 67 82 90 69 71 50 75 59 57 44 47 52 56 66 74 77 78 84 86 94 95

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Rank. 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124

Author

Cozzi, Guido Dolmas, Jim Fatás, Antonio Taylor, M. Scott Corriveau, Louis Bernard, Andrew B. Yanagawa, Noriyuki Dutt, Amitava Krishna Steger, Thomas M. Marquis, Milton H. Cohen, Daniel Deardoff, Alan V. Griliches, Zvi Palokangas, Tapio Michel, Philippe Zhang, Junxi Eriksson, Clas Ram, Rati Serletis, Apostolos Walz, Uwe Pesaran, M. Hashem Glaeser, Edward L. Rebelo, Sergio T. Roubini, Nouriel Helpman, Elhanan Mankiw, N. Gregory Bencivenga, Valerie R. Palivos, Theodore Sachs, Jeffrey D. Jorgenson, Dale W. Zilibotti, Fabrizio Besley, Timothy Chatterjee, Satyajit Fischer, Stanley Goodfriend, Marvin G. Sarte, Pierre-Daniel Kaganovich, Michael Justman, Moshe Morrison, Catherine J. Rao, J. Mohan Verdier, Thierry Caballé, Jordi Ishikawa, Jota Osang, Thomas Potter, Simon M.

81 Stand. Pages

Affiliation

N. of articles

Counts

Rank.

New York U. Southern Methodist U. INSEAD U. of British Columbia U. of Ottawa MIT U. of Tokyo U. of Notre Dame U. of Greifswald Board of Governors of the F.R.S. Ecole Normale Supérieure U. of Michigan Harvard U. U. of Helsinki Université de la Méditerranée U. of Hong Kong U. College of Gävle Illinois State U. U. of Calgary U. of Florida U. of Cambridge Harvard U. U. of Rochester Yale U. Harvard U. Harvard U. U. of Texas-Austin Tilburg U. Harvard U. Harvard U. London School of Economics London School of Economics F.R.B. of Philadelphia MIT F.R.B. of Richmond F.R.B. of Richmond Indiana U. Ben-Gurion U. Tufts U. U. of Massachusetts ENS U. Autonoma de Barcelona Hitotsubashi U. Southern Methodist U. U. of California, L.A.

2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 1,9 1,8 1,8 1,7 1,7 1,7 1,7 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5

31,4 31,2 30,4 30,3 29,3 29,1 28,0 27,1 26,4 26,1 24,7 24,6 24,6 21,2 20,7 19,7 17,3 16,8 16,5 7,1 52,3 30,4 42,4 34,0 34,9 31,9 31,7 24,3 58,8 58,4 36,4 33,2 32,9 32,9 32,1 29,3 29,1 29,0 28,5 28,3 28,0 27,6 27,5 27,5 27,3

105 106 110 112 115 117 123 128 137 141 155 156 157 202 213 236 287 302 310 750 46 111 65 85 81 99 102 161 37 39 76 88 91 92 96 116 118 119 120 121 122 124 125 126 127

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Table 8. Continued

Rank.

Author

125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147

Olivier, Jaques Mino, Kazuo Muniagurria, María E. You, Jong-Il Carlino, Gerald A. Ades, Alberto F. Marrewij, Charles van Bose, Niloy Leon-Ledesma, Miguel A. Loewy, Michael B. Benhabib, Jess Papell, David H. Boltho, Andrea Irwin, Douglas A. De Hek, Paul A. Rogers, Carol Ann Ni, Shawn Corneo, Giacomo Ploeg, Frederick van Der Gradstein, Mark Rustichini, Aldo Huggett, Mark Wolff, Edward N.

Affiliation

National U. of Singapore Tohoku U. U. of California, Santa Cruz U. of Notre Dame F.R.B. of Philadelphia Goldman Sachs & Co. Erasmus U. Rotterdam U. of Manchester U. of Kent U. of South Florida New York U. U. of Houston U. of Oxford Dartmouth College U. of Amsterdam Georgetown U. U. of Missouri-Columbia U. of Bonn U. of Amsterdam Ben-Gurion U. New York U. U. of Illinois MIT

Stand. Pages

N. of articles

Counts

Rank.

1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5 1,5

26,9 25,9 25,9 25,7 25,4 25,2 25,0 22,6 22,3 22,1 21,5 20,8 20,7 19,9 19,4 19,3 18,8 18,5 18,5 17,7 16,9 9,0 8,2

131 143 144 146 149 152 153 173 179 182 193 209 211 233 240 242 254 259 260 276 299 598 655

Source: Own statistics.

In general, Table 8 displays 27 authors with 4 or more produced articles, while the other 73 are in the range of 2 to 4 articles. This means that there are 100 authors (9.9% of the total) with 2 or more articles (33.7% of the total). Meanwhile, on the bottom of Table 8 we can see that only 47 authors published from 1.5 to 2 articles and that 863 contributed with less than 1.5 articles.

Contributions Level by Country Table 9 shows the standardized pages concentration, the number of articles, authors and academic institutions related to economic growth by country. Only 45 countries accredited the total registered publication by their academic centers. A high concentration of the publication per country can be observed and it extends in a range that goes from 5 to 10,051 pages. The United States dominates this ranking with 10,051 standardized pages, corresponding to 539 articles published by 915 authors in 182 university centers during 1992-2002. The United Kingdom is the second with 1,794 pages attributed to 106 published articles by 167

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authors in 65 universities. Canada is the third and France the fourth. These four top ranking countries contributed with 78% of the total pages on economic growth. Following the leading countries, we can see Israel, China, Spain, Netherlands, Japan and Australia. As a whole, these 10 top countries contributed with 88% of the standardized pages although stressed disparities among them were observed. Only one country had a production superior to 10,000 pages, whereas only two countries can be counted with more than 1,000 pages. Moreover, there are 6 countries in the range of 300 to 1,000 pages. An equal number of cases is noticed in the range of 100 to 300 pages. In the middle section of Table 9 it can be observed that there are 11 countries whose contributions on standardized pages oscillate in the range of 40 to 100 pages, while the remaining 19 of the bottom section have contributions of below 40 pages each one.

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Table 9. Geographical concentration of economic growth publications, 1992-2002 Rank.

Country

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

U.S. United Kingdom Canada France Israel China Spain Netherlands Japan Australia Sweden Ireland Italy Germany Korea Mexico Chile India Belgium Brazil Denmark Norway Switzerland Island New Zealand Finland Singapore Colombia Jamaica Turkey Cyprus

Standard pages 10.051,55 1.793,91 687,72 466,38 335,38 324,36 306,25 300,68 230,28 222,47 222,16 221,10 208,84 203,81 104,45 87,43 69,15 64,24 63,30 62,57 58,74 58,60 54,91 51,75 43,40 40,85 36,90 27,00 27,00 25,27 25,20

N. of articles

N. of authors

N. of Univ.

539,45 106,59 44,01 31,20 19,08 20,33 16,65 18,28 14,33 13,83 13,03 12,28 15,07 13,67 6,25 5,25 4,17 3,25 6,50 4,00 3,45 4,00 3,58 2,50 4,08 3,17 2,03 1,00 1,00 1,33 1,79

914,83 167,17 63,99 46,17 34,33 39,33 26,50 32,17 20,00 17,33 23,33 14,00 18,50 19,83 9,50 9,00 6,50 5,00 12,50 6,00 6,67 7,00 6,17 4,83 8,00 4,00 2,17 2,00 1,00 3,00 0,83

182 65 28 27 6 17 11 7 13 9 11 7 19 18 7 4 2 4 10 2 7 8 3 1 4 2 1 1 1 1 1

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Vicente German-Soto Table 9. Continued Rank. 32 33 34 35 36 37 38 39 40 41 42 43 44 45

Country Nigeria Czech South Africa Saudi Arabia Pakistan Russia Greece Malaysia Luxembourg Portugal Zimbabwe Hungary Philippines Indonesia

Standard pages 22,90 18,65 16,60 15,80 14,70 13,80 13,72 10,80 10,30 9,80 5,80 5,77 5,30 5,00

N. of articles

N. of authors

N. of Univ.

1,00 1,50 1,00 1,00 1,00 1,00 1,04 0,50 0,50 1,00 0,50 0,17 0,50 0,33

1,00 1,50 1,00 2,00 1,00 2,00 3,00 1,00 1,00 1,00 1,00 0,33 1,00 1,00

1 2 1 1 1 2 3 1 1 1 1 1 1 1

Source: Own statistics.

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The ratio of the standardized pages per country to number of universities shows that the countries with the highest ratios are Israel and U.S. (with a similar ratio of 55 pages per center), following them are Island (51 pages), the Netherlands (43 pages), Singapore (36 pages), and Chile (43 pages). Although the difference between Israel and U.S. is huge (from 10,051 to 335) they have a similar proportion of publications according to this ratio.

ECONOMIC GROWTH TRENDS: CHARACTERISTICS, KEY FACTORS AND MODELS Characteristics Furthermore, I picked up data about four different characteristics of the articles on economic growth: type of analysis, countries, model or theoretical trend, and geographical scope of the research. Figure 3 shows the evolution of economic growth studies regarding the analysis on which the authors base their study: empirical, theoretical or both. It was observed that the theoretical analysis dominated the merely empirical ones in the economic growth field. In Figure 3, two specific observations are emphasized. First, both types of analyses followed a clearly growing and positive tendency at the time. Moreover, the studies with a mixed analysis (both empirical and theoretical) experimented similar performance. Second, a similar evolution was observed in both empirical and theoretical analyses since the start year until 1996, and from then on, an increasing gap developed: the theoretical analysis surpassed the empirical one. A conjecture that tries to explain this conduct pattern leads us again to the Mankiw, Romer and Weil (1992) article as a stimulating factor of the theoretical debates about economic growth, particularly about endogenous growth and the

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recent mathematical applications –like game theory– to this field of Economics. Another possible explanation that comes out to light from the observed behavior alludes to the improvement of the applied mathematical techniques to the economic growth theory. The minor contribution of an empirical analysis indicates that we are dealing with highly theoretical journals.

A. Accumulated frequency 450 400 350 300 250 200 150 100 50 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Empirics

Theorics

Both

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0,600 0,500 0,400 0,300 0,200 0,100 0,000 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Empirics

Theorics

Both

Source: own estimations.

Figure 3. Evolution of economic growth publications by type of analysis.

The economic growth studies by classification of countries in developed, developing and mixed countries are shown in Figure 4. The number of studies in developed countries was higher than in developing countries during those eleven years. In addition, a trend towards a

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slowdown of the scientific production was appreciated in developing countries. The production on economic growth was also favorable to the studies for both developed and developing countries since an increasing tendency of this category is noticed in Figure 4-A. In general, a preference from authors to empirical applications in developed countries is emphasized. Better quality of available data motivates the highest quantity of studies in these countries. Furthermore, I think that Summers and Heston’s and Maddison’s databases may have influenced the huge increase in publications for this type of countries.

A. Accumulated frequency 250 200 150 100 50 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Developing

Developed

Both

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B. Annual sharing 0,600 0,500 0,400 0,300 0,200 0,100 0,000 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Developing

Developed

Both

Source: own estimations.

Figure 4. Evolution of economic growth publications by kind of country.

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Figure 5 is especially important due to recent debates about the two main economic growth theories (endogenous and exogenous growth). It shows the evolution of these two theoretical currents in the period. The most noticeable fact is the large quantity of endogenous publications in this sample of journals.

A. Accumulated frequency 350 300 250 200 150 100 50 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Endogenous

Exogenous

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B. Annual sharing 0.450 0.400 0.350 0.300 0.250 0.200 0.150 0.100 0.050 0.000 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Endogenous

Exogenous

Source: own estimations.

Figure 5. The economic growth evolution by theoretical model.

The trends to publications on economic growth by geographical scope are shown in Figure 6. The annual evolution points out the hegemony of the studies within the international scope. One hypothesis associated to this conduct observes recent improvements in the international databases: the aforementioned databases of Summers and Heston and the ones by Madisson, the periodical publications of United Nations, OECD, and the International

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Monetary Fund, among others. A possible explanation of the poor results at the regional level is that we are dealing with a sample of leader journals where regional science has little coverage.

A. Accumulated frequency 400

Axis Title

350 300 250 200 150 100 50 0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Regional

National

International

B. Annual sharing 0.700 0.600

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0.500 0.400 0.300 0.200 0.100 0.000 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Regional

National

International

Source: own estimations.

Figure 6. The economic growth evolution by geographical scope.

It seems that the studies of economic growth at aggregate levels are more important. However, some works suggest investigating at more disaggregate levels like the regional one, for example.38

38

See, for instance, Rodriguez-Pose, A. (1994), Bernard and Jones (1996a and 1996b), Hobijn and Franses (2000), Krueger and Lindahl (2001), De la Fuente (2002), among others.

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Key Factors in Economic Growth Studies

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In this section, I discuss the factors used by the authors to test hypotheses about economic growth in the 30 journals. The set of factors is considered from the hypotheses tested in the investigation articles. The objective is to find out the main tendencies to explain economic growth. I analyze the variables in four different categories of the scientific production: per year, per model (endogenous and exogenous), according to the geographic scope and country. In the 948 articles, around 160 different variables were studied by the authors as explanatory variables of economic growth. I built these variables as a result of aggregating simple variables into more general categories for a best description. For example, Investment is one of the general categories built from a set of variables more specifically related to this topic as equipment investment, private investment, among others. Moreover, Tax includes variables such as capital taxes, consumption taxes, progressive taxes and income taxes. Other examples of global categories built this way are Financial Development, Trade Openness, Technological Change, Public Expenditure, Fertility, Learning, International Finance, among others. So, I obtain 160 categories, which I analyze in this section. In Table 10, I report the variables that were used in two or more articles to explain economic growth during 1992-2002. The variables of highest ranking are Financial Development, R&D, Technology, Income, Human Capital, Education, Inflation, Investment, Income Inequality, Fiscal Policy and Trade Openness. In general, these 11 variables were used in 30% of the articles to explain economic growth. Following this first group are Exports, Taxes, Infrastructure, Productivity, International Trade, Income Distribution, Environmental Factors, Fertility, Technological Change, Social Inequality, International Finance and Institutional Reforms. All these variables were studied in nearly 20% of the articles. Table 10. The most contrasted variables in economic growth studies Ranking 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Variable Financial development R&D Technology Incomes Human capital Education Inflation Inversion Income inequality Fiscal policy Trade openness Exportations Taxes Infrastructure Productivity International trade

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Counts 35 22 21 20 19 18 18 18 17 16 15 15 14 12 12 11

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Table 10. Continued Ranking 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61

Variable Environmental factors Fertility Technological change Social inequality International finances Institutional reforms Physical and human capital Trade Learning Demographic factors Savings Public capital Govern Unemployment Public expenditure Innovation Public policies International risk Spillovers Business cycles Growth Employment Foreign Direct Investment (FDI) Institutions Profitability Human capital accumulation Capital accumulation Capital External debt Macroeconomic factors Fluctuations Regional instability Poverty Tariffs Urbanization International aids Regional characteristics Knowledge Consumption Corruption Credit Property rights Public debt Public firm

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Counts 11 11 10 10 10 10 9 9 8 8 7 7 7 6 6 6 6 6 6 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3

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Worldwide Rankings in Economic Growth Ranking 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91

Variable Public finances Geography Finances intermediation Trade policy Output Wages Social security Aggregate value Agglomeration Life’s quality Colonialism Intra-industrial trade Communications Social conflict Unitary costs Democracy Money Scope economies Imitation Informatics Regional integration Markets Migration Mobility Patents Monetary policy Natural resources Health Social status

91 Counts 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Source: Own statistics.

The ranking per year is as follows: in 1992 the variables with highest ranking were Trade Openness, Investment and Productivity; in 1993 the highest ranking variable was Inflation; in 1994 we have Exports; in 1995 R&D was shown as the most tested by the authors; in 1996 and 1997 Financial Development; for 1998 there were two variables: Trade Openness and Financial Development; in 1999 was Infrastructure; in 2000 three variables were the leading ones: Financial Development, Education and R&D; while in 2001 four variables were observed at the top: Human Capital, Financial Development, Education and Fiscal Policy; and finally, in 2002, the leader position was for the Technology variable. Concerning the two main currents (endogenous and exogenous) in economic growth, the most used categorical variables were R&D, Fiscal Policy, Taxes, Financial Development, Technology, Inflation, Learning, Technological Change and Innovation for endogenous growth. For exogenous models, we have Income, Education, Human Capital, Trade Openness, Financial Development, Inequality of Income, Investment, Physical and Human Capital, Income Distribution and Institutional Reforms as the highest ranked variables. These

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results reflect that there is a different preference of variables to explain economic growth according to the essay model. Only Financial Development was chosen by both models. The economic growth trends may also be explained by geographical scope. Thus, at international level, the most used variables were Financial Development, Investment, Wage Inequality, Trade Openness, R&D, International Trade, Exports and Technology, while in the national field among the most outstanding variables were Technology, Exports, Productivity, Financial Development, Inflation, Infrastructure, Learning, Technological Change and Human Capital. Finally, on the regional level we have Income, Regional Characteristics, Education, Employment, Urbanization and Agglomeration. According to countries, we have the following results. In developed countries, the variables were Income, R&D, Technology, Public Capital, Financial Development, Exports, Fiscal Policy and Learning. In developing countries, the ranking was made up by Financial Development, Trade Openness, Exports, Inflation, Productivity, Institutional Reforms and Social Inequality. When I considered studies that analyzed both developed and developing countries, the most important variables were Financial Development, Inequality of Income, Human Capital, Investment, Physical and Human Capital, International Trade, Education, Trade Openness, Environmental Factors and Income. In general, an important concentration of authors for few variables is observed. For example, 30% of the articles only used 6% of the variables. Meanwhile, 10% of the articles contributed with 42% of the proposed variables.

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Predicting the Model in Economic Growth In this section I try to explain the authors’ decision about the used model to analyze economic growth. The study is restricted to the possibility of choosing between two models: endogenous or exogenous models. I estimated a limited dependent variable model where decision variable is the endogenous or exogenous model as a dependent variable, and it equals to 1 when the model is endogenous and 0 when the model is exogenous. The classification between endogenous and exogenous models was decided on the basis of the coefficient sign of the initial income variable. Kocherlakota and Yi (1995) used a growth model to demonstrate that the endogenous and exogenous models can be differentiated this way.

The Logit Model In economic growth, the debate about the relevant factors to explain the performance of economies may be grouped in two categories: the positions that adopt one endogenous criterion of economic growth and those positions that consider economic growth as a result of exogenous factors. Since an economic growth author is either in the endogenous position or not, endogenous is a yes or no decision. Hence, the response variable, or regressand, can take only two values, say, 1 if the author is in the endogenous position and 0 if he or she is in the exogenous one. In other words, the regressand is a binary, or dichotomous, variable. In this case, authors’ decision is a function of a variety factors, such as the relevance of the journal,

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journals’ thematic lines, kind of country, geographical scope of the empirical work, among others. In these models, where regressand Y is qualitative, the objective is to find the probability of something happening, such as authors’ decision about current of economic growth. Hence, we have to estimate qualitative response regression models. A Logit model considers the following regression equation:

Yi = β1 + β2 X i + ui

(1)

Pi = E (Y = 1/ X i ) = β1 + β2 X i

(2)

Alternatively,

where X is any variable that explains authors’ decision about model implemented, Y takes the value 1 if authors’ decision is the endogenous model and 0 if it is the exogenous one. Now, consider the following representation:

Pi = E (Y = 1/ X i ) =

1 1 + exp

−( β1 + β2 X i )

(3)

It is known that (3) can be expressed as:

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Pi =

1 exp z = 1 + exp− Zi 1 + exp z

(4)

where Zi = β1 + β 2 X i . Equation (4) represents what is known as the (cumulative) logistic distribution function (Gujarati, 2004). It is widely demonstrable that (4) cannot be estimated by an ordinary least squares (OLS) procedure, but equation (4) can be linearized as follows. If Pi, the probability of choosing an endogenous model is given by (4), then

(1 − Pi ) ,

the probability of not choosing an

1 1 + exp Zi

(5)

endogenous model is:

1 − Pi = Alternatively,

Pi 1 + exp Zi = = exp Zi − Zi 1 − Pi 1 + exp

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(6)

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Vicente German-Soto The right side term, Pi

(1 − Pi ) , in the expression (6) is interpreted as the odds ratio in

favor of a chosen endogenous model, that is to say, the ratio of the probability that one author’s decision is the endogenous model option to the probability that he or she chooses the exogenous model. Finally, taking the natural log of (6), it is possible to obtain the called Logit model for this kind of models:

⎛ P ⎞ Li = ln ⎜ i ⎟ = Zi ⎝ 1 − Pi ⎠ = β1 + β 2 X i + ui

(7)

where L is the log of the odds ratio and term ui is the stochastic error term included for estimation purposes. Equation (7) has some interesting properties. For example, one can add as many regressors as may be dictated by the underlying theory. If L, the logit, is positive, it means that when the value of the regressors increases, the odds that the regressand equals 1 increase. If L is negative, the odds that the regressand equals 1decrease as the value of variables X increases.

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Empirical Results of the Logit Model I estimate a Logit model with the next explicative variables:39 the impact factor of the journal where the article was published (IF), the cited half-life of the articles in each journal (CHL); kind of country: developing (A1), developed (A2), or both (A3); type of article: empirical (C1), theoretical (C2); geographical scope: regional (S1), national (S2), and international (S3). Each variable, except the first two, is a dummy variable. For IF and CHL variables, the values are given in the ISI Web of the Social Science. The results are shown in Table 11. Results indicate that the null hypothesis of all coefficients being zero is rejected (see log likelihood function and Hosmer-Lemeshow value). Also, we can see that geographical scope (S1, S2 and S3) does not influence the election of either an endogenous or an exogenous model. Moreover, developed countries variable does not turn out to be significant. The remainder of the variables indeed proves to be significant. A global analysis indicates that, when one article is published in journals with a major CHL index or it is a theoretical work (C2), then the probability that the article is endogenous increases. The probability that an article is endogenous is calculated by equation (8):

39

I report the variables name abbreviation in parentheses.

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2 3 3 ⎧ ⎫ exp ⎨ βˆ1 + βˆ2 IF + βˆ3CHL + ∑ θˆi Ci + ∑ ωˆ i Ai + ∑ ϕˆi Si ⎬ i =1 i =1 i =1 ⎩ ⎭ P ( MOD = 1) = 2 3 3 ⎧ˆ ˆ ⎫ 1 + exp ⎨ β1 + β 2 IF + βˆ3CHL + ∑ θˆi Ci + ∑ ωˆ i Ai + ∑ ϕˆi Si ⎬ i =1 i =1 i =1 ⎩ ⎭

(8)

In the Logit model, the interpretation of the coefficients is by means of the odds-ratio.40 For example, the negative relationship between the Impact Factor and the endogenous model indicates that articles published in journals with the highest Impact Factor reduce the probability of including an endogenous growth model. When the Impact Factor is increased, the publication of endogenous models tends to diminish.

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Table 11. Logit model results on economic growth meta-analysis +---------------------------------------------+ | Multinomial Logit Model | | Maximum Likelihood Estimates | | Dependent variable MOD | | Weighting variable None | | Number of observations 532 | | Iterations completed 6 | | Log likelihood function -257.0815 | | Restricted log likelihood -360.0450 | | Chi squared 205.9269 | | Degrees of freedom 10 | | Prob[ChiSqd > value] = .0000000 | | Hosmer-Lemeshow chi-squared = 5.07306 | | P-value= .74974 with deg.fr. = 8 | +---------------------------------------------+ +---------+--------------+----------------+--------+---------+----------+ Variable | Coefficient | Standard Error |b/St.Er.|P[|Z|>z] | Mean of X| +---------+--------------+----------------+--------+---------+----------+ Characteristics in numerator of Prob[Y = 1] Constant -.2353570619 .72623519 -.324 .7459 IF -.2522411771 .12160090 -2.074 .0380 1.4390244 CHL .1430057854 .70159694E-01 2.038 .0415 8.4746241 C1 -1.067959373 .29303643 -3.644 .0003 .26315789 C2 1.220364123 .41270067 2.957 .0031 .47556391 A1 -1.722055286 .85910594 -2.004 .0450 .11090226 A2 -1.286764443 .83138938 -1.548 .1217 .21428571 A3 -2.084933932 .85176677 -2.448 .0144 .22744361 S1 .1605381240E-01 .85218871 .019 .9850 .63909774E-01 S2 1.278531189 .84948324 1.505 .1323 .14473684 S3 .9383384133 .82648408 1.135 .2562 .36842105 (Note: E+nn or E-nn means multiply by 10 to + or -nn power.)

Source: own estimations.

Likewise, for any couple of observations, one article published in a journal with 1% of cited half-life (CHL) higher than others has a 1.15 odds-ratio for the model to be endogenous. This means that the endogenous growth models tend to publish in journals that quote articles with the highest age average.

40

{

}

The odds-ratio for the variable i is calculated with the equation Odd ratioi = exp βˆi , θˆï , ωˆ i , ϕˆi , depending on which variable is chosen.

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The ‘empirical’ and ‘theoretical’ variables have opposite effects in the forecaster of the endogenous model. Empirical works (C1) reduce the probabilities by 0.344, while the theoretical ones (C2) raise them by 3.39 odds. When a piece of work is empirical, the probabilities that it includes an exogenous model are increased. Moreover, if the work is theoretical, it is more probable that it may be an endogenous model. This finding confirms the highest theoretical structure that dominates endogenous models. The kind of country variable has negative impacts on the forecaster of endogenous models. However, it is not significant for developed countries variable (A2). Developing countries variable (A1) has a 0.179 oddsratio to include an exogenous model, while the probabilities in favour of an exogenous model are 0.124 when the analysis includes both kinds of countries (A3). Other results obtained with Logit are shown in Table 12, where the predictions for the model are displayed. The adjust of the model is acceptable (McFadden index is estimated by nearly 29%), while Akaike’s and Schwarz’s information criteria suggest that the present model is better than others previously essayed with similar characteristics.

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Table 12. Fit measures for binomial choice model Logit +----------------------------------------+ | Fit Measures for Binomial Choice Model | | Logit model for variable MOD | +----------------------------------------+ | Proportions P0= .409774 P1= .590226 | | N = 532 N0= 218 N1= 314 | | LogL = -257.08154 LogL0 = -360.0450 | | Estrella = 1-(L/L0)^(-2L0/n) = .36614 | +----------------------------------------+ | Efron | McFadden | Ben./Lerman | | .35379 | .28597 | .68763 | | Cramer | Veall/Zim. | Rsqrd_ML | | .35423 | .48523 | .32096 | +----------------------------------------+ | Information Akaike I.C. Schwarz I.C. | | Criteria 1.00783 583.20617 | +----------------------------------------+

Source: own estimations.

Finally, in Table 13 the predicted values are collected according to the model. In general, it is possible to see that the estimated model has an efficiency of 78.4%, a result that shows the fit degree of the model for prediction purposes. Table 13. Observed and predicted values of the Logit model Threshold value for predicting Y=1 = .5000 Predicted ------ ------------+------Actual 0 1 | Total ------ ------------+------0 160 58 | 218 1 57 257 | 314 ------ ------------+------Total 217 315 | 532

Source: own estimations.

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Elements outside the main diagonal of Table 13 are the model errors and/or the atypical cases. For example, result 58 indicates the quantity of observations that the model does not forecast as endogenous, although it has a probability higher than 50% to be endogenous. In addition, the number of result 57 refers to observations that are endogenous, but our model is forecasted as exogenous.

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CONCLUSION This chapter ranks academic institutions and individuals in relation to economic growth over a span of 11 years, covering the period 1992-2002. These rankings are based upon standardized page counts in 30 journals. Methodology is the same followed in other metaanalytic works, thus the usual caveats apply. One could question the 30 journals used, or the conversion factors applied even after adjusting them by citation impact factors, size and age of the journal. However, I support the idea that in the top journals are the main contributions in economic growth theory. Although economic growth registered a great impulse in the 1990s and the past decade, to date there has not been a bibliographical work that summarizes advances and also shows statistics of publications in this area of economics. This chapter constitutes an important effort in this sense. Among the multiple aspects developed in this chapter, there are geographical concentration of the publications and the relative importance of the economic growth theme. I find a notable concentration of publications on economic growth in a few countries, outstanding the education institutions belonging to developed countries as the most dynamic. One aspect to highlight is that the endogenous growth models tend to publish in journals that quote articles with the highest age average. We can see economic growth as a field of “great importance” to economic research due to the scientific production on this topic in the 30 journals, which represents nearly 8% of the total of publications in Economics. However, economic growth covers one space of the 10% in the first 8 journals of the ranking. The interest of the scientific production on economic growth has been influenced by several factors. The developments of new mathematical models, the econometric tests, and the new data sets guide this tendency. It was commented that nearly 38% of the articles developed a new mathematical method out of the traditional endogenous and exogenous models. Finally, this chapter offers a view of the current state of investigation in this specific field of Economics. I believe these rankings are a helpful guide to graduate students, faculty members and academic administrators.

REFERENCES Anselin, L., Rey, S. & Talen, E. (2000). The Expanded and Revised IRSR Subject and Author Index. International Regional Science Review, 23(4), 345-349. Bairam, E. I. (1994). Institutional Affiliation of Contributors to Top Economic Journals 19851990. Journal of Economic Literature, 32(2), 674-679.

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Baltagi, B. H. (1998). Worldwide Institutional Rankings in Econometrics: 1989-1995. Econometric Theory, 14, 1-43. Baltagi, B. H. (2003). Worldwide Institutional and Individual Rankings in Econometrics over the Period 1989-1999: An Update. Econometric Theory, 19, 165-224. Beed, C. & Beed, C. (1996). Measuring the Quality of Academic Journals the Case of the Economics. Journal of Post-Keynesian Economics, 18(3), 369-396. Bernard, A. & Jones, C. I. (1996a). Comparing Apples to Oranges: Productivity Convergence and Measurment Across Industries and Countries. American Economic Review, 86(5), 1216-1238. Bernard A. & Jones, C. I. (1996b). Productivity Across Industries and Countries: Time Series Theory and Evidence. Review of Economics and Statistics, 78(1), 135-146. Chung, K. H. & Cox, R. A. K. (1990). Patterns of Productivity in the Finance Literature: A Study of the Bibliometric Distributions. Journal of Finance, 45(1), 301-309. Colander, D. (1989). Research on the Economics Profession. Journal of Economic Perspectives, 3(4), 137-148. Collins, J. T., Cox, R. G. & Stango, V. (2000). The Publishing Patterns of Recent Economics Ph. D. Recipients. Economic Inquiry, 38(2), 358-367. Coupé, T. (2003). Revealed Performances. Worlwide Rankings of Economists and Economics Departments, 1969-2000. Forthcoming, Université Libre de Bruxelles. Cribari-Neto, F., Jensen, M. J. & Novo, A. A. (1999). Research in Econometric Theory: Quantitative and Qualitative Productivity Rankings. Econometric Theory, 15(5), 719-752. De la Fuente, A. (2002). On the Sources of Convergence: A Close Look at the Spanish Regions. European Economic Review, 46(3), 569-599. Dundorf, M., Perrons, D., Reilly, B. & Bull, R. (2002). Citations, Authors and Referees: Regional Studies 1981-2002. Regional Studies, 36(9), 1053-1065. Dusansky, R. & Vernon, C. J. (1998). Rankings of U.S. Economics Departments. Journal of Economic Perspectives, 12(1), 157-170. Elliot, C., Greenaway, D. & Sapsford, D. (1998). Who’s Publishing Who? The National Composition of Contributors to some Core US and European Journals. European Economic Review, 42, 201-206. Figlio, D. (1994). Trends in the Publication of Empirical Economics. Journal of Economic Perspectives, 8(3), 179-187. Frey, B.S. & Eichenberger, R. (1993). American and European Economics and Economists. Journal of Economic Perspectives, 7(4), 185-193. Gujarati, D. N. (2004). Basic Econometrics. New York: The McGraw-Hill Companies. Hall, A. D. (1990). Worlwide Rankings of Research Activity in Econometrics: An Update, 1980-1988. Econometric Theory, 6, 1-16. Hobijn, B. & Franses, P. H. (2000). Asymptotically Perfect and Relative Convergence of Productivity. Journal of Applied Econometrics, 15(1), 59-81. Hondgson, G. M. & Rothman, H. (1999). The Editors and Authors of Economics Journals: A Case of Institutional Oligopoly? Economic Journal, 109(453), F165-F186. Isard, W. (1999). Regional Science: Parallels from Physics and Chemistry. Papers of Regional Science, 78(1), 5-20. Isserman, A. M. (1995). The History, Status, and Future of Regional Science: An American Perspective. International Regional Science Review, 17(3), 249-296.

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Kalaitzidiakis, P., Mamuneas, T. P. & Stengos, T. (1999). European Economics: An Analysis Based in Publications in the Core Journals. European Economic Review, 43(4-6), 11501168. Kocherlakota, N. R. & Yi, K. (1995). Can Convergence Regressions Distinguish Between Exogenous and Endogenous Growth Models? Economics Letters, 49, 211-215. Krueger, A. B. & Lindahl, M. (2001). Education for Growth: Why and For Whom? Journal of Economic Literature, 39, 1101-1136. Laband, D.N. & Piette, M. J. (1994). The Relative Impact of Economics Journals. Journal of Economic Literature, 32(2), 640-666. Liewowitz, S. J. & Palmer, J. P. (1984). Assessing the Relative Impact of Economics Journals. Journal of Economic Literature, 22, 77-88. Lucas, R. F. (1995). Contributions to Economics Journals by the Canadian Economics Profession, 1981-1990. Canadian Journal of Economics, 28(4), 945-960. Mankiw, N. G., Romer, D. & Weil, D. N. (1992). A Contribution to the Empirics of Economic Growth. Quarterly Journal of Economics, 107(2), 407-437. Nijkamp, P. & Poot, J. (2002). The Last Word on the Wage Curve? Working Paper No. 029/3, Tinbergen Institute. Rey, S. & Anselin, L. (2000). Regional Science Publication Patterns in the 1990s. International Regional Science Review, 23(4), 323-344. Rodríguez-Pose, A. (1994). Socioeconomic Reestructuring and Regional Change: Rethinking Growth in the European Community. Economic Geography, 70(4), 325-343. Sarafoglou, N. & Haynes, K. E. (1996). University Productivity in Sweden: A Demonstration and Explanatory Analysis for Economics and Business Programs. The Annals of Regional Science, 30(3), 285-304. Sauer, R. D. (1988). Estimates of the Returns to Quality and Coautorship in Economic Academia. Journal of Political Economy, 96(4), 855-866. Scott, L.C. & Mitias, P. M. (1996). Trends in Rankings of Economics Departments in the U.S.: An Update. Economic Inquiry, 34(2), 378-400. Strathman, J. G. (1992). Analysis of Theoretical, Methodological and Empirical Research in the Journal of Regional Science. Journal of Regional Science, 32(4), 501-509. Suriñach, J., Duque, J.C., Ramos, R. & Royuela, V. (2003). Publication Patterns in Regional and Urban Análisis. Have Topics, Techniques and Applications Changed During the Nineties? Regional Studies, 37(4), 353-365. Van den Bergh, J. C. & Button, K. J. (1997). Meta-Analysis of Environmental Issues in Regional, Urban and Transport Economics. Urban Studies, 34(5-6), 927-944. Wichmann M. C. & Schwarz, A. W. (1999). Scientific Centres in Europe: An Analysis of Research Strength and Patterns of Specialisation Based on Bibliometric Indicators. Urban Studies, 36(3), 45, 3-477.

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Chapter 4

ECONOMIC GROWTH, INEQUALITY AND FISCAL POLICIES: A SURVEY OF THE MACROECONOMICS LITERATURE Leonel Muinelo-Gallo and Oriol Roca-Sagalés Universitat Autònoma de Barcelona – Department of Applied Economics

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ABSTRACT The relationship between economic growth and income inequality has attracted a great deal of attention in recent years. The growth experience of several countries during the last decades with different behaviors in terms of economic inequalities has generated a growing strand of theoretical and empirical literature trying to explain these events. Although one could argue that economic growth and inequality influence each other, it is also possible that different public policies could influence the relationship between both macro aggregates. Fiscal policy has traditionally been considered an effective instrument trough which to influence aggregate demand, the distribution of income and wealth, and the economy’s capacity to produce goods and services. Therefore, a correct selection of the composition and combination of these policies has become of crucial importance for the purpose of achieving a broad-based stable path of economic growth across countries. Within this framework, this chapter reviews the evolution of economic literature that analyzes the relationship between growth and inequality. We perform a comparative analysis of different theoretical and empirical developments, with particular focus on the importance, in terms of size and composition, of different fiscal policies, explaining that relationship.

1. INTRODUCTION The relationship between economic growth and income inequality has attracted a great deal of attention in recent years. The growth experience of different economies with different

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behaviors in terms of economic inequalities has generated a growing strand of theoretical and empirical literature trying to explain these events. An economy’s growth rate and its income distribution are both endogenous outcomes of the economic system. They are therefore subject to common influences, both with respect to structural changes as well as macroeconomic policies. Due to the importance of fiscal policy as a redistributive tool and as an instrument to promote economic growth (Musgrave, 1959), it is considered one of the key mechanisms to achieve goals in terms of efficiency and equity. In general, it is possible to distinguish three major periods in the study of the relationship between economic growth and inequality and the influence of fiscal policies. During the first period, initiated by the seminal work of Kuznets (1955), it was considered that economic development affects factorial and sectorial income distribution, with no important scope for fiscal policy to affect both macro-aggregates in the long-run. In turn, income inequality became a topic of lower interest in the later macroeconomic analysis. Thus, in the neoclassical growth models, inequality of income and wealth among consumers was considered the passive result of the aggregate dynamics and market interactions. The endogenous growth models putting forward new ideas about the effects of economic development on income inequality initiated the second period.41 The contributions following this approach incorporated three new phenomena into the analysis: the increased diffusion of new technologies in different productive activities; the rapid growth of international trade, and the emergence of new organizational forms. All this new growth models have revived the interest of fiscal policy as an effective instrument to correct undesirable outcomes of the process of economic growth in terms of inequality. In contrast, in the extensive literature on development that has appeared during the 1990s, the causation between inequality and growth runs in the opposite direction and the central concern mainly focuses on the role of income and wealth inequality in the process of economic growth. Two main groups of studies can be identified in this theoretical approach: one group suggests various transmission channels through which greater initial inequality fosters economic growth, while the other suggests several economic and political channels through which initial inequality might be harmful for growth. On the empirical side, the relationship between income inequality and economic growth has received considerable attention. This literature is largely based on cross-country regressions trying to explain economic growth and, to a lesser extent, on panel data econometrics. Whereas cross-country regressions are used to examine the relationship in the long-run,42 panel data estimates aim at measuring the relationship in the short and medium-term.43 In a parallel strand of empirical literature, the macroeconomic effects of fiscal policies on economic activity have been widely examined with contrasted views. Numerous works have used time series models, especially vector autoregressive models, to estimate the effects of different fiscal policy shocks on economic activity, but the issue of the sign and magnitude of these effects across different countries is very much an open question. Other studies used a cross country approach to examine the impact of aggregate measures of fiscal policies on 41

Previous theoretical contributions using endogenous growth models were made on the basis of a simple representative agent, without giving importance to distributional issues (see, for example, Romer, 1986; and Lucas, 1988). 42 See for example, Persson and Tabellini (1994) and Perotti (1994 and 1996). 43 See Li and Zou (1998), Forbes (2000), Barro (2000), Lundberg and Squire (2003), Voitchovsky (2005); and, for more recent empirical contributions, see Lin et al. (2009), Huang et al. (2009), and Castelló-Climent (2010).

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economic growth for an extensive sample of countries. However, the results are not particularly robust, showing that the impact and significance of the fiscal variables depend on the set of control variables included and also on the initial conditions of the economy. Overall, no matter the approach, there is little consensus among economists as to the magnitude or even the sign of the effects of fiscal policies on economic growth. The majority of these empirical studies use aggregate measures of fiscal policy to evaluate their impacts on economic activity and rarely take into account distributive issues. The joint response of economic growth and income inequality to fiscal policies has been largely overlooked, with significant exception of a few recent theoretical and empirical papers that find a significant trade-off between some fiscal policies in terms of efficiency and equity. However, some of these studies also underline that in certain circumstances, and through certain combination of fiscal policies, this trade-off can be avoided. In this chapter, we review different contributions trying to explain theoretically and also empirically the relationship between growth and inequality. We focus on those approaches that can help to understand the role of fiscal policies in the relationship between these two macro-aggregates. In this sense, our revision emphasizes the importance of how causation between both variables is considered: it could run from growth to inequality (section 2), from inequality to growth (section 3), or there may be other factors that simultaneously determine both (section 4). Finally, section 5 contains some concluding remarks.

2. EFFECTS OF ECONOMIC GROWTH ON INEQUALITY

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2.1. The Traditional Approach Seminal studies by Lewis (1954), Kuznets (1955) and Kaldor (1956) suggested that income inequality is mostly determined by the level of economic development. More precisely, they analyzed how economic development affects distribution in the long-run suggesting a potential increasing effect of growth on factorial and sectorial inequality in the first stages of economic development, and a decreasing effect in the later stages (“inverted-U hypothesis”).44 The neoclassical growth model (Solow, 1956), with linear savings functions and perfect credit markets, provides a theoretical underpinning for the relationship between inequality and capital accumulation as emphasized by Kuznets and his followers. At the initial stages in the process of capital accumulation, the distribution of income and wealth becomes more unequal, but after sufficient wealth has become accumulated (so that wages have sufficiently grown and investment returns have sufficiently fallen), the wealth and income distribution equalizes. More precisely, according the standard neoclassical assumptions (all individuals have the same amount of labor remunerated according to its marginal productivity, the relation consumption/saving is exogenous and linear with respect to income, and capital productivity decreases as more capital is accumulated), income distribution does not affect economic growth. In turn, when the marginal consumption propensity is constant and 44

For theoretical studies of this “inverted-U hypothesis”, see Robinson (1976), Greenwood and Jovanovic (1990), and Helpam (1998). For more recent empirical studies, see Mushinski (2001), Huang (2004), and Huang and Lin (2007). Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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identical across households, wealthy people consume so much that, in steady state, all wealth differences (beyond those implied by non-accumulated factors) will eventually vanish. So, the accumulation implies a tendency toward equality in the distribution of income and wealth when the (exogenously given) distribution of non-accumulated factor is relatively equal. When all families are equally endowed with the non accumulated factor there will be absolute convergence (see Stiglitz, 1969; Tamura, 1991; and Bértola et al., 2006 chapter 2).45 Some studies used the neoclassical framework to study the effects of fiscal policy on economic activity. For example, Sato (1967), Krzyzaniak (1967) and Feldstein (1974) analyze the effects of different taxes on growth; Summers (1981) and Auerbach and Kotlikoff (1987) adapt the model of overlapping generations of Diamond (1965) to analyze the dynamic effects of fiscal policy; Judd (1985) and Chamely (1986) used the model developed by Cass and Koopmans (1965) to study the effects of fiscal policy considering endogenous saving rates. In general, all these models emphasize the transitory effects of different instruments of fiscal policy. In this context, the differences in tax and expenditure policies can be important determinants of the level of output, but are unlikely to have significant permanent effects on economic growth. The public-policy neoclassical growth models contrast with the predictions of the endogenous growth models, where investment in human and physical capital does affect the steady-state growth rate and, consequently, there is much more scope for tax and government expenditure to play a role in the growth process. The common property of the endogenous growth models is that choices made by economic agents collectively determine the growth rate (this is not conducted by exogenous factors), and, in turn, these choices can be influenced by economic policies that change the relevant trade-offs. So, the endogenous approach tends to transform the temporary growth effects of fiscal policy that the neoclassical model involves, into permanent effects. It follows that fiscal policy can affect the level of output as well as its long-term growth rate. In this context, one case of particular interest rises from Barro (1990) and Barro and Sala-i-Martín (1992), where a public good financed by taxation is considered as an additional input in the production function. These models distinguish public expenses as productive or non productive, introducing them as arguments in the private production function (when classified as productive, public expenses might have a positive direct effect on the growth rate), and taxes as distorting or not distorting, depending on whether they do or do not affect private investment decisions with respect to physical and human capital and, consequently, the economic growth rate. In other endogenous growth models, like Mendoza et al. (1997), consumption taxation becomes distortionary, with a negative effect on growth if leisure is included in the utility function, affecting 46 education/labor-leisure choices and thus capital/labor ratios in production.

45

However, when households’ savings choices are based on intertemporal utility maximization over an infinite horizon, the distribution of lifetime wealth may well become increasingly unequal in a neoclassical growing economy. This is the case when consumption-smoothing motives lead poorer consumers to choose a flatter consumption path in order to ensure the satisfaction of a minimum consumption standard: if subsistence consumption is important, poor households cannot afford to save, while wealthier ones choose steeper consumption paths and accumulate relatively more wealth (see Bértola et al., 2006, chapter 3). 46 Other studies of public policy endogenous growth models are Jones, Manuelli and Rossi (1993); Glomm and Ravikumar (1992 and 1997), Stokey and Rebelo (1995), Turnosvsky and Fischer (1995), Baier and Glomm (2001), Li and Sarte (2004), Park and Philippopoulos (2003 and 2004), and Cassou and Lansing (2006).

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This endogenous growth literature opened new avenues through fiscal policy can have permanent effects on economic growth. In turn, as we will see below, has brought to light new paths trough which growth and inequality may affect each other. In this context, fiscal policy has acquired a significant importance as an effective instrument to affect aggregate demand as well as an important tool for the purpose of redistribution.

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2.2. The New Growth Theories Approach The increasing inequality experienced by the OCDE countries during the eighties and 47 nineties, hardly consistent with the traditional view of Kuznets, entails the development of new endogenous growth contributions. New growth theories have focused on three related phenomena trying to explain these events: the increased diffusion of new technologies in different productive activities, the rapid growth of international trade, and the emergence of new organizational forms. Thus, some authors argued that skill-biased technological progress (arguably the major source of economic growth) may lead to higher inequality whenever it affects the productivity of different types of labor in various ways. In general, this argument is based on the capital-skill complementarity conjecture of Krussel et al. (2000). This conjecture comes from the fact that the decrease in equipment prices induced by a higher productivity has brought in an increase of the use of capital in the production process; and taking into account that qualified labor is relatively more complementary to this equipment than non qualified labor, this bigger capital stock increases the skill premium of qualified workers, enlarging wage inequality across 48 49 different educational cohorts, and within cohorts with the same educational level. In turn, several authors argued that during the 90’s the skill-biased technological change has induced a reduction on workers unions jointly with decentralization in the wage bargaining process. The higher complementarities between capital and qualified workers have modified worker’s incentives to unionize increasing wage inequality across workers and also between workers and employers. This policy response represents an additional channel through which technological diffusion may affect income distribution, in addition to their direct impact via wage structure (Acemoglu et al., 2001; Ortigueira, 2002; and, Checchi and García-Peñalosa, 2010). The second explanation, based on the Heckscher-Ohlin model, focuses on the effects of rapid growth in international trade. According to some authors, the gains from international trade affect mainly the most abundant production factor in the country (Wood 1994, and Wood and Ridao-Cano 1999). Thus, in developing countries abundant in unskilled labor, the major exports of labor-intensive goods increases the demand and wages of unskilled workers, while demand and wages of skilled workers falls. This process reduces income inequality within these countries, sinking the wage differential between the two types of workers. On the other hand, in developed countries abundant in skilled labor, higher international trade will result in more imports of goods intensive in unskilled labor and more exports of goods intensive in skilled labor, increasing the demand for qualified workers and thus extending 47

See Berman et al (1994), Atkinson (1996), Gottschalk and Smeeding (1997), or Autor et al (1998). See Eicher (1996), Jovanovic (1998), Aghion and Howitt (1998, chapter 8), Aghion et al. (1999, subsection 3.3.1), and Violante (2002). 49 See Violante (1996), Aghion et al. (1999 subsection 3.3.2), and Hassler and Rodríguez-Mora (2000). 48

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their wage differential relative to unskilled workers. However, some empirical studies indicated that very little of the increases in wage differentials between skilled and unskilled workers in developed countries are due to increases in imports from developing countries.50 Finally, a third explanation refers to the influence of new organizational forms. Technological change has modified the internal organization of firms, increasing the importance of direct or horizontal forms of communication between workers, and diversifying the tasks that they can perform. In this context, skilled workers are more able to perform various tasks and learn from the activities of other agents. In addition, if they are able to exploit the comparative advantage of their education, they will receive important wage premiums, and consequently income inequality among workers will rise.51 In the context of these new growth theories where the technological change and the human capital appear as the most relevant factors throughout economic growth influences income distribution, fiscal policy has acquired a significant importance as an effective instrument to influence economic growth as well as an important tool for the purpose of redistribution. In this framework, it is important to consider that growth-enhancing fiscal policy (such as expenses on R+D and/or human capital investment) could have important effects on income inequality, although their direction is not clear. On the one hand, these policies will reduce income inequality by allowing more individuals access to new general knowledge, but at the same time, as these policies encourage skill-biased technological progress they may also increase wage premiums and consequently income inequality in the long run. In addition, it’s important to note that this skill biased technological progress calls for permanent redistributive policies, such taxes and transfers, who can partially offset the undesirable effects of economic growth on the distribution of income (see Aghion et al., 1999). However, these permanent redistributive policies could become unsustainable in the long run when technology becomes too skill-biased (see Hassler et al., 2003, and Bénabou, 2005).

3. EFFECTS OF INEQUALITY ON GROWTH In contrast, in the extensive literature on development appeared during the 1990s, the central concern focuses on the role of income and wealth inequality in the process of economic growth, and consequently the causation between inequality and growth runs in the opposite direction. Two main groups of studies can be identified following this approach: one group suggests various transmission channels through which greater initial inequality fosters economic growth; the other suggests several economic and political-economy channels through which initial inequality might be harmful for growth. In this context, redistributive policies would have opposite effects on growth according to these two different approaches.

50 51

See Borjas et al. (1992); Berman et al. (1994) and Krugman (1995). See Lindbeck and Snower (1997); Caroli (2001); Möbius and Schoenle (2006), Garicano and Rossi-Hansberg (2006); and Grossman and Rossi-Hansberg (2008).

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3.1. The Pro-growth Effects of Inequality The strand of literature pointing to the pro-growth effects of inequality basically focuses on the following factors: different saving propensity of economic agents, investment indivisibilities and incentive considerations. According to the growth models of Lewis (1954), Kaldor (1957) and Pasinetti (1962), the marginal propensity to save of the rich is bigger than the poor. If the growth rate relates directly to the proportion of the national revenue saved, most unequal economies will grow faster than economies characterized by a more egalitarian distribution. In this line, Bourguignon (1981) shows that, with a convex saving function, aggregate output depends on the initial income distribution and is higher the more unequal the economy is. More recently, Galor and Moav (2004) have considered a nonlinear relationship between inequality and growth that varies with economic development and obtained different conclusions depending on the economy maturity. Thus, in early stages of development, when physical capital is scarce and its returns are high, inequality stimulates growth by allowing the channeling of resources towards individuals whose propensity to save is higher. However, at higher levels of development, when human capital emerges as a key factor for economic growth, equality alleviates the adverse effects of credit constraints and stimulates growth by allowing greater investment in human capital. The second argument focuses on investment indivisibilities, especially, when the implementation of new industries and innovations involve big sunk costs. In the absence of a perfect credit market, the wealth needs to be sufficiently concentrated to be able to cover such costs and, therefore, to initiate a new industry. Consequently, a more unequal economy will carry more investment projects and as a result it is going to grow faster than a more egalitarian one. This issue has been emphasized by policy advisors to transition economies in Central and Eastern Europe and the former Soviet Union.52 Finally, the third argument comes from Mirrlees (1971) and is based on the idea that there is a trade-off between productive efficiency and equity due to incentive considerations. Namely, in a moral hazard context where output depends on the unobservable effort bear by agents or “employees”, rewarding the employees with a constant wage independent from output performance will discourage them from any investment effort. On the other hand, making the reward too sensitive to output performance may also be inefficient from an insurance point of view when output realizations are highly uncertain and the employees are risk averse.53 Focusing on the importance of incentives at microeconomic level, recently GarcíaPeñalosa and Wen (2008), incorporated new arguments related to entrepreneurship. Thus, in a Schumpeterian context, innovation is performed by entrepreneurs and hence the determinants of entrepreneurship - characterized by large risks - will affect growth. Then, in order to induce individuals to become entrepreneurs and innovators rather than employees, large returns are required to compensate for these risks. The immediate implication is that the higher the income of a successful entrepreneur, the larger the fraction of the population that chooses entrepreneurship, and hence the faster the rate of innovation is. That is, greater

52 53

For more details, see Aghion and Howitt (1998), chap. 9. See Prendergast (1999), for a discussion about the trade-off between risk and incentives.

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income inequality will result in more innovation and entrepreneurship and, as a result, faster technological change and growth.54 In fact, the traditional incentives view in macroeconomic theory (Okun, 1975) is that there is a fundamental trade-off between growth and equality, i.e. redistribution trough income taxes has negatives effects on growth. It reduces differences on income and wealth and consequently reduces growth; and also, it has a negative effect on growth as income redistribution financed through income taxes diminishes incentives to accumulate wealth. In the same direction, Rebelo (1991) has shown that in a Ramsey-Cass-Koopmans growth model with perfect capital markets, greater taxation reduces the return to saving, thus lowering the incentives to accumulate capital and hence the rate of growth.

3.2. Inequality Being Harmful for Growth A second group of studies explains how initial inequality in income and wealth reduces the long-term potential growth of the economy. This theoretical literature suggests several economic and also political-economy channels through which inequality might be harmful for growth. So, redistributive fiscal policies that reduce inequality can therefore be growthenhancing in the medium and long term.

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3.2.1 Economic Arguments The main economic arguments are related to capital market imperfections, the domestic market size and endogenous fertility rate. Stiglitz (1969) in a neoclassical economy, where aggregate output is produced by the aggregate stock of capital, points out that when there are decreasing returns to capital and capital markets are imperfect, individual wealth will not converge to a common level and the aggregate level of output may be affected by its redistribution. More recent endogenous growth theories argue that when aggregate output is the sum of the output generated by each economic agent (agent’s output is a function of her own physical or human capital), the rate of growth depends on the distribution of individual capital investments as a result of learningby-doing process. In this context, since the liquidity constraints due to credit market imperfections, prevent the poor agents from carrying out indivisible productive investments, the negative impact of inequality on growth will be higher as the initial wealth distribution is more unequal. So, in these endogenous growth models with concave individual production function, redistributing wealth from the rich (whose marginal productivity of investment is relatively low, due to decreasing returns to individual investments) to the poor (whose marginal productivity of investment is relatively high, but who cannot invest more than their limited endowments), would enhance aggregate productivity and growth. Therefore redistribution creates investment opportunities, which in turn increases aggregate productivity 54

Surprisingly, in this context the fact that greater inequality induces more entrepreneurship does not imply that redistribution hampers growth. On the contrary, a certain degree of income redistribution can increase entrepreneurship and the growth rate because it provides insurance to all agents undertaking risky activities as it guarantees a minimum income in the case of failure reducing income uncertainty and hence induces more entrepreneurship.

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and growth.55 However, economic efficiency of these progressive redistribution measures requires that the economy reach a minimum level of development. Otherwise, if the economy is characterized by a very low level of national income, these policies may cause long-term stagnation (persistence of the economy in an “underdevelopment trap"), by reducing the number of individuals who are rich enough to cover the fixed costs of large investment projects needed for the "take-off" (see Barro, 2000; and Bértola et al., 2006, chapter 7).56 A second argument is related to the domestic market size and the influence of income distribution on the variety of goods that consumers demand. In this sense, the initial distribution of income can affect the long-run growth rate by modifying the size and the composition of the domestic demand. These developments are based on the assumption that consumption patterns vary with consumer’s income level due to indivisibilities in consumption. In a sense, considering consumption invisibilities make it possible to establish a parallelism with the former models based on capital market imperfections: while low income families were not able to finance certain investments projects in the former models, in these models low income families are excluded from some consumption activities because of the existence of imperfect markets allowing the producers to fix high prices. In this context, a more equal distribution of purchasing power make it possible to shift the domestic demand towards manufactures which can be effectively produced internally only on a very large scale. Therefore, redistributive fiscal policies could increase domestic demand, fostering the development of local industry. 57 According to the endogenous fertility argument, initial income inequality reduces future growth rate due to its positive effect on average fertility rate. Poor parents with relatively low levels of education may not finance the education of their children. In contrast, wealthy parents prefer to invest in quality (education) rather than quantity (number of sons). In this context, a more equal distribution usually reduces the average fertility rate through a progressive transfer of incomes or human capital assets. If this drop in the overall rate of fertility is simultaneously associated with a rising investment rate in human capital, then the economic growth rate will increase in the long run.58 The main conclusion we can obtain from the above mentioned economic arguments is that when agents are heterogeneous and capital markets are imperfect, greater inequality may have a negative impact on growth. In this context, redistributive policies that alleviate income inequality could enhance economic growth. And taking into account that most industrial economies suffer from insufficiently developed capital markets,59 these redistributive policies could enhance growth not only in less-developed countries, but also in many developed economies. 55

See Galor and Zeira (1993), Bénabou (1996) and Aghion et al. (1999, section 2.2), for a reduced form representation of credit market imperfections. However, see Banerjee and Newman (1993), Aghion and Bolton (1997), Piketty (1997), and Aghion et al. (1999, section 2.3), for ex-ante moral hazard considerations. 56 Inside this strand of literature, the models of Aghion and Bolton (1997) and Aghion et al. (1999, section 2.4), postulate that inequality can take the form of unequal access to investment opportunities across individuals, which, jointly with a high degree of capital market imperfection, can generate persist investment volatility. Such volatility in turn implies that there are unexploited production possibilities (idle funds) and hence the long run growth rate is lower that it could be. 57 See Murphy, Shleifer and Vishny (1989), Jamarillo (1995), Falkinger and Zweimüller (1996 and 1997), Foellmi and Zweimüller (2004), and Zweimüller and Brunner (2005), among others. 58 See, Becker and Barro (1988), Perotti (1996), Galor and Zang (1997), Dahan and Tsiddon (1998), Morand (1998), Koo and Dennis (1999), and Kremer and Chen (2000). 59 See Laporta et al. (1997, 1998), and the Development Financial Report 2010 - World Economic Forum.

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3.2.2. Political Economy Arguments Additionally to the above discussed economic arguments, other political-economy explanations suggest the existence of a negative relationship between initial inequality and subsequent growth. Firstly, a more unequal income distribution increases redistributive tax pressures, which deters private investment and decreases future economic growth. Thus, early models of “endogenous fiscal policy”, under the assumption of perfect capital markets, highlight a longterm negative relationship between inequality and growth.60 These models are based on the "median voter" hypothesis, initially developed by Meltzer and Richard (1981), where the level of government taxes and transfers is the result of a democratic voting process ("majority rule"). In this case, the gross personal income (pre-government intervention) is the primary determinant of voter preferences. The main idea is that a more unequal democratic societies, demand redistribution financed by distortionary taxes, and a rise in these taxes decreases private investment and consequently reduces economic growth. An alternative approach of these pioneering models of political economy puts greater emphasis on the analysis of socio-political instability and its consequences.61 The main argument is that the social and political instability provoked by high levels of inequality can lead to irresistible pressures for redistribution and expropriation, producing disincentive effects on capital accumulation and as a result on economic growth. In this context, greater fiscal redistribution through distortionary taxes, while it may reduce investment incentives, also decreases social conflict and contributes to greater stability that encourages productive activities and capital accumulation. Therefore, the net effect of these fiscal policies will be the result of two opposite effects: the distortion effects due to higher taxes and the pro-growth effects associated with the reduction of social conflict.62 More recent models of political economy tried to relax the main assumptions of the two aforementioned political economy approaches, i.e. perfect capital markets and distortionary taxes. Thus, this new approach introduces the consideration of externalities associated with human capital investment. The idea is that the trade-off between efficiency and equity highlighted by the aforementioned models could be avoided if human capital investment is financed by non-distortionary taxes (Saint-Paul and Verdier, 1993). In this case, we observe positive effects of redistribution policies on economic growth by allowing greater investment in human capital. However, if redistribution is financed through distortionary taxation, two opposite effects appear: the standard effect whereby taxation reduces net capital returns, and the growth enhancing effect provoked by the increase in human capital investment. In fact, in Bénabou (2000 and 2005) this trade-off allows for two scenarios. One, termed “growthenhancing redistributions”, is consistent with pro-growth effects of transfers meanwhile tax distortions remain relatively small; the faster growth under the more redistributive fiscal policies is provoked by more efficient allocation of investment expenditures.63 The other relevant scenario, termed “eurosclerosis”, explain how European voters choose more redistribution than Americans, not because they are intrinsically more risk averse, but because 60

See Bértola (1993), Alesina and Rodrik (1994) and Persson and Tabellini (1994). See Gupta (1990), Alesina and Perotti (1996), and Bourguignon (1998). 62 See Bourguignon (1999) for a discussion of this trade-off. 63 This scenario is particularly relevant for human capital investment and public health expenditures, where the contrasted path of East Asia and Latin America were observed. 61

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they vote for more cohesion societies which, ex ante, would be valued enough to compensate for lesser growth prospects. Finally, other lines of more recent models of political economy literature endogenize the behaviour of political institutions and focuses on three aspects: the role of property rights, the vulnerability of governments to different pressure groups, and the predatory nature of authoritarian leaders. According to this approach, an inegalitarian distribution of economic resources results in a greater political power of the wealthiest members of the society, and consequently inequality will not be associated with more redistribution; there is no scope for the implementation of policies aimed at the reduction of inequalities. 64

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4. THE MACROECONOMIC EFFECTS OF FISCAL POLICY The empirical effects of fiscal policies have been widely examined with contrasted views. Numerous works have used time series models, especially vector autoregressive models, to estimate the effects of different fiscal policy shocks on economic activity, but the issue of the sign and magnitude of these effects across different countries is very much an open question.65 Other studies have used a cross country approach to examine the impact of aggregate measures of fiscal policies on economic growth for an extensive sample of countries. However, in this approach, inspired by Easterly and Rebelo (1993), who add fiscal variables in an ad-hoc manner to an empirical growth equation, the results are not particularly robust, showing that the impact and significance of the fiscal variables depend on the set of control variables included and also on the initial conditions of the economy.66 On the other hand, there are some empirical studies that have included fiscal policy variables in an inequality equation in order to explain their redistributive impact.67 In this sense, we can distinguish between two main groups of contributions. A first group of papers discuss the impact of public spending on income distribution for OECD countries and they find a significant negative effect of total government spending on inequality (see Gustafsson and Johannson, 1999; and Galli and van der Hoeven, 2001). In turn, Alfonso et al., (2010) highlight important differences between European countries: the Southern countries exhibit a low efficiency pattern of government spending, while Nordic countries report a relatively high efficiency. Finally, Wolff and Zacharias (2007) analyses the case of United States using a panel of states and show that the reduction in inequality is due to government spending, rather than taxes. A second group of studies evaluates the distributive effect of different fiscal policies implemented in developing countries showing, in general, very weak redistributive impacts of these policies. Thus, in the case of Andean countries, Barreix et al. (2007) indicate that the full effect of taxes is slightly regressive, due to a weak capacity for income tax collection. In turn, Goñi et al. (2008) attributes the poor performance of redistributive policies in six Latin

64

See Bénabou (1996), Ades y Verdier (1996), Bourguignon and Verdier (2000 a, b ,c, d), Acemoglu and Robinson (2000), and Glaeser et al. (2004). 65 Perotti (2005) provide surveys of this literature. 66 For a survey of this empirical literature see Myles (2009). 67 For a survey of this empirical studies see Atkinson and Brandolini, (2006, Table 14.1).

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American countries to the low volume of resources collected and transferred, the existence of regressive taxation and misguided transfers.68 Also, Lopéz et al. (2010) focusing on a larger sample of 40 developing countries, show that reallocating government spending from private goods and non-social subsidies to public and semi-public goods is associated with reductions in poverty, even though their redistributive effect is neutral implying poor targeting. In the case of the Central American countries, Cubero and Hollar (2010) find that the impact of social spending on poverty and income distribution is undermined by its relatively low absolute level. Similarly, Chu et al. (2000) using a sample of developing economies finds significant impact of direct taxes reducing inequality but these effects are also extremely small in magnitude. Finally, Li et al. (2000) use a panel of 84 countries that includes developed and developing countries and obtain no statistically significant effects of total government expenditure on income distribution. In summary, the results of these empirical studies show that the redistributive impact of fiscal policies seem to be strongly related to the country’s development and government capacity. Taking a theoretical approximation, García-Peñalosa and Turnovsky (2007) and Chaterjee and Turnovsky (2010) seek to model the effects of different instruments of fiscal policy on economic growth and also on inequality. A central concern of both papers is the role of government spending programs, especially public investment, in stimulating economic growth and reducing inequality. Thus, García-Peñalosa and Turnovsky (2007) examined the distributional impact of different ways of financing an investment subsidy in an endogenous growth model with elastic labor supply. Their results indicate that policies aimed at increasing the growth rate result in a more unequal pre-tax income. This is because growth is fostered by policies that increase the return of capital, and since capital is more unequally distributed than labor, higher returns to capital translate into greater income inequality. However, the analysis also indicates that such policies tend to reduce post-tax inequality suggesting that gross income inequality is a poor proxy for the assessment of the effects of policy on the distribution of welfare. Because of some policies tend to have opposite effects on the pre-tax (gross) and post-tax gross (net) distributions of income, it is possible to induce faster growth in conjunction with a more equal distribution of post-tax income. Overall, the analysis provides support for the use of either a tax on capital income or a tax on consumption to finance a subsidy on investment, in that both policies increase the growth rate and reduce inequality in post-tax income and welfare. An even more attractive policy consists of adopting a consumption tax together with an equal-in-magnitude wage subsidy to finance the investment subsidy, since this does not distort the labor-leisure choice. In a more recent paper, Chaterjee and Turnovsky (2010) analyzed the effects of progrowth policies, such as government investment in infrastructure, on wealth and income inequality and how the relationships are affected by the method of financing. They use a general equilibrium endogenous growth model with heterogeneous agents, where the heterogeneity is due to the initial endowments of private wealth. Their results suggest that government spending in public capital will increase wealth inequality gradually, regardless of 68

The countries analyzed are Argentina, Brazil, Chile, Colombia, México and Peru.

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how it is financed. Government investment tends to enhance the productivity of private capital, thereby stimulating its accumulation, and with private capital being more unequally distributed among agents than is labor; this tends to increase wealth inequality. In contrast, the consequences for income inequality are sensitive to how public investment is financed and may be characterized by sharp intertemporal trade-offs. While government investment financed by a lump-sum or consumption tax leads to a short-run decline in income inequality, this is completely reversed over time, leading to an increase in the long-run dispersion of income. Public expenditure financed by capital or labor income taxes yields sharp differences between pre-tax and post-tax income inequality, both in the short run and over time. But regardless of the financing method, both measures of income inequality increase over time. From an empirical perspective the joint response of economic growth and income inequality to fiscal policies has been largely overlooked, with significant exceptions in recent papers. Thus, López (2003) uses a panel of 91 countries over the period 1960-2000 and finds that improvements in infrastructure and education reduce inequality while promoting economic growth. Calderón and Servén (2004) evaluate the impact of infrastructure investment on economic growth and income distribution using an unbalanced panel of 121 countries during the period 1960-2000 and highlight the positive effects on growth and negative impacts on inequality. Finally, Muinelo and Roca-Sagales (2010) analyze the short run impact of different instruments of fiscal policy on economic growth as well as on income inequality, using an unbalanced panel of 43 upper-middle and high income countries for the period 1972-2006. Their empirical results suggest that an increase in the size of government measured through current expenditures and direct taxes diminishes economic growth while reducing inequality. Public investment seems to be the only fiscal policy that may break this trade-off between efficiency and equity, since increases in this item reduces inequality without harming output, confirming the predictions of García-Peñalosa and Turnovsky (2007), and Chaterjee and Turnovsky (2010). The importance of these more recent theoretical and empirical works is that they indicate that under certain circumstances the classic trade-off between efficiency and equity to implement specific tools of fiscal policy could be avoided. In particular, in the short run, increased public investment could stimulate growth and, in turn, reduce income inequality.

5. CONCLUSION This chapter surveys the contributions that analyze the relationship between inequality and economic growth and presents a comparative analysis of different theoretical and empirical developments, with particular focus on the importance, in terms of size and composition, of different fiscal policies, explaining that relationship. Recent times have seen government spending, taxation, and deficit financing move to the forefront of policy analysis. Due to the importance of fiscal policy as a redistributive tool and as an instrument to promote economic growth, it is commonly considered one of the key mechanisms to achieve goals in terms of efficiency and/or equity. In section 2 of the survey we examine the effects of economic growth on inequality. We show that, according the traditional wisdom, there is no important scope for fiscal policy as an effective tool to affect both macro-aggregate in the long-run. However, in the context of

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the new endogenous growth theories approach, where technological change and human capital appear as the most relevant factors through which economic growth influences income distribution, growth-enhancing fiscal policies (i.e. R+D and human capital investment) could have important effects on income inequality, although it is not clear their direction. On the one hand, they will reduce income inequality by allowing more individual’s access to new general knowledge, but at the same time, by encouraging skill-biased technological progress they may also increase wage premiums and income inequality. In addition, this skill biased technological progress calls for permanent redistributive policies, such taxes and transfers, which can partially offset the undesirable effects of economic growth; however, these permanent redistributive policies could become unsustainable when technology becomes too skill-biased. More recent growth models have revived the interest of fiscal policy as an effective instrument to promote economic growth and to correct undesirable outcomes of the process of skill-biased economic growth in terms of inequality In section 3, we analyze recent theories where the central concern mainly focuses on the role of income and wealth inequality in the process of economic growth. Two main groups of studies are identified in this theoretical literature: one group suggesting various transmission channels through which greater initial inequality fosters economic growth; the other suggesting several economic and political channels through which initial inequality might be harmful for growth. Redistributive policies would have opposite effects on growth according these two different approaches. Only when inequality is harmful for growth, due to several economic and also political-economy channels, redistribution to the less well endowed, by reducing inequality, can therefore be growth-enhancing. However, economic efficiency of these progressive redistribution measures requires that the economy has reached a minimum level of development. Otherwise, if the economy is characterized by a very low level of national income, these policies may cause long-term stagnation (persistence of the economy on an “underdevelopment trap"), by reducing the number of individuals who are rich enough to cover the fixed costs of large investment projects needed for the "take-off". In this context, the theoretical analysis calls for further empirical evidence. However, the majority of existing empirical studies have focused on the effects of fiscal policy on economic activity without considering the redistributive effects and, not offering, in turn, an analysis of the impact of different fiscal policy instruments. Only recently some theoretical and empirical papers in this line have appeared. The importance of these more recent works is twofold. On the one hand, these empirical studies showed that the redistributive impact of fiscal policies seem to be strongly related to the country development and government capacity. On the other hand, in certain circumstances the classic trade-off between efficiency and equity when implementing specific tools of fiscal policy could be avoided; in particular, in the short run, increased public investment could stimulate growth and, in turn, reduce income inequality.

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Mushinski, D.W. (2001), “Using non-parametrics to inform parametric tests of Kuznets hypothesis”. Applied Economics Letters 8, pp. 77–79. Musgrave, R.A. (1959), “The Theory of Public Finance”. McGraw-Hill, New York. Muinelo-Gallo, L. and O. Roca-Sagalés (2010) “Economic Growth and Income Inequality: The Role of Fiscal Policies”. Working Paper 11-05, Departament d’Economia Aplicada, Universitat Autònoma de Barcelona. Myles, G. D. (2009), “Economic Growth and the Role of Taxation: Aggregate Data”. OECDEconomics Department Working Paper No. 714. Okun, A. M. (1975), “Equality and efficiency: The big trade-off”. Washington: The Brookings Institution. Ortigueira, S. (2002), “The Rise and Fall of Centralized Wage Bargaining”. Mimeo Cornell. Park, H. and A. Philippopoulos, (2003), “On the dynamics of growth and fiscal policy with redistributive transfers”. Journal of Public Economics, vol. 87(3-4), (March), pp. 515-538. Park, H. and A. Philippopoulos, (2004), “Indeterminacy and fiscal policies in a growing economy”. Journal of Economic Dynamics and Control, vol. 28(4), (January), pp. 645660. Pasinetti, L. (1962), “Rate of profit and income distribution in relation to the rate of economic growt”. The Review of Economic Studies, 29, pp. 267-279. Perotti, R. (1994), “Income distribution and investment”. European Economic Review 38(34), pp. 827-835. Perotti, R. (1996), “Growth, income distribution and democracy: what the data say”. Journal of Economic Growth 1(2), pp. 149-187. Perotti, R. (2005), “Estimating the Effects of Fiscal policy in OECD Countries”. CEPR Discussion Paper No. 4842. Persson, T. and G. Tabellini (1994), “Is inequality harmful for growth?”. American Economic Review 84, pp. 600-621. Piketty, T. (1997), “The dynamics of the wealth distribution and the interest rate with credit rationing”. Review of Economic Studies, vol. 64(2), No. 219, pp. 173-189. Prendergast, C. (1999), “The Provision of Incentives in Firms”. Journal of Economic Literature, Vol. 37, No. 1, pp. 7-63. Rebelo, S. (1991), “Analysis and Long-Run Growth”. Journal of Political Economy, Vol. 99, No.3, pp. 500-521. Robinson, S. (1976), “A Note on the U Hypothesis relating Income Inequality and Economic Development”. American Economic Review 66(3), pp. 437-440. Romer, P. M. (1986), “Increasing Returns and Long-Run Growth”. Journal of Political Economy, Vol. 94, No. 5, pp. 1002-1037. Saint-Paul, G. and T. Verdier (1993), “Education, democracy and growth”. Journal of Development Economies 42, pp. 399–407. Sato, K. (1967), “Taxation and Neo-Classical Growth”. Public Finance 22(3), pp. 346-70. Solow, R. M. (1956), “A Contribution to the Theory of Economic Growth.", Quarterly Journal of Economics, 70, pp. 65-94. Stiglitz, J. E. (1969), “The Distribution of Income and wealth Among Individuals”, Econometrica, 37(3); pp. 382-397. Stokey, N. L. and S. Rebelo (1995), “Growth effects of Flat-Rate-Taxes”. Journal of Political Economy 103, pp. 519-50

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Summers, L. H. (1981), “Capital taxation and accumulation in a life cycle growth model”. American Economic Review 71(4), pp. 533–544. Tamura, R. (1991), “Income Convergence in an Endogenous Growth Model”. Journal of Political Economy 99, pp. 522-54. Turnovsky, S. and W. Fisher (1995), "The Composition of Government Expenditure and its Consequences for Macroeconomic Performance". Journal of Economic Dynamics and Control, 19, pp. 747-786. Violante, G.L. (2002), “Technological Acceleration, Skill Transferability and the Rise in Residual Inequality”. Quarterly Journal of Economics 117, pp. 297-338. Voitchovsky, S. (2005), “Does the Profile of Income Inequality Matter for Economic Growth?: Distinguishing Between the Effects of Inequality in Different Parts of the Income Distribution”. Journal of Economic Growth 10, pp. 273-296. Wolff, E. N. and A. Zacharias (2007), "The Distributional Consequences Of Government Spending And Taxation In The U.S., 1989 And 2000," Review of Income and Wealth, Blackwell Publishing, vol. 53(4), pp. 692-715, December. Wood, A. (1994), “North-South Trade, Employment and Inequality: Changing Fortunes in a Skill Driven World”. Oxford: Clarendon Press. Wood, A., and C. Ridao-Cano (1999), “Skill, Trade and Internationally Inequality”. Oxford Economic Papers 51, pp. 89-119. Zweimüller, J. and J. K. Brunner (2005), “Innovation and Growth with Rich and Poor Consumers”. Metroeconomica, 56, pp. 233-62.

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Chapter 5

ENERGY EFFICIENCY AND CARBON TRADING – TOWARDS A GREENER MALAYSIA T. H. Oh Faculty of Engineering and Technology, Multimedia University (MMU), Jalan Ayer Keroh Lama, Bukit Beruang, Melaka, Malaysia

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1. INTRODUCTION It is a known fact that the total energy being consumed today is at a rate that has never been seen before in the human history. As the world becomes more developed, this has led to a significant increase in industrial activity which consequently results in a massive increase of pollutants being released to the atmosphere, water and soil, altering their composition, and causing harmful effects on the environment and human health. Although environmental problems are not an issue of interest to the world until the last century, some historical events have shown that the concerns on the effect of certain man-made pollutants on human health have begun some centuries ago [1]. Air pollutants mainly come from discharges of gases from industry, motor vehicles and domestic wood burning [2]. The most widespread pollutant which is called primary pollutant is none other than the major greenhouse gas (GHG), carbon dioxide (CO2). Due to the harmful impact of air pollutants, regulatory agencies have enacted strict regulations to limit their emission, with the important international accord, Kyoto Protocol inked in 1997 to battle global warming and more than a decade later, climate change has worsened and accelerated beyond some of the grimmest of warnings made back then. As the world has talked for years what is the next step to take, new ship passages are opened through the ice frozen summer sea ice of the Arctic. In Greenland and the Antartica, ice sheets have lost trillions of tonnes of ice. Mountain glaciers in Europe, South America, Asia and Africa are shrinking faster than ever before. And in the dozen years leading to the 2009 Climate Summit in Copenhagen recently, the world’s oceans have risen by about 3.7 cm and experts estimate the sea level to rise by 100 cm by year 2100 [3]. Temperatures over the past 12 years are 0.4°C warmer since 1997. Consequently, in recent years, news on droughts, wildfires and

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deluges that wrecked havoc all over the globe can be heard quite frequent. The fact that the gloomiest climate models back in the 1990s did not even forecast results quite this bad and this fast have set off the alarms all over the world on the urgency to address the issues of global warming and climate change. The effects of GHGs are more prevailing and happening sooner than anticipated. The planet warming by 7°C and sea levels rising by 100 cm by 2100 are scenarios that just two years ago viewed as improbable. In the widest overview on global warming since a landmark report by the United Nation Inter-government Panel on Climate Change (IPCC) report in 2007, reported that manoeuvring room for tackling the carbon crisis is now almost exhausted [4]. Since 1980, global CO2 emission has been increasing as depicted in Fig. 1 and the atmospheric CO2 concentration has been rising steadily year-on-year and hit a record high of 385.99 parts per million (ppm) as in November 2009 as shown in Fig. 2. Emissions of heat-trapping CO2 from fossil fuels are tracking near the highest scenarios considered so far by the IPCC. They are nearly 40% higher in 2008 than in 1990, with a three-fold acceleration over the past 18 years. Even if global emission rates are stabilized at present-day levels, just 20 more years of emissions would give a 25% probability that warming exceeds 2°C, even with zero emissions after 2030. Every year of delayed action increases the chances of exceeding 2°C warming [7]. Generally, CO2 emission is closely related to human activities, namely power generation, deforestation, transportation, industrial, residential and commercial activities. CO2 is discharged into the atmosphere from combustions of fossil fuels such as oil, natural gas and coal as a source of energy. If left unchecked, the CO2emission can exacerbate global warming and lead to environmental destruction and health hazards which are already quite rampant nowadays. Since it is undeniable that many countries are still very much dependent on fossil fuels to sustain their growth, the energy policies implemented in these countries can directly and significantly impact the amount of CO2 reduction achieved. As energy demand is inevitably on the rise due to rapid development and growing populations, it is only judicious to divert energy from fossil fuels to renewable and sustainable energy sources.

Figure 1. Global CO2 emissions from 1980 – 2005 [5].

Even though bears no obligation in reducing GHGs emissions as a non-Annex I country, Malaysia has started to strive towards a low carbon economy and community through its various green policies and energy efficiency (EE) programmes in recent years. The energy scenario and various policies that are adopted by Malaysia in part of its CO2 emission mitigation efforts are highlighted in this chapter, which includes the various EE initiatives

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that have taken place so far in the country. Also covered here is the carbon trading potential which is part of the Clean Development Mechanism (CDM) programme introduced in the Kyoto Protocol and the various challenges faced in Malaysia to achieve a sustainable clean development and its CO2 emission reduction obligation simultaneously.

Figure 2. Atmospheric CO2 concentrations [6].

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2. MALAYSIA ENERGY SCENARIO 2.1. Energy Consumption and CO2 Emission Total energy consumption in Malaysia was estimated at about 2.5 quadrillion Btu as in 2007, which is a 400% increase from the early 1980s (see Fig. 3), is considered relatively high among developing countries and was even higher than some developed countries [8]. The final commercial energy demand in 2007 increased by 9.8% to 44,268 ktoe compared to 40,318 ktoe in 2006, with industrial sector (43.2%) and transport sector (35.5%) on top. Following further behind were residential and commercial (14.0%), non-energy (6.7%) and agriculture sectors (0.6%), as all sectors showed an upward trend compared to the previous year. Malaysia’s total installed electricity generation capacity as of end 2007 was 21,815 MW, increase 7.9% from 20,224 MW in 2006. Meanwhile, the total available capacity as of end 2007 was 20,789 MW. Electricity gross generation registered 101,325 GWh, up 8.7% from the 2006 figure. On the other hand, the electricity consumption was upped 5.6% to 89,298 GWh in the same period. Similarly, electricity consumption in the residential and commercial sectors was heading north as well, respectively charting a 5.5% and 9.6% hike to 1,598 ktoe (18,572 GWh) and 2,496 ktoe (29,009 GWh). The electricity consumption in the industrial sector recorded an increase of 3.2% to register 3,587 ktoe (41,689 GWh), mainly influenced by higher gross domestic product (GDP) in the manufacturing sector recorded in 2007.

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Consumption from the transport sector, however, decreased to 3,554 toe (41 GWh) from 5,421 toe (63 GWh) back in 2006. Natural gas still provides the largest portion in the electricity generation mix with 56.6%, follows by coal and hydropower at 34.2% and 6.9%, respectively. The remaining 2.3% is contributed by oil and others [9].

Figure 3. Total primary energy consumption in Malaysia [8].

Figure 4. CO2 emissions by sectors in Malaysia [10]. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Evidently, Malaysia is still very much dependent on fossil fuels, namely natural gas and coal, in its commercial energy demand and electricity generation. With the escalating energy demand to sustain growth in years to come, it is inevitable that CO2 emission will continue to climb, as long as fossil fuels remain as the main contributor in the energy mix. Fig. 4 depicts the CO2 emission in Malaysia by sectors in 2005. The transportation sector which fully utilizes petroleum products is no doubt the main contributor in CO2 emission, followed closely by the electricity sector which is mostly powered by fossil fuels like natural gas and coal. The total CO2 emission in Malaysia has increased quite drastically towards the end of 1990s and exceeded 160 million metric tonnes by 2003, and has stayed above that level since, as illustrated in Fig. 5. With future energy demand expected to grow at a rate of 5–7.9% annually for the next 20 years from 2004 onwards [11], energy security is becoming a serious issue as fossil fuels are non-renewable energy and will deplete eventually.

Figure 5. Total CO2 emission in Malaysia [8].

2.2. Energy Policy At present, most of the developed countries are committed to cap their CO2 emissions as stipulated under Kyoto Protocol as well as the recent declaration during the recent 2009 Climate Summit. In this respect, developing countries are still lacking behind most of the developed countries, but are catching up quickly. Being a country of responsible, Malaysia as one of the fastest growing countries in Southeast Asia, is continuously combating global warming with aggressive efforts. Over the years, the government has devised quite a number

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of energy-related policies to ensure sustainability and security in its energy supply. But in the last three decades, pragmatic energy policies have facilitated a more environment-friendly energy development path, started with the introduction of the National Energy Policy in 1979 with three primary objectives; supply, utilization and environmental. The National Depletion Policy was announced in 1980 and a year later, the Four-Fuel Diversification Strategy 1981 was introduced, with the former to prolong lifespan of the country’s oil reserves for future security and stability of oil supply and the latter to pursue balanced utilization of oil, gas, hydro and coal. The fuel diversification policy is reviewed from time to time to ensure that the country is not over-dependent on one main energy source, especially after the international oil crisis in the 1970s. This policy was replaced in 1999 with the Five-Fuel Diversification Strategy and renewable energy (RE) was made the fifth fuel in the energy supply mix. The direct result from the fuel diversification strategy saw the drastic drop of oil in the energy mix contribution, from a high 87.9% in 1980 down to a mere 2.2% in 2005, with the remaining 70.2% and 21.8% contributed by natural gas and coal respectively [12]. Nevertheless, as fossil fuels still form a large portion in Malaysia energy consumption, not only will these non-renewable energies be totally exhausted one day and cause energy security threat, their significant and prolong contribution to the emission of GHGs from their combustions is hastening the global warming as well. Thus, in addition to the five-fuel policy, the government has endorsed the Kyoto Protocol in September 2002 and being a non-Annex 1 country, Malaysia can utilize the CDM to reduce domestic CO2 emissions as well as transfer advanced technologies from developed countries. The five-fuel policy targets to contribute 5% of the country energy mix by year 2005 and mitigate 70 million tonnes of CO2 over a span of 20 years [13]. In order to meet this goal, the Small Renewable Energy Programme (SREP) was launched in May 2001 under the initiative of the Special Committee on Renewable Energy (SCORE) to support the government’s strategy to intensify the development and utilization of RE as the fifth fuel resource in power generation, which is also stipulated in the objectives of the Third Outline Perspective Plan (OPP) for 2001– 2010 and the 8th Malaysia Plan (2001–2005) (8MP). The primary focus of SREP is to facilitate the expeditious implementation of grid-connected RE resource-based small power plants [14]. The RE resources in this program include biomass, solar, mini-hydro and municipal solid waste (MSW), with the first two identified as having the most potential to perform. The biomass resources in Malaysia are mainly from palm oil residues, wood residues and rice husks that can be used in the heat and electricity generation [11]. Table 1 summarizes the RE potential estimation in Malaysia by the Malaysia Energy Commission. By August 2005, SCORE reported that a total of 63 projects were approved with biomass and mini-hydro accounted for 92% of the total number of projects and the remaining 8% from MSW. There was no project approved under solar and wind. The statistics on these projects are tabulated in Table 2. Table 1. Renewable energy potential in Malaysia [15] Renewable Energy Hydropower Mini-hydro Biomass/biogas (oil palm mill waste) Municipal solid waste Solar PV Wind

Potential (MW) 22,000 500 1,300 400 6,500 Low wind speed

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Table 2. Status of SREP projects approved by SCORE as in 2005[16, 17] Type Biomass

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Landfill gas Mini-hydro Wind and solar TOTAL

Energy Resource Empty fruit bunches Wood residues Rice husk Municipal solid waste Mix fuels

Approved Application

Generation Capacity (MW)

Grid Connected Capacity (MW)

25

220.5

174.8

1 2

6.6 12.0

6.6 12.0

1

5.0

5.0

3 5 26

19.2 10.2 101.9

19.2 10.0 97.4

–

–

–

63

375.4

325.0

Although the SREP has targeted to generate 5% (600 MW) of the country’s electricity from RE by 2005, only 0.3% was achieved. Obviously, the progress in bringing RE generation into the mainstream has been slow due to several reasons and limitations. For any green technology industry to succeed, the right support mechanisms must be in place to create the market. The main obstacles to RE development in Malaysia are the lack of a policy framework and a financial mechanism. Without a legal and financial framework, the promotion of RE usage is often difficult. Moreover, the prohibitive price of RE gives households and businesses little incentive to adopt the technology, on top of the limited loans allocated for RE development. Beyond this, a lack of consulting services and access to the information on RE are also hampering its development [11]. Another key stumbling block is the high capital cost of RE implementation and the low sales price of electricity (17 cents/kWh) make the production of RE considered as uneconomical [18]. The green technology promotion was further emphasized in the 9th Malaysia Plan (2006– 2010) (9MP) where efforts in the utilization of RE resources and efficient use of energy are further encouraged. The establishment of the Ministry of Energy, Green Technology and Water to replace the Ministry of Energy, Communications and Multimedia in early 2009 reflects Malaysia’s seriousness in driving the message that ‘clean and green’ is the way forward towards creating an economy that is based on sustainable solutions. The launch of the new National Green Technology Policy in April 2009 by the current Prime Minister, Datuk Seri Najib Tun Razak, shall provide guidance and create new opportunities for businesses and industries to impact on the economic growth positively. The National Green Technology Policy is built on four pillars – 1) Seek to attain energy independence and promote efficient utilization; 2) Conserve and minimize the impact on the environment; 3) Enhance the national economic development through the use of technology; and 4) Improve the quality of life for all. It will also form the basis for all Malaysians to enjoy an improved quality of life, in line with the national policies, including the National Outline Perspective Plan where the growth objectives for the nation will continue to be balanced with environmental consideration [19]. While fossil fuels is expected to remain the dominant source of energy for decades to come, energy from RE such as wind, solar, biomass, biofuel and geothermal heat is expected to double between now to year 2030, although their share in the energy mix is most likely still be around 5.9% of the total energy demand by 2030 [20].

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3. ENERGY EFFICIENCY (EE) There is in general a stronger focus on energy supply than on energy use. One reason for this is that secure, reliable and competitive energy supply is crucial for the industry which has a major influence on the prevailing energy policies in any countries. Another reason is that energy users are less well organised than energy suppliers. Thus, the role of governments and their energy policies are becoming more and more important [21]. As a result, besides promulgating the use of RE to ensure energy security and sustainability for continuous economic growth, EE is explicitly addressed in the 9MP by the government. EE programs are more focused on energy saving features in the industrial and commercial sectors as well as domestic residential sectors. The industrial sector is expected to implement measures for improvements in plants, equipment and processes as well as end uses. Efficient Management of Electrical Energy Regulations are to be introduced, Uniform Building By-Laws to be amended to incorporate EE features, and specifications promulgated for accurate and informative electrical appliance labelling to be further enhanced. Promotion of the use of high efficiency motors includes initiatives to develop local expertise in the manufacture of energyefficient equipment and machinery. EE measures are to be intensified in the industrial, transport and commercial sectors, and in government buildings [15]. The industrial sector is the largest consumer of energy. Over the 8MP, the energy consumption was projected to grow at an average of 7.8% annually and more than double over a 10-year period if no initiatives are implemented to improve the EE performance in the sector. The manufacturing sector consumed 38.2% of the total commercial energy at the end of 2005, an increase from 37.1% in 2000 (at the end of the 7MP), a growth rate of 8.5%. In keeping the plan targeting the Malaysian industrial energy consumers, the Malaysian Industrial Energy Efficiency Improvement Project (MIEEIP) was jointly initiated in late 2000 by the government, Global Environment Facility (GEF) and United Nation Development Program (UNDP), with the mandate to reduce the barriers to industrial EE and conservation, besides building institutional capacities in relevant organisations for sustainability. In addition to the burning of fossil fuels, major industry sources of GHG emissions are cement, steel, textile, and fertilizer manufacturers. The main gases emitted by these industries are methane, nitrous oxide and hydroflurocarbons, which increase the atmosphere's ability to trap infrared energy. Energy audit activities carried out in eight energy intensive industrial sectors (wood, food, glass, cement, rubber, pulp and papers, iron and steel, ceramic) revealed potential energy savings amounting to 7.1 million gigajoules (GJ) per year with an estimated capital expenditure of RM100.4 million (US$28.7 million). At the same time, the Malaysian Energy Efficiency Plan (EEP) envisages a potential energy saving of over 1,400 GWh over the equipment life-time, equivalent to RM238 million (US$68 million) for an investment of RM33 million (US$9.4 million) by the government in program expenses over the remaining period of 8MP, and extended up to 2006. Among the achievements of MIEEIP as in January 2008 can be found in [22]. Table 3 below summarizes the reductions in terms of energy consumptions, costs and CO2 emissions achieved by MIEEIP in all the eight sectors from a total of 48 audited industrial companies up to 2007.

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Table 3. Emission reduction impact of MIEEIP energy audits [22] Sectors Energy consumption (‘000GJ/yr) Energy costs (106 RM/yr) - No cost - Low cost - High cost Total savings (‘000 GJ/yr) Total cost savings (106 RM/yr) CO2 emission reductions (kt/yr) # of audited factories Factories registered

Food

Wood

Ceramic

Cement

Glass

Rubber

Pulp & Paper

Iron & Steel

Total

1,835

1,032

774

21,557

4,000

611

5,080

4,223

39,113

42.2 24 111 238 374

13.5 8 132 221 361

24.1 39 75 42 155

204.2 1 7 337 345

97.8 31 14 59 104

16.9 57 21 84 162

84.2 52 69 691 812

160.1 64 57 149 270

643.0 277 486 1,821 2,583

8.5

5.2

6.0

33.8

2.5

4.3

19.8

5.3

85.3

28.0

30.4

14.5

444.7

8.1

18.9

194.4

22.8

761.7

10 471

7 75

6 54

3 54

3 18

9 134

6 134

4 148

48 1,088

132

T.H. Oh

A more recent EE effort in Malaysia that is worth mentioning is the Green Building Index (GBI) launched in May 2009 by the Malaysia Architect Association and the Association of Consulting Engineers Malaysia (ACEM) to assess the impact of a new building on the environment based on the six criteria of EE – indoor environment quality, sustainable site and management, materials and resources, water efficiency, and innovation. The index is soon becoming a standard for all buildings in Malaysia because it recognizes and rewards advances in EE through better technology and smart design [14]. Commercial and residential buildings alone account for 13% and 48% of total energy and electricity consumption in Malaysia respectively, indicating that the country has a strong need and great potential to apply EE strategies in lowering energy consumption in buildings [23]. Thus, the government is embarking on energy conservation in the building sector, starting with the government offices. The low energy office (LEO) building completed in 2004 which currently houses the Ministry of Energy, Green Technology and Water has set the benchmark for more buildings to be built in the country with EE and RE features integrated in the building design [24]. The LEO building was targeted to achieve a building energy index (BEI) of 100 kWh/m2 per year and energy savings of more than 50% compare to buildings without EE design. Table 4 shows the basic comparison analysis of the LEO versus a conventional building [13]. Table 4. Basic economic comparison analysis between the LEO and a conventional building [13]

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Description Conventional building BEI = 275 kWh/m2 LEO building BEI = 114 kWh/m2 Savings, (A) – (B) Percentage savings (%)

Energy cost (RM/year) Cooling energy

Electrical energy

Total

478000

620000

1099000

156000

338000

493000

322000 67.4

282000 45.5

604000 55.1

LEO building base cost = RM50 mil (air conditioned area = 19200 m2). Additional cost for installation of EE features in LEO building – RM5.048 mil (10% of base cost). Annual energy saving = RM0.604 mil/year. Payback period = 8.4 years.

Taking full advantage of the solar potential, in 2005, the 5-year Malaysian Building Integrated Photovoltaic Technology Application Project (MBIPV) was launched. This project is jointly funded by the government, Global Environment Facility (GEF), and the private sector with the intention to encourage the long term cost reduction of non-emitting GHG technologies by the integration of energy generating photovoltaic (PV) technology in building designs and envelopes. Over the lifetime of the project, the energy generated is expected to be able to avoid 65,100 tonnes of CO2 emissions from the country’s power sector [25]. The project has several demonstration PV projects in various sectors including residential houses and commercial buildings. The most considerable recent project is the green energy office (GEO) building, an administration-cum-research office for Malaysia Energy Centre, constructed following the success of the LEO. The GEO building is a pilot project and demonstrator building which

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marked another milestone towards greater promotion and adoption of sustainable building concept. The building PV panels are integrated into the building design to provide electricity for the building uses and are connected to the national electricity distribution grid by feeding electricity into the network and shaving the peak power demand of the grid during the peak daylight hours. The system provides almost 50% of everyday electrical needs. In daytime, the system will feed any surplus of energy back to the distribution grid. At night, the electrical energy was imported back from the grid to be used for the cooling system. At the moment, the GEO building has achieved BEI of 65 kWh/m2 per year without PV generation and this can further reduce to 35 kWh/m2 per year if PV generation is used. With more and more government buildings with EE and RE features to be constructed in the future, it is hoped that the private sector will be encouraged to follow suit and practice EE as a way of life. Other green technology features of the building can be found in [26]. In the recent Malaysia Budget 2010 announcement, the GBI is given a further boost as incentives will now be given to owners/buyers of buildings with GBI certificates. An owner of a building who incurs capital expenditure to obtain a GBI certificate will be granted an allowance equal to 100% of the capital expenditure incurred which may be offset against 100% of its statutory income. Buyers of buildings and residential properties which have GBI certificates will be entitled to stamp duty exemptions in respect of the additional costs incurred to obtain the GBI certificate. It is unclear at this stage as to how the mechanism of this exemption will operate, but this will presumably require the developers to indicate the additional costs incurred to obtain the GBI certificates. These incentives will apply in relation to costs incurred per building purchased between 24 Oct 2009 to 31 Dec 2014 [27].

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4. CARBON TRADING To have a better understanding on how carbon trading started from the Kyoto Protocol, a brief explanation on the mechanism is presented.

4.1. How Does Carbon Trading Work? The concept of carbon credits come into existence as a result of increasing awareness on the need for pollution control. It was formalized in the Kyoto Protocol, an international agreement between 169 countries under the United Nations Framework Convention on Climate Change (UNFCCC). The protocol sets quantified and binding targets for the developed (Annex I) countries to reduce emission of GHGs by an average of 5.2% of the 1990 level over a five-year commitment period from 2008 to 2012. To meet their commitments under the protocol, these countries must give priority to the implementation of regional or national policies and measures. Three market-based mechanisms of the Kyoto Protocol are set up to help meet their targets in a cost effective and green manner; 1) International emission trading (IET) – the carbon credit market, 2) Clean development mechanism (CDM), and 3) Joint implementation (JI). Under JI, a developed country with relatively high costs of domestic greenhouse reduction would set up a project in another developed country that has a relatively low cost. Under CDM, a developed country can take up a GHG reduction project activity in a developing country where the cost of

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such activities is usually much lower. The developed country would be given credits for meeting its emission reduction targets, while the developing country would receive the capital and clean technology transfer to implement the project. Under IET, countries can trade in the international carbon credit market. Countries with surplus credits can sell them to countries with quantified emission limitation and reduction commitments under the Kyoto Protocol [29, 30]. Of these three mechanisms, CDM is the only mechanism that involves non-Annex I countries aims at promoting co-operative measures between the industrialized (Annex I) and the developing (non-Annex I) countries. As a non-Annex I country, the CDM is thus the only mechanism under the protocol that is relevant for Malaysia. The CDM is proposed with the twin objectives of helping Annex I countries to achieve their emission reduction targets and at the same time helping non-Annex I countries to promote sustainable development in their economies. The CDM idea is to facilitate co-operative projects between developed and developing countries to reduce GHG emissions, with the opportunity for additional financial and technological investments in GHG reduction projects. The GHG reductions achieved by each CDM project will be quantified in standard units, to be known as Certified Emission Reductions (CERs), a form of carbon credits. It involves the trading of emission reductions resulted from a specific project (called CERs once such reductions are certified) to countries that can use these CERs to meet their targets. In return for the CERs, there will be a transfer of money to the project that actually reduces the GHGs [31]. Obviously, carbon credits are a tradable permit scheme, creating a market for reducing GHG emissions by giving a monetary value to the cost of polluting the air. A credit gives the owner the right to emit one tonne of CO2. International treaties such as the Kyoto Protocol set quotas on the amount of GHGs countries can produce. These countries, in turn, set quotas on the emissions of businesses. Businesses that are over their quotas must buy carbon credits for their excess emissions, while businesses that are below their quotas can sell their remaining credits. By allowing credits to be bought and sold, a business for which reducing its emissions would be expensive or prohibitive can pay another business to make the reduction for it. This minimizes the quota's impact on the business, while still reaching the quota. Credits can be exchanged between businesses or bought and sold in international markets at the prevailing market price [29]. In effect, the buyer is being charged for polluting, while the seller is being rewarded for producing less contaminant. Presently, carbon trading is most developed in the European Union (EU), where the EU trading system that has been in effect since 2005, accounted for US$24 billion (about 80% of total trades) in 2006. There are currently two exchanges for carbon credits: the Chicago Climate Exchange and the European Climate Exchange. The World Bank has estimated the global carbon credit market to be worth US$30 billion in 2006, up three-fold from 2005 [31].

4.2. Potential in Malaysia As GHG emission levels are predicted to keep rising over time, it is envisioned that the number of companies wanting/needing to buy more credits will increase, thus pushing the market price up and encourage more groups to undertake environmentally friendly activities that will create for them carbon credits to sell. Another model as mentioned before is that,

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companies that use below their quota can sell their excess as 'carbon credits.' The possibilities are endless hence making it an open market [29]. Despite carbon trading being relatively new in Malaysia, a biomass project in Sabah, a state in east Malaysia, is actually the first in the world to be awarded CERs by the United Nation Executive Board of CDM. In fact, corporate sectors in the country such as power, manufacturing, waste management, forestry, oil and gas, manufacturing, agriculture and transportation sectors which have been identified as potential beneficiaries, have been proactive to capitalize on CDM participation. As in March 2009, based on data released by the United Nations Environment Programme (UNEP) resource centre, there are a total of 4,660 future CDM projects registered, with Malaysia having 156 projects or 3.3% of the list in the pipeline, as charted in Fig. 6. Asian countries are generally making headway in carbon trading, with China and India leading the pack at 55.24% and 12.78% respectively, based on the reported average annual CERs from registered projects as in 2008 (see Fig. 7). Malaysia already has 22 registered CDM projects with most the CERs coming from biomass plants. As of March 2007, two of the 22 CDM projects had sold 320,000 tonnes of CERs valued at less than RM10 million (US$2.86 million) [32]. According to the Malaysia Energy Centre, agricultural and natural resources-rich Malaysia has 100 million tonnes of carbon credit, which is translated to RM4.8 billion (US$1.37 billion) in revenue and could potentially benefit from carbon trading, which is now worth US$60 billion globally. UNFCCC estimates carbon trading has the potential to grow to US$1 trillion in the next ten years. As the emission trading scheme under the Kyoto Protocol commences in 2008 and couples with financial contribution to projects by CDM in reducing GHG emissions, various domestic sectors are poised to benefit from carbon trading [33].

Figure 6. Rough estimation of CDM projects in Asia by country by UNEP as of March 2009 [28].

Among the criteria for a project to qualify as a CDM project, it should be able to demonstrate that the revenues from CDM can help to overcome some existing financial or other barriers which are not possible without the financial assistance. Thereafter, several transaction costs have to be made, ranging from US$40,000 to US$150,000, to register a project as a CDM project before tradable CERs can be generated. Projects in the pipeline can be grouped in the following categories; agriculture (composting), EE, landfill gas to electricity, landfill gas flaring reduction, manufacturing industry, RE (biomass, biogas and hydropower) and animal waste.

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Table 5 provides an overview of the expected potential of CER revenues for different types of projects in Malaysia and the corresponding amount of megawatt (MW) that can be installed from RE in 2010. The results are only based on an assessment of the potential in the energy sector and still in preliminary stage. The realisation of this potential will depend upon the removal of other existing barriers for these project types [30].

Figure 7. Average annual CERs from registered projects by country 2008 [28].

Table 5. Estimated CDM revenues from various projects in Malaysia [30]

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Project type

a b

Biogas POMEa and animal manure Landfill gas Reduction of gas flaring from oil production Mini hydro Biomass CHPb Others Total

Estimated CERs in 2010 (RM‘000)

Potential electricity (MW)

5,900

190

3,700

45

4,600

N/A

70 380 3,150 17,800

25 90 N/A 350

palm oil mill effluent. combined heat and power.

As a developing country with ample of agricultural and natural resources, the most obvious beneficiary CER trading in Malaysia is no doubt in plantation sector, particularly oil millers, when the carbon trading legislation is imposed in the western countries. Malaysia is one of the top palm oil producers in the world, second only to Indonesia. With an annual crude palm oil production of 17.7 million tonnes as in year 2008 and the 395 operating oil mills, Malaysia has the potential to rake in RM252 million (US$72 million) of yearly income from three typical projects; composting of empty fruit bunches (EFB) and palm oil mill effluents (POME), biogas recovery from effluent to energy, and conversion of biomass (palm kernel shells, EFB) to energy. Apart from the country’s abundant biomass waste resources from oil palm, wood residues and agro-industries such as rice husk also have huge potential to be utilized as biofuel, either for stationary or transport applications. As a type of RE, apart

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from reduction in GHG emission from their combustion, biomass and biofuel actually provide security of supply and sustainability for the industries in the country.

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4.3. Challenges and The Way Forward The cutback on GHGs emissions can be accomplished by restructuring company operations and processes to physically reduce emissions and through purchases of carbon credits to meet the carbon emission reduction deficits. The reduction can be achieved through financial exchanges by supporting the CDM or simply by buying carbon credits from companies or developed countries that have excess allowances. Carbon credits are awarded to projects in a country by the Designated Operational Entity (DOE) after grilling through the stringent and complex procedures adopted by the UNFCCC to be certified as having reducing a real and quantifiable amount of GHGs [34]. Since CERs can be traded and used by developed countries to comply with emission reduction targets, hence this shall create a winwin situation between developing and developed nations. The objective of the Kyoto Protocol is noble, but the complex trading system has been open to abuses. Problems emerge due to serious flaws in the checking system on actual achievement in GHG reductions. Under the protocol, a CDM project needs to demonstrate that it will lead to a quantifiable reduction in GHGs and that it would not have been economically viable without the additional capital generated by carbon trading. It is estimated that up to 20% of the carbon credits issued did not match genuine reductions, thus risks creating a false sense of security in the system. Some parties have argued that the CDM process has been manipulated, particularly by the owners of large-scale hydropower plants, which remain environmentally controversial. Besides questioning the effectiveness of carbon markets, carbon credits have been disputed as a way for an organization to throw money at a problem instead of taking action to reduce their own carbon footprint of their operations. To drive large scale investments and financial flows to developing countries for significant global emissions reduction, investment barriers need to be resolved, present CDM need to be extended and streamlined or new mechanisms established, regional and national carbon markets need to be linked internationally [28]. Malaysia government has been very supportive and instrumental in the CDM participation and has established the machinery and mechanisms for smooth implementation to tackle the GHGs emissions and the promotion of carbon trading in the country. To encourage corporations to go green, the Malaysian government has exempted carbon credit income from tax from 2008 to 2010. From a corporation’s perspective, the main incentive to go green would be that such practices make good corporate social responsibility as well as its cost recovery potential [33]. In the announcement of the country’s Budget 2008, an additional 10-year pioneer status were granted to companies involved in energy conservation, on top of 3-year tax exemption for income derived from carbon credits trading. In the more recent Budget 2010 measures outlined by the Prime Minister, Datuk Seri Najib Tun Razak, among other green technology developments to be initiated by the government are [35]: ƒ

Restructure the Malaysia Energy Centre as the National Green Technology Centre tasked with formulating a green technology development action plan. This centre will

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ƒ

ƒ

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ƒ

function as the focal point to set standards and promote green technology. To intensify green awareness activities and practise environment-friendly lifestyle, an allocation of RM20 million will be provided. An international exhibition on green technology to be organized in April 2010. The exhibition is expected to attract internationally renowned companies and experts in green technology. Develop Putrajaya and Cyberjaya as pioneer townships in green technology, as a showcase for the development of other townships. Priorities are to be given to environment-friendly products and services that comply with green technology standards in government procurement.

A fund amounting to RM1.5 billion (US$430 million) will be allocated to provide soft loans to companies that supply and utilize green technology, with maximum financing up RM50 million (US$14.3 million) for suppliers and RM10 million (US$2.9 million) for consumer companies, while the government shoulders 2% of the total interest rate. In addition, the government is providing a guarantee of 60% on the financing amount, with the remaining 40% by banking institutions. Loan applications are made through the National Green Technology Centre and this scheme which commences on 1 Jan 2010 is expected to benefit 140 companies [33]. Although the funding amount is pale in comparison to many similar commitments in other countries, it is considered a first major step taken by the government to show its seriousness in addressing global warming and moving towards a low carbon economy. The recently concluded 2009 Climate Change Conference offered the best hope for a global framework of co-operation on climate issues, whereby under this convention are the fair principles of equity and historical responsibilities due to the need of Annex I parties to repay their climate debts. In the summit, Malaysia has taken its stand and made a voluntary pledge to adopt a national reduction indicator of 40% in terms of its 2005 GDP emission intensity levels by 2020 as its contribution towards global efforts to combat climate change. The voluntary indicator will serve as a measure to the country’s progress in climate action. However, the indicator is conditional upon the transfer of technology and adequate financing from Annex I partners. In order to realize the 40% target, it will very much depend on a coherent national plan and a specific climate-related legislation which the country is currently lacked of. However, the launch of the National Green Technology Policy in April 2009 with its five objectives which include decreasing energy consumption while enhancing economic development, facilitating the growth of green technology industry and enhancing its contribution to the national economy, did give a new breath of fresh air in the national policy scene as it is set to play an important role in charting the country’s development where green technology will be the new driver for economic growth. A Green Technology Council which is chaired by the Prime Minister himself will also be established to facilitate the role of stakeholders to ensure the successful implementation of the green technology roadmap. Not to be taken lightly the impact from the private sector, the government is studying incentives for the private sector that adopts green technology in their business. As going green is about new technology, a different type of employee is necessary to work in a green economy and technology-based companies should also look into researching new and more efficient RE. Currently, there is still a lack of awareness among Malaysians on what going green really means and only large corporations with huge carbon emissions will embrace such

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practices. Smaller companies with significantly less carbon emission will find it time consuming and not cost effective to invest in such schemes because of the stringent guidelines and criteria set under the Kyoto Protocol. But companies that adopt green and sustainability practices normally tend to progress much faster and are perceived as good employment choices. Therefore, all corporations should not detract from their sustainable practices just because it incurs additional cost to do so. Qualitatively, engaging in sustainable, environmentally sound strategies and practices also makes for good corporate responsibility and contributes to a cleaner environment. In fact, by not observing sustainable practice, a company might actually run the risk of going out of business as the looming fossil fuel-led industrial era will eventually replace by the low carbon era. This calls for a policy where the development of RE technologies goes hand in hand with a more efficient use of the primary energy in order to reduce dependence on traditional energy sources. In this respect it is important that decision makers are updated on the actual development, status and potential of RE technologies in order to provide relevant incentives. In addition, it is important that these incentives are introduced in relation to stronger and more far-sighted measures to enhance a more efficient use of primary energy.

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5. CONCLUSION Every country should play their part to contribute on the basis of the well-being of the environment and existing knowledge on RE, EE and deforestation in order to make a big difference in decades to come. A long-term framework of incentives is required to succeed the Kyoto Protocol and to develop the technologies for a sustainable future. The seriousness of Asia powerhouses such as China and other emerging markets with similar enthusiasm to participate in tackling climate change issue offers a huge opportunity that should be grasped and take note of. The fact that oil has once inched close to US$150 a barrel not so long ago is an exemplary reason of energy security why every nation needs to change the nature of their economies to drive down carbon dependencies. In the light of concerns about global warming due to human enhancement of the greenhouse effect, there is clearly a growing concern about how energy needs are addressed on a sustainable basis. Considering the high and often fluctuating fossil fuel market prices, the fact that Malaysia is richly endowed with RE sources have become a more attractive option for sustainable energy and electricity generation. Despite a long-term effort in Malaysia, RE sources, EE and carbon trading are not yet utilized to anywhere near their full potentials. With the Kyoto Protocol commitment between 2008 to 2012, Malaysia is nevertheless well positioned to benefit from the CDM projects through RE and EE. However, there is a need to build capacity in the country to adapt policies and regulations, harmonize policy instruments and achieve local terms to promote these concepts [36].

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T.H. Oh Cheremisinoff NP. Handbook of Air Pollution Prevention and Control. Elsevier Science, USA; 2002. Science Daily. Rising sea levels set to have major impacts around the world. http://www.sciencedaily.com/releases/2009/03/ 090310104742.htm. IPCC Fourth Assessment Report (AR4) – Climate Change 2007: Synthesis Report. http://www.ipcc.ch/publications_and_data/ publications_ipcc_fourth_assessment_report_synthesis_report.htm. Energy Information Administration. 2006 energy-related emissions data & environmental analyses. http://www.eia.doe.gov/environment.html. Scripps CO2 Program: CO2 concentration at Mauna Loa Observatory, Hawaii. http://scrippsco2.ucsd.edu/. Allison I, et. al. The Copenhagen Diagnosis: Updating the world on the latest climate science. The University of New South Wales Climate Change Research Centre (CCRC), Sydney, Australia; 2009. 60pp. http://www.copenhagendiagnosis.org. Energy Information Administration: Malaysia Energy Profile. http://tonto.eia.doe.gov/ country/country_energy_data.cfm?fips=MY. Malaysia Energy Database & Information System: Energy Info Highlights. http://medis.ptm.org.my/highlights.html. Energy Information Administration (EIA). International Energy Annual 2005 – CO2 World Carbon Dioxide Emissions from the Consumption of Coal, 1980-2006. http://www.eia.doe.gov. Shigeoka H. Overview of international renewable energy policies and comparison with Malaysia’s domestic policy. http://www.ptm. org.my/biogen/index.aspx?id=41. Razak MRA, Ramli MR. A brief presentation on the Malaysia electricity supply industry. Conf. of Fuel Options for Power Generation, Bangkok, Thailand; 2008. Lau LC, Tan KT, Lee KT, Mohamed AR. A comparative study on the energy policies in Japan and Malaysia in fulfilling their nations’ obligations towards the Kyoto Protocol. Energy Policy 2009;37:4771–4778. Oh TH, Pang SY, Chua SC. Energy policy and alternative energy in Malaysia: Issues and challenges for sustainable growth. J. Of Renewable and Sustainable Energy Reviews 2009. doi:10.1016/j.rser.2009.12.003 Hasan AF. Energy efficiency and renewable energy in Malaysia. Energy Commission. http://www.teeam.com/st_paper_15july09.pdf. Energy Commission (SCORE Meeting). http://www.ptm.org.my/biogen/ index.aspx?id=62; August 2005. Lalchand G. Component 3: Policy Development. MBPIV project – Post 9th Malaysia Plan: What’s next? BiPV Seminar: What’s In It For Me? Kuala Lumpur; March 2006. BioGen, 2005. New and Renewable Energy in Malaysia. http://www.biogen.org.my/ bris/BioGen/Tech/(d)Documents/technology(d)6.pdf. National Green Technology policy. Ministry of Energy, Green Technology and Water. http://www.ktak.gov.my/template01.asp?contentid=253. Najib M. Keynote address: 14th Annual Asia oil and Gas Conf., Kuala Lumpur; June 2009. Dalenback JO. Diversification: Reflecting on renewable energy and energy efficiency. Elsevier reFOCUS (4) 2004:54–55.

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[22] Akker JVD. Final evaluation: Malaysian Industrial Energy Efficiency Improvement Project (MIEEIP). ASCENDIS 2008. http://www.undp.org.my/uploads/mieeip% 20final%20evaluation%20report%20jan%202008.pdf. [23] Malaysia Economic Planning Unit. 9th Malaysia Plan 2006 – 2010, Kuala Lumpur, Malaysia; 2006. [24] Mansor SA. Keynote address: Powergen Asia Conf., Kuala Lumpur; Oct. 2008. [25] Solar Energy. Energy Information Bureau. Malaysia Energy Centre. http://eib.ptm.org. my/index.php?page=article&item= 100,136,143. [26] Green Energy Office, GEO-PTM. http://www.ptm.org.my/PTM_Building/intro.html. [27] 2010 Malaysian Budget Highlights. Tax Insights. http://www.docstoc.com/docs/ 16589733/2010-malaysian-budget-highlights. [28] Carbon credits explained. http://www.climateavenue.com/cdm.carbon.cred.index.htm. [29] Q2 Engineering: Carbon credits. http://www.q2.com.my/english/?Carbon_Credits. [30] Clean Development Mechanism for Energy Sector. http://cdm.eib.org.my. [31] Business Star: Asia the growing hub for carbon emission reduction programmes; 26 Sept 2009. http://biz.thestar.com.my/news/story.asp?file=/2009/9/26/business/ 4676903&sec=business. [32] Business Star: Huge potential in carbon trading; 7 Jan 2008. http://biz.thestar.com. my/news/story.asp?file=/2008/1/7/business/19916365&sec= business. [33] CSR Malaysia: 5 more years for Malaysia to realise full potential in carbon trading. http://www.csr.malaysia.org/news/ environment/malaysia-realise-potential-carbontrading-2008030277. [34] Climate Avenue: Malaysia has huge reserve of carbon credits. http://www. climateavenue.com/cdm.carbon.malaysia.htm. [35] Najib TAR. The 2010 Budget Speech. http://www.docstoc.com/docs/19707607/ Malaysia-Budget-2010-Speech. [36] [Lidula NWA, Mithulananthan N, Ongsakul W, Widjaya C, Henson R. ASEAN towards clean and sustainable energy: Potentials, utilization and barriers. Renewable Energy 2007;32:1441–1452.

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In: Theories and Effects of Economic Growth Editor: Richard L. Bertrand, pp. 143-158

ISBN: 978-1-61209-795-4 © 2011 Nova Science Publishers, Inc.

Chapter 6

INFLUENCE OF THE ECONOMIC CONJUNCTURE ON SME INVESTMENT: EMPIRICAL EVIDENCE USING DYNAMIC PANEL ESTIMATORS Silvia Mendes1, Paulo Maçãs Nunes2 and Zélia Serrasqueiro2 1

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Escola Superior de Tecnologia e Gestão de Oliveira do Hospital, Instituto Politécnico de Coimbra, Portugal 2 Departamento de Gestão e Economia, Universidade da Beira Interior, Portugal and CEFAGE-UE (Centro de Estudos e Formação Avançada em Gestão e Economia), Universidade de Évora

ABSTRACT Based on a sample of 1845 Portuguese SMEs for the period 1999-2006, and using the two-step estimation method in order to solve the problem of sample bias as a consequence of the matter of survival, we investigate if the economic conjuncture has significant effects on the investment of Portuguese SMEs. The empirical evidence obtained by using dynamic panel estimators, corresponding to the second step of the estimation method, lets us conclude that the economic conjuncture has a significant impact on investment by Portuguese SMEs: 1) higher reference interest rates for loans have a restricting effect on investment; and 2) economic growth, in terms of Gross National Product, contributes to increased investment. In addition, the empirical evidence obtained from probit regressions, corresponding to the first step of the estimation method, also allows us to conclude that: 1) higher reference interest rates for loans contribute to diminished probability of the survival of Portuguese SMEs; and 2) economic growth contributes to increased probability of the survival of Portuguese SMEs. In general we find the economic conjuncture has a significant impact on investment by Portuguese SMEs. Concerning companies’ intrinsic determinants: 1) Investment in the Previous Period; 2) Cash Flow; 3) Sales; 4) Debt; 5) Age; and 6) Growth Opportunities, the empirical evidence obtained allows us to conclude that: 1) investment in the previous period and cash flow are positive determinants of investment in Portuguese SMEs; 2) debt is a restrictive determinant of investment in Portuguese SMEs; and 3) sales, age and

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Silvia Mendes, Paulo Maçãs Nunes and Zélia Serrasqueiro growth opportunities are neither positive nor restrictive factors of investment by Portuguese SMEs. Summarizing, the empirical evidence obtained in this study lets us conclude that investment by Portuguese SMEs is persistent, since we find a positive and statistically significant relationship between investment in the previous period and investment in the current period. In addition, we find that investment by Portuguese SMEs is dependent on the economic conjuncture (interest rates and GNP) and the financial situation of SMEs (cash flow and debt). Given the importance of SMEs in Portugal for stimulating economic growth and employment, we suggest considerable reinforcement of financial support from government bodies to SMEs that are limited financially. This financial support could be particularly relevant at times of economic recession.

Keywords: Dynamic Panel Estimators; Economic Conjuncture; Investment; SMEs; Two-step Estimation Method.

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1. INTRODUCTION Forms of investment can be divided into categories: investment in fixed capital (in the form of expenditure on machinery, equipment, and manufacturing, commercial, distribution and administrative premises); investment in the residential and building sector; investment in R&D; investment in financial assets and shares. In this study, the term of investment will be used to designate company investment in fixed capital. Motivation to study the behaviour and dynamics of company investment arises from its relevance as a determinant variable of economic growth, and therefore also a determinant in the formation of economic cycles. There may be a relationship between business investment and an economy’s level of performance. The interest rate as a determinant variable of the cost of external capital was already considered by Neoclassic theory as a determinant of investment. Bernanke and Gertler (1995), Gilchrist et al. (2006) claim interconnection between monetary policy and investment, as the effect these policies have on the cost of capital eventually influences company investment, so that a fall in the level of investment will provoke a spread of shocks through the credit cycles. Gilchrist et al. (2006) found a statistically negative relationship between interest rates and capital. Authors such as Bernanke and Gertler (1989), Gertler and Gilchrist (1994) and Oliner and Rudebusch (1996), claim companies that are restricted financially, and that operate in imperfect markets, are more affected by times of economic recession, in this way increasing their financial limitations. At times of economic recession, we can expect capital markets to be more restrictive in granting credit, therefore affecting investment negatively. In these situations, companies will be obliged to resort to their own cash flow, which could be more limited due to the market’s recessive behaviour (Kaufmann and Valderrama, 2008). At times of economic growth, companies on one hand will have easier access to credit, and on the other higher levels of cash flow, which will facilitate investment. However, the air of uncertainty in periods of economic recession will also have negative repercussions for investment, since companies, and notably the youngest ones, that operate in a market of imperfect competition adopt an attitude of waiting until the market becomes established again (Fuss and Vermeulen, 2004).

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The main objective of this study is to analyze if the economic conjuncture has an effect on SME investment. More specifically, we intend to determine if interest rates for investors and economic growth, measured by GNP, are positive or restrictive determining factors of SME investment. Besides interest rates for investors and GNP, we consider other variables normally used in the literature as determinants of company investment: 1) cash flow, as a measure of internal finance; 2) sales; 3) debt, as a measure of external finance; 4) age; and 5) growth opportunities. Methodologically, we use panel data. The panel is made up of a total of 1845 SMEs for the period 1999-2006. So as to conveniently solve the problem of possible bias in the estimated results, as a consequence of the matter of survival, we use the two-step estimation method proposed by Heckman (1979) to estimate the empirical evidence of this study. At a first stage we estimate probit regressions, considering all SMEs in the sample. From estimation of the probit regressions, we calculate the inverse Mill`s ratio, which will be used in the investment regressions as an additional explanatory variable. Use of the inverse Mill`s ratio in the investment regressions lets us solve the problem of possible result bias, as a consequence of the matter of survival. At a second stage, we estimate relationships between determinants and investment, considering only surviving SMEs in the sample, using the inverse Mill’s ratio as an additional explanatory variable. At the second stage, to estimate relationships between determinants and investment, we turn to dynamic panel estimators, namely the GMM (1991) and GMM system (1998) estimators. The empirical evidence obtained in this study allows us to conclude that the economic conjuncture is a determinant of investment by Portuguese SMEs. More specifically, we find that higher interest rates for investors are a restrictive factor of Portuguese SME investment, economic growth being vitally important for increased investment by Portuguese SMEs. We also find that higher interest rates for investors contribute to diminished probability of survival in Portuguese SMEs, economic growth contributing to increased probability of survival in Portuguese SMEs. Concerning the relationships identified between other determinants used in this study and SME investment, it stands out that internal financing, measured by cash flow is a positive factor of Portuguese SME investment, whereas external financing, measured by debt, is a restrictive factor of Portuguese SME investment. After this introduction, this study is structured as follows: 1) section 2 presents the database, variables and econometric method used; 2) section 3 presents the results; 3) section 4 discusses the results; and 4) section 5 presents the principle conclusions and implications of the study.

2. DATABASE, VARIABLES AND ECONOMETRIC METHOD 2.1. Database This study uses the SABI (System Analysis of Iberian Balance Sheets) database, supplied by Bureau van Dijks for the period 1999-2006.

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We select SMEs based on the European Union recommendation L124/36 (2003/361/CE). According to this recommendation, an enterprise is considered small and medium-sized when it meets two of the following criteria: (1) fewer than 250 employees; (2) assets under 43 million euros; and (3) sales under 50 million euros. Based on the criteria mentioned above, we selected 1845 unlisted SMEs for the period 1999-2006, and so we have a panel made up of 12053 observations To solve the problem of possible result bias, as a consequence of the matter of the survival effect on SME investment, and also with the aim of having a more representative sample of the state of Portuguese SMEs, we consider three types of SMEs: i) SMEs that are in the sample for the entire period of analysis (1999-2006); ii) SMEs entering the market during the period of analysis (1999-2006); and iii) SMEs leaving the market during the period of analysis (1999-2006). However, given the use of dynamic panel estimators, there are restrictions in including SMEs that are in the sample for a very limited number of years. Indeed, Arellano and Bond (1991) conclude that given the relevance of second order autocorrelation tests for validation of estimated results, to be effectively considered in those tests companies must be included in samples for at least four consecutive years. Based on the conclusions of Arellano and Bond (1991), and so that all SMEs are effectively considered in the second order autocorrelation tests, in selecting SMEs, besides the criteria mentioned above, we consider inclusion in the sample for at least four consecutive years. Therefore, the final selection of SMEs used in this study is formed as follows: 1) 1411 SMEs that remain in the market for the entire period of analysis (1999-2006), corresponding to a total of 9877 observations; 2) 236 SMEs that enter the market in the period of analysis (1999-2006), corresponding to a total of 1228 observations; and 3) 198 SMEs that leave the market in the period of analysis (1999-2006), corresponding to a total of 948 observations.

2.2. Variables Our main objective is to test if the economic conjuncture has an effect on SME investment. With this aim, we consider SME investment as the dependent variable, investment ( I i ,t ) being given by the ratio of the variation of fixed capital less amortization and depreciation to fixed assets in the previous period1. As independent variables we have: 1) interest rates in the current period ( IRt ) which are market reference interest rates for investors for 1year; 2) the measure of economic growth in the current period ( GNPt ), given by the logarithm of Gross National Product at constant prices.

1

Given the use of dynamic panel estimators, the relationship is estimated between investment in the previous period and investment in the current period. Therefore, we have an additional independent variable, namely investment in the previous period ( INVi ,t −1 ), given by the ratio of the variation of fixed capital in the previous period less the period’s amortization to fixed assets two periods out of step.

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We use other independent variables usually considered in diverse studies about company investment2: 1) cash flow in the current period ( CFi,t ), as a measure of internal financing, given by the ratio of operational results plus amortization to total assets; 2) sales in the previous period ( SALESi ,t −1 ), given by the logarithm of sales; 3) debt in the previous period ( LEVi ,t −1 ), given by the ratio of total debt to total assets; 4) age in the previous period ( AGEi ,t −1 ), given by the logarithm of the number of years of company existence; and 5) growth opportunities in the previous period ( GOi ,t −1 ), given by the annual rate of sales growth.

2.3. Econometric Method Studying the determinants of SME investment without correcting possible sample bias, as a consequence of not considering the situation of companies that left the market during the period of analysis, could lead to bias of the results obtained, due to omission of the situation of SMEs with survival difficulties, something which could be different from that of companies with good possibilities for survival. The best way to solve this problem is to use the two-step estimation method proposed by Heckman (1979). At the first stage, considering all SMEs, both surviving and non-surviving, we estimate a probit regression in which the dependent variable takes on the value of 1 if the SME is in the market and the value of 0 if it left the market. As independent variables we consider the investment determinants used.

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The probit regression estimated in the first step lets us calculate the additional variable, the inverse Mill’s ratio, which allows control of possible sample bias. At a second stage, when estimating regressions referring to investment determinants, we only consider surviving SMEs, adding the inverse Mill’s ratio as another explanatory variable, so as to control for possible data bias as a consequence of survival. The probit regression to estimate, corresponding to the first step, is given by:

Pr(δ i ,t = 1) = α 0 + φINVi ,t −1 + γ 1 IRt + γ 2GNPt + γ 3CFi ,t + γ 4 SALESi ,t −1 + γ 5 LEVi ,t −1 +

γ 6 AGEi ,t −1 + γ 7 GOi ,t −1 + S S + d t + zi ,t

(1)

3

in which: S S are dummy sector variables ; d t are dummy annual variables measuring the impact of alterations in the economic conjuncture on the likelihood of bankruptcy; and z i ,t is the error.

2 3

As for example in Moyen (2004), Aivazian et al. (2005), Ascioglu et al. (2008) and Brown et al. (2009). We consider six industry sectors: i) agriculture, ii) forestry and fisheries, iii) construction, iv) manufacturing, v) wholesale and retail trade, and vi) service industries. Classification is according to a firm´s primary activity, indicated by its single-digit SIC/NACE code).

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After determining the inverse Mill’ ratio , for each of the observations, we consider it as an additional explanatory variable of SME investment. At the second stage, in order to estimate regressions related to investment determinants, we use dynamic panel estimators, namely the GMM (1991) and GMM system (1998) estimators. Use of dynamic estimators has the following advantages over traditional panel models (random effect panel models and fixed effect panel models): 1) greater control of endogeny; 2) greater control of possible collinearity of explanatory variables; and 3) more effective control of the effects caused by the absence of relevant independent variables to explain the dependent variable. In addition, use of dynamic estimators allows correct determination, i.e., without result bias, the level of persistence of SME investment5. The regressions to estimate, through use of the various dynamic panel estimators, are given by the following expression:

INVi ,t = α 0 + δINVi ,t −1 + β1 IRt + β 2GNPt + β 3CFi ,t + β 4 SALESi ,t −1 + β 5 LEVi ,t −1 +

β 6 AGEi ,t −1 + β 7 GOi ,t −1 + S S + d t + zi ,t

(2)

in which: λ i,t is the inverse Mill`s ratio; vi are non-observable individual effects; and e i ,t is the error which assumes normal distribution. Estimating the regressions presented above using traditional panel methods, considering fixed or random individual effects, we obtain biased and inconsistent estimates of the parameters, since as well as the existence of correlation between u i and INVi ,t −1 , there is

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also correlation between e i ,t and INVi ,t −1 . Arellano and Bond (1991) recommend estimation of equation (2) with the variables in first differences, using the lagged profitability and determinants at level. By estimating equation (2) in first differences, non-observable individual effects ( vi ) are eliminated, eliminating the correlation between vi and INVi ,t −1 . Use of the lags of profitability and lags of the determinants creates orthogonal conditions between eit and INVi ,t −1 , eliminating their correlation. However, Blundell and Bond (1998) state that in situations of persistence of the dependent variable, i.e. when high correlation is found between the dependent variable in the previous and current periods, and the number of periods is not particularly high, the GMM (1991) estimator leads to inefficient results because the instruments are weak, leading to bias of the estimated results. This bias is particularly relevant concerning the estimated parameter measuring the relationship between the dependent variable in the previous and current period. In situations of high persistence of the dependent variable, Blundell and Bond (1998) propose use of an alternative estimator, considering a system of variables at levels in first differences. For the variables at level, the instruments are given in first differences. For the variables in first differences, the instruments are given in levels.

4 5

To see in detail how to calculate the inverse Mill’s ratio, consult Heckman (1979). The level of persistence of SME investment is given by the relationship between investment in the previous period and investment in the current period.

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For the results obtained from using the GMM (1991) and GMM system (1998) estimators to be considered robust, two conditions must be verified: 1) the restrictions created from use of the instruments have to be valid; and 2) there can be no second order autocorrelation. To test validity of the restrictions created from use of the instruments, we use the Sargan test in the case of the GMM (1991) estimator and the Hansen test in the case of the GMM system (1998) estimator. In both cases, the null hypothesis is validity of the restrictions created by using the instruments used, the alternative hypothesis being non-validity of use of the restrictions created by use of the instruments. We also test for the existence of first and second order autocorrelation. The null hypotheses indicate non-existence of first and second order autocorrelation, the alternative hypotheses indicating the existence of first and second order autocorrelation. In the case of not rejecting the null hypotheses of validity of the restrictions created by the instruments and non-existence of second order autocorrelation, we conclude the results obtained from using the GMM (1991) and GMM system (1998) estimators are robust.

3. RESULTS 3.1. Analysis of Survival The following table presents the results referring to the survival analysis, corresponding to the first step of the two-step estimation method proposed by Heckman (1979). Table 1. Survival Analysis – Probit Regression Dependent Variable:

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Independent Variables Ii,t-1 IRt GNPt

Pr(δ i ,t = 1)

I

II

III

IV

IV

VI

0.0492*** (0.0112) -0.0928*** (0.0301) 0.0201*** (0.0078)

0.0472*** (0.0089)

0.0453*** (0.0091)

0.0416*** (0.0076)

0.0389** (0.0138)

0.0591*** (0.0181)

0.2172*** (0.0452) 0.0566*** (0.0174)

0.0309*** (0.0078) 0.3181 -776.54 1845 12053

0.0298*** (0.0085) 0.3761 -781.50 1845 12053

0.2617*** (0.0563) 0.0476** (0.0233) 0.1388*** (0.0346) 0.0656*** (0.0210) 0.0717 (0.1253) 0.0281** (0.0136) 0.4671 -796.76 1845 12053

0.0574*** (0.0109) -0.1091** (0.0530) 0.0178*** (0.0056) 0.2192*** (0.0516) 0.0483** (0.0235) 0.1181** (0.0551) 0.0608** (0.0178) 0.1013 (0.1439) 0.0271* (0.0144) 0.5647 -812.90 1845 12053

0.2466*** (0.0618)

CFi,t SALESi,t-1 LEVi,t-1 AGEi,t-1 GOi,t-1 CONS R2 Log Likelihood Companies Observations

0.0302*** (0.0112) 0.3667 -780.92 1845 12053

0.0317*** (0.0097) 0.3298 -779.06 1845 12053

Notes: 1. standard deviations in parenthesis. 2. *** statistical significance at the 1% level. 3. ** statistical significance at the 5% level. 4. * statistical significance at the 10% level. 5. the estimates include sectoral and time dummy variables, but not shown. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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On one hand, the results obtained allow us to conclude that investment in the previous period, cash flow, sales, debt, age and GNP are factors that contribute to increased probability of SME survival. On the other, the interest rate is a factor restricting the probability of SME survival. Growth opportunities are neither a restrictive nor positive factor of the likelihood of SME survival. Irrespective of the variables considered in the regressions, no significant alterations are found in the estimated parameters, concerning sign, statistical significance and magnitude of the estimated parameters, which confirms the robustness of the empirical evidence obtained.

3.2. Investment Determinants The following tables present the results of the explanatory regressions of SME investment, using the GMM (1991) and GMM system (1998) dynamic estimators. Table 2. SMEs Investment Determinants - GMM (1991) Estimator Dependent Variables: Ii,t Independent Variables Ii,t-1 IRt GNPt

I

II

III

IV

V

VI

0.1163*** (0.0244) -0.1172*** (0.0324) 0.0265*** (0.0066)

0.1049*** (0.0219)

0.1289*** (0.0234)

0.1166*** (0.0239)

0.1244*** (0.0219)

0.0872 (0.1829)

1.1844*** (0.2981) 0.0911 (0.2119)

-0.2387*** (0.0589) 0.0491*** (0.0134) 166.75*** 41.90 -5.12*** 0.22 1647 8004

-0.2211*** (0.0541) 0.0298* (0.0151) 171.68*** 45.12 -6.15*** 0.48 1647 8004

1.2007*** (0.3415) 0.1011 (0.2891) -0.0798*** (0.02001) -0.0179 (0.0561) 0.0367 (0.0918) -0.1911*** (0.0487) 0.0320** (0.0157) 175.90*** 39.89 -6.32*** 0.12 1647 8004

0.1250*** (0.0200) -0.1048*** (0.0291) 0.0214*** (0.0051) 1.2366*** (0.3401) 0.1088 (0.2918) -0.0966*** (0.0242) -0.0246 (0.0469) 0.0326 (0.0873) -0.2466*** (0.0718) 0.0101 (0.0215) 184.89*** 38.76 -6.28*** 0.19 1647 8004

1.2389*** (0.3332)

CFi,t

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SALESi,t-1 LEVi,t-1 AGEi,t-1 GOi,t-1 λi,t CONS Wald (χ2) Sargan (χ2) m1(N(0,1)) m2N(0,1)) Companies Observations

-0.1728*** (0.0453) 0.0384*** (0.0122) 174.98*** 38.11 -6.10*** 0.14 1647 8004

-0.2140*** (0.0516) 0.03192** (0.0156) 170.98*** 43.89 -5.67*** 0.34 1647 8004

Notes: 1. standard deviations in parenthesis. 2. *** statistical significance at the 1% level. 3. ** statistical significance at the 5% level. 4. * statistical significance at the 10% level. 5. the estimates include sectoral and time dummy variables, but not shown.

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Table 3. SMEs Investment Determinants - GMM System (1998) Estimator Dependent Variable: Ii,t Independent Variables

II

III

IV

V

0.1718*** (0.0498) -0.1435*** (0.0501) 0.0234*** (0.0065)

0.1559*** (0.0339)

0.1661*** (0.0342)

0.1347*** (0.0289)

0.1614*** (0.0419)

VI

0.1541*** (0.0422) -0.1313*** IRt (0.0401) 0.0191*** GNPt (0.00345) 0.9881*** 1.0289*** 0.9546*** 1.0049*** CFi,t (0.1435) (0.1891) (0.1617) (0.1716) 0.12445* 0.0918 0.0881 0.0954 Salesi,t-1 (0.0637) (0.0907) (0.1415) (0.1569) -0.0932*** -0.1242*** LEVi,t-1 (0.0281) (0.0345) 0.0016 -0.0054 AGEi,t-1 (0.0379) (0.0255) 0.0946* 0.0833 GOi,t-1 (0.0480) (0.0804) -0.1838*** -0.1500*** -0.1311*** -0.1998*** -0.2163*** -0.2001*** λi,t (0.0466) (0.0256) (0.0243) (0.03498) (0.0471) (0.0308) 0.0089 0.0165 0.0271** 0.0118 0.0178 -0.0092 CONS (0.0277) (0.0364) (0.0131) (0.0402) (0.0492) (0.0414) F(N(0,1)) 80.54*** 75.90*** 70.12*** 75.63*** 81.34*** 92.34*** 118.88 112.38 114.19 117.89 120.87 130.38*** Hansen (χ2) -6.04*** -5.66*** -6.44*** -5.17*** -5.81*** -5.55*** m1(N(0,1)) m2N(0,1)) 0.49 0.45 0.67 0.45 0.38 0.38 Companies 1647 1647 1647 1647 1647 1647 Observations 9651 9651 9651 9651 9651 9651 Notes: 1. standard deviations in parenthesis. 2. *** statistical significance at the 1% level. 3. ** statistical significance at the 5% level. 4. * statistical significance at the 10% level. 5. the estimates include sectoral and time dummy variables, but not shown. Ii,t-1

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I

The results of the Sargan test, referring to use of the GMM (1991) dynamic estimator, and the results of the Hansen test, referring to use of the GMM system (1998) dynamic estimator, irrespective of the regression estimated, allow us to conclude we cannot reject the null hypothesis of validity of the instruments used. What is more, whether using the GMM (1991) estimator or the GMM system (1998) estimator, irrespective of the regression estimated, we cannot reject the null hypothesis of absence of second order autocorrelation. Based on the results of the Sargan and Hansen tests, we can consider the empirical evidence obtained with the GMM (1991) and GMM system (1998) dynamic estimators as valid. Whatever the regression estimated and estimator used, from observation of the results presented in Tables 2 and 3, we can state there are no significant alterations in the estimated parameters measuring the relationships between determinants and investment, concerning sign, statistical significance and magnitude of the estimated parameters. This evidence confirms the robustness of the empirical evidence obtained concerning the relationships estimated between determinants and SME investment.

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The empirical evidence presented in Tables 2 and 3 allows us to conclude that: 1) investment in the previous period, GNP and cash flow are determinants stimulating SME investment; 2) rate of interest and debt are factors restricting SME investment; and 3) sales, age and growth opportunities are factors that neither stimulate nor restrict SME investment. Besides the above, it is worth highlighting that, whatever the estimator used and the regression estimated, the relationship between the inverse Mill´s ratio and investment is negative and statistically significant. Based on these relationships identified, we can conclude that inclusion of the inverse Mill´s ratio as an explanatory variable of SME investment is shown to be appropriate for solving possible result bias as a consequence of the survival issue. Given the negative relationships identified between the inverse Mill´s ratio and SME investment, non-inclusion of the inverse Mill´s ratio as an additional explanatory variable of SME investment would lead to overvaluing the estimated parameters measuring relationships between determinants and SME investment.

4. DISCUSSION OF THE RESULTS

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4.1. Analysis of Survival Investment in the previous period contributes to increased probability of survival in SMEs. This result shows that for SMEs the dynamics of investment is very important for remaining in the market. The continuous nature of investment seems to be a way of signalling to the market, and to other economic agents, that the company has sufficient vitality to overcome difficulties in its environment, namely the competition and financial restrictions. Higher interest rates contribute to increased probability of bankruptcy in SMEs. This result is related to the stress borne by SMEs in paying off debt charges, when internal financing is insufficient, to meet investment expenditure. Increased interest rates contribute to increasing the cost of SME capital, increasing the risk of bankruptcy and consequently diminishing the probability of survival in their operating markets (Müeller and Zimmermann (2009). Economic growth contributes positively to the probability of SME survival. At times of economic growth, markets are less restrictive and so enable greater success of SME activity (Fazzari et al., 1988; Fuss and Vermeulen, 2004; Kaufmann and Valderrama, 2008). Cash flow contributes to increased probability of SME survival. Cash flow is a determinant factor, given the considerable restrictions SMEs face when accessing external finance, for SMEs to be subject to less stress in managing their financial resources, so allowing them to invest more efficiently in profitable projects. The importance of cash flow in the sphere of SME activity has been corroborated by various authors, such as Fazzari et al. (1988), Cooley and Quadrini (2001) and Cabral and Mata (2003). Sales are also a determinant factor for greater probability of SME survival. For one thing, greater sales allow SMEs to obtain larger market quotas, increasing their medium-long term sustainability in their operating markets. For another, greater sales volume allows firms to make greater use of internal financing to fund their growth opportunities, becoming less exposed to the restrictions SMEs as a rule are subject to when accessing external finance (Müeller and Zimmermann (2009).

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Debt is shown to be an important variable for promoting the probability of SMEs remaining in their operating markets. According to Baker and Nelson (2005) and George (2005), the possibility of greater efficiency in managing resources, as a consequence of needing to pay off the debt and its charges, seems to be relevant for debt being a determinant factor of SME survival. Age also emerges as an important variable that increases the probability of remaining in the market. According to Hardwick (1997), Fiegenbaum and Karnani (1991), Winter (1994), Goddard et al. (2005), age and size make it more possible to achieve economies of scale and diminish business risk, as a consequence of the possibility to diversify company activities. Müeller and Zimmermann (2009) mention that increased age will mean a greater learning effect, which will be beneficial for increasing SME performance. According to Diamond (1989), the positive relationship between age and remaining in the market could be the consequence of the effect of the reputation conferred by age, allowing firms to obtain credit on more advantageous terms, so diminishing the financial restrictions companies face in financing their activities. Strangely, growth opportunities are not a factor stimulating the probability of SME survival in their operating markets. This may be due to the fact that SMEs do not wish to invest beyond a given size they consider optimal, and consequently they may not take advantage of all the good investment opportunities that present themselves. This empirical evidence seems to corroborate the conclusions of Myers (1977) for companies in general.

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4.2. Investment Determinants We find a positive and statistically significant relationship between investment in the previous period and investment in the current period. We can conclude that SME investment is of a continuous nature over time. As already mentioned, when analyzing survival, the continuous character of investment may be important as a sign of financial robustness to the market and creditors, which may contribute to diminishing the information asymmetry in the relationships owners/managers establish with creditors, something which is normally a considerable obstacle for SMEs in accessing external finance. The interest rate, as a capital cost, is shown to be statistically significant in explaining SME investment. Higher interest rates contribute to reduced investment. These results corroborate Neoclassic theory that factors outside the company, such as the cost of capital, determine investment behaviour. Additionally, these results corroborate the studies by Bernanke and Gertler (1995) and Gilchrist et al. (2006) which identify that higher interest rates correspond to reduced investment by companies. GNP, as a measure of economic growth, was shown to be statistically significant in explaining SME investment. In periods of economic growth, SMEs increase investment, reducing investment in periods of recession. At times of economic growth, SMEs will find access to credit easier, at the same time as they will also have higher levels of cash flow since servicing the debt should cost less due to the less restrictive behaviour of the financial markets. At times of economic recession, SMEs reduce their levels of investment due to the recessive behaviour of the market itself. This empirical evidence corroborates the empirical evidence obtained by Kaufmann and Valderrama (2008).

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We identify a positive and statistically significant relationship between cash flow and investment. This empirical evidence allows us to consider that internal finance is particularly relevant in the dynamics of company investment, corroborating the empirical evidence obtained by Fazzari et al. (1988) and Fazzari and Peterson (1993). It is also important to mention that the importance of cash flow for investment by smaller companies is in agreement with the studie by Gertler and Gilchrist (1994), which show the relevance of the cash flow variable as a determinant of investment by smaller firms, since these are the firms most likely to suffer from problems of financial restrictions in recourse to debt, which leads them to turn to cash flow to finance their investments. The relationship between sales and investment is not statistically significant. This empirical evidence does not corroborate the arguments of Hall and Jorgenson (1967), that variables outside the company, such as sales, are relevant in explaining company investment. Taking large firms as the subject of analysis, Jorgenson (1971), Chirinko (1993), Lang et al. (1996) and Aivazian et al. (2005) identify a positive and statistically significant relationship between sales and investment. The fact of this study not identifying an identical relationship between sales and investment reveals that sales are of greater importance in explaining investment by large firms, than they are in the case of SME investment. In other words, the empirical evidence obtained in this study shows that sales are of less importance in explaining investment when companies are smaller. We find a negative and statistically significant relationship between debt and SME investment. These results corroborate the conclusions of Myers (1977), Jensen (1986), Stulz (1990), McConnell and Servaes (1995), Ahn et al. (2006), Firth et al. (2008) and Lee and Ratti (2008), that we can expect a negative relationship between debt and investment, as a consequence of the possible relevance of problems of information asymmetry in relationships formed between company owners/managers and creditors. These problems can be particularly relevant in the case of SMEs, given that their smaller size, and consequently greater risk in their business and of bankruptcy, can lead creditors to impose particularly severe terms of credit, increasing these firms’ stress in managing their financial resources, which may mean diminished investment. Besides what has been said, just as Jensen and Meckling (1976), Jensen (1986) and Stulz (1990) conclude, debt can also serve as a mechanism whereby owners discipline managers’ actions, so that managers do not make firms grow beyond the optimal size desired. However, since in the great majority of SMEs ownership and management are concentrated in the same individuals, this problem is of limited relevance in the case of SMEs. Age is neither a positive nor restrictive factor of SME investment. Various studies (Yasuda, 2005; Honjo and Harada, 2006, Lotti et al., 2010) conclude that the youngest SMEs grow more than the oldest SMEs. Greater SME growth will be associated with a higher level of investment. Nevertheless, as Diamond (1989) concludes, SMEs at later stages of their lifecycle are firstly more able to retain profits over time, and secondly have a greater reputation conferred by age. These factors may be preponderant for SMEs increasing investment at later stages of their life-cycle. In this study, the empirical evidence does not let us conclude that the youngest SMEs invest more as a consequence of their greater need to grow or, on the contrary, that they invest more when they are older, as a consequence of retaining profits over time and greater ability to contract credit due to their greater reputation with creditors. The statistically insignificant relationship between age and SME investment appears to indicate that these two contrary effects may cancel each other out.

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Finally, we find a statistically insignificant relationship between growth opportunities and SME investment. These results corroborate the conclusions of Carpenter and Guariglia (2008), the authors stating that large firms increase investment as a function of good growth opportunities, compared to what happens in smaller firms. Besides, SMEs may be particularly sensitive to the fact of not wanting to increase their size beyond the optimal level desired, not necessarily increasing investment as a function of good growth opportunities. This empirical evidence seems to corroborate the conclusions of Myers (1977), since the author concludes that firms in general may not be willing to increase investment as a function of good investment opportunities, so that the value of firms does not decrease in the future.

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5. CONCLUSION AND IMPLICATIONS In this study, considering a sample of 1845 Portuguese SMEs, using the two-step estimation method, we examine whether the economic conjuncture is a determinant of SME investment. The empirical evidence obtained lets us conclude that the economic conjuncture, namely interest rates for investors and economic growth, in this study measured by GNP, is a determinant of Portuguese SME investment. Firstly, we identify a negative relationship between interest rates for investors and SME investment. In addition, we find that higher rates of interest for investors contribute to diminished probability of SME survival. Due to their smaller size, SMEs are more exposed to the risk of bankruptcy, with the consequently greater relevance of the information asymmetry in relationships formed between SME owners/managers and creditors. That greater information asymmetry may lead creditors to hinder SME access to credit, namely through higher interest rates. Payment of higher debt charges by SMEs may mean greater stress in managing their financial resources, contributing to a reduction in their levels of investment. Secondly, economic growth may show itself to be an important factor for increased SME investment, contributing to lessening the restrictive effects of the cost of credit. We also find that economic growth contributes to a greater probability of SME survival. Indeed, the empirical evidence obtained in this study lets us conclude that in periods of economic expansion, SMEs increase their levels of investment, the probability of surviving in their markets also increasing. However, in periods of recession, besides SMEs reducing their levels of investment, the probability of them surviving in their markets also diminishes. The empirical evidence obtained in this study lets us conclude that economic cycles may be particularly relevant in explaining SME investment. Of the remaining empirical evidence, we highlight three important results: 1) cash flow as a stimulating determinant of SME investment; and 2) debt as a restrictive determinant of SME investment. The fact that cash flow is particularly important in explaining SME investment shows they can be particularly dependent on internal financing to finance their investments. This may happen due to the particular difficulty SMEs have in accessing external finance, because of their smaller size and consequently greater likelihood of bankruptcy, which may lead creditors to hinder access to credit by SMEs. The importance of internal financing for SME activity is also supported by the relevance of cash flow for increasing their probability of survival.

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The need for efficiency in managing debt, as a consequence of the particularly adverse terms SMEs face when accessing external finance, may explain the fact that SMEs with higher levels of debt reduce investment. The considerable stress SMEs may be subject to in paying off the debt and its charges may be determinant in less finance being available to fund investment. Nevertheless, we find that debt is a relevant factor for increased probability of SME survival, possibly as a consequence of SMEs’ need to turn to external financing, when internal finance is insufficient, to fund the multiple investment opportunities that arise. SMEs in Portugal, as in most European countries, have a vital role in stimulating employment and economic growth. However, Portugal is currently experiencing a particularly adverse economic situation, with the likelihood of economic recession, increased unemployment and a considerable increase in company bankruptcy, mainly SMEs. What is more, almost no Portuguese SMEs have access to the capital market, and the tradition of accessing risk capital is practically nil. Therefore, when internal finance is insufficient, debt is the first source of finance. The multiple empirical evidence obtained in this study shows that for one thing, SMEs are quite vulnerable to the economic conjuncture, namely to fluctuations of interest rates for investors and economic growth, and for another, we find they are dependent on internal financing and may have particular difficulty in accessing external finance. We suggest that government bodies support Portuguese SMEs through the creation of particularly beneficial lines of credit, in situations where companies clearly have considerable potential but are restricted financially from taking advantage of the multiple investment opportunities that arise. In addition, at a time when the Portuguese government is increasing the tax burden for companies and consumers, aiming to reduce the considerable deficit in the country’s public accounts, we suggest it alleviates, as far as possible, the tax burden for SMEs that have potential for growth and survival but find themselves restricted financially.

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Blundell, M. and Bond, S. (1998), “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models, Journal of Econometrics, 87, pp. 115-143. Brown, J., Fazzari, S. and Petersen, B. (2009), Financing Innovation and Growth: Cash Flow, External Equity and the 1990s R&D Boom, Journal of Finance, Forthcoming. Cabral, L. and Mata, J., (2003), On the Evolution of the Firm Size Distribution: Facts and Theory, American Economic Review, 93, pp. 1075-1090. Carpenter, R. and Guariglia, A. (2008), Cash Flow, Investment and Investment Opportunities: New Tests Using UK Panel Data, Journal of Banking and Finance, 32, pp. 1894-1906. Chirinko, R. (1993), Business Fixed Investment Spending: Modelling Strategies, Empirical Results and Policy Implications, Journal of Economics Literature, 31, pp. 1875-1911. Cooley T. and Quadrini V. (2001), Financial Markets and Firm Dynamics, American Economic Review, 91, pp. 1286-1310. Diamond, D. (1989), Reputation Acquisition in Debt Markets, Journal of Political Economy, 97, pp. 828-862. Fazzari, S., Hubbard, R. and Peterson B. (1988), Financing Constraints and Corporate Investment, Brookings Papers on Economics Activity, 1, pp. 141-195. Fazzari, S. and Peterson, B. (1993), Working Capital and Fixed Investment: New Evidence on Financing Constraints, Rand Journal of Economics, 24, pp. 328-342. Fiegenbaum, A. and Karnani, A. (1991); Output Flexibility - A Competitive Advantage for Small Firms, Strategic Managerial Journal, 12, pp. 101-114. Firth, M., Chen, L. and Wong, S. (2008), Leverage and Investment Under a State-Owned Bank Lending Environment: Evidence from China, Journal of Corporate Finance, 14, pp. 642-653. Fuss C. and Vermeulen P. (2004), Firm´s Investment Decisions in response to Demand and Price Uncertainnty, Working Paper Series, European Central Bank 37. George, G. (2005), Slack Resources and the Performance of Privately Held Firms. Academy of Management Journal, 48, pp. 661-676. Gertler M. and Gilchrist S. (1994), Monetary Policy, Business Cycles and the Behaviour of Small Manufacturing Firms, Quarterly Journal of economics, 109, pp. 309-340. Gilchrist S., Natalucci F. and Zakrajsek E. (2006), Interest Rates and Investment Redux, NBER. Goddard, J., Tavakoli, M. and Wilson, J. (2005), Determinants of Profitability in European Manufacturing and Services: Evidence From a Dynamic Panel Data, Applied Financial Economics, 15, pp. 1269-1282. Hall, R. and Jorgenson D. (1967), Tax Policy and Investment Behaviour, American Economic Review, 58, pp. 391-414. Hardwick, P. (1997), Measuring Cost Inefficiency in the UK Life Insurance Industry, Applied Financial Economics, 7, pp. 37-44. Heckman, J. (1979), Sample Selection Bias as a Specification Error, Econometrica, 47, pp. 153 – 161. Honjo, Y. and Harada, N. (2006), SME Policy, Financial Structure and Firm Growth: Evidence From Japan, Small Business Economics, 27, pp. 289-300. Jensen, M. and Meckling, W. (1976), Theory of the Firm: Managerial Behaviour, Agency Costs and Ownership Structure, Journal of Financial Economics, 3, pp. 305-360. Jensen, M. (1986), Agency Costs of Free Cash-Flow, Corporate Finance and Takeovers, American Economic Review, 76, pp. 323-329.

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Jorgenson, D. (1971), Econometric Studies of Investment Behaviour: a Survey, Journal of Economics Literature, 9, pp. 1111-1146. Kaufmann S. and Valderrama, T. (2008), Bank Lending in Germany and the UK: Are There Differences Between a Bank-Based and a Market-Based Country?, International Journal of Finance and Economics; 13, pp. 266-279. Lang, L., Ofek, E. and Stulz R. (1996), Leverage, Investment, and Firm Growth, Journal of Financial Economics, 40, pp. 3-30. Lee S. and Ratti, R. (2008), Bank Concentration and Financial Constraints on Firm-Level in Europe; Department of Economics, University of Missouri, Columbia. Lotti, F., Santarelli, E. and Vivarelli, M. (2009), Defending Gibrat`s Law as a Long – Run Regularity, Small Business Economics, 32, pp. 31-44. McConnell, J. and Servaes, H. (1995), Equity Ownership and the Two Faces of Debt, Journal of Financial Economics, 39, pp. 131-157. Moyen N. (2004), Investment Cash-Flow Sensitivities: Constrained Versus Unconstrained Firms, Journal of Finance, 69, pp. 2061-2092. Müller, E. and Zimmermann, V. (2009), The Importance of Equity Finance for R&D Activity, Small Business Economics, 33, pp. 303-318. Myers, S. (1977), The Determinants of Corporate Borrowing, Journal of Financial Economics, 5, pp. 147-176. Oliner, S. and Rudebusch, G. (1996), Monetary Policy and Credit Conditions: Evidence From the Composition of External Finance: Comment, American Economic Review, 86, pp. 300–309. Stulz, R. (1990), Managerial Discretion and Optimal Financial Policies, Journal of Financial Economics, 26, pp. 3-27. Winter, R. (1994), The Dynamics of Competitive Insurance Markets; Journal of Financial Intermediation, 3, pp. 379-415 Yasuda, T. (2005), Firm Growth, Size, Age and Behaviour in Japanese Manufacturing, Small Business Economics, 24, pp. 1-15.

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Chapter 7

THE CONVERGENCE HYPOTHESIS OF ECONOMIC GROWTH DISPLAYED IN ADVANCED ECONOMIES Sahar Bahmani Georgia Southern University, Statesboro, Georgia, USA

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ABSTRACT Positive economic growth is a major goal for all countries and long-run economic growth is an important focus, rather than observing what is happening in the short-run because ups and downs in business cycles and other short-run fluctuations in economic growth are unable to give an accurate picture of the overall performance of an economy and may lead to biased observations. When countries experience growth at small rates, though this may not be regarded as a significant improvement, it is essential to understand that it is thanks to these small changes that accumulate over time to eventually having a very large impact on an economy’s performance, helping them to become more and more developed. No matter how small the changes, each improvement should be regarded as helping any economy in the right direction. Investment, economic resources of capital, land and labor and technological progress are argued to be vital essentials when it comes to the economic growth of a country because they are highly needed, which will be discussed extensively in this chapter. We will also look at five positive advantages that come along with economic growth for a country. First, income inequality, the gap between the rich and poor, decreases, secondly, economic growth has helped to significantly decrease the amount of global poverty that persists, third, economic growth is linked to the improvement in the quality of life of the citizens in an economy, fourth, economic growth leads to further specialization and exchange, and finally, economic growth improves the global position of a country. We will look at how the four Asian tigers and five new Euro countries, the nine countries to be analyzed with their respective data in this chapter, have moved from being considered developing economies to now being included in the category of advanced economies, which is regarded as the ultimate goal being achieved for any country that started off as a less developed economy. These countries once suffered from very little economic activity and industrialization, high population growth was a major obstacle to hurdle over, and low levels of standard of living, but went on to becoming proof of the convergence hypothesis, which states that the GDP growth rates of less developed countries will rise faster than richer countries,

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Sahar Bahmani tightening the gap between the two categories of countries due to the catching-up process, leading to their convergence. Merging and the idea of catching-up are both to be expected because the poorer countries can copy and incorporate the methods and techniques used by the rich countries and also because when you are already an industrialized country, you cannot grow too rapidly as was once the case before, since diminishing returns can be ever so present. Initially, industrialized countries may have grown at rapid rates but eventually, that rate slows down due to diminishing returns. In this chapter, by using data from these nine countries, it is shown that small rates of growth over time contributed to helping them transition from being developing countries to advanced countries, proving that the convergence hypothesis is valid.

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I. INTRODUCTION Positive economic growth is a major goal for numerous countries, promising a better standard of living and more opportunities, higher levels of employment, lower poverty rates, more productivity, efficiency and success. Negative growth signifies a shrinking economy which is accompanied by troubled times ahead with high unemployment rates, recessionary times, and inflation. Long-run economic growth is an important focus for countries because they do not want to go with the simple observations of the recurring ups and downs of business cycles, which are the short-run fluctuations in economic growth that are unable to give an accurate picture of the overall performance of an economy. While countries may only grow at small rates, it is essential to understand that it is with these small changes that over time accumulate to eventually having a very large impact on a country’s economic performance. It is a well known fact that the smallest of growth rates can contribute to having positive impacts on an economy. When an economy finds itself developing further and further, it becomes more efficient and productive. Economic growth is a top priority for every country as is achieving long-run economic development. The overall direction that an economy finds itself moving towards is a result of how efficiently it is utilizing its resources, and if it is fully employing all of its resources. An increase in all resources, land, labor, capital, as well as an increase in technology, trade, and research and development are all driving forces behind economic growth. In introductory economic courses, the production possibilities curve, a concave curve that shows various different combinations of goods and services that an economy is currently capable of producing with its current amount of resources and technology, shifts outward to the right when economic growth occurs since it is the only way in which an economy can produce more over time. Solow (1956) showed that the rate at which GDP grows in an economy is negatively related to the starting level of output, meaning that if a country starts off initially with a low level of output, their GDP growth rate will be high. Solow’s discovery contributed to the extensive literature on neoclassical growth models, which argue that it is poor economies that grow at a far faster rate than rich ones and that they are successfully able to catch-up to rich countries because of the convergence in GDP growth rates and income over time. Originally, these ideas were regarded as being absurd because many did not believe that GDP growth rates are inversely related to the initial level of output a country has, rather they insisted that GDP growth rates should be higher when an economy is starting out with a higher level of output. Mankiw, Romer and Weil (1992) focused on the determinants of growth and convergence in standards of living by developing a model that concluded that countries do in

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fact converge at the rate that the augmented Solow (1956) model identifies, indicating the validity and empirical proof of the Solow model. Based on a regression of economic growth on the initial productivity level from 1870 to 1979 for sixteen industrialized countries, Baumol (1986) proves there was a high amount of convergence between all of the sixteen industrial nations because they were all economies that shared common characteristics, such as having similar property rights and government policies, rules and regulations. Barro and Sala-i-Martin (1991) also conclude with findings that support Solow’s argument of an indirect relationship between GDP growth rates and initial levels of output, justifying the validity of neoclassical growth models by showing that poor countries do indeed grow faster than the rich economies. Exogenous growth models are part of the literature on the neoclassical theories of growth. Solow and Swan (1956) looked at how technology and new forms of capital help the advancement of economic growth, placing importance on the amount of resources and how the growth rate of resources is essential when the population is growing and an economy is trying to maintain high GDP growth rates. We are now able to turn to why resources are so important when it comes to economic growth, focusing on how they are determinants of economic development and stability. Resources need to increase and grow over time in order for economic growth to take place.

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II. DETERMINANTS OF ECONOMIC GROWTH The rate of economic growth that an economy is able to attain depends on many factors that play a vital role and without these, economic growth would be impossible to achieve. These factors also need to be maintained for long-run economic growth as well. Investment, inputs of land, capital and labor and technological progress are argued to be vital essentials when it comes to the economic growth of a country. The influence that natural resources, raw materials, human resources and capital resources have on economic growth are immense. Human capital, being the vital source that it is for economic growth because it increases individual productivity, thereby increasing the productivity of the nation as a whole, not only includes education and acquiring skills. Human capital also contributes to the improvement of healthcare and advancements in medicine, and both contribute to increasing mortality rates, which is certainly needed in order to protect human capital and assure that it is a resource that continues to grow. Less developed countries find themselves struggling because their education is lacking and not adequate and therefore, its people suffer from not having acquired the right amount of skills and knowledge and they also suffer from not having the same opportunities and access to education that other nations offer their people. Capital, the physical aids that help the production process along, is an important determinant of economic growth because the more factories, tools, machinery, and equipment that a country has, the more well-off it is because it is able to produce more goods and services. Technological advancements are one of the most important factors when it comes to economic growth because it contributes to labor productivity, innovation, inventions, and research and development and these all contribute to a better standard of living. Land is another resource that can grow, perhaps not the amount of land that a country has but instead, the productive manner in which they use that land. For example, land that is being utilized to build a new shopping district, land which was not being used before, contributes to an increase in land

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because you are activating a certain region that was not contributing to the economy and now it is becoming a market where buyers and sellers meet and economic activity occurs and this contributes to the growth of the economy. When there are more people in the labor force, this also increases economic growth. Some examples of an increase in labor are people deciding to retire late, teens deciding to get jobs earlier and more students working part or full-time. It is also important to note that economic growth, in turn, increases employment in an economy. All in all, the increase in land, labor, capital and technology are the main ways in which an economy can transition itself toward becoming more and more efficient, productive and successful, which is in every economy’s best interest. The structure of institutions and governmental structure, as well as the stability of both are important variables involved in the rate of economic growth that a country goes through, playing a big role in which direction the economy is moving toward. Institutional structure is extremely important because increasing rates of economic development depends on having governments that are working toward the greater good of the economy and that are not corrupt and an economy is also in need of efficient institutions. Studies report that efficient and corrupt-free governments have led to the reduction of poverty, helping economic development and serving as a key determinant of economic development. Of course, governments that have a high volume of corruption almost always lead to an economy that is in turmoil and struggling to be stable. The level of world economic activity that takes place between countries and the level of openness to trading between countries are two other factors that play an influential role in how much economic growth a country experiences, hence the reason why it is important for all countries to participate and be part of the international community rather than isolating themselves and becoming closed economies. When a country decides to become closed off to trade and isolates itself from the international community, they are not only hurting their own economy but they are putting their own people at risk and sabotaging their economic growth rate. The degree to which an economy allows trading to occur with other economies, known as the degree of trade openness, has a major impact on that particular economy’s efficiency and productivity, as well as its rate of economic growth. The more open an economy is, the more growth it can experience. Theoretical growth literature shows that the trade policies that an economy decides to put into place, impacts its rate of growth, indicating that countries should be very careful when picking trade policies, recognizing that the more open they are, the more doors and opportunities they are opening up for their own economy and their own people. Trade theory confirms that the main advantage from a country deciding to be more open to trade, though there are many gains from trade, is that it increases global competitiveness and improves a country’s global position, contributing to economic growth. Bahmani (2010) discovered that a country that trades more with other countries is said to become relatively more open and this has a significant and positive relation with the adjustment speed of macro variables back to their equilibrium, regardless of which measure of openness is used. There are three measures of openness used by previous research and throughout the literature. The first is defined as the ratio of nominal imports (M) to nominal GDP, or M/GDP. The second is defined as the ratio of nominal exports (X) to nominal GDP, or X/GDP. Finally, the third measure is defined as the summation of both imports and exports to nominal GDP, or (M+X)/GDP. Harrison (1996) established a strong and positive relationship between openness and economic growth, using the openness measure as exports plus imports divided by GDP. It is important to note that economies with a higher amount of

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exports plus imports divided by GDP will grow faster than other economies, showing countries that the best type of trade policy to adopt is one that is more open to trading with others and that becoming closed off and isolating your economy will only lead to problems. Yanikkaya (2003) and literature focused on new growth theory, argue that because progress in research and development is the newest driving force behind growth, more countries should work on increasing the amount of research and development that they are engaging in. New growth theory argues that the more trading between countries helps them to have more access to different technological advancements from other countries that it trades with, meaning that they can share the knowledge, helping advancement to take place. Developing countries have access to developed countries when trading occurs, just as developed countries have access to less developed countries when they are trading, which is highly beneficial because they can deal with far larger markets. Due to more innovation, increasing activity and the sharing of knowledge between countries, research and development is further advanced. Trade openness increases both the amount of foreign direct investment and trade between nations, contributing to the development of economies. Closed economies that are not open to trade put a stop to accessing other markets and it also stops support of their own market by other countries, furthering isolating themselves. Barriers to trade hinder the economic growth of an economy. New growth theory insures that trading helps all countries to be better off, increasing the amount of accessibility to different markets, which helps to learn about new methods and improves research and development. The theory of comparative advantage points out the benefits of gaining economic productivity and growth when countries behave efficiently by exporting goods and services that they are relatively efficient at producing and by importing those goods and services that are too costly, in terms of time and resources, for themselves to produce, which increases each country’s utility and efficiency. Hence the reason why countries emphasize the importance of specialization both on a microeconomic level, with specific majors students must chose or specified tasks and duties given to you at your position in a place of employment, all the way to the macroeconomic level, where we see that some countries have a comparative advantage in the production of oil and that is why they are the lead exporters of that good. Therefore, the volume of imports and exports play a big role on both economic performance and growth and knowing which goods and services you are most efficient at producing helps the productivity rate rise. Mayer and Wood (2000) prove that the theory of comparative advantage holds true with a broad cross-section of countries, pointing out that the differences in what different countries decide they should be exporting are due to the differences in the supply and amount of human capital and education, capital, land, labor and technology. Not every country can be the most efficient at producing everything and that is where trading comes into the picture and for those countries that are closed to trading with other countries, it makes production very challenging on their economy and inefficient as well. Just like on a microeconomic level, people major in one field and are good at just a small handful of things, most people are not efficient at making their own clothes, do their own taxes, cooking, and servicing their car, for example. The reason why is because of specialization and the law of comparative advantage, which simply states that if it is going to take you many days to do your own taxes and you still make mistakes or if it takes you the whole day to make a meal and it still tastes bad, then this indicates that you do not have a comparative advantage in these activities and that it would be more efficient in terms of time and resources for you to pay someone else to do your taxes and you should eat out and use the

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time you just saved toward the activity that you are actually good at doing. The literature on comparative advantage is unanimous in concluding that it does promote economic prosperity and growth, therefore, for those countries that close themselves off from trade, they are signing themselves up for becoming inefficient and suffering from an economic slowdown.

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III. ADVANTAGES OF ECONOMIC GROWTH Let us now focus on the positive advantages that come along with economic growth for a country. First, income inequality, the gap between the rich and poor, decreases. A widening of the gap between the income levels of these two categories of people does not help economic growth to be attained or sustained. Kuznets (1955) found that income inequality can either rise or fall depending on a country’s pattern of economic growth. Using data from the United States, England, and Germany, it was shown that annual income has been moving toward equality since the 1920s, therefore the gap has not been widening but has been diminishing, which is an advantage of economic growth. These now developed countries that were used in the study have also experienced significant increases in aggregate income, which usually goes hand in hand with economic growth. Income inequality means that the income in an economy is not evenly distributed, causing problems such as crime and social unrest. It has been shown throughout the literature that the more income inequality that exists in an economy, the slower that economy will be able to grow and prosper. The wider the gap grows between the rich and the poor in a particular country will actually hurt its potential to grow because resources and income are not distributed evenly. Secondly, economic growth has helped to dramatically decrease the amount of global poverty in the world, which is another major goal because poverty has a negative impact on the global situation, both on a macroeconomic level and on a microeconomic level as well. When economic growth spreads, it has been shown by the experiences of many countries, data and the literature that global poverty falls. Economic growth reduces poverty not only through stimulating aggregate demand, government spending, foreign investment, and private investment, but also through high levels of public spending, both of which are excellent methods to combat poverty. Innumerable studies all point to the fact that both in the past and in the present, it is unanimous, poverty decreases when there is economic growth. When an economy experiences an increase in any economic resource, such as land, labor, capital or technology, Krugman and Wells (2009) discover that, “The rise in the level of production makes more wealth available for those people who were otherwise too poor to afford them.” The welfare of an economy and the state in which it is performing in is negatively impacted by its poverty rate and the overall welfare of an economy is sacrificed when poverty rises. By promoting economic growth, this reduces poverty which increases economic opportunity, improving the economic outlook. Eliminating poverty helps an economy gain more stability and independence, which helps to secure its future. Poverty can negatively hurt an economy even though there may be many people who do not fall below the poverty line, the economy is still hurt by it immensely. Since economic growth leads to poverty reduction through different processes, it is important to focus on each of them. Throughout the economic development research, the literature links three variables, which are economic growth, poverty and income inequality. Kuznets (1955) discovered the famous and useful Kuznets inverted U curve when

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studying a time series of inequality measurements, much like the Gini coefficient used to measure income inequality, for the cases of the U.S., Germany and England. The inverted U curve exists between two variables that are plotted, which are growth and income inequality, and the inverted U takes form because in the starting stages when a country is in the initial stages of development and economic growth, income inequality rises and over time as there is more economic growth as the years pass, income inequality falls. In order to explain this behavior, Lewis (1954) justified this occurrence by pointing out that the main explanation behind why the relationship between growth and income inequality when plotted behaves in an inverted U curve is because labor is being transferred from low productivity sectors to high productivity sectors and therefore, labor is moving from sectors where there is low inequality to high inequality sectors. Lewis (1954) made this discovery and throughout the literature, it is agreed upon that this is the main reason that justifies why the plotted relationship of growth and income inequality behaves in this manner. The more economic growth that an economy experiences, the more capital it accumulates, which is a vital economic resource. The reason behind this is because the more growth there is, the more investment takes place, and more capital comes into the picture, leading to even further investment, and the cyclical flow continues onward. The rise in accumulated capital increases the wealth and investment of both categories of people, both the rich and poor, which causes more investment to take place and this all leads to more accumulation of capital. All economists agree on the fact that economic growth reduces poverty. They do, however, have different views and opinions when it comes to the rate of economic growth that is or can contribute to the decline in poverty, posing the important issue of how much economic growth needs to take place, in order to reduce poverty by 10 percent, or to possibly cut it in half, for example, in a particular country. Innumerable empirical studies, that focus on both individual countries as well as cross-country cases, prove that economic growth reduces poverty rates and the data all support the indirect relationship between growth and poverty. Let us now focus on these studies. Ravillion and Chen (1997) look at economies that are in transition in Eastern Europe and Central Asia. The authors confirm that economic growth that helped these countries become more developed also reduced poverty rates in these very same countries, establishing proof that economic growth reduces poverty rates. Decreasing poverty rates in less developed countries is not an easy task. The literature states that to cut the percentage of people living in poverty, less developed countries must strive for higher economic growth rates. Increasing openness to trade helps to sharply decrease poverty rates, as does improving technology, capital and infrastructure. Infrastructure contributes to economic growth because it helps that economy develop because of the investment put towards roads, railways, highways, ports and telephones that contribute to the development of a society. The literature also cites infrastructure as one of the important stepping stones for an economy on the road to becoming more industrialized, because it is important to maintain good communication and transportation networks. Many less developed countries find themselves lacking these items, slowing down their growth potential. Third, economic growth improves the quality of life because when a country is able to successfully grow, the people of that country are able to enjoy a better life, hence the reason behind the constant pursuit for innovation, increasing international trading, research and development, along with advancements in technology. Increases in the rate of output growth helps to improve the welfare of the economy and the standard of living that the people face. Economic growth directly causes an improved standard of living because when a country is producing more, its people consume more goods and services, and businesses do better

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because of the heightened amount of investment, and this keeps employment levels high. Economic growth contributes to how much more better off people are in that economy currently, compared to decades ago. When an economy is well off and has a good education system and the government creates jobs for these skilled workers, the findings of Bradburn (1969), Wilson (1967) and Davis (1965) show that happiness and an economy’s standard of living are directly related to economic growth. Standard of living is a very important indicator of how industrialized an economy is. Economic growth is important because it helps countries to have more access to technology, education, investment, economic resources, and goods and services. Each country strives for a better standard of living as the years pass because people expect better for the future generations, a better life than the one they had, and they expect people to live longer, have access to more opportunities, better education, and medicine. Fourth, economic growth leads to even further specialization and exchange. Earlier, it was stated that the law of comparative advantage, specialization and exchange cause economic growth, and economic growth causes even further exchange. Lastly, economic growth improves the global position of a country when it comes to the international market, which can help their economy to grow even further, for their currency to be strong, and for their country to do more trading with other countries.

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IV. THE CONVERGENCE HYPOTHESIS AS DISPLAYED BY DEVELOPING COUNTRIES BECOMING ADVANCED ECONOMIES Let us now focus on how the four Asian tigers and five new Euro countries, that make up the nine countries to be analyzed with their respective data, have moved from being considered developing economies to now being categorized as advanced economies. The four Asian tigers are Hong Kong, Singapore, South Korea and Taiwan while the five Euro countries that have also graduated from being developing countries to advanced economies are Cyprus, Slovenia, Malta, Czech Republic and Slovakia. These countries once suffered from very little industrialization, high population growth, poor education systems and low levels of standard of living. These countries are proof of the convergence hypothesis, which states that the per capita incomes of poorer countries will rise at faster rates than those of industrialized countries. Since the rate of income is rising for the poor economies, this narrows the gap between the two countries due to the catching-up process, leading to their convergence. Convergence is to be expected because the poorer countries can copy the methods and techniques used by the rich countries and because the economy of an industrialized country will not be able to grow at the rates that it once did because of diminishing returns. There are requirements that an economy must meet before catching-up to industrialized countries can take place, or else all poor countries would become industrialized, which is certainly not the case. Abramovitz (1986) stated that a prerequisite that an economy needed to have met in order for catch-up growth to occur is having social capabilities, which refers to the ease at which an economy is able to accumulate new technology. Economies need to strive to be active members in the global market by participating regularly, trading frequently and accumulating more investment and capital. The small rates of growth over time for these nine countries contributed to helping them improve their position in the international market, thereby proving the convergence hypothesis to be valid.

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The four Asian A tigers and a five new Euro countriees transitionedd from being developing ecconomies to advanced a econnomies thanks to fully emplooying all of thheir resources,, increasing teechnology and d innovation, trading moree and experieencing an incrrease in theirr economic reesources. Decrreasing their population p grrowth, improvving their educational systems and an inncrease in inveestment also played p very im mportant roles as well. Decreeasing populattion growth raates helps with h population coontrol and prevventing overcrrowding and thhe problem off not having ennough resourcces for all. Thhe improvemennt of the educcation system insures people with the skkills needed to o place them with a job but also helps the economyy as a whole by b keeping unnemployment rates low andd increasing thhe amount of research r and development, d inventions, annd innovation.. All nine of thhe countries were w able to suuccessfully inccrease their GDP G growth raates for many years y and the small changess in their GDP growth rates accumulated a innto helping thhem graduate from f being devveloping counttries into grow wing into advannced economiees, which is a very importan nt accomplishm ment that not all a countries aree able to achieeve.

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* The GDP grow wth rate data was retrieved from m the Internationnal Monetary Fuund’s Internationnal Financial Statistics.

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V. CONCLUSIO ON t be less developed, d devveloping or It is in thee best interest of all countriies, whether they hiighly industriaalized, to achiieve positive economic groowth because the alternativve, negative grrowth, signifiees a shrinkingg economy annd slows downn growth poteential. Attaininng positive ecconomic grow wth comes withh many advanntages for any country, advaantages that arre ideal for im mproving an economy’s e futture. Five maajor advantagees come with economic grrowth for a coountry. First, income i inequaality, the gap between the rich r and poor, decreases andd secondly, ecconomic grow wth has helped to dramaticallly decrease the amount of global g poverty that exists. Third, economiic growth improves quality of life and fouurth, economicc growth leads to further a exchange. Lastly, econnomic growth strengthens the t global poosition of a sppecialization and coountry in the international market. Longg-run econom mic growth is an importantt focus for coountries ratherr than monitoriing the short-rrun fluctuationns, which are unable u to give an accurate poortrayal of how w well or how w poorly an ecconomy is perfforming. Increeases in annual growth of agggregate incom me accumulatte over time, eventually having h a largee impact on a country’s ecconomic perfo ormance. Inveestment, inputts of economiic resources, such as land,, labor and caapital, and tech hnological proogress are vitall essentials whhen it comes too the economicc growth of a country. The four Asian tigers t and fivee new Euro countries, c once considered developing ecconomies, butt now are cateegorized as addvanced econoomies because their GDP grrowth rates haave risen stead dily throughouut the past deccades. The small increases inn aggregate inncome each yeear accumulateed over the deccades, helpingg these econom mies succeed. Even thoug gh these counttries suffered in the past froom low levelss of economicc resources, inndustrialization n, and standaard of livingg as well as very poor education e systtems, high poopulation gro owth, poor innfrastructure and governaance, they suupport the coonvergence hyypothesis, which states thatt the GDP grow wth rates of reelatively poor countries willl rise faster thhan those of richer countrries, thereby diminishing d t gap betweeen the two due to the the caatching-up pro ocess, which leads to merrging. Converrgence is to be b expected because b the

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poorer countries can copy the methods used by the rich countries and because industrialized countries cannot grow as much as they once did because of diminishing returns. In the case of these nine countries, it is shown that their small rates of growth over time contributed to helping them transition from being developing countries to advanced economies, thereby proving the convergence hypothesis to be valid. Clearly, an economy trying to transition from being a less developed country to becoming an advanced economy, is aware that this transition does not happen overnight but with careful planning and effort, it can happen over much time passing, which is still a wonderful achievement for any country and a definite goal for all less developed countries. Since economic growth assists a country with having a positive economic outlook and future, because it reduces income inequality and poverty, improving the quality of life, many countries are putting forth a great deal of effort toward moving from being a third-world country or a less developed country to becoming a developed or advanced country, or even a highly industrialized nation.

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REFERENCES Abramovitz, M. (1986), “Catching Up, Forging Ahead, and Falling Behind,” Journal of Economic History. Bahmani, S. (2010), “Openness and the Speed of Adjustment,” Journal of Economics and Finance 34(2), 218-227. Barro, R. J. and X. Sala-i-Martin (1991), “Convergence Across States and Regions,” Brookings Papers on Economic Activity no. 1, 107-182. Baumol, W. (1986), “Productivity, Growth, Convergence and Welfare: What the Long-Run Data Show,” American Economic Review 76(5), 1872-1085. Bradburn, N.M. (1969), “The structure of psychological well-being,” Chicago, Illinois: Aldine. Davis, J.A. (1965), “Education for positive mental health,” Chicago, Illinois: Aldine. Harrison, A. (1996), “Openness and growth: a time series, cross-country analysis for developing countries,” Journal of Development Economics 48, 419– 447. Krugman, P. and R. Wells (2009), Macroeconomics. 2. New York City: Worth Publishers. Kuznets, S. (March 1955), “Economic Growth and Income Inequality,” The American Economic Review 45(1), 1-28. Lewis, W.A. (1954), “Economic Development with Unlimited Supplies of Labor” Manchester School 22, 139-191. Mankiw, G., D. Romer, and D. N. Weil (1992), “A Contribution to the Empirics of Economic Growth,” Quarterly Journal of Economics 107, 407-437. Mayer, J. and A. Wood (2000), “South Asia’s Export Structure in a Comparative Perspective” IDS Working Paper No. 91. Ravillion, M. and S. Chen (1997), “What Can New Survey Data Tell Us About Recent Changes and Distribution and Poverty?” World Bank Economic Review 11, 357-382. Solow, R. (1956), “A Contribution to the Theory of Economic Growth,” Quarterly Journal of Economics 70, 65-94. T.W. Swan (1956) "Economic Growth and Capital Accumulation", Economic Record 32(2), 334-361. Wilson, W. (1967), “Correlates of avowed happiness,” Psychological Bulletin 67, 294-306.

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Yanikkaya, H. (2003), “Trade openness and economic growth: a cross-country empirical investigation,” Journal of Development Economics 72, 57-89.

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Chapter 8

ECONOMIC GROWTH AND ENVIRONMENT INTERACTIONS Serkan Gürlük Uludag University, Agricultural Economics Department, 16059 Bursa, TURKEY

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ABSTRACT Economic growth has negative impacts on environment at the first phases of development. After passing a threshold, it affects the environmental quality positively Economic development strategies indicate differences in various regions of the world because countries have different economic backgrounds and economic structure. Scale, production composition and technological effects have given forms the environmental impacts of economic growth. The negative environmental effects of the economic growth start with increasing of population, and then turn to positive by transition to knowledge-producing industries through high technology. Developed countries have some advantages because they have finance for infrastructure investments. Yet, it is very difficult to implement environmental policies due to weak economic structure. The most important way to prevent global environmental pollution is to act together. If developed countries use technology transfer for the benefits of themselves and developing countries by giving up excessive consumer roles, economic growth creates much more positive impacts on environmental quality and natural resources than expected.

Keywords: Economic growth, Environmental Kuznets curve, Environmental pollution.

INTRODUCTION Economic growth was one of the most controversial issues of the economic history of the world. Developed countries resolved this issue with unfriendly ways to nature and reached their development levels of today. Nobody can accuse the developed countries for their

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polluter roles in the world economic history. Yet, there is a reality that the earth has entered to the phase that she is not able to endure uncontrolled economic growth. While the developed countries are interested in how they can prevent environmental disasters, the developing countries have discussed how economic growth can be increased with least cost, without unemployment. Mankind attempts to the economic incentives in order to carry out its economic growth rapidly. Those economic incentives are aimed at reducing the imbalance between human’s unlimited needs and limited natural resources. In order to reduce this imbalance, there are three main economic problems to be resolved. Those are: • •

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•

To be able to benefit from all resources owned; To utilize the resource in a fashion that will be best meet the human’s unlimited needs; To increase the resources owned and manufactured goods and services.

Although benefit from all resources owned seems like possible with participation of all factors of production, land, labor and capital goods, to the production, it is not likely to resolve the issues by using all those factors of productions alone in today’s circumstances that environmental issues are an important phenomenon. It is necessary to use the existing resources inefficient ways while corresponding to human needs. This calls for making preferences among the limited resources. This problem, generally called "efficiency principle", should be provided in both of production and distribution. In addition to these two main economic problems, one another problem is to increase the amount of produced goods and services with helping of the resources owned. Resolving of this problem, supplementary of the other two problems, may be linked to the economic growth. We can state it with production-possibility curve’s increase by a shift to the right as written in economics textbooks. As long as the economic growth is raised, capacity of production that will be able to meet the human needs will increase as well. Macroeconomics textbooks emphasize the economic growth’s main sources as an increase in the size of the labor force, quality of the labor force, size of the stock of physical capital, quality of the capital stock and improvements of combined capital and labor to produce input. At this point, we can state that economic growth is a concept including either increment of the amounts of goods and services that will meet human needs or increment of production power of the goods and services. Consequently, the economic growth points out quantitative increments of goods and services that can be consumed by community. That humans’ welfare level is raised as the amount of good and services increase is a widespread consensus. Therefore the main aim of many economy policies is to increase the economic welfare levels of individuals and thus raise the amount of goods and services that can be consumed.

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Table 1. Annual average economic growth rates for selected regions fo the world

Regions

Per capita annual economic growthrate (%)

Annual economic growth rate (%)

Periods

Periods

1961-70

1971-80 1981-90 1991-00 2001-06 1961-2006

1961-70

1971-80 1981-90 1991-00 2001-06 1961-2006

Asia (except the Middle-East)

6,78

2,67

2,5

1,58

2,83

3,27

9,21

4,76

4,86

3,09

3,98

5,18

Central America and Caribbean’s

3,5

3,24

-0,22

1,86

0,18

1,71

6,82

6,06

1,9

3,63

1,01

3,88

Europe

…

…

…

1,65

2,05

1,85

…

…

…

1,91

2,11

2,01

Middle-East and North Africa

…

…

…

2,17

0,7

1,44

…

…

…

4,82

1,56

3,19

North America

2,61

2,25

2,14

2,02

1,01

2,06

3,96

3,35

3,25

3,3

2,5

3,27

South America

2,24

3,1

-1,09

1,5

1,9

1,53

4,91

5,52

0,92

3,13

3,28

3,55

Sub-Saharan Africa

…

…

-1,53

-5,3

1,83

-1,67

2,62

2,33

4,48

3,14

Developed countries

…

…

1,72

1,72

1,86

1,77

…

…

…

2,33

2,21

2,27

Developing countries

3,87

3,57

0,85

3,23

3,5

3,00

6,75

6,02

3,45

5,16

4,83

5,24

1,36

1,37

1,66

1,91

5,34

3,81

3,12

2,85

2,01

3,43

World 3,28 1,9 ource: Adapted from World Development Indicators 2009

176

Serkan Gürlük

Another economic concept is economic development and triggered by economic growth. The definition of economic development includes positive changes of related community’s socio-cultural structure in addition to economic growth. Consequently, reason of the economic development is essentially the growth of economy itself. Measurement of economic growth is defined by the increases of per capita gross domestic product (GDP). The GDP indicates short-run power of production because it is the money value of all final goods and services becoming available to the nation from economic activity. Furthermore, the economic growth brings about high living standards and international prestige. Hence, the race of economic growth has become unlimited among the all countries in globalizing world. The developments in every sector at the last century are much higher than that of in the last millennium. After all, the environmental issues experienced in the last fifty years had never become destructive compared to entire history of humanity. As this race of economic growth among the countries has continued in today, there is a dramatic differences in growth rates among the various regions of the world. Such a circumstance calls for dealing with global environmental issues more comprehensively and making up environmental policies more stringent in different part of the world. Yet, some countries are such poor that they cannot implement expensive environmental policies. Table 1 indicates per capita and total GDP rates in selected parts of the world. According to the table 1, even if economic growth rates show an advance from the 1960s to date, per capita growth rates remained lower. Especially the higher growth rates of Asian economies are remarkable. The growth rates at the developing countries are higher than world average. Table 2 exhibits rates of sectors’ contributions to the economic growth. As seen from the table 2, driving forces of the economic growth has come from the sectors of industry and services. While the sectors of industry and services have welfare-accelerating impacts, it causes other issues such as more uses of fossil fuels and greenhouse gases releases. Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

Table 2. Rates of sectors’ contributions to the economic growth Regions Agriculture Asia (except the Middle-East) 0,44 Central America and Caribbean’s 0,23 Europe 0,09 North America 0,07 South America 0,47 Sub-Saharan Africa 1,17 Developed countries 0,08 Developing countries 1,06 World 0,19

Industry 2,40 1,20 1,09 1,32 2,00 4,60 1,18 3,61 1,60

Services 4,20 3,15 2,80 4,40 3,90 3,30 3,20 5,30 3,96

Source: Adapted from World Development Indicators 2009

In the next section, economic growth’s environmental impacts of the interactions between them are examined more comprehensively. Section three examines algebraic reasons of these interactions while the theory of environmental Kuznets curve is explained in the fourth section. Section five gives a case study from the Mediterranean Countries to understand the environmental Kuznets curve better. Section six concludes.

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2. ECONOMIC GROWTH AND ENVIRONMENTAL POLLUTION Beginning of economic growth-environmental pollution debates is expressed with that the general economic circumstances start to remedy mankind’s socioeconomic conditions. In fact, developing economic circumstances, first, resolved many health problems of humans and helped to more comfortable living and sheltering conditions. All of these led to increase of world population. While increasing population is raised the need for total production of goods and services, amount of per capita good and services were not in the same rate. This is an important factor that makes up essence of environmental issues. In order to meet increasing population’s needs such as sheltering, nourishment and dressing, either more production is made and released more wastes or more natural resources are depleted. Depleted and degraded natural resources have led to other problems such as immigration of rural communities who are dependent on the natural resources closely. Especially, in developing countries, higher immigration rates from rural to urban areas are considerable. Hence, gigantic metropolitan areas whose populations are more than ten millions resulted in different regions of the world. This unlimited expansion of urban population has led to new problems such as insufficient food supply, increasing demand of energy and water resources. Although natural resource use has environmental impacts, their benefits to developing world are considerable. Asafu (2005) considered twelve of developing Asian countries and Australia in order to measure the impacts of energy on human development. Therefore, per capita GDP was correlated to per capita commercial energy consumption (in kilograms of oil equivalent). Results indicate that to per capita commercial energy consumption positively affected rapid economic growth in the above-mentioned countries. A unit increment on commercial energy consumption has caused 3.5 percent increase on per capita GDP while a tone of oil equivalent increment has increased the life expectancy up to three years. Furthermore, it was emphasized that infant mortality rates are decreased while energy consumption is increased. It is clear that energy use raised the living Standard and then social welfare (Soytaş et al, 2007). Similar consequences are available in various studies such as Gürlük, 2009; Gürlük and Ward, 2009. In these studies, it is observed that increasing water resource use and food security raises the welfare. Which one is preferable if economic growth contributes to human development, but decreases environmental quality? Is there any limit to the economic growth? Which level economic growth is preferred? To be able to response such questions correctly contributes to robust ecological-economic development strategies. Hence, economic growth-environmental relationships are the most controversial issues that environment economists have discussed. We can examine the interactions between economic growth and environment in three dimensions: Scale effect, production composition effect and technological effect (Grossman and Kruger, 1991). I stated that we need more natural resource extraction in order to meet all needs of increasing population. More output, first, implies more natural resource depletion. Secondly, more output means more wastes and emissions; this is linked to decreasing environmental quality. Explanations are mostly related with scale of production and thus this is the scale effect of economic growth. Economic growth may have also positive impacts over environmental quality. We can explain those impacts through "production composition effects". The structure of economy shifts from rural to urban economies. Especially, at the first periods of development rural

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economy prevails. In some countries, environmental issues may tend to increase when passing from agriculture to industry. Yet, environmental degradation starts to fall as long as the structural changes in an economy shift to knowledge and services intensive industries from energy intensive industry. Developing information technologies introduce a country to a more prosperous phase. This is explained with that information technologies are of more valuable goods in the world markets. Furthermore, the research and development investments help the improved production techniques to enter into every sector of an economy. Consequently, a new economic system whose production processes are cost-efficient and friendly to nature occurs. In such information communities, environmental quality improves as long as economy grows. It is called as technological effect of economic growth. Those three dimensions necessitate that different growth strategies are implemented in different countries and in many economic incentives. For instance, foreign trade leads to increase in size of the economy. Increasing volume raises the environmental pressures. Environmental quality is degraded by increasing trade volume. At this point, we can talk about scale effects. On the other side, production composition and technological effects have also affected environmental dimension of the foreign trade. Some countries can be in advantageous position, with international trade, by producing cleaner goods while some countries produce pollution intensive goods. While a country’s production composition is cleaner, one another country’s production may be dirtier. After all, some countries can maneuver through good management practices such as implementation of the technology transferred. The technology transfer through foreign direct investment may reduce pollution in developing countries (Copeland and Taylor 1995). We can explain this by technological effects of economic growth. Environmental pollution migrates from the countries implementing stringent environmental policies to those which implement weaker environmental policies. Therefore developed countries become importer of the goods having pollution-intensive production process while developing countries become exporter of such goods (Cole, 2004, Janicke et al 1997, Stern et al 1996). Heavy industries at China and India, foreign originated automotive industries in Turkey, Czech Republic and Mexico are such examples in the world. Environmental pollution imposes high costs to the polluters in the countries having strong economy. In addition, developed countries alleviate their environmental standards and regulations because developing countries have lower environmental standards and regulations. Developed countries may not want to flow away their capitals to the developing countries. After all, world countries mostly depend on international community and several economic incentives are blocked due to international agreements. That is, international community may have efficient roles in order to decrease the environmental issues. Market mechanism exhibits differences in various countries. Some countries adopt liberal economy policies while transition economies prevail in some countries. Particularly, in developed market economies, natural resource use efficiency is increased through market agents. Market prices may reflect the natural resource prices correctly. Excessive uses of the natural resources displace by optimal uses due to good-defined natural resource price. Market agents may have important roles on environmental protection in developed market economies. Financial sector may not support the firms which have not considered environmental conservation. Firms may not want to provide their intermediate good needs from polluter firms while consumers don’t want to prefer the goods produced with dirty methods. Furthermore, bad information regarding certain firm’s emission releases indicates

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that the firm has old-fashion production techniques and weak technologies. It makes impacts on market value of the firm. Advent of new technologies and innovation makes productivity-accelerating effects. Yet, it creates also new hazardous wastes, risks and other problems. For instance, agricultural productivity increased considerable thanks to speed of chemical sector improvement in the last 30 years. However, existence of several new chemical resistant species is also a reality. In addition to all those factors, informal institutions such as non-governmental organizations (NGOs) express the importance of environmental protection to related community. Yet, in developed countries, number of NGOs and their funding are better off than developing countries. In other words, economic growth would be consistent with environmental quality. However, costs of environmental policies are paid in order that income levels are increased. Inferences regarding interactions between income level and demand for environmental quality are explained by elasticity concept in the economics. After a certain income level, the rates of willingness to pay for better environmental quality are higher than the rates of income increases. Individuals who have higher income levels are tend to willingness to pay more for better environmental standards and regulations that can be enacted. All explanations are discussed comprehensively in the next section.

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3. AN ALGEBRAIC EXPLANATIONS TO ECONOMIC GROWTH AND ENVIRONMENT DEBATE Generally speaking, the economy has a dynamic structure, and its main sectors experience fluctuations in intervals (Cornwall and Cornwall, 1994). Yet, these fluctuations reach a balanced structure over time (Gupta and Barman, 2009). These fluctuations are available for environmental polluters as well and are based mainly on economic growth. We can explain the economic development path and environmental pollution with three phases. Figure 1 indicates the phases that an economy could experience over a large time interval. In the beginning, the countries enter the polluter phase, which is shown as phase 1 in Figure 1, in accordance with the nature of economic growth. The countries experiencing phase 1 have a low technological level, weak environmental awareness, and a lower educational level. The second phase is the 'stationary phase' or the steady-state condition with more technical. The impacts of economic growth on environmental quality are not as influential as during phase 1. In other words, pollution increases are stable even if the economy grows. Countries experiencing this phase can import technology and knowledge, and this may accelerate transition to the next phase. After remaining in this phase for a period of time, the countries enter phase 3. The third phase is the 'cleaning up' phase, and in addition, a recovery-period for environmental pollution starts with increasing economic development. High technology and environmental consciousness combine to play a role in reducing environmental pollution. After a long time period, the countries may reach a better environmental quality level than the initial environmental quality level. Yet, such a situation does not exist unless environmental priorities are more important than any other economic and social interests.

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Serkan Gürlük Environmental  Pollution  Phase I 

Phase II

Phase III

GDP 

Figure 1. Phases of environmental pollution and economic growth. Phase I: Pollution phase. Low technology level. Phase II: Steady-state path. The pollution does not increase as long as economy grows. Transfer of the technology is possible. Phase III: Cleaning up phase. The countries can produce technology.

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The pollution path of an economy may be analyzed by using a pollution production function between the per capita GDP and CO2 emissions. Figure 2 shows such an economy. The function p=f(g) indicates pollution production where p is per capita CO2 emissions. The slope of the curve p at point a, indicates that the per capita CO2 is produced by any additional per capita GDP. In other words, marginal product of the GDP (MPG) is the slope of the pollution production function (Figure 2). Therefore we may write the marginal product of the GDP as following: MPG = f(g+Δg) – f(g)

(1)

If g increases as the amount of Δg, p also increases as MPG unit. As long as g increases, the pollution production function gets flatter due to the effects of diminishing marginal production. That is, the slope of pollution production decreases (Silberberg and Suen, 2001). Such a production function asserts the product of diminishing marginal pollution of the GDP. Rises in the GDP reveals less pollution compared to former GDP accumulation. In the case of a lower GDP condition, additional GDP makes up more pollution in the graphical explanation. In case of a higher GDP condition, additional GDP makes up for less pollution, that is, less pollution is produced. Accordingly, these results fit the inferences associated within the environmental-economic growth debate at the beginning of this section. The environmental pollution arisen from economic growth would reach its steady state in the long term. After a certain point such as g*, the environmental pollution would remain constant. Followed environmental policies, new regulations, taxes and punishments help that a country enters a phase in which environmental pollution decreases. In the other side, the environmental quality would be higher than former. This phenomenon had caused to the advent of the theory of environmental Kuznets curve.

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CO2 (P) 

p=f(g) c MPG = f(g+Δg) ‐ f(g)

a  Δg 

b

f(g) 

g 

(g+Δg)

g*

GDP 

Figure 2. Pollution function.

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4. AN IMPORTANT APPROACH TO ECONOMIC GROWTH AND ENVIRONMENT DEBATE: ENVIRONMENTAL KUZNETS CURVES Main theory in the environmental economics literature is the environmental Kuznets curve, EKC. The fundamentals of EKC are based on a research carried out by Simon Kuznets, Nobel Laureate in Economics in the 1950’s. He designed an inverted U-shaped relationship between per capita income and income inequality, and shed light on the advent of EKC theory. Many researchers, in the early 1990's, stated that there is also a similar relationship between environmental pollution level and per capita income and approved that such analysis be called EKC analysis (Grossmann and Krueger, 1991; Shafik and Bandyopadhyay, 1992; Torras and Boyce, 1998; Vivek and Chapman, 1998). Grossman and Krueger (1991) and Panayotou (1993) are of first scholars studying on the relationships between environmental quality and per capita income. According to Grossman and Krueger (1991), intensive and inefficient economic incentives, first, have caused to environmental pollution while economic development continuing. After a certain period, shifting production composition and technique, in the higher income levels, have caused more productive economic incentives and finally it has affected the environmental quality positively. In their researches regarding urban air polluters, Grossman and Krueger (1991) explored that pollution concentrations increase as per capita income raises and then starts declining after a threshold level of income. They asserted that the cure is an inverse-U typed. In a workshop held by the Harward University, in 1992, T. Panayotou made a presentations titled "Environmental Kuznets Curve: Empirical Tests and Policy Implications", and asserted that increasing income level cause severe environmental issues and mention existence of critical income levels for arious polluter types (Panayotou, 1993). In the EKC studies, various pollution parameters such as sulphur emissions released by anthropogenic factors, carbon dioxide levels, water pollution, deforestation, biodiversity were employed by several authors (McPherson and Nieswiadomy, 2005; Torras and Boyce, 1998). Although data availability is an important problem confronted by the EKC experts, there are

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many national, international and private research institutions publishing periodicals. World Resource Institute (WRI), World Bank, Food and Agriculture Organization’s water resources database (AQUASTAT), Global Environmental Monitoring System (GEMS), Carbon dioxide Information Center and European Union’s environmental agency have long run data such as water and air quality, forest resources, biodiversity. Those institutions’ internet addresses are given in the reference section.

 

Environmental Pollution 

Income (a) 

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(d) 

(b)

(e)

(c)

(f)

Figure 3. Curve types that will be followed in the analysis of environmental Kuznets curve.

In the EKC analysis, a quadratic mathematical form is previously investigated. According to conventional statistical significances other function types are included to the analysis. If data matches the quadratic functional form, relationship has a turning point. The turning point offers considerable information on implementation of environmental policies. If a country has a turning point, we can infer that she has started to development sustainably. If a turning point has not existed, forecasts may be investigated whether she can reach a turning point. Following figure 3 indicates possible basic curve types that can be followed in the EKC analysis. Figure 3d is called as environmental Kuznets curve and has turning points. Figure 3e and 3f are polynomial curves and have more than a turning point. Such curves are followed by long run data, short run fluctuations may be occurred through seasonal shocks. It is necessary to know related period’s socio-economic and environmental dynamics in order to make robust interpretations (Shafik, 1994). Figure 3a and 3b are followed by industrializing countries while figure 3c is followed by medium-income countries approaching their steadystate conditions in terms of environmental pollution. World countries have to determine strategies on sustainable uses of environmental good and services. Some countries experience economic development period by considering environmental quality while some do not consider the environmental quality in the same

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periods. In such circumstances, irreversible ecological losses and hazards may be experienced in the long run. At this point, height of EKC curves is very important. The higher the EKC, the more likely it is that critical ecological thresholds will be crossed. That is, environmental costs of economic growth would be larger in the countries having higher EKC curves. Environmental pollution is a phenomenon that has international dimensions. Developed countries completed the polluter period without considering the environment. Developing countries have yet experienced this period. Hence such researches offer to understand differences, in terms of sustainable development, between developing and developed countries. In other words, results do not mean that developed countries are not polluting the environment. The countries which have environmental Kuznets curve have released lower environmental pollution according to their incomes earned. Apart from a couple of developing countries such as India and China, pollution concentrations are in the lower levels in the developing countries compared to developed ones. Environmental pollution

Unsustainable development type

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Ecological threshold

Gelir

Figure 4. Threshold of ecological damage.

There are many environmental disasters that create irreversible ecological hazards in the world. Particularly, tropical deforestation, the loss of biodiversity and extinction of species in the regions in which fragile ecosystems prevail are such ecological hazards. Economic incentives would lead to irreversible ecological losses in the countries having regions abovementioned. It is clear that the environmental price of economic growth in those countries is larger than other countries. Arrow et al., (1995) called this as threshold of ecological hazard. Figure 4 exhibits such curve. The figure gives some hints on existence of sustainable development. There is no doubt that environmental issues are inevitable with efforts of economic development. Yet, environmental costs of those issues have increased gradually with passing over ecological threshold. It is necessary to define sustainable development policies in every sector of economy, reduce excessive chemical subsidies in agriculture and internalize the environmental externalities in order to reach an economic growth that remains below the ecological threshold or reduce the environmental costs of economic growth. In the next section, an EKC case study carried out in the Mediterranean Region is given.

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5. A CASE STUDY FROM THE MEDITERRANEAN COUNTRIES’ ENVIRONMENTAL KUZNETS CURVES The research was carried out to describe the macroeconomic indicators and industrial pollution in the Mediterranean countries; to test the effects of human development index (HDI) and Biological Oxygen Demand (BOD) with respect to industrial pollution; and to compare the relationships between BOD and per capita GDP in European, Euro-Asian and African-Mediterranean countries, which have different economic and institutional backgrounds. Those countries were France, Spain, Italy, Greece, Albania, Malta, Slovenia, Turkey, Syria, Cyprus, Israel, Egypt, Algeria, Morocco and Tunisia. The Mediterranean countries have a long history of cooperation for environmental conservation despite of political, economic, social, cultural, and technological differences. The Mediterranean Region is recognized as one of the richest and most vulnerable in the world regarding its biodiversity, in particular. Marine components in the region reflect great diversity in the Mediterranean Sea. However economic development efforts in the Mediterranean countries have led to serious environmental problems. Environmental pollution has arisen from point sources such as discharge of sewage or leakage from unsanitary landfills, and nonpoint sources such as fertilizer and pesticides run-off due to unsustainable agricultural practices. In addition, municipal and industrial discharges to the bodies of water are considerable problems that cause environmental problems in the region. The environmental problems also intensely affect coastal zones of the region. The coastal zones have experienced severe anthropogenic pressure because such zones support the countries' economy considerably. In fact, all pollution sources mentioned above have affected the most productive areas of the Mediterranean marine environment, including estuaries and shallow coastal waters (Gürlük 2009). The paper estimates the relationship between the BOD and per capita gross domestic production (GDP) by examining the effects of the HDI of the UNDP. The BOD is referred to as the main reason for industrial and urban water pollution. Environmental Pollution Agency of the USA (EPA, 2008) states the BOD as the amount of oxygen that bacteria in water will consume while breaking down waste. Overloaded pollution in fresh water resources exhausts the dissolved oxygen content that aquatic animals need. Low levels of dissolved oxygen in water can impact the health of aquatic resources and ecosystems. A quadratic functional relationship is expected between per capita GDP and BOD in developed countries, and a logarithmic increasing relationship is expected between per capita GDP and BOD in developing countries of the region. With solving the model via regression, a significant nonlinear functional relationship between macroeconomic indicators and biological oxygen demand in the Mediterranean countries occurred. However expected quadratic functional relationship was not significant at various significance levels for developed countries of the Mediterranean Region apart from the case of France. The model France followed a quadratic function (the EKC relationship) and had a turning point. This point was the level of 22161 US$ for the France. The remaining countries of the European Mediterranean (EM) Region followed either logarithmic increasing or inverse-logarithmic increasing function between the BOD amounts and per capita GDP. The models Turkey, Israel, and Syria followed logarithmic increasing relationship between the BOD and per capita GDP while Cyprus had inverse-logarithmic functional relationship. African Mediterranean (AM) countries followed

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logarithmic increasing functional relationship. Such functional relationships are revealed through inadequate environmental infrastructure due to development efforts of developing countries. The developing economies have lower GDP, and this limited economic resource is allocated to other sectors rather than environmental infrastructure. Also they need to produce more without environmental awareness (Gürlük, 2009). The developing countries of the EA Mediterranean countries and all AM countries have experienced industrialization path and consequently natural resources have been exploited intensively. Those countries have not yet had any turning point in the industrializing path. Developed countries testing the long-run effects of environmental degradation enforce more and more stringent environmental policies. On the contrary, developing countries which are interested in fast economic growth are likely to allow less stringent environmental policies. However, installing clean high-tech production techniques would necessitate considerable amounts of funds for developing countries (Jones and Manuelli, 1997; Mora et al., 2006; Nixon et al., 2000). Human development has played an important role in sustainable economic development for developing countries such as Algeria, Egypt, and Tunisia. At the first periods of the development path, the human capital accumulation would not be available due to weak economic resources. Current paper supported this idea. If effective policies are implemented to human capital by investing educational infrastructure, developing institutional structure in a democratic environment, developing countries would not experience unsustainable path.

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6. CONCLUSIONS Economic growth has polluter impacts on environment at the first phases of development. After passing a threshold, it affects the environmental quality positively indeed. Economic development strategies indicate differences in the different regions of the world because countries have different economic backgrounds and economic structure. Developed countries reached today’s development levels by damaging the environment. Developing countries have not yet polluted the environment as developing countries. Natural resources have capabilities of regeneration unless excessive uses are experienced. Yet, severe impacts of economic growth have caused irreversible environmental disasters on fragile ecosystems. The most important discussion is whether economic growth is controlled. How will be resolved finance issues if controlled economic growth is carried out in developing countries. Environmental policies are expensive and depend on some conditions in developing countries. If developed countries use technology transfer for the benefits of themselves and developing countries by giving up excessive consumer roles, economic growth creates much more positive impacts on environmental quality and natural resources than expected.

REFERENCES Arrow, K., Bolin, B., Costanza, R., Dasgupta, P., Folke, C., Holling, C., Jansson, B., Levin, S., Maler, K., Perings, C., Pimental, D. 1995. Economic growth, carrying capacity and the environment. Science 268: 520-521.

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Asafu, A. J. 2005. Environmental Economics for Non-Economists: Techniques and Policies for Sustainable Develoment. World Scientific Publishing Company, NJ, USA. Copeland, B. R., Taylor, M. S. 1995. Trade and environment: a partial synthesis. American Journal of Agricultural Economics 77: 75-771 Cole, M. A. 2004. Trade, the pollution haven hypothesis and environmental Kunets curve: examining the linkages. Ecological Economics 48: 71-81. Cornwall, J., Cornwall, W. 1994. Growth theory and economic structure. Economica 61: 237251. Costantini, V., Monni, S. 2008. Environment, human development and economic growth Ecological Economics, Volume 64, Issue 4, 1 February 2008, Pages 867-880. EPA 2008. Environmental Protection Agency of the USA. www.epa.gov/waterscience/ pollcontrol. Grossman, G. M., Krueger, A. B. 1991. “Environmental Impacts of a North American Free Trade Agreement’’, NBER Working Paper 3914, Cambridge MA. Gürlük, S. 2009. Economic growth, industrial pollution and human development in the Mediterranean Region. Ecological Economics 68 (8-9), 2327-2335. Gürlük, S., Ward, F. A. 2009. Integrated Basin Management: Water and Food Policy Options for Turkey. Ecological Economics, 68 (10), 2666-2678. Janicke, M., Binder, M., Monch, H. 1997. Dirty industries: patterns of change in industrial countries. Environmental and Resource Economics 9: 467-491. Jones, L. E. and Manuelli, R., 1997. The sources of growth. Journal of Economic Dynamics and Control 21, 75-114. McPherson, M. A., Nieswiadomy, M. L. 2005. Environmental Kuznets Curve: threatened species and spatial effects, Ecological Economics, Volume 55, Issue 3, November 2005, Pages 395-407. Mora, N. H., Llamas, R. and Cortina, M. L., 2006. Misconceptionsin Aquifer overexploitation: Implications for Water Policy in Southern Europe’, Edition book by Cesare Dosi: Agricultural use of groundwater. Kluwer Academic Publisher. London, UK. Nixon, S. C., Lack, T. J., Hunt, D. T. E., 2000. Sustainable use of Europe’s waters? European Environment Agency Environmental Assessment Series, No:7, Kopenhag, Denmark, pp. 34. Panayotou, T., 1993. Empirical Tests and Policy Analysis of Environmental Degradation at Different Stages of Economic Development. World Employment Research Programme, Working Paper, International Labour Office, Geneva, p.42. Selden, T. M., Song, D. S., 1994. “Environmental Quality and Development: Is There a Kuznets Curve for Air Pollution Emissions?”, J.Environmental Econ. Management. 27, 147-162. Shafik, N. 1994. Economic Development and Environmental Quality: An Econometric Analysis, Oxford Economics Paper. 46, p.757-773. Shafik, N., Bandyopadhyay, S., 1992. “Economic Growth and Environmental Quality: TimeSeries and Cross-Country Evidence”, World Bank Working Papers, WPS 904, Washington, 52 pp.13. Silberberg, E., Suen, W. (2001). The Structure of Economics. McGraw-Hill International Edition, USA.

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Soytaş, U., Sarı, R., Ewing B. 2007. Energy consumption, income, and carbon emissions in the United States. Ecological Economics, Volume 62, Issues 3-4, 15 May 2007, Pages 482-489. Torras, M., Boyce, J. K. 1998. Income, Inequality and Pollution: A Reassessment of the Environmental Kuznets Curve, Ecological Economics, 25, p.147-160. Vivek, S. and D. Chapman. 1998. “Economic growth, trade and energy: implications for the environmental Kuznets curve”, Ecological Economics, Volume 25, Issue 2, May 1998, Pages 195-208.

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Web sources European Union Environment Agency www.eea.europa.eu World Bank: www.worldbank.org Food and Agriculture Organization (AQUASTAT): www.fao.org World Resource Institute: http://www.wri.org/ Carbon Dioxide Information Analysis Center (CDIAC): http://cdiac.ornl.gov Global Environment Monitoring System: http://www.gemswater.org

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In: Theories and Effects of Economic Growth Editor: Richard L. Bertrand, pp. 189-201

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Chapter 9

WHAT IS THE OPTIMAL RATE OF INFLATION FOR LONG-RUN GROWTH? A CROSS-COUNTRY ANALYSIS∗ Hakan Yilmazkuday† Temple University, Department of Economics, Temple University, Philadelphia, Pennsylvania, USA

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ABSTRACT Although the relationship between financial development and growth is almost obvious, the effect of inflation on the finance-growth nexus is still a subject of debate. In particular, what is the optimal rate of inflation for long-run growth? To answer this question, I analyze the relation between finance, inflation and growth by using a semiparametric graphical approach. I find that the optimal level of inflation that leads to higher long-run growth rates is around 10 percent. I also show that the positive effects of low inflation on growth are more apparent when there are high levels of financial depth. Finally, when both the levels of inflation and financial depth are low, the growth rate of the economy is volatile.

JEL Classification: E31, E44, F36 Keywords: Financial development; Economic growth; Inflation; Cross-country analysis

1. INTRODUCTION

∗ †

I thank Peter Rousseau for his helpful comments and suggestions. All errors are my own responsibility. E-mail address: [email protected]; Tel: +1-215-204-8880; Fax: +1-215-204-8173; Address: Department of Economics, Temple University, Philadelphia, PA 19122, USA.

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There is still a growing literature on economic growth and its determinants. Although it is a topic of which origins can be traced back to old time literature, the analysis of specific relation between finance and growth belongs to “new” growth literature. In this context, the earliest theoretical attempts that stress the connection between a country’s financial superstructure and its real infrastructure belong to Goldsmith (1969), McKinnon (1973) and Shaw (1973). While Goldsmith focuses on the effect of financial superstructure of an economy on the acceleration of economic growth to the extent that the economic performance is related to the migration of funds to the best projects available, McKinnon and Shaw emphasize the government restrictions, such as interest rate ceilings, high reserve requirements, and directed credit programs, that encumber financial development, and ultimately reduce growth. Similar conclusions are reached by other papers that have developed endogenous growth theories, in which growth and financial structure are determined explicitly in models. In the group of these endogenous growth models, Greenwood and Jovanovic (1990) concentrate on the concepts of information collection, information analysis and risk sharing in order to analyze the effects of financial structure on economic growth. My topic of interest in this paper is how the finance–growth nexus mentioned above is affected by inflation rates. Recently, Rousseau and Wachtel (2002) show that there is an inflation threshold for the finance–growth relationship.1 According to their results, financial depth has a positive effect on growth only when inflation falls below a threshold that varies between a five-year average inflation rate of 13 percent to 25 percent depending on the measure of financial depth. The effects become significantly positive when inflation falls below a threshold of about 6 percent to 8 percent. Disinflations are associated with strong positive effects of finance on growth with most measures of financial depth. Inflation has a negative effect on financial depth when the five-year average inflation rate is below about 15 percent to 20 percent. Another recent paper related to how the finance–growth nexus is affected by inflation rates is by Rousseau and Yilmazkuday (2009). They find that high levels of financial depth are important for achieving long-run growth. Rousseau and Yilmazkuday also show that high inflation affects the finance-growth nexus negatively, but the effects of inflation are not that sensitive to its level once a country is in the high-inflation range. They show that, at middlerange inflation rates, the finance-growth link across countries seems quite sensitive to small differences in inflation rate, and these effects are stronger for developing countries than for developed ones. Compared to Rousseau and Wachtel (2002), in this paper, I will search for an optimal level of inflation by using a three-dimensional graph. Specifically, instead of analyzing the bilateral relations between finance, growth and inflation in two-dimensional graphics, following Rousseau and Yilmazkuday (2009), I will use a three-dimensional graphic to show the trilateral relation between them. This method will help me to show the most adequate level of finance-inflation pair sufficient for the highest level of economic growth. In order to find a trilateral graphical relationship between finance, growth and inflation, by using a semi-parametric approach, I extend the analysis of Rousseau and Yilmazkuday (2009) who use a pure parametric approach. This has several benefits for the sake of the 1

Also see Dehesa et al. (2007), Duttagupta and Cashin (2008), Favara (2003), Feldmann and Wagner (2002), Mehl et al. (2006), Rajan (2006).

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robustness. First, I can use the parametric approach for the part of the model that has an accepted functional form in the literature. Second, for the part of the model that does not have a well known functional form in the literature, I can use the nonparametric approach. Thus, I don’t restrict my analysis with an ad hoc parametric model, in which case the results are sensitive to the selection of the model. Third, I find a surface which fits best to my data2. Compared to curve fitting or regression planes, surface fitting helps me show the possible linear and nonlinear relations between finance, growth and inflation triple. I extend the analysis of Rousseau and Yilmazkuday (2009) also by considering 10 year growth measures in my analysis. The rest of the paper is organized as follows: Section 2 describes the data and depicts the results from the linear regression analysis. Section 3 introduces the trilateral graphical approach, and represents the relevant results. Section 4 concludes.

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2. DATA AND BASE LINE GROWTH REGRESSIONS My data set is constructed as a panel of country observations from the World Bank’s World Development Indicators, and includes as many as 84 countries over the period 1960– 2003. I use different samples in order to catch the long-run effect of inflation and finance on growth, namely five-year average data, five-year average data for developed countries (of which per capita GDP is higher than $3,000), five-year average data for developing countries (of which per capita GDP is lower than $3,000), ten-year average data, overall (forty-fouryear) average data and ten-year cross sectional analysis for periods 1970-79, 1980-89 and 1990-99. Specifically, for five-year average data, I regress the average growth rates of each country over five-year periods on the initial values of the set of conditioning variables (named above) for that five-year period. For five-year average data sets for developed and developing countries, I follow the same method, except, for this time, the data are divided into two parts according the per capita income levels of the countries. Similar methods are followed for tenyear average and overall average data sets. Finally, for ten-year cross-sectional analysis, I use the same method after splitting the data into three periods named above. Prior to analyzing trilateral graphical relations between finance, inflation and growth, I will start with linear regression analysis for the data set that is defined above. Following Barro (1991), and Levine and Renelt (1992), my base line growth equations include a standard set of explanatory variables that provide robust and widely accepted proxies for growth determinants. I will follow this approach in my analysis. My dependent variable is the growth rate while the independent variables are initial GDP, initial secondary school enrollment rate, inflation, and financial depth (measured as M3/GDP). The results are given in Table 1 and Table 2. The regression results on ten-year average and ten-year crosssectional data sets are given in Table 1. In this sense, I can categorize the samples in Table 1 as ten-year samples. In Table 1, specifically, the log of the initial secondary school enrollment rate, a measure of human capital investment, is significant in all equations except for the one for the period 1970-79. Similarly, the level of M3/GDP, a measure of financial sector depth, is highly significant in all equations except for the one for the period 1990-99. The other variables, namely log initial GDP and inflation are not significant in any sample of Table 1. 2

In this sense, one can call my analysis as surface fitting.

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Table 1. Sample 1

Sample 2a

Sample 2b

Sample 2c

-0.887 (0.28)

2.885 (0.05)

-1.451 (0.30)

-2.647 (0.05)

Log initial GDP

-0.206 (0.17)

-0.236 (0.37)

-0.262 (0.33)

-0.257 (0.32)

Log initial SEC

0.733 (0.01)

0.178 (0.69)

0.831 (0.10)

1.593 (0.01)

Inflation

-0.000 (0.52)

M3/GDP

0.022 (0.00)

-0.032 (0.49) 0.043 (0.00)

-0.004 (0.75) 0.033 (0.01)

-0.000 (0.34) -0.002 (0.83)

R-bar sqd.

0.26

0.26

0.16

0.11

Constant

Notes: p-values are in parenthesis. Estimation is by OLS. Sample 1 consists of ten year averages of all countries, Sample 2a consists of ten year cross-sectional data of all countries for the period between 1970-79, Sample 2b consists of ten year cross-sectional data of all countries for the period between 1980-89, and Sample 2c consists of ten year cross-sectional data of all countries for the period between 1990-99. Sample 1 includes fixed effects for time periods that are not shown. The sample sizes for Sample 1, Sample 2a, Sample 2b and Sample 2c are 179, 48, 64 and 67, respectively.

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Table 2. Sample 3

Sample 4

Sample 5a

Sample 5b

Constant

1.644 (0.10)

-1.639 (0.03)

-0.646 (0.71)

0.156 (0.92)

Log initial GDP

-0.544 (0.00)

-0.231 (0.06)

-1.004 (0.00)

-0.247 (0.33)

Log initial SEC

0.907 (0.00)

0.890 (0.00)

2.019 (0.00)

0.569 (0.07)

0.017 (0.60) 0.031 (0.00)

-0.000 (0.16) 0.020 (0.00)

-0.000 (0.65) 0.019 (0.00)

-0.000 (0.32) 0.023 (0.02)

0.40

0.20

0.29

0.12

Inflation M3/GDP R-bar sqd.

Notes: p-values are in parenthesis. Estimation is by OLS. Sample 3 consists of overall (forty-four-year) average for each country, Sample 4 consists of five year averages of all countries, Sample 5a consists of five year averages of developed countries (countries of which per capita GDP is higher than $3,000), Sample 5b consists of five year averages of developing countries (countries of which per capita GDP is lower than $3,000). Sample 4, Sample 5a and Sample 5b include fixed effects for time periods that are not shown. The sample sizes for Sample 3, Sample 4, Sample 5a and Sample 5b are 49, 467, 202 and 265, respectively.

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The regression results for the data sets of overall average, five-year average, five-year average of developed countries and five-year averages of developing countries are given in Table 2. In this table, almost all of the independent variables are significant expect for inflation. If I compare the R-bar squared of the regressions, one can see that the most explanatory regression is the one for overall average data. In terms of my data set, this one can be called as the longest-term analysis. In both of the tables, the signs of the variables are as expected. Specifically, the sign for log initial GDP is negative, which is due to real convergence. Everything else held constant, a high GDP country will have a lower growth rate since gradual convergence is expected. The log of the initial secondary school enrollment rate (called SEC in the tables) has also a positive sign, as expected, in both tables. They are a good overall indicator of the commitment towards investments in human capital. The measure of financial sector depth— the ratio of M3 to GDP— has also a positive sign as expected. As a financial sector becomes more developed and exhibits greater depth, there will be more activity by financial intermediaries. Nevertheless, the results in both tables do not explain the role of inflation on growth3. This may be due to the model selection, which is linear in my case. In order to not restrict my analysis with such model selections, I will use a semiparametric approach. The semiparametric approach and its graphical results are presented in the following section.

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3. TRILATERAL GRAPHICAL APPROACH In order to get a trilateral graph, first, I have to reduce the dimensionality of the system, simply by reducing the number of variables in my analysis. Since the linear effects of the log initial GDP, the log initial SEC, the fixed time effects on growth are highly accepted in the literature, I first eliminate the effects of these variables on my system. I have two choices in this elimination process. First, I can eliminate the effects of these variables from the growth, the initial M3/GDP and the initial inflation, by interpreting each of the data matrices of growth, initial M3/GDP and initial inflation as the residuals from the projection on the data matrices of log initial GDP, log initial SEC and fixed time effects. Second, I can eliminate the effects of these variables only from growth, again by interpreting the data matrix of growth as the residuals from the projection on the data matrix of log initial GDP, log initial SEC and fixed time effects. Nevertheless, recall that the main goal of this paper is to find the effects of finance and inflation on the unexplained part of growth, i.e., the Solow residuals. Moreover, I want to use a three-dimensional graphical method in my analysis. So, following Rousseau and Yilmazkuday (2009), when I use the first approach for the elimination of log initial GDP and log initial SEC, I end up with a graphical analysis in which I use the residuals of the variables in the axes of my graphics. In such a case, my three-dimensional graph will be a graph of the residuals (of growth, finance and inflation), instead of a graph explaining the effects of 3

The insignificance of inflation doesn’t change even when I include initial trade, initial government spending or initial private investment. I don’t show these specific results to save space, but they are available upon request. Because of the inclusion of these variables in my sensitivity analysis, I have restricted myself to a data set which is a subset of the data used by Rousseau and Yilmazkuday (2009). So, my regression results are slightly different from them.

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finance and infflation on thee unexplained part of Solow w residual. Inntuitively, thee danger of ussing this elimiination approaach is the implicit assumption of the caussality from thee log initial G GDP and the lo og SEC to thee initial M3/G GDP and the innitial inflationn. However, acccording to thhe existing litterature, the causality c betw ween these vaariables is billateral. So, itt would be m misleading to allow a for such an implicit asssumption in my m analysis. Because off the reasons given g above, I consider the second s approaach for the elim mination of loog initial GDP P and log initiial SEC from my system. According A to this approachh, I retrieve thhe Solow resid duals from thhe regression of o growth on log initial GD DP, log initiaal SEC and fixed time effeccts. After thatt, I use the nonnparametric appproach in ordder to capture the effects wth graphicallly. The detaills of the nonnparametric off financial deepth and inflaation on grow appproach are given in the Teechnical Appeendix. I start my m presentatioon with Figure 1a which usses the five-yeear average daata for all counntries (sample 4 in Table 2)..

Figure 1a. Fiive-Year Averagge Data.

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Figure 1c. Fiive-Year Averagge Data.

This graph h needs some explanations since s it is the first time thaat it is introduuced. In the hoorizontal axes, there are finaance (M3/GDP) and inflatioon levels. In thhe vertical axiis, there are grrowth residuaals obtained from f the regrression of groowth on initiaal log seconddary school ennrollment (SE EC), initial logg real GDP andd fixed effectss for time periiods. The darkkness of the suurface increasees as the grow wth residuals get g higher. Thaat is to say, thee part of the suurface with thhe highest leveel of darkness represents thee highest level of growth inn the figure. Thhere is also a projection of the surface, which w is in tw wo dimensions, in the bottom m of the figurre. One can ween finance, inflation and growth. In allso use this prrojection in orrder to see thee relation betw thhis projection,, the area witth the highestt level of darrkness represeents the higheest level of grrowth associatted with relevant levels of finance f and infflation. After this brief b introducction, I can saay that, in Figure 1a, the hiighest level off growth is acchieved when the level of inflation i is aroound 10 perceent and the leevel of financiial depth is arround 170. In n other wordss, a high leveel of financiall depth togethher with a loow level of innflation leads to t the highest level of grow wth. Since the areas in the prrojection withh the lowest leevel of darkneess represents the lowest leevel of growthhs, I can say that t the lowesst levels of grrowth are achiieved when finnancial depth is around 25, independent of o the levels of o inflation. Lastly, by look king at the surrface, one can see that, wheen the levels of o inflation annd financial v growthh structure. deepth are both low, there are lots of smalll hills which represent a volatile That is to say, when both thhe levels of finnancial depth and inflation are low, one cannot say n about the levvels of growthh. annything certain Just to giv ve an idea abbout how my three-dimenssional graphicc looks like, I will now prresent the sam me figure, Figuure 1a, from a different anggle. I make thaat presentationn by Figure 1bb. Figure 1b is the same as Figure 1a except for thhe fact that they t are preseented from diifferent pointss of view. By the help of Figure 1b, one can see the projection p of the t surface, w which is given in the bottom m of the figurre, more clearly. In this proojection, the path, p which shhows that the level of grow wth increases with lower leevels of inflation and higheer levels of financial depth, is important. And finally, I will presennt the same figgure, Figure 1a, with the saample points. This presentaation is made in Figure 1c. Figure 1c iss the same as Figure 1a, exxcept for the fact f that the lattter includes thhe sample poiints on it.

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Now, I can n introduce the three-dimennsional analysis of other sam mples. Figure 2 uses the five-year averaage data for developed d couuntries (samplle 5a in Table 2). In orderr to obtain me method thhat I use to obttain Figures 1aa, 1b, and 1c. Fiigure 2, I use exactly the sam

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Figure 2. Five-Year F Averrage Data for Developed D Counntries.

The resultss obtained from m Figure 2 aree similar to thhe results obtaiined from Figures 1a, 1b annd 1c. The hig ghest level of growth is achhieved by a level of financial depth arounnd 170 and ann inflation lev vel around 10 percent. p Whenn I look at low w levels of finnancial depth, the growth leevel is also low w, independennt of the level of inflation. It I means that inflation i beginns to affect thhe level of gro owth only afteer the econom my has a modeerate level of financial deptth. In other w words, accordin ng to Figure 2, 2 higher inflattion cannot leaad to higher grrowth in the loong-run. In orrder to have higher h levels of o growth, the economy has to have a higgher (at least a moderate) leevel of financiial depth. Oncce the econom my reaches a moderate m level of financial depth, d then, thhe level of infllation becomes important annd effective onn long-run groowth.

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Similarly, I use the five-yyear average data d for develooping countriees (sample 5b in Table 2) inn order to obtaiin Figure 3. I again a use exacctly the same method m that I use u for other saamples. Figure 3 sh hows that the average level of financial depth of developing counttries is less thhan the averag ge level of finnancial depth of developed countries. Thhis is because of the fact thhat the samplee points in Figgure 3 are scatttered betweenn financial deppth levels of 0 and 75. In thhis financial depth d range, thhe optimal levvel of inflation for long-runn growth for developing coountries is bettween 0 and 30 3 percent. Fiinally, the higghest level of growth is achhieved by a financial depth level of 75 annd an inflationn level around 8 percent.

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Figure 4. Teen-Year Averagge Data.

I use the teen-year averagge data for alll countries (saample 1 in Taable 1) in ordeer to obtain hich I again usse exactly the same methodd that I use forr other samplees. Figure 4 Fiigure 4, in wh giives similar reesults as other figures in thee sense that thee high levels of o financial deevelopment toogether with lo ow levels of innflation lead too higher levelss of growth.

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Now, I will use ten-year cross-sectionaal data in ordeer make a com mparison betweeen periods 19970-79, 1980--89 and 19900-99. This anaalysis will not only help too compare the levels of financial depth between perioods, but also helps h to see thhe effects of itt, together witth inflation, d periods. I start withh presenting thhe ten-year avverage data forr the period onn growth for different 19970-79 in Figu ure 5.

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Figgure 6. Ten-Yeaar Average Dataa for 1980-89.

As one can n see from Figgure 5, the sam mple is ranged between the financial f depthh level of 0 annd 70. If I com mpare Figure 5 with Figure 4, I realize thhat the averagee level of financial depth iss lower in thee period 1970-79 than in period 1970-99. The highhest level off growth is acchieved with a moderate leevel of financial depth and an inflation level l around 15 1 percent. N Now, I can pressent the ten-yeear average daata for the periiod 1980-89 by Figure 6. In Figure 6, 6 the sample points p are now w ranged betw ween the financcial depth leveels of 0 and 1225. This show ws the fact thatt the financial depth levels of o countries haave increased from f 1970799 to 1980-89. The optimal levels l of inflattion that lead to higher grow wth rates are between b 10 annd 30 percentss. Finally, I preesent the ten-year average daata for the period 1990-99 inn Figure 7.

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In Figure 7, 7 the sample range for finnancial depth is i between 0 and 170. Thaat is to say, coompared to Fiigure 6, the leevel of financcial depth hass increased froom 1980-89 to 1990-99. A And, similar to my previous findings, the optimal o levels of inflation thhat lead to higgher growth raates are around d 10 percent. The last graph that I willl present is thee one for overaall average daata (sample 1 in i Table 2). A I mentioned As d before, com mpared to otheer samples suuch as five-yeear and ten-yeear average daata sets, this saample can be called as the longest-run l daata. The resultss are given in Figure 8.

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Fiigure 8. Overalll (Forty-Four Year) Y Average Data. D

Since I am m taking thee overall averrage of my data, Figure 8 representss only one obbservation forr each countryy over my sam mple period 1960-2003. Acccording to this figure, the opptimal level of o financial deepth that leadss to higher groowth rates is around a 50, whhich can be caalled a moderrate level. How wever, the opptimal level off inflation thatt leads to highher growth raates is not un nique. There are a two optim mal levels of inflation: i onee is around zeero percent (cconstant price level), and thhe other is beetween 10 andd 20 percents. In sum, the longest-run l grrowth has beeen achieved thhrough a modeerate level of financial f grow wth and an infl flation level eiither zero perccent, or betweeen 10 and 20 percents. p

4. CONCLUSION O NS a the reelation betweeen finance, I used a trrilateral graphhical approachh in order to analyze innflation and growth. g Comppared to Rouusseau and Yilmazkuday Y ( (2009) who use u a pure paarametric app proach, I havee used a semi--parametric appproach in my m analysis. Thhe obvious paart of my resu ults is for thee relation betw ween financiall depth and growth. As exppected, my grraphs showed d that higher levels of grow wth are assocciated with hiigher levels of o financial deepth. This ressult is consisttent with the existing grow wth literaturee. The other part p of my reesults, which is the main object o of this paper, is aboout the effect of inflation on o financegrrowth nexus. I found that thhe optimal levvel of inflationn that leads too higher long-rrun growth raates is around 10 percent forr different dataa sets.

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Other than that, by using the five-year average data, which is accepted and used as the basic long-run growth sample in the literature, I showed that the positive effects of low inflation on growth are more apparent when there are high levels of financial depth. Nevertheless, when both the levels of inflation and financial depth are low, the growth rate is not consistent. In other words, it is volatile in such a case. More things remain to be investigated for future research. In particular, although no parametric relation is imposed, the trilateral graphical approach of this paper uses growth rate as the dependent variable and other variables (i.e., inflation rate and financial development) as independent variables. However, all inflation, finance, and growth are just variables that are correlated with each other; the causation between these variables is still a debate in the literature, and it is subject to change across time periods. In this context, a more unstructured and nonparametric graphical approach that is independent of causality issues is necessary to investigate the exact relation between inflation, finance, and growth.

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APPENDIX This appendix depicts the technical details of my trilateral graphical approach. I use the method of natural neighbor interpolation as introduced by Watson (1994) in order to get a three-dimensional graph of inflation, finance and growth. According to this method, the natural neighbor algorithm uses a circular areal-based procedure for interpolation. Unlike Delaunay triangles where there may be more than one way to assign the triangles to the data, natural neighbor circles form a unique arrangement. The basic algorithm (with zero tension) is best thought of as a taut rubber sheet connecting all of the points. In this instance, the interpolant is C1 everywhere except at the data nodes where discontinuities exist. A C1 (once continuously differentiable) interpolant will occur when a tension value of one or greater is set. In this instance, gradient information is used to blend out the discontinuity at the nodes. The interpolant is planar and utilizes a linear weighted average of the natural neighbor function values. The C0 interpolant and lower tensions of the C1 interpolant may be of value in the accurate integration of topographical data. I use the software called TalbeCurve 3D, Version 4.0, in my analysis. By using this software, the data are automatically scaled to a unit cube. Tensions of 1 through 5 automatically set the tautness factors in the algorithm to (3,9), (2,4), (1.5,2.25), (1.25,1.5625), and (1,1). The data perturbation introduced to insure the uniqueness of natural neighbor circles has been decreased in magnitude to reproduce the precision of input values to 7-8 digits. The natural neighbor relationships of data are specified by the shared natural neighbor circles. The Watson (1994) algorithm uses a simple weighted average of the z values of the natural neighbors of the interpolation point. This type of linear interpolation in natural neighbor coordinates is the equivalent of planar interpolation in rectangular coordinates. No gradient information is used for the non-tension interpolant. For the tension interpolant, natural neighbor gradients are computed using the natural neighbors of a data point, but not the data point itself. A compound exponential blending function is used to add the influence of the gradients and render the interpolant C1 at the nodes. The blending function does not use the tension directly, modifying it in accord with an outlier or roughness index. For data

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fitted well by smooth functions, the highest tension setting is likely to produce the greatest accuracy. The algorithm uses a large triangle which encompasses the whole of the data. Artificial data are created at these vertices by least-squares fitting of a plane to the entirety of the data. Extrapolation is then accomplished using these vertices. This is a highly conservative form of extrapolation that is not likely to be at all accurate, although the wild fluctuations that often occur within extrapolation are avoided.

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REFERENCES Barro, R.J., 1991, Economic growth in a cross section of countries, Quarterly Journal of Economics 106, pp. 407–443. M. Dehesa, P. Druck, A. Plekhnaov, 2007. Relative Price Stability, Creditor Rights, and Financial Deepening. IMF Working Paper 07/139. R. Duttagupta, P. Cashin, 2008. The Anatomy of Banking Crises. IMF Working Paper 08/93. G. Favara, 2003. An Empirical Reassessment of the Relationship Between Finance and Growth. IMF Working Paper 03/123. R. Feldman, N. Wagner, 2002. The financial sector, macroeconomic policy and performance. EIB Papers 7(2), pp. 13-30. J. Greenwood, and B. Jovanovic, 1990. Financial Development, Growth and Distribution of Income,” Journal of Political Economy, 98, pp. 1076-1107. R. Goldsmith, 1969. Financial Structure and Development, Yale University Press, New Haven, CT. R. Levine, and D. Renelt, 1992. A sensitivity analysis of cross-country growth regressions, American Economic Review 82, pp. 942–963. R. McKinnon, 1973. Money and Capital in Economic Development, The Brookings Institution, Washington, DC. A. Mehl, C. Vespro, A. Winkler, 2006. Financial sector development in South-Eastern Europe: quality matters. In Liebscher, K. et al (eds). Financial Development, Integration and Stability, Edward Elgar, Cheltenham, pp. 187-203. P.L. Rousseau and P. Wachtel, 2002. Inflation Thresholds and the Finance-Growth Nexus. Journal of International Money and Finance 21, pp. 777–793. P.L. Rousseau and H. Yilmazkuday, 2009. Inflation, Financial Development and Growth: A Trilateral Analysis, Economic Systems, 33, 310-324. R. Rajan, 2006. Has Finance Made the World Riskier? European Financial Management 12, pp. 499-533. E.S. Shaw, 1973. Financial Deepening in Economic Development., Oxford Univ. Press, New York. Watson, D. F., 1994. nngridr: An implementation of natural neighbour implementation, vol. 1 of Natural Neighbour Series. David Watson.

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In: Theories and Effects of Economic Growth Editor: Richard L. Bertrand, pp. 203-230

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Chapter 10

WELFARE EFFECTS OF NATIONAL CLIMATE POLICIES AND THE GROWTH RATE OF INTERDEPENDENT ECONOMIES Karl Farmer and Andreas Rainer University of Graz, Graz, Austria

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ABSTRACT After COP15 in Copenhagen 2009, national interests dominate negotiations for PostKyoto policies to mitigate global climate change. While enforceability on national levels clearly betters the prospects for global climate policy, there is the concern that national emission targets are set not ambitiously enough to prevent catastrophic climate change. This chapter investigates whether and why these concerns might be warranted within an overlapping generations’ model of two internationally interdependent economies with producer greenhouse gas emissions and national emission permits systems. We find that when the natural growth rate of the world economy is less than the real interest rate national permits reduction diminishes the welfare in both countries. Moreover, net foreign debtor countries (USA) have minor incentives than net foreign creditor areas (EU) to implement a more stringent climate policy. In general, it remains open whether dynamic inefficiency betters the prospects for national climate policy.

JEL Classification: Q52, Q54, O41 Keywords: Emission permits, climate policy, welfare, dynamic (in-) efficiency, growth.

INTRODUCTION After COP15 in Copenhagen 2009 and some achievements at COP16 in Cancún 2010 notwithstanding, national interests dominate negotiations for Post-Kyoto policies to mitigate global climate change. Instead of an internationally binding treaty like the Kyoto Protocol, each country (or group of countries like the EU) is now entitled to set nationally acceptable

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emissions reduction targets enforceable under their respective law. While enforceability betters the prospects for success in climate policy, there remains the concern that national emission targets, especially of the largest emitters China and the USA, are not set ambitiously enough to minimize the risk of catastrophic climate changes. The reason for climate political laxity is, that unilateral policies to reduce the emission of greenhouse gases through e.g. the introduction and strengthening of an emissions trading system like the EU ETS are usually associated with negative effects on economic growth (capital accumulation), international competitiveness and consumer welfare, and these short-term economic costs of emission reduction are deemed to be higher than the long-term environmental benefits from current lower emissions. While the negative impact of a unilateral permits reduction policy (national climate policy) on national economic growth and welfare is intuitively plausible, it is in general only true under some preconditions concerning the external balance and the dynamic efficiency of internationally interdependent countries (Bednar-Friedl et al., 2010, Bednar-Friedl and Farmer, 2010). In particular, in a two-country extension of Ono’s (2002) closed-economy model, Bednar-Friedl and Farmer (2010) show that a permits reduction in one of the two countries unambiguously reduces the non-environmental part of domestic welfare when the permits reducing country is a net foreign debtor and the two-country world economy is dynamically efficient. If, on the contrary, dynamic inefficiency prevails which means that the natural growth rate of the world economy is larger than the real interest rate, the welfare effect is in general ambiguous. There are admissible parameter constellations under which unilateral permits reduction might even increase national non-environmental welfare. While these results – if they were true in general – would clearly better the prospects for nationally more ambitious emission reduction targets, they are in fact achieved under the simplifying assumption that the natural growth rate is zero. In the case of small open economies the assumption is not really restrictive when the (real) interest rate can be assumed to be exogenously given. In a two-country world economy, however, in which the countries are interconnected through trade in produced commodities and financial assets (like government bonds), the real interest rate is endogenously determined and the natural growth rate is only one of several parameters which determine the equilibrium solution. Changing the natural growth rate from zero towards a strictly positive value will affect the intertemporal general equilibrium solution and it remains an open question whether the results obtained by Bednar-Friedl and Farmer (2010) also hold under strictly positive natural growth rates. It is the objective of this chapter to answer this question by generalizing the two-country, two-good overlapping generations model of Bednar-Friedl et al. (2010) towards the incorporation of a strictly positive natural growth rate of two interdependent large economies like the EU and the USA. Within this more general model setting the case of dynamic inefficiency is of particular interest since the world economy changed from dynamic efficiency in the 1990s into dynamic inefficiency through 2000 - 2007 (IMF 2010, 208).1 Given that also under a positive natural growth rate national non-environmental welfare increases when emissions are unilaterally reduced in case of dynamic inefficiency, the prospects for bottom-up approaches to the global climate change problem have indeed bettered during this decade and coming years. 1

The average of yearly real growth rates of world GDP between 1992 and 1999 was 3.1% while the real interest rate was 3.8%. Between 2000 and 2007 the average real growth rate of world GDP was 4.2% while the real interest rate was 2.1% (IMF 2010, 208).

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Our modeling approach is based on an earlier strand of literature published after the unilateral fiscal expansion of the United States of America in the 1980s which aimed to understand the international consequences of unilateral fiscal policy among highly developed nations (Frenkel and Razin, 1986). In particular, unilateral fiscal expansion was shown to reduce capital accumulation (GDP growth) domestically and abroad (Lipton and Sachs 1983), and to impact negatively on the terms of trade of the debt-expanding country when this is a net foreign debtor (Zee 1987). As regards the factors which determine the non-environmental welfare effects of a unilateral expansion of public debt, Persson (1985) points to the net foreign asset position and the dynamic efficiency of the world economy: the domestic welfare loss is lower (or turns even to a welfare gain) when the more indebted country is a net foreign creditor given that the world economy is dynamically efficient. While there are common factors determining the welfare effects of unilateral fiscal and national climate policy, there is a remarkable difference regarding the impact on the terms of trade. Under the proviso that the countries are similar in terms of technology, fiscal policy does not affect the terms of trade, and hence welfare is not affected by this channel (Farmer and Friedl, 2010). In contrast, unilateral permits reduction policy hampers production in the policy implementing country since greenhouse gas emissions are an indispensable production factor. If the expenditure shares for the domestic and foreign commodity are constant and domestic supply is reduced, the domestic commodity gets more scarce, and hence the terms of trade improve which counteracts the negative welfare effect through the output channel (in a static context, see Copeland and Taylor, 2005). Building on Persson’s (1985) welfare analysis of fiscal policy albeit in a two-good context we will derive the domestic (and foreign) welfare effects of national climate policies within a two-country, two-good overlapping generations (OLG) model with producer greenhouse gas emissions. After determining the steady state (= GDP growth is stationary) effects of a unilateral permits reduction, we show how the resulting domestic and foreign welfare effects can be disentangled into an indirect effect via the channels of the real wage rate, the real interest rate and the terms of trade, as well as into a direct effect of permits reduction on the real wage rate net of a lump sum tax and on the real interest rate. The chapter is organized as follows. In the next section we provide a description of the two-country, two-good OLG model with log-linear intertemporal utility functions and CobbDouglas production functions. To mitigate disastrous climate change, the governments of both countries are assumed to establish markets for nationally tradable emission permits.2 After the derivation of the intertemporal equilibrium dynamics, existence and dynamic stability of steady state solutions will be thoroughly investigated. Comparative steady state effects of unilateral climate policies on terms of trade and on domestic and foreign private capital per capita are derived thereafter. The main part of the chapter is devoted to the analysis of the steady welfare effects of unilateral permits reduction policies under alternative combinations of net foreign asset positions and the dynamic efficiency respectively inefficiency of the interdependent economies. The chapter closes with some conclusions.

2

In view of the EU – USA example this assumption seems to be at odds with reality. However, since in all industrialized countries air pollution (including greenhouse gas emissions) is regulated, at least partially, by environmental law, we assume that the limitation of emissions by law in the country without tradable emission permits can be equivalently represented by a finite number of emission permits. Applied to the example of the USA, the amount of emission permits represents emission standards such as CAFÉ to curb pollution.

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TRADABLE EMISSION PERMITS IN A TWO-COUNTRY, TWO-GOOD OLG MODEL Consider two infinite-horizon economies named Home and Foreign which are interconnected through perfectly competitive markets for country-specific commodities and government bonds. Each country is composed of a large number of firms producing one country-specific commodity, respectively, and finitely lived households. Following the standard Heckscher-Ohlin trade-theoretic framework we assume that the life-cycle utility functions of younger households in Home and Foreign are identical and that the production technologies of firms in both countries are also identical with the exception of international differences in total factor productivity. Initially, Home and Foreign differ mainly by their levels of public debt per capita which is essential for the emergence of international trade before climate policy is implemented. Internationally differing public-debt levels also imply non-zero net foreign asset positions of both countries. For the real world application we have in mind, we assume that Foreign (representing the USA) is a large net foreign debtor while Home (representing the EU before Eastern enlargements) is a (small) net foreign creditor to the world economy. There are two tradable goods, indexed by x and by y * . Home specializes completely in

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the production of x and Foreign produces only y * 3 while both commodities are consumed by the households in each country. Part of the production in Home and Foreign is used for investment into country-specific real capital. Both goods are produced by employing labor and capital services, and commodity production causes a flow of greenhouse gas emissions. Younger households accumulate wealth by investing in internationally immobile real capital and internationally mobile government bonds, where the supply of government bonds per efficiency-weighted capita is constant over time (as in Diamond, 1965). Moreover, we assume exogenous and internationally identical growth rates of the work force and its efficiency in each country. For the sake of simplicity, the depreciation rate of real capital is set equal to unity in both countries. Regarding greenhouse gas emissions and their regulation by the establishment of a national permits trading system, we follow the established approach in closed-economy models (Ono, 2002; Jouvet et al., 2005a, b; Bréchet et al., 2009). Our model provides an open-economy extension of these closed-economy models and can thereby be used to analyze not only domestic effects but also international feedback effects of national climate policies in interdependent economies. We further assume that the country-specific caps on greenhouse gas emissions are exogenously set and changed. Time is discrete and indexed by t = 0,1, K . In each time period, two kinds of households overlap for one modeling period, namely the representative working household indexed by the superscript Y (stands for Young) and the retired household indexed by the superscript O (stands for Old). Each working household retires in the subsequent time period, whereas each retired household disappears by the end of the current period. Young households in both countries do not face a labor-leisure choice, and it is assumed for simplicity that each younger 3

By this assumption our model deviates from the Heckscher-Ohlin setting. Our model can be regarded as an OLG analogue to Obstfeld’s (1989) and Gosh’s (1992) two-country, two-good infinitely lived agent models.

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household in both countries supplies exactly one unit of labor in every period. There are Lt (

L*t ) younger households in period t in Home (Foreign), and hence Home’s (Foreign’s) aggregate labor supply equals Lt ( L*t ). Due to the long-term nature of climate policy it is not premature to assume full employment of younger households in both countries. Labor workforce and the services of the aggregate real capital stock in each time period are employed to produce jointly the country-specific commodity and greenhouse gas emissions. The production output of Home commodity x , denoted by X t , is generated by a technology described by the following Cobb-Douglas function

~ 1−α~ α~ X t = Z t M (at Lt ) (K t ) ,

(1)

whereby K t denotes the capital stock in Home, at is Home’s efficiency level per employee,

0 < α~ < 1 represents the production elasticity of capital in Home, and 0 < Z t ≤ 1 indicates an

index of the technology in use (Stokey 1998, 4). Higher values for Z t yield more goods but also more greenhouse gas emissions. Potential output is attained by using the most emission intensive technology, setting Z t = 1 . As mentioned above, the labor force in both countries evolves according to the common and exogenously given growth factor G L and labor efficiency in both countries changes over time due to the growth factor G a (labor augmenting technical progress) which is also exogenously given and does not differ among ~ countries. Finally, M > 0 denotes total factor productivity in Home. The emissions of greenhouse gases in time period t denoted by Pt are supposed to Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

depend positively on total output X t and on the technology in use (Ono 2002, 77):

Pt = Z tθ X t ,

(2)

where θ > 0 is a constant parameter. A larger θ indicates more emissions given the final output. Elimination of Z t between the production function (1) and the emission function (2) yields the following modified Cobb-Douglas production function

X t = M (at Lt )

1−α − β

(K t )α (Pt )β ,

(3)

~ where M := M θ (1+θ ) , 0 < α := α~ θ (1 + θ ) < 1 and 0 < β := 1 (1 + θ ) < 1 . Note that the output of Home’s commodity depends now on three factors of production, namely efficiency labor, capital and greenhouse gas emissions. In order to control greenhouse gas emissions Home’s government assigns in each period quotas on emissions to firms S i , i = 1,K, I which in the aggregate sum up to S = i S i .

∑

Emission permits could be freely traded as financial instruments among firms on the basis of the quotas. There is a competitive market for these permits, where the unit price is et . Each Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Karl Farmer and Andreas Rainer

firm takes the permit price as exogenously given from the permits market. If firm i emits Pit < S i ( > S i ) units, then it can sell S i − Pit units (buy Pit − S i units) of permits in the market at price et . In each period, the representative firm chooses K t , Lt and Pt to maximize the profit

Πt :

Π t = M (at Lt )

1−α − β

K t Pt − wt L t −qt K t − et (S − Pt ) , α

β

where wt denotes the real wage rate and qt is the rental price of capital in terms of output. Then the first-order conditions (FOCs) for profit maximization read as follows:

wt = (1 − α − β )Mat k t pt ,  α

qt = αMat kt

β

(4)

α −1

pt , 

 

(5)

α

β −1

 

(6)

et = βMat k t pt

β

 

, 

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where k t = K t (at Lt ) and pt = Pt (at Lt ) denote respectively capital input per efficiency capita and greenhouse gas emissions per efficiency capita. Clearly, FOC (4) says that the real wage rate is equal to the marginal productivity of labor input, and similarly FOCs (5) and (6) state that the real rental price of capital equals marginal productivity of capital input, and the real price of emission permits in Home is equal to the marginal productivity of greenhouse gas emissions, respectively. Profit maximization implies that firm’s revenues net of the payments to the production factors give a profit equal to the market value of the initial endowment of quotas. This excess profit is however collected by the government. In essence, this particular modeling of the permit system guarantees that although quotas are distributed to firms free of charge (‘grandfathered’), the permit allocation is non-distortionary. Besides the extra profits of firms the government receives tax revenue, which is scheduled as a per-capita lump-sum tax τ t , and the proceeds from newly emitted government bonds Bt +1 , such that the government is able to pay the interest it Bt on outstanding government bonds Bt > 0 and to repay these

bonds: Bt +1 + Ltτ t + et S t = (1 + it )Bt . In per-efficiency capita notation, the government’s budget constraint can be written as follows:

τ t = a t [(1 + it )bt − Gbt +1 − et S t (a t Lt )] ,

(7)

where bt = Bt (at Lt ) and G = G a G L denotes the natural growth factor. Since we are focusing on steady states below we assume as Diamond (1965) timestationary, per-efficiency capita government debt bt +1 = bt = b and moreover time-stationary,

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per-efficiency capita emission quotas s . We also assume that country-specific permits markets clear in each period, i.e. for Home:

pt = s .

(8)

Insertion of (4) – (6) into (7) implies under these assumptions that equation (7) can be rewritten as follows:

(

)

τ t = at αMs β kt α −1 − G − at βMs β k t α ,

(9)

whereby we assumed full depreciation of real capital in each time period and a no-arbitrage condition between the return factor on real capital qt and the return factor on government bonds 1 + it : qt = 1 + it . Taking into account the first-order condition for profit maximization (4), the real wage net of lump-sum tax of the younger household reads as follows:

(

wt − τ t = (1 − α )Ms β at k t − at αMs β k t α

α −1

)

−G b.

(10)

With the real net wage (10) the representative younger household in Home buys ctHY of the commodity produced in Home and ctFY of the commodity produced in Foreign while one foreign commodity unit costs 1 ht domestic commodity units and ht denotes Home’s terms of trade (= units of the Foreign commodity per unit of Home commodity). The remaining part of the net wage (10) is used by the younger household in Home for savings per capita sa t Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

which are invested in Home’s real capital (per capita) K t +1 Lt , in bonds emitted by Home government (per capita) BtH+1 Lt , and in bonds emitted by Foreign’s government (per capita)

Bt*,+1H Lt ,i.e. sat = K t +1 Lt + BtH+1 Lt + (1 ht ) Bt*,+1H Lt . Hence, the following budget

constraint holds during the working period of the younger household:

ctHY + (1 ht )ctFY + sat = wt − τ t .

(11)

When retired, the household in Home is subject to the following budget constraint:

(

) (

)

* *, H FO H ctHO +1 + (1 ht +1 )ct +1 = (1 + it +1 ) K t +1 Lt + Bt +1 Lt + 1 + it +1 (1 ht ) Bt +1 Lt .

(12)

The younger household in Home maximizes the following intertemporal utility function

max

FO ctHY ,ctFY ,ctHO +1 , ct +1 ,

[

]

FO ς ln ctHY + (1 − ς ) ln ctFY + η ς ln ctHO +1 + (1 − ς ) ln ct +1 ,

(13)

where 0 < ς < 1 ( 0 < ς < 1 ) denotes the utility elasticity (expenditure share) for the domestic (foreign) commodity and 0 < η < 1 is the future discount factor of the younger generation in Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Karl Farmer and Andreas Rainer

Home. It is not difficult to see from the retirement-budget constraint (12) that domestic real capital and domestic bonds per capita are perfectly substitutable for foreign bonds per capita. Thus, the younger household holds strictly positive quantities of all three assets when maximizing intertemporal utility only if the following no-arbitrage condition (= real uncovered interest parity condition) holds:

1 + it +1 ht . = ht +1 1 + it*+1

(14)

Taking into account the real uncovered interest parity condition (14) and maximization of (13) subject to the budget constraints (11) and (12) yields the following utility maximizing consumption quantities and optimal savings per capita:

ctHY =

ς 1+η

(wt − τ t ) , ctFY

=

1− ς ht (wt − τ t ) , 1+η

FO ctHO +1 = ςσ (1 + it +1 )(wt − τ t ) , ct +1 = (1 − ς )σ (1 + it +1 )ht +1 (wt − τ t ),

sa t = σ (wt − τ t ), σ ≡ η (1 + η ).

(15a)

(15b)

(16)

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Regarding the interpretation of (15a), notice that optimal current consumption of the domestic commodity stands in a positive, fixed proportion to the real wage rate net of taxes. The propensity to consume in youth the domestic commodity out of net wage income is equal to 1 (1 + η ) times the expenditure share for the domestic commodity, ς . Optimal working time consumption of the foreign commodity by the younger household in Home is positively dependent on the real net wage rate and on Home’s terms of trade. The propensity to consume in youth the foreign commodity out of net wage income is equal to 1 (1 + η ) times the expenditure share for the foreign commodity, 1 − ς . As regards the interpretation of (15b), it is obvious that optimal retired-period consumption of the domestic commodity depends positively on the retired-period real interest factor and on working-period real net wage while the proportionality factor is equal to the savings rate out of net wage income times the expenditure share for the domestic commodity. It is also apparent that optimal retired-period consumption of the foreign commodity depends positively on the retired-period real interest factor, on retired-period terms of trade and on working-period real net wage while the proportionality factor is equal to the savings rate out of net wage income times the expenditure share for the foreign commodity. Equation (16) transpires that due to the loglinearity of the intertemporal utility function optimal savings per capita are positively proportional to the net wage rate and are independent of the real interest rate. The proportionality factor equals the savings rate out of net wage income. Without going into detailed derivation as for Home, Foreign’s first-order conditions for profit maximization are stated as follows where all stared variables and parameters refer to Foreign:

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( ) (s ) α

wt* = (1 − α − β )M * at k t*

* β

, 

211

 

(4*)

( ) (s )

, 

 

(5*)

( ) (s )

. 

 

(6*)

qt* = αM * at k t* et* = βM * at k t*

α −1

α

* β

* β −1

The economic interpretation of (4*) - (6*) is similar to that of the FOCs (4) - (6), and it is also obvious that we assumed that the permit market in Foreign is cleared in each period, i.e.

pt* = s*

(8*)

However, notice, that the production elasticities of capital and greenhouse gas emissions in (4*) - (6*) are assumed to be equal to the corresponding production elasticity in Home while total factor productivities might differ among countries. Foreign younger households maximize an intertemporal utility function similar to (13) with the exception of a different time-preference parameter η * subject to working-period and retirement-period budget constraints similar to (11) and (12) above. The utility maximizing consumption quantities and optimal savings read as follows: *

ctHY =

(

(

*

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)

(

)

* 1−ζ 1 ζ , ctFY = wt* − τ t* wt* − τ t* , * * ht 1+η 1+η

)(

* * * * ctHO +1 = ζσ 1 + it +1 wt − τ t

) h1

(15a*)

(

)(

)

* * * * , c tFO +1 = (1 − ζ )σ 1 + i t +1 wt − τ t , *

(15b*)

t +1

(

)

sat* = σ * wt* − τ t* ,

(

(16*)

)

with σ * := η * 1 + η * and

( ) a (k )

wt* − τ t* = (1 − α )M * s *

(

)

β

* α t

* t

(

[

( ) (k )

− a t* αM * s *

β

* α −1 t

]

− G b*.

(10*)

)

b * = Bt* at* L*t and s * = S t* a t* L*t are exogenously given. As usual, besides FOCs for profit maximization and for intertemporal utility maximization and national market clearing conditions for permits trading (8) and (8*), further market clearing conditions are needed to obtain an international general equilibrium solution in each period and across periods. The condition for the clearing of the output market (in per efficiency-capita terms) in Home reads as follows:

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Karl Farmer and Andreas Rainer

(

[ (

)

)]

(

)[ (

)]

(

)(

)

x t = (1 a t )c tHY + 1 G L (1 a t )c tHO + Gk t +1 + L*t Lt a t c tHY + 1 G L L*t Lt a t c tHO , (17) *

*

whereas foreign product market clearing demands:

(

)

(

*

)(

)

(

*

)

y t* = 1 a t* c tFY + 1 G L 1 a t* c tFO + Gk t*+1 + Lt a t* L*t c tFY + 1 G L Lt a t* L*t c tFO . (17*)

The world market for Home government bonds clears according to:

Bt = BtH + BtF ,

(18)

and symmetrically for foreign governments bonds we have:

Bt* = Bt*,H + Bt*,F .

(18*)

Clearing of the world asset market demands that the total amount of savings (in terms of Home’s output) worldwide equals the total supply of assets from Home and Foreign:

(

)

[

)]

(

sat at + (1 ht ) L*t (Lt at ) sat* = G k t +1 + b + (1 ht ) k t*+1 + b * .

(19)

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INTERTEMPORAL EQUILIBRIUM, EXISTENCE AND STABILITY OF STEADY STATES Using the FOCs for profit maximization in Home (4) - (6) and in Foreign (4*) - (6*), the utility maximizing consumption functions in Home (15a) - (15b) and in Foreign (15a*) (15b*), the optimal savings function (16) and (16*) as well as the market clearing conditions (8) and (8*), (17) - (18) and (17*) - (18*), and (19), we derive next the intertemporal equilibrium dynamics of ht , k t +1 , kt*+1 , t = 0,1, K consisting of three difference equations in each period. To obtain the first difference equation, we multiply Foreign’s commodity market clearing condition (17*) on both sides by at* L*t (1 − ς ) and Home’s commodity market clearing

condition (17) on both sides by at Lt ht ς . Then, we subtract the former result from the latter after having inserted the optimal consumption functions (15a) - (15b) and (15a*) - (15b*) respectively. The final step is to substitute the FOCs for profit maximization (4) - (6) and (4*) - (6*) for the real factor prices as well as (10) respectively (10*) for the real wage rates net of lump-sum taxes within the consumption functions (15a) - (15b) and (15a*) - (15b*) respectively. As a consequence of these easy but tedious operations, the following first difference equation of the intertemporal equilibrium dynamics results:

ht k t +1 −

ς 1−ς

k t*+1 = ht (M G )s β k t − α

(M 1−ς ς

*

)( ) (k )

G s*

β

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* α t

. 

(20)

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213

The second equation of motion is obtained by starting from the asset-market clearing condition (19) and inserting into (19) the optimal savings functions (16) respectively (16*). Since we assumed above that the population growth factor is internationally identical, it is not restrictive to set Lt = L*t . Then, after substituting (10) respectively (10*) for the real net wage rates in Home respectively Foreign, the second difference equation of the intertemporal equilibrium dynamics reads as follows:

ht k t +1 + k t*+1 = ht σ (M G )s β k t

(

)( ) (k ) [(1 − α )k

+σ * M * G s

* β

* α −1

t

α −1

* t

[(1 − α )k t − αb] − ht b(1 − σ ) +

]

(

)

− αb * − ht b * 1 − σ * . 

(21)

The third difference equation follows almost immediately from real uncovered interest parity condition (14) after taking into account the no-arbitrage conditions 1 + i t = q t respectively 1 + it* = qt* and substituting FOC (5) respectively FOC (5*) for the real interest factors in Home respectively Foreign:

ht +1

( )

M * s* = ht Ms β

β

⎛ k t*+1 ⎞ ⎟ ⎜ ⎜k ⎟ ⎝ t +1 ⎠

α −1

. 

 

(22)

Equations (20) - (22) represent a three-dimensional system of difference equations for

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determining the variables ht , k t +1 and kt*+1 . In its structure the intertemporal equilibrium dynamics depicted by equations (20) - (22) is similar to the equilibrium dynamics as investigated by Farmer et al. (2010) and it coincides with the intertemporal equilibrium model of Farmer (2010) however without emission permits. Nevertheless, the intertemporal general equilibrium dynamics (20) - (22) generalizes the corresponding equilibrium dynamics in Farmer et al. (2010) by both considering a non-zero natural growth rate and internationally divergent saving rates.4 In addition to differences in the saving rates, the two countries in our intertemporal general equilibrium model differ also by their levels of government debt per efficiency capita. As developed originally by Zee (1987) in two-country OLG model without emission permits and more fully elaborated by Farmer et al. (2010) in a two-country OLG model with emission permits but identical saving rates, there is a close relation between public debt (per efficiency capita) and the net foreign asset position of Home (Foreign) denoted Φ t ( Φ *t ) which is defined as the difference between Home’s (Foreign’s) investment and Home’s (Foreign’s) aggregate savings, i.e.

Φ t +1 = K t +1 + Bt +1 − Lt σ (wt − τ t ) , 

4

 

(23)

The inclusion of internationally divergent saving rates clearly enhances the empirical applicability of our model in view of the significantly differing saving rates between some advanced countries (i.e. USA) and Asian economies (Japan, China).

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Karl Farmer and Andreas Rainer

(

)

Φ *t +1 = K t*+1 + Bt*+1 − L*t σ * wt* − τ t* . 

 

(23*)

Using the per-efficiency capita version of (23), φ t +1 = Φ t +1 (at +1 Lt +1 ) , and (23*),

(

)

φt*+1 = Φ *t +1 at*+1 L*t +1 , the asset market clearing equation (21) can be alternatively written as ht = −

φ t*+1 .  φ t +1

 

(24)

Obviously sgn φt +1 = − sgn φt*+1 because ht > 0 . It is less obvious which country is the net foreign debtor and which one is the net foreign creditor country because the net foreign asset position represents an endogenous variable and not an exogenous parameter in a twocountry model. Farmer et al. (2010, 519) are able to show that under internationally identical savings rates the country with the relatively larger public debt per-efficiency capita is the net foreign debtor while the other country is the net foreign creditor country. In view of the empirical differences in the public debt to GDP ratios between China and the USA, the net foreign-creditor position of China and the net foreign-debtor position of the USA seem to be consistent with our model design. However, under significant differences in the saving rates across countries the highly indebted country might also become a net foreign creditor mimicking the Japanese example. Up till now we did not investigate whether the intertemporal equilibrium dynamics depicted by the difference equations (20) - (22) enable an economically feasible solution

ht > 0 , k t +1 > 0 , k t*+1 > 0 for t = 0,1, K . Of particular interest is the question whether the equilibrium dynamics approaches a feasible steady-state solution defined as

(h, k , k ) = (h , k , k ) = (h

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*

t

t

* t

* t +1 , k t +1 , k t +1

),    

(25)

as time goes to infinity. The application of the definition of a steady state (25) onto the intertemporal equilibrium (20) - (22) yields the following functional relationships among steady-state variables:

[(

k = μk , h = μ ς (1 − ς ), μ = M (s *

(

)

*

) ) (Ms )]

* β

(

β

1 1−α

, 

(26)

)

k = H k ; b, b* = Γ(k ;ϑ ) + (1 − ς )ΔσΔΓ k ; b* ,

Γ(k ;ϑ ) = σ (M G )s k β

(

)

α −1

ΔΓ k ; b = (M G )s k *

β

[(1 − α )k − αϑ ] − ϑ (1 − σ ), [(1 − α )k − α b* μ ]+ b* μ ,

α −1

(27)

where Δσ = σ * − σ denotes the difference between the saving rates of the two countries and

ϑ = ς b + (1 − ς ) b * μ is an average of public debt levels in Home and Foreign weighted by

the common expenditures for the domestic and foreign commodity and the ratio of domestic

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and foreign emission quotas. Acknowledging the concavity of Γ and ΔΓ in k , the following existence proposition can be stated.

(

)

Proposition 1: For each parameter set M , M * , G, s, s * , ς , α , σ , Δσ there exists some

b >0

and for each

(b, b )∈ (0, b )× (0, b ) *

*

( )

b ∈ 0, b

b * (b ) > 0

there exists a

exactly two steady states

(h, k , k ) = (μ ς *

such that for all

(1 − ς ), k j , μk j ) j = L,H

with

[

(

0 < k L < k H < k = (M G )s β (1 − α ) ςσ + (1 − ς )σ *

)]

1 1−α

(28)

occur, where k L and k H are solutions of (27). For the special case Δσ = 0 , b * is given by

(

)

b* = h b −b . The idea behind the proof of Proposition 1 is illustrated in Figure 1 which is based on the

(

)

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parameter set M , M * , G, s, s * , ς , α , σ , Δσ = (1,1,1,1,1,0.5,0.3,0.375,0) .

Figure 1. Existence of Steady States.

More generally, at k L and at k H the concave function Γ + (1 − ς )ΔσΔΓ cuts the 45° line. The function Γ + (1 − ς )ΔσΔΓ is decreasing in both b and b * and therefore only for

(b, b ) < (b , b (b)) two steady state solutions occur. The claim (b , b ) < ∞ *

*

[Γ + (1 − ς )ΔσΔΓ] = −∞ .  lim * 2

(b,b )→∞

*

 

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2

is true due to (29)

216

Karl Farmer and Andreas Rainer For

(b, b ) = (b , b ) *

*

the two steady states coincide, i.e. k L = k H . For the same

(

parameter set as used in Figure 1, the lower and higher steady-state capital stocks k L , k H

(

)

)

associated with ϑ ∈ 0, ϑ := ςb are presented in Figure 2.

Figure 2. Steady States Dependent on Weighted Public Debt.

As can be seen from steady-state relations (26) and (27), the steady-state solutions

(h, k , k ) depend on the policy parameters (b, b , s, s ) . An infinitesimal change db for example shifts the steady-state solution by (dh, dk , dk ) . This shift can be derived by total *

*

*

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*

~

differentiation of (26) and (27) with respect to b and on defining 1 + i := (1 + i ) G . The

results read as follows:

~ 1 ∂k * ∂k 1+ i σ = = −ς μ ∂b ∂b 1− Hk

⎧< 0 k = k H ,  ⎨ L ⎩> 0 k = k

(30)

where H k denotes the partial derivative of H with respect to k . In order to determine the sign of the derivative in (30), the sign of the denominator and of the numerator is needed.

( )

( )

Regarding the sign of the denominator, notice that H k k H < 1 and H k k L > 1 as a

consequence of the fact that H (k ) is concave and that the function H intersects the 45°-line at k L from below and at k H from above. As concerns the sign of the numerator we know

~

~

that i ≥ −1 > − 1 σ because 1 + i > 0 always holds. Thus, the sign of the derivative in (30) depends on the sign of 1 − H k , and therefore the sign of the derivative in (30) holds as claimed. Moreover, dh db = 0 , i.e. a variation in public debt per efficiency capita does not influence the terms of trade.

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As a crucial implication of the existence-result of Proposition 1 and the comparative static result in (30), Proposition 2 below provides a strong lower bound to the steady state interest rate i .This information will prove helpful when we investigate the dynamic stability of steady states. Proposition 2: For k = k H the steady state interest rate i is an increasing function of

b and b * . The interest factor is strongly bounded from below and finite, namely

αG ≤ 1 + i < ∞ .  ςσ + (1 − ς )σ * (1 − α )

[

]

(31)

Proposition 2 which is proven in the Appendix follows immediately from k = H (k ;0,0 ) ,

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(27) and (30). The lower and an upper bound for the interest factor are illustrated in Figure 3 based on the same parameter set as Figure 1.

Figure 3. Lower and Upper Bounds on the Interest Factor.

A Corollary to Proposition 2 yields the following necessary and sufficient characterization of dynamic efficiency (dynamic inefficiency) of a steady-state solution: A steady solution is dynamically efficient (dynamically inefficient), i.e. 1 + i > G ( 1 + i < G )

(

) ( ) (

)

for all b, b * ∈ 0, b × 0, b * if and only if

ςσ + (1 − ς )σ * >

α ⎛ α ⎞ * ⎜ ςσ + (1 − ς )σ < ⎟. 1−α ⎝ 1−α ⎠

(32)

Next, (local) dynamic stability of the intertemporal equilibrium depicted by (20) - (22) in

(

)

(

the neighborhood of a steady-state solution h, k , k * can be examined. To this end, let b, b * Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

)

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Karl Farmer and Andreas Rainer

(

)

be chosen such that two steady states k L , k H exist due to Proposition 1. Then the following Proposition 3 holds (the proof can be found in the Appendix). Proposition 3: Assume the existence of two distinct steady states k L < k H of (20) (22) defined by (26)-(27). Then k H is (locally) saddle path-stable, whereas k L is (locally) saddle path-unstable. Note, that saddle path-stability in the present context implies the existence of a onedimensional unstable submanifold of R 3 , because the terms of trade ht constitute a forwardlooking jump variable and both k t and kt* are sluggish.

WELFARE EFFECTS OF UNILATERAL CLIMATE CHANGE MITIGATION POLICIES

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After being assured that there are feasible policy parameters which ensure the existence of one saddle-path stable steady state we explore in this section steady-state (long-run) welfare effects of unilateral policies to mitigate climate change in the neighborhood of k H . To pursue the objective to reduce the risk of catastrophic climate change the government in Home (Foreign) seeks to reduce greenhouse gas emissions by reducing the number of quotas on emissions in Home (Foreign). Since after Copenhagen 2009 national bottom-up approaches to global climate policy proliferate, we assume that each country decides unilaterally, i.e. without coordinating its reduction policy to the reduction policy of the other country, how much to reduce its emission permits. In order to single out the effects of national quota reduction on domestic and foreign capital formation and on the terms of trade as well as on domestic and foreign welfare as simple as possible we assume that private agents do not anticipate the quota reduction, and assume that the quota reduction is permanent. Before investigating the steady-state welfare effects we analyze the effects of a marginal reduction of the number of quotas on greenhouse gas emissions in Home (while leaving the number of quotas in Foreign unchanged) on domestic and foreign private capital perefficiency labor and on Home’s terms of trade. The effects on the terms of trade, on foreign capital per-efficiency labor and on domestic capital per-efficiency labor read as follows:

β s dh s dk * s dk β =− , * , = − h ds 1 − α k ds k ds 1 − α β s dk = k ds 1 − α

(33)

~ ⎛ b 1 + σ i ⎞ ⎧> 0 k = k H ⎟⎨ ⎜⎜1 + ς ,  k 1 − H k ⎟⎠⎩< 0 k = k L ⎝

(34)

~

where again the definition 1 + i := (1 + i ) G is used. (33) and (34) follow from partial differentiation of (26) and (27) with respect to

s , and acknowledging (30),

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dk ds = H k dk ds + H s and (s k )H s = β (1 − α )[1 + σ (1 + i ) G − σ ] as proven in the Appendix. To facilitate the economic interpretation of the comparative steady-state results in (33) and (34) notice that a quota reduction policy is formally equivalent to ds < 0 . Thus, the negative sign of the first derivative in (33) implies that Home’s terms of trade increase when Home’s number of quotas on greenhouse gas emissions is reduced. This result might at first sight appear surprising but closer inspection provides the economic intuition for the result. The quota reduction reduces greenhouse gas emissions in Home. Since greenhouse gas emissions are an indispensable production factor and full employment of all factors prevail in both countries, Home producers respond to the quota reduction by decreasing the output of Home’s commodity. On the other hand, consumers in both countries allocate a fixed proportion of their real net wage to the consumption of both commodities. With unchanged expenditures for Home’s commodity and a diminished output the relative price of Home’s commodity increases, i.e. Home’s terms of trade rise. It follows from (34) that in the neighborhood of the larger steady state the sign of the derivative is positive which means that a unilateral permits reduction in Home diminishes private capital per-efficiency labor. As a larger public debt, a more stringent policy to mitigate climate change crowds out private capital in the policy implementing country. The right-hand side of (34) also transpires that the crowding out-effect increases with larger public debt in the policy implementing country. Finally, from the right-hand side of the second derivative in (33) it follows that unilateral quota reduction on domestic emissions crowds out not only domestic private capital but due to international asset market interdependence also foreign private capital is crowded out albeit to a lesser extent. The reason for crowding out of steady-state private capital in both countries is the first steady-state relation in (26), i.e. the international real interest parity condition. Since the quota reduction in Home diminishes potential output private capital in Home is diminished too. Less private capital in Home increases due to diminishing returns the real interest rate while the quota reduction counteracts to some extent the increase in domestic real interest rate. International real interest parity demands that the foreign real interest rate rises also which in turn leads due to diminishing returns to a decline of foreign private capital. The analysis of the steady-state impacts of national permits reduction shows so far that the terms of trade of Home are positively affected while domestic and foreign private capital per-efficiency capita are negatively impacted. While these comparative steady-state effects are unambiguous, this is a priori not the case for the associated effects on consumer welfare in Home and in Foreign. From the point of view of political economics (Persson and Tabellini 2002, chap. 2) it is the welfare of the median voter which determines the political decisions in democratic political systems. Hence, to know how the welfare of the younger households is affected by policies to mitigate climate change is crucial for evaluating the prospects for the implementation of these policies in democracies. Disregarding the rather long-run positive effects on the natural environments and the benefits future generations will gain from the environmental improvements5, it is clear that the quota on emissions of greenhouse gases will be reduced by politicians in Home (Foreign) if the steady-state welfare of the younger household in Home (Foreign) increases, otherwise nothing will be done. 5

Bednar-Friedl and Farmer (2010, 985) include the environmental benefits in their welfare analysis.

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In order to analyze the sign of the welfare change in response to a marginal reduction of the number of national emission quotas, notice first that the maximal life-time welfare of the younger household in Home (13)6 depends through optimal working- and retirement-period consumption quantities (15) indirectly on the real wage rate net of lump-sum taxes, on the real interest rate and on the terms of trade. Second, we know from equations (10) and (10*) that the real wage net of lump-sum taxes per-efficiency capita is determined by private capital per-efficiency capita and the assigned number of quotas on greenhouse gas emissions in Home (Foreign). Third, acknowledging equations (5) and (5*) it is immediate that the real interest factor in Home (Foreign) is also determined by private capital per-efficiency capita and the assigned number of quotas on greenhouse gas emissions in Home (Foreign). In sum, the purely economic welfare effects of national permit policies can be differentiated by effects through changes in private capital stocks per-efficiency capita ( dk ds > 0 , dk * ds > 0 ) and the terms of trade ( dh ds < 0 ) as well as direct impacts of a change in s

on factor prices ( ∂ (w − τ ) ∂s > 0 , ∂ (1 + i ) ∂s < 0 ). To derive the steady-state welfare effects in Home of a national permits reduction in Home (Foreign), we start with the definition of Home’s steady-state indirect intertemporal utility function V (I ,1 + i , h , s , s *) ≡ ζ ln {[ζ (1 + η )]I } + (1 − ζ ) ln {[(1 − ζ ) (1 + η )]hI } + ηζ ln [ζσ (1 + i )I ] + η (1 − ζ ) ln [(1 − ζ )σ (1 + i )hI ] with I t ≡ (w t − τ t ) a t as real wage rate

net of lump-sum tax per-efficiency capita. Total differentiation of V with respect to holding s * fixed yields:

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dV 1 dh ⎞ σ d (1 + i ) ⎛ 1 dI = (1 + η )⎜ + + (1 − ζ ) ⎟, ds h ds ⎠ ⎝ I ds 1 + i ds

1 dI [(1 − α )k − αb] d (1 + i ) (1 − α )(1 + i ) dk β (1 + i )k = + = I ds αGI ds αGI ds αGIs

⎡ b ⎞⎤ ⎛ ⎢1 + αΞ (k )⎜1 + k ⎟ ⎥ , ⎠⎦ ⎝ ⎣

β sa d (1 + i ) ~ Ξ(k ) ≡ ς (b k ) 1 + σ i (1 − H k ) , = −(1 − α )Ξ (k ) 1 + i ds 1−α

(

)

Insertion of the expressions for (1 I )(dI ds ) and sa (1 + i ) d (1 + i ) ds into dV ds gives:

1 − α sa dV = AΞ (k ) + B β 1 + η ds , with A = (1 − α )

k 1+ i (1 + b k ) − σ (1 − α ) , B = (1 − α ) k 1 + i − (1 − ς ) . I αG I G

(35)

With these expressions for dV ds at hand, we are now able to state under which conditions national (unilateral) permits reduction leads − in spite of positive welfare effects as

6

Analogously for Foreign!

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the increase in Home’s terms of trade and the interest factor7 − nonetheless to a decrease of welfare in Home and in Foreign. Proposition 4: For σ = σ * and a dynamically efficient world economy (i.e. 1 + i > G ), the welfare of both Home and Foreign decreases if the number of quotas on greenhouse gas emissions s is reduced in Home. Proof. To show dV ds > 0 , it suffices to show that both A and B are positive (note that Ξ > 0 for k = k H ). The first part of the proof is therefore completed if

(

)

~ k 1 + i (1 + b k ) > Iσ and

(

)

~ k (1 − α ) 1 + i (1 + b k ) > αI .

(36) (37)

(

~

)

~

~

But (36) holds because I = (k α )(1 − α ) 1 + i − b i and i = (1 + i ) G − 1 > 0 hold as assumed. But assuming this also for (37) – using (31) for σ = σ * – leads to

~ ~ ~ i + b k > −2 i b k , which is true by assumption i > 0 . dV * ds > 0 is shown in the

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appendix. Proposition 4 points out that for such values of the exogenous parameters, i.e. G, α , β ,η , ζ that the exogenous growth rate of the world economy is smaller than the endogenous real interest rate unilateral permits reduction in Home (national climate policy) leads unambiguously to a decline of consumer welfare in both countries. Intuitively, this result is not very surprising. However, in view of the counteracting welfare effects of increasing terms of trade and rising real interest rate on the one hand and decreasing real wage rate net of lump-sum tax it is not obvious at all. It is also worth mentioning that Proposition 4 generalizes Proposition 2 in Bednar-Friedl and Farmer (2010, 985-986) in so far as dV ds > 0 holds irrespective of the fact whether Home is a net foreign debtor or a net foreign creditor. This leads us to the question for the economic rationale for the unambiguity of the overall welfare effect of unilateral national climate policy in spite of the counteracting net wage and terms of trade and interest rate effect. When the parameter set is such that at the saddle-path stable steady-state solution the real interest rate is larger than the natural growth rate, we start from a state of under-accumulation of private capital. Reducing s reduces private capital in Home and in Foreign and hence aggravates under-accumulation and the welfare loss caused by deviation from the Golden Rule (= real interest equals natural growth rate) is enlarged. Finally, Proposition 4 helps us to understand better why in the 1990s the disincentive among advanced countries to implement unilaterally a more stringent climate policy was larger than in the decade thereafter: as mentioned in the Introduction it is a matter of fact that during the former decade the world economy was in a state of dynamic efficiency and hence national climate-political activities were certainly associated with national welfare loss while in the latter decade dynamic inefficiency of the world economy (IMF 2010, 208)

7

Following Ono and Shibata (2005), the welfare effects of rising terms of trade and of the real interest rate are called the „terms-of-trade “ and the „interest-rate effect“. Moreover, the welfare changes through the real wage net of lump-sum taxes are called the “wealth effect”.

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does not unambiguously imply national welfare losses as a consequence of stricter national policies to mitigate global climate change. The question, which of the two countries suffers more (in relative terms) from a reduction of crucially depends on the net foreign asset position φ , which was introduced in (23). To

~

simplify notation, we set again 1 + i := (1 + i ) G .

~

Proposition 5: For σ = σ * it is true that i φ > 0 implies dV ds > dV * ds .

(

~

)

~

Proof: Equations (35) and (A.6) – using I = (k α )(1 − α ) 1 + i − b i - lead to * * dV dV * ~ ⎛ k + b k + b ⎞⎟ ~ > ⇔ IΞ(1 − α ) 1 + i ⎜⎜ − > −b i . * ⎟ ds ds I ⎝ I ⎠

(

)

Using φ = k + b − σI and φ * = k * + b * − σI * , we obtain for φ > 0 and φ * = −hφ that * dV dV * ~ ⎛φ φ ⎞ ~ > ⇔ IΞ(1 − α ) 1 + i ⎜⎜ − * ⎟⎟ > −b i , ds ds ⎝I I ⎠

(

)

which completes the proof. Proposition 5 shows that if (i) the saving rates are internationally identical, (ii) the world economy is dynamic efficient, and (iii) Home is a net foreign debtor, i.e. φ > 0 , then the

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welfare loss in Home exceeds the welfare loss of Foreign, i.e. dV ds > dV * ds when Home

unilaterally reduces the number of quotas on greenhouse gas emissions. Not surprisingly, in comparing the welfare effects across countries the net foreign asset position of the countries and thus their international interdependence matter! In order to provide an economic intuition for the result in Proposition 5 remember that the reduction of quotas on greenhouse gas emissions in Home crowds out private capital in both countries, and the world wide real interest rate rises. By the rise of the interest rate income and hence welfare is redistributed from workers/taxpayers to wealth owners in both countries. In the case of Home being a net foreign debtor, some wealth holders in Home are foreign residents and hence the consumption possibilities (welfare) for the Home economy are reduced. Thus, the welfare loss of a unilaterally strengthened climate policy in a net foreign-debtor country is larger than if Home were a net foreign creditor country. Even if it is true that national politicians do not compare the domestic to the foreign welfare consequences of their own policies, the result of Proposition 5 suggests why net foreign debtor countries have a larger disincentive to adopt a stricter national climate policy or to implement obligations from an international treaty like the Kyoto-Protocol domestically. Applying this suggestion empirically, the EU-US divide in multilateral climate policy of the 1990s comes to one’s mind. While the USA became the largest net foreign debtor to the world economy, the EU-15 was a net foreign creditor to the rest of the world (IMF 2006, 74). Acknowledging the dynamic efficiency of the world economy until the beginning of 2000, Proposition 5 explains why EU-15 as a net foreigncreditor area acted as forerunner in implementing the obligations from the Kyoto-Protocol by

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introducing in 2005 the EU ETS while the USA withdrew from the Protocol and did not agree (so far) on an internationally binding emissions reduction target. Moreover, it is worth mentioning that the differences in the sign and the magnitude of the net foreign asset position of a country makes observable international differences in climate policy better understandable but would also follow from the perspective of a global social planner who has to accept the fact that the individual countries fail to agree on a global climate policy (i.e. the “first-best” solution). Bednar-Friedl and Farmer (2010, 986) show in their Proposition 3 that a global social planer who takes not only the domestic but also the foreign welfare effects of a national permits reduction into account, and compares a permits reduction in Home to that in Foreign, favors a more stringent permit policy in the net foreign creditor and not in the net foreign-debtor country since the sum of the domestic and the foreign welfare loss of national permits reduction is less in the net foreign creditor than in the net foreign-debtor country. As a related point, it is also interesting to ask the question whether a net foreign creditor country, that has unilaterally implemented a more stringent policy of emission reduction, should strive to achieve a multilateral agreement which requires the net foreign-debtor country to implement a stricter policy to mitigate climate change too. With Proposition 4 are Bednar-Friedl and Farmer (2010, 986) able to answer this question albeit under some additional assumptions concerning basic parameters. The authors speak of a multilateral policy when the level of global permits reduction is exogenously fixed and both countries agree to reduce national quotas on greenhouse gas emissions according to exogenously fixed shares. They find that “it is beneficial for Home in terms of her welfare to achieve a multilateral permit reduction instead of a unilateral domestic one.” (Bednar-Friedl and Farmer, 986). This result is true independent of whether Home is a net foreign-creditor or net foreign-debtor country. To provide an economic intuition for the result that multilateral policy is less welfare reducing than unilateral climate policy notice that in case of equal-reduction burden-sharing between both countries the terms-of-trade effect vanishes while the effects on private capital stocks are more evenly spread across countries than in case of unilateral policy. However, since the welfare reducing effect through the decreased real wage rate net of lump-sum taxes is always larger than the welfare increasing effect of higher terms of trade (and interest rate), the welfare loss of unilateral permits reduction is larger than that of a multilaterally coordinated permits reduction. Finally, it remains the question, whether for a country, which has not implemented a unilateral permits reduction or has withdrawn from a multilateral agreement as the USA, it is beneficial of being affected by the already implemented unilateral policy by the other country than to accord to a multilateral agreement. Again under some additional parameter restrictions, Bednar-Friedl and Farmer (2010, 986-987) are able to show that in a dynamically efficient status of the world economy a net foreign-debtor country suffers from a lower welfare loss when it unilaterally implements a permits reduction than when it agrees to a more even multilateral permits reduction. The reason is that an assumed unilateral permits reduction abroad (i.e. in the EU) generates less welfare loss in Home (USA) than a balanced reduction of permits in Foreign and Home (multilateral policy) because the welfare loss triggered by the reduction of the net real wage in the country which does not reduce the permits is smaller than under a multilaterally agreed reduction. As a consequence, this result might help to explain why the USA both after their withdrawal from the Kyoto-Protocol and the implementation of the EU ETS did not much engage even in national climate policy.

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However, it is important to notice that the results reported so far from Bednar-Friedl and Farmer (2010) presume dynamically efficiency or the Golden Rule for the world economy, while the authors are unable to get unambiguous results under dynamic inefficiency. As mentioned above, since 2000 the world economy has empirically entered a stage of dynamic efficiency (IMF 2010, 208). Thus, the question arises whether in view of the recent empirical relevance of dynamic inefficiency unambiguous results beyond Bednar-Friedl and Farmer (2010) can be obtained which address incentives for unilateral climate policy even in a large net foreign-debtor country like the USA. However, as a result of intensive analytical investigation, the answer to this question must in general remain ambiguous. Nonetheless, there are plausible structural parameter values for which it can be numerically shown that under dynamic inefficiency even a large net foreign creditor country will gain by pro-actively (unilaterally) reducing its quota on greenhouse gas emissions than awaiting the welfare consequences of emission reduction in Foreign. Since this claim holds only for some numerical values of structural parameters, we conclude by formulating it as a suggestion. Suggestion. Under dynamic inefficiency and Home being a net foreign debtor, the welfare loss of a unilateral permits reduction in Foreign is larger than that of permits reduction in Home.

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CONCLUSION This chapter investigates the effects of national climate policies defined as unilateral reductions of quotas on greenhouse gas emissions on terms of trade, capital accumulation and welfare in interdependent, equally advanced economies under a positive natural growth rate. After setting up the two-country (Home, Foreign), two-good general equilibrium model with two-period lived overlapping generations we derive the intertemporal equilibrium dynamics of Home’s terms of trade, and of Home’s and Foreign’s private capital stocks per efficiency capita. When public debts per efficiency capita are not too large, the dynamic system exhibits two steady state solutions of which the one associated with higher private capital stocks in Home and Foreign is saddle-path stable while the other one is saddle-path unstable. When Home unilaterally reduces the cap on greenhouse gas emissions while Foreign’s cap remains unchanged (unilateral climate policy), Home’s terms of trade increase (Foreign’s terms of trade decrease) since Home’s commodity becomes in relation to the fixed expenditure shares more scarce. With rising terms of trade, however, private capital stocks are crowded out in both countries, but the crowding-out effect is stronger in the country which reduces the cap. Thus, while both countries grow more slowly than without a stricter climate policy, domestic growth is affected more strongly than growth in Foreign because factor price diminishing effects of cap-reduction in Foreign are lacking. To evaluate the overall effect of rising terms of trade and rising interest rate on the one hand and falling capital stocks on the other hand, we investigate the steady-state welfare change for younger households by differentiating their indirect life-cycle utility function with respect to the number of quotas on greenhouse gas emissions in Home. While Home’s terms of trade improvement is clearly welfare enhancing since Home’s households can buy more foreign goods, a stricter national climate policy has also welfare consequences through factor prices: the real wage rate net of lump-sum taxes declines, while the real interest factor (= real

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rental price of capital) and the real permit price increase. In line with the literature, these welfare effects are called the terms of trade effect, the interest effect and the wealth effect. Our first main result with respect to the welfare effects of national climate policies is that under dynamic efficiency of the world economy (real interest rate larger than natural growth rate) a stricter cap on national greenhouse gas emissions diminishes unambiguously the welfare in both countries. While the welfare decline as such is not surprising it comes as a surprise that the counteracting terms of trade and interest effects on the one hand and the wealth effect on the other hand can be unambiguously resolved. The main reason is that under dynamic efficiency a stricter climate policy increases capital under-accumulation and hence the welfare loss from the divergence from Golden Rule welfare maximum. Our second major result emerges when comparing the domestic and foreign welfare effects caused by a reduction of the number of Home’s quota on greenhouse gas emissions. If the world economy is dynamically efficient and Home is a net foreign debtor, the welfare loss in Home is unambiguously larger than in Foreign. In the contrary case, in which Home is a net foreign creditor the welfare loss in Home is less than in Foreign. Thus, there is a burdenshifting effect through international interdependency. National permits reduction leads to an increase of the worldwide real interest rate and hence in both countries to a redistribution of income from tax-paying to wealth-owning households. When Home is a net foreign creditor, some wealth owners in Foreign are Home residents and hence the rising interest revenues from the ownership of Foreign’s government bonds enlarge the revenues of Home’s younger households. As a consequence, Home’s consumption possibilities and thus the welfare of Home’s younger household increase in the case of Home being a net foreign creditor. Reporting results from Bednar-Friedl and Farmer (2010) we further point out that it is even optimal from the point of view of a global social planner that a net foreign creditor country and not net foreign debtor countries reduce unilaterally emission permits. Moreover, if the growth rate of the world economy is less than the real interest rate in steady-state equilibrium, multilateral climate policy is preferable to unilateral permits reduction irrespective of the net foreign asset position of the country considered. When one of the two countries has already unilaterally implemented a stricter climate policy, then in the case of dynamic efficiency (including the Golden Rule) and irrespective of the net foreign asset position the other country is better off by awaiting the negative welfare effects caused by foreign permits reduction than becoming climate-politically active by itself. Bednar-Friedl and Farmer (2010) are unable to state any unambiguous welfare effects when the world economy is dynamically inefficient. Since the beginning of 2000 the growth rate of the world economy is larger than the real interest, and thus the incentive for a large net foreign debtor-country to implement a unilateral permits reduction instead of awaiting the welfare loss caused by the permits reduction abroad might have been increased. However, while there are certainly some admissible combinations of model’s parameters, we are unable to state a general proposition. Some interesting lessons can be drawn from our theoretical analysis. First, in the 1990s when empirically the growth rate of the world economy was less than the real interest rate, there were no good incentives for unilateral permits reduction while multilateral approaches like the Kyoto-Protocol were relatively preferable. However, the incentives to act unilaterally to mitigate climate change were larger for net foreign creditors like the EU-15 than for net foreign debtors as the USA. When the EU credibly announced to implement a system of permits trade, there remained much welfare economic rationale for the climate political

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reluctance of the USA, because it was less costly for the latter to bear the spill-over effects from the EU than to implement an own permits trade. Thus our dynamic general equilibrium analysis in this chapter and in earlier papers for two equally developed and internationally interdependent countries explains why unilateral (and multilateral) policies to mitigate global climate change is not in the national interest of some highly developed economies. It is an open question whether the incentives for a large net foreign debtor like the USA to implement unilaterally climate policy than awaiting the consequences of the EU climate policy became stronger since the world economy entered again the state of dynamic inefficiency.

APPENDIX Proof of Proposition 3: To proof Proposition 3 the eigenvalues λ1, 2,3 of the Jacobian matrix

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⎡ dh ⎢ t +1 ⎢ dht ⎢ dk J = ⎢ t +1 ⎢ dht ⎢ dk t*+1 ⎢ ⎢⎣ dht

dht +1 dk t dk t +1 dk t dk t*+1 dk t

dht +1 ⎤ ⎥ dk t* ⎥ ⎡ j 11 dk t +1 ⎥ ⎢ ⎥ = j 21 dk t* ⎥ ⎢ ⎢j dk t*+1 ⎥ ⎣ 31 ⎥ dk t* ⎥⎦

j12 j 22 j32

j13 ⎤ j 23 ⎥⎥ j33 ⎥⎦

(A.1)

are needed. More concretely, the elements of J at any of the two steady states read as follows:

j11 = 1 + (1 − α )(h k )( j 21 − j31 μ ) ,

j1l = (1 − α )(h k )( j 2l − j3l μ ) , l = 2,3

(A.2)

hj 21 − ς j31 = (k α )(1 + i ) G − k ,

hj 22 − ς j 32 = h (1 + i ) G ,

hj 23 − ς j33 = −ς (1 + i ) G ,

(A.3)

hj 21 + j 31 = −φ (k ) ,

hj 22 + j32 = hσ (1 − α )(1 + b k )(1 + i ) G ,

(

)

hj22 + j32 = σ * (1 − α ) 1 + b * k * (1 + i ) G ,

(A.4)

where ς ≡ ς (1 − ς ) . An eigenvalue λ of J is determined by solving det (J − λE ) = 0 . Using basic linear algebra, this linear system of three dimensions can be solved. To this end, start with

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[( j11 − 1) + (1 − λ )]k j12 (1 − α )h (1 − α ) h k j 22 − λ − j 32 μ

j 21 − j 31 μ

227

j13

(1 − α ) h k

= 0, j 23 − ( j 33 − λ ) μ

and subtract the second and third row from the first row to get – using (A.2) and multiplying the rows by appropriate constants – the following equivalent equation

−

(1 − λ )k (1 − α )hλ

−1

1μ

j 21

j 22 − λ

j 23

− ς j 31

− ς j 32

− ς ( j 33 − λ )

= 0.

Next, add the second row h times to the third row, and you will then get after inserting (A.3) and then dividing by (1 + i ) G − λ

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−

(1 − λ )k (1 − α )hλ

1μ

−1

j 21 (k α )(1 + i ) G − k (1 + i ) G − λ

j 22 − λ h[(1 + i ) G − λ ] (1 + i ) G − λ

j 23 = 0. − ς (1 + i ) G + ς λ (1 + i ) G − λ

The final step is to add the first row to the last one, after the last row was divided by h , which yields

−

(1 − λ )k (1 − α )hλ j 21

−1

(k α )(1 + i ) G − k [(1 + i ) G − λ ]h

j 22 − λ 0

1μ j 23 = 0 . 0

The eigenvalues are therefore determined first by

(1 + i ) G − α (1 + i ) G − λ

=

α (1 − λ ) , λ (1 − α )

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which yields the eigenvalues λ1 = (1 + i ) (αG ) and λ 2 = α . Clearly λ 2 < 1 . Furthermore,

λ1 > 1 due to (31). The third eigenvalue directly can be read off from the claim −1 1μ =0 j 22 − λ j 23 and reads

⎧< 1 k = k H L ⎩> 1 k = k

λ3 = μ j 23 + j 22 = H k ⎨

which can be seen by using (A.3) and (A.4), leading to

j 22 = (1 − ς )(1 + i ) G + ς (1 + i )σ (1 − α )(1 + b k ) G and

(

)

μ j 22 = −(1 − ς )(1 + i ) G + (1 − ς )(1 + i )σ * (1 − α ) 1 + b * k * G , which – knowing H k from (27) – completes the proof. Proof of equation (34): Starting with the alternative representations for H and H k

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k=H =

H k = (1 − α ) using

the

~

[

]

1+ i (1 − α )σ~ − αϑ~ − ϑ + ϑ~ , (A.5) αG

(

)

1+ i ~ ~ σ −ϑ k , G abbreviations

ϑ ≡ ςσb + (1 − ς )σ b μ ,

σ~ ≡ ςσ + (1 − ς )σ * ,

ϑ ≡ ςb + (1 − ς ) b * μ

and

H s = H 1+i ∂ (1 + i ) ∂s + H ϑ ∂ϑ ∂s + ~ H ϑ~ ∂ϑ ∂s . As a consequence, (s μ ) ∂μ ∂s = − β (1 − α ) , ∂ϑ ∂s = σ * ∂ϑ ∂s and * *

one

can

calculate

~

∂ϑ ∂ϑ ∂μ β b* (1 − ς ) , = = ∂s ∂μ ∂s 1 − α μ which is used to get

1−α

β

sH s =

[

]

* * 1+ i ⎧ ~ − αϑ~ (1 − α ) − σ *α (1 − ς ) b ⎫ − 1 − σ * (1 − ς ) b . ( ) − α σ 1 k ⎨ ⎬ αG ⎩ μ⎭ μ

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(

)

Welfare Effects of National Climate Policies and the Growth Rate ...

229

Applying (A.5) and performing some rearrangements one gets

~ ~ ϑ ϑ 1+ i ϑ b* 1−α s 1 + i b* Hs = 1− Hk + − + − σ * (1 − ς ) − 1 − σ * (1 − ς ) , β k μ k k G k G μ

(

)

which again can be manipulated to get the desired result. Proof of dV * ds > 0 in Proposition 4: Analogously to the derivation of dV ds in the main text, the change of welfare of younger households in Foreign due to a change in Home’s climate policy is given by

sa dV * sa dI * sa d (1 + i ) sa dh = * +ς −ς , 1 + η ds 1 + i ds 1h ds I ds

(

)

where I t* = wt* − τ t* at and

sa dI * β 1 + i ⎛ b* ⎞ * ⎜1 + ⎟ Ξ . ( ) k 1 = − α 1 − α GI * ⎜⎝ k * ⎟⎠ I * ds Thus, the foreign welfare effect of home climate policy reads as follows:

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1 − α sa dV * = A* Ξ (k ) + ς , β 1 + η ds

(A.6)

(

)

(

~

)(

)

and therefore dV * ds > 0 if A* = k * I * (1 − α ) 1 + i 1 + b * k * − σ (1 − α ) > 0 . This is

~ true for i > 0 using the same reasoning as in the proof to Proposition 4 in the main text.

REFERENCES Bednar-Friedl, B., K. Farmer (2010), External Balance, Dynamic Efficiency, and the Welfare Effects of Unilateral and Multilateral Permit Policies in Interdependent Economies, Economic Modeling 27, 980-990. Bednar-Friedl, B., K. Farmer (2010), and A. Rainer (2010), Effects of Unilateral Climate Policy on Terms of Trade, Capital Accumulation, and Welfare in a World Economy, Environmental and Resource Economics 47, 495-520. Bréchet, T., S. Lambrecht, and F. Prieur (2009), Intertemporal Transfers of Emission Quotas in Climate Policies.Economic Modeling 26, 126-134. Copeland, B. R., M.S. Taylor (2005), Free Trade and Global Warming: A Trade Theory View of the Kyoto Protocol. Journal of Environmental Economics and Management 49, 205234.

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230

Karl Farmer and Andreas Rainer

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Diamond, P. A. (1965), National Debt in a Neoclassical Growth Model. American Economic Review, 55, 1135–1150. Frenkel, J. A., A. Razin (1986), Fiscal Policies in the World Economy. Journal of Political Economy, 94 (3), 564-594. Gosh, A. R. (1992), Fiscal Policy, the Terms of Trade, and the External Balance. Journal of International Economics, 22, 105-125. IMF (2006, 2010). World Economic Outlook. Washington: International Monetary Fund. Jouvet, P.-A., P. Michel, G. Routillon(2005a), Equilibrium with a Market of Permits. Research in Economics 59, 148-163. Jouvet, P.-A., P. Michel, G. Routillon (2005b), Optimal Growth with Pollution: How to Use Pollution Permits? Journal of Economic Dynamics and Control 29 (9), 1597-1609. Lipton, D, J. Sachs, Accumulation and Growth in a Two-Country Model, Journal of International Economics15 (1-2), 135-159. Obstfeld, M. (1989), Fiscal Deficits and Relative Prices in a Growing World Economy. Journal of Monetary Economics, 23, 461-484. Ono, T. (2002), The Effects of Emission Permits on Growth and the Environment. Resource & Environmental Economics, 21, 75-87. Ono, Y., & Shibata, A. (2005), Fiscal Spending, Relative-Price Dynamics, and Welfare in a World Economy. Review of International Economics, 13 (2), 216-236. Persson, T., G. Tabellini (2002), Political Economics. Explaining Economic Policy. The MIT Press: Cambridge. Persson, T. (1985), Deficits and Intergenerational Welfare in Open Economies. Journal of International Economics, 19, 67-84. Stokey, N. (1998), Are There Limits to Growth? International Economic Review 39 (1), 1-31. Zee, H. H. (1987), Government Debt, Capital Accumulation and the Terms of Trade in a Model of Interdependent Economies. Economic Inquiry 25, 599-618.

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In: Theories and Effects of Economic Growth Editor: Richard L. Bertrand, pp. 231-240

ISBN: 978-1-61209-795-4 c 2011 Nova Science Publishers, Inc.

Chapter 11

D OES R&D I NCREASE E CONOMIC G ROWTH ? Bernard C. Beaudreau∗ Department of Economics, Universit´e Laval, Qu´ebec, Canada, G1K 7P4

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Abstract Responding to the productivity slowdown in the mid-1970s, Western countries invested trillions of dollars in R&D, the idea being that R&D is a key determinant of growth. In 2007, a total of $1.145 trillion was invested in R&D worldwide [16]. Unfortunately, thirty-five years after the fact, growth rates have not returned to their postWWII levels, which raises the obvious question, does R&D actually increase growth? This paper examines the science behind the policy. More precisely, it examines the theory of R&D-based growth and the evidence. It comes to the conclusion that the science that underlies R&D-based growth is surprisingly weak. For example, there is little theory behind the R&D-growth nexus. Similarly, there is little empirical evidence that R&D increases growth. Moreover, when examined from the point of view of the underlying physics, R&D-growth runs contrary to the very laws that govern material processes, a result that is consistent with t he reported failure of R&D to restore growth levels.

Keywords: R&D, R&D Policy, Growth Slowdown.

1.

Introduction

The story of R&D and its role in economic growth is one worth telling.1 It is the story of half measures, of weak science, of magical thinking, and of crisis. It could be argued that R&D is, by far, the most celebrated and poorly understood growth-related constructs. While throughout the 19th century, growth was tied to capital accumulation, in the 20th century—especially in the latter part—it was tied to R&D. But what is R&D and how does it affect growth? Interestingly enough, no one asked nor answered this question. Rather, ∗ 1

E-mail address: [email protected] Throughout this paper, we will use R&D, ideas, innovation and invention interchangeably.

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from the very start, R&D assumed mythical, if not magical status. Finding themselves with a non-negligible residual in their accounts of post-WWII growth and its causes, Moses Abramovitz, Jan Tinbergen and others attributed it to knowledge. And so began a practice that has gone unquestioned, unproven, and, for the most part un-understood. The fallout is there for all to see. Today, R&D is often invoked by academics and politicians as a means of increasing economic growth, yet there is no hard evidence. Like a magic wand, it’s underlying essence is ignored. What exactly is R&D and how does it increase growth? Do all forms of R&D increase growth? Is growth increasing in knowledge—all knowledge? This paper examines the science behind R&D. More specifically, we look at both the theory and evidence of the R&D-growth nexus. Unlike previous attempts, we delve further into the question of how R&D actually increases society’s ability to increase wealth by reexamining basic production theory per se. Specifically, we present a consilient model of material processes based on process engineering and, as such, basic physics (classical mechanics and thermodynamics). In so doing, we are able to distinguish between outputincreasing and non-output-increasing forms of R&D. Our results show the existence of very few types of output-increasing R&D, a result that owes to the constancy or near-constancy of second-law efficiency. As the latter is bounded from above, it stands to reason that second-law efficiency-related R&D is, by definition, limited—in fact, very limited—in its ability to increase wealth. Which we invoke as the underlying reason for the documented absence of a statistically-significant relationship between R&D and economic growth.

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2.

The Productivity Slowdown, Policy Responses and R&D Expenditure

The world changed in 1975. That year witnessed a tectonic shift in growth rates in Western industrialized economies and indeed in the world economy. For most of the postWWII period, economic growth not only high, but robust. G6 countries could expect growth in the 4-6 percent range. After 1975, growth plummeted to just over one percent [12]. The fallout was catastrophic, to say the least. Lower growth rates altered the social fabric, a fabric that had become used to rising per-capita wealth. Governments floundered under the weight of growing deficits and ballooning debt loads. Making matters worse, however, was the mystery surrounding the “productivity slowdown.” Two hundred years after Adam Smith’s initial foray into the nature and causes of the “Wealth of Nations,” the economics profession was (and still is) at a loss to explain this ”tectonic shift” in growth. What had gone wrong? What factor or factors were to blame? After all, economics is the science of wealth. Yet, in the West’s hour of need, it was unable to ”rise to the occasion.” In the face of what Moses Abramovitz referred to as “our measure of ignorance,” the profession embarked on a research program unequaled since the Keynesian revolution. The question of growth soon came to dominate the research agenda. The profession’s “best” minds stopped what they were doing to study growth, resulting in what I refer to as the “growth imperative.” A good example is Nobel laureate Robert Lucas who all but abandoned his work on rational expectations to focus on economic growth. The growth imperative exacted a heavy toll on governments. Growth had slowed down.

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The question was: how to reverse the trend? How to restore growth to post-WWII levels? Adding to their conundrum was the dearth of knowledge. And by knowledge, we mean proven theories and hypotheses—not just hypotheses. There did, however, exist a growth literature per se, one that was speculative in nature. According to this literature, roughly half of post-WWII growth owed to technological change. Or, put differently, research and development—otherwise known as the Solow Residual—a hypothesis, not a law. As odd as it may seem, this hunch (hypothesis) became the cornerstone of government policy the world over. Wanting to restore growth, governments turned to R&D. Tax incentives, subsidies, and changes to intellectual property laws were just a few of the policy measures adopted by most Western industrialized countries. Given its near mythical status, let us examine briefly its early history.

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3.

Residual Growth, “Our Measure of Ignorance” and R&D

While some concepts enter a science from the front door, others enter from the side door or even the back door. R&D falls into the latter category, that is, entered the growth literature from the back door. As a residual. Once capital and labor growth rates, the Brahman inputs of production and growth theory, had been factored out of GDP growth rates, what remained was simply attributed to knowledge, information and ultimately R&D. Unlike capital and labor which were front and center in the science of wealth that was political economy in the 19th century, information, knowledge and R&D were absent from economic theory. Just how these factors affected material processes was unknown at the time, beyond of course the obvious (e.g. the steam engine). The post-WWII period changed all of this—by default. With the Keynesian revolution came government statistical agencies. If governments were to fine-tune the economy, they would need detailed macroeconomic data. Consequently, macroeconomic time-series on GDP, employment and investment were collected. Out of this was to come the foundations of modern growth theory. According to Abramovitz, measurement of growth and its components was initiated by several individuals, including Jan Tinbergen, Jacob Tinter, and Robert Solow. Many approaches were used, including the “shifter” in the production function and the output-over-total input index. In a nutshell, they found that GDP growth rates exceeded, substantially, capital and labor growth rates, leaving a substantial part of overall post-WWII growth unexplained. Milton Friedman referred to it as “technical change.” And was born the notion of the growth “residual.” The first to provide explicit calculations of this “residua l” was Jan Tinbergen who using the Cobb-Douglas framework, provided estimates of the “efficiency residual.” Similar work was carried out in the U.S. at the NBER. The upshot of this literature was clear. As Griliches explains: At this point, the gauntlet had been thrown: even though it had been named “efficiency,” “technical change,” or most accurately a “measure of our ignorance,” much of observed economic growth remained unexplained. It was now the turn of the explainers. [8;5] Abramovitz’s explainers were few in number and included the likes of Edward Dension and Zvi Griliches, both of whom were part of what we refer to as the first generation of

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“explainers.” What is remarkable about this first generation is the breadth of their work. While later generations focused on single causes, they were exhaustive in their search for the causes of growth. For example, Denison attributed the reported increase in output per unit input (the equivalent of multifactor productivity) to (i) restrictions against optimum use of resources, (ii) reduced waste of labor in agriculture, (iii) industry shift from agriculture, (iv) advance of knowledge (v) change in lag in application of knowledge, (vi) economies of scale-independent growth of local markets and (vii) economies of scale-growth of national market. According to Denison and Griliches, education and advances in knowledge were the two main sources of multifactor pro ductivity growth in the post WWII period. The second generation of “explainers” included Robert Solow and Trevor Swan who, unlike Denison, brought formal analysis to bear on the problem. Following in the footsteps of Tinbergen, they provided estimates of multifactor productivity growth. Whereas the first generation had focused on education, they were more succinct. Productivity growth owed to advances in knowledge. If nothing else, formalization catapulted the question of growth and its causes to the forefront of the profession. The Solow-Swan growth model soon became the gold standard in so far as growth models were concerned. Ironically, the model could only explain half of the observed growth, with the other half being a residual—the Solow residual. Such was the state of growth theory and the causes of growth for roughly a quarter century. That productivity growth was, for the most part, unexplained, was of no consequence. After all, growth rates remained robust throughout the period. Understandably, all of this changed in 1975, when growth rates plummeted. When it became clear that the low growth rates of the mid-1970s were not the exception, but rather the “new” rule, the profession mobilized itself. Answers were required. For real. Why did growth rates plummet? And, more importantly, how could the West restore them to pre-1975 levels. And thus was born, the “growth imperative.”

4.

The Latter-Day Explainers

Within a decade, the full force of the economics profession had been unleashed on the Solow residual. While Solow had formalized the early writings of Tinbergen and others especially with regard to capital and labor, now the profession would formalized what amounted to the frontier in so far as growth analysis was concerned, namely the residual— the black box of economic growth. In little time, new approaches were forthcoming, including Paul Romer’s Ak analysis which stressed economies of scale in innovation/R&D activity, Robert Lucas’ work on growth and human capital, and Philippe Aghion and Peter Howitt’s work on Schumpeterian “creative destruction.” Collectively, this literature became known as “endogeneous growth literature.” Whereas the first two generations of “explainers” were content to identify and measure the residual, this generation gave itself the objective of understanding it. And so began a new chapter in the growth literature, one that was exhau stive and unrelenting in its desire to understand growth in general and the productivity slowdown in particular. The upshot of this literature has been the view, shared by most, that growth is increasing in knowledge. Ergo, anything and everything that increases the stock of knowledge will increase growth. Research and development is a case in point. Whereas advances in knowledge in the 19th century were more fortuitous in

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nature, all of this changed in the 20th century with the birth of industrial and government research—in short, with specialization. Today, the world allocates roughly one trillion dollars to R&D expenditure. According to UNESCO, there are roughly 7,209,700 scientists and others engaged in R&D activity [16;12]. But this raises the question: has growth increased as a result? Is there evidence of an R&D-growth nexus? We now turn and examine the corresponding empirics.

5.

The Evidence

In general, empirical work to identify the macroeconomic relationship between research and growth focused upon linking measures of research activity either to total factor productivity or to long run patterns of economic growth. This work typically begins by identifying a measure of technical knowledge. Let qt be the measure of new knowledge in period t. The stock of knowledge Tt then evolves according to (1). Tt+1 = (1 − δT )Tt + qt

(1)

where δT is the rate at which ideas ”depreciate.” The key to ideas-based growth models is that Tt is an important determinant of macroeconomic variables, and that it changes over time as the result of volitional research activity by agents. Thus, the aggregate behavior of the economy is given by two production functions. First, the production function of aggregate output yt depends upon Tt , in addition to aggregate capital kt and labor nt

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k yt = zt Ttθ ktαk n1−α t

(2)

where Tt is a factor of TFP, and zt is a productivity residual. Second, the quantity of new knowledge is given by an ideas production function qt = st Ttφ xψ t

(3)

where xt indicates the input of resources into research (i.e. R&D expenditure), and st is a residual analogous to zt . Empirically, the variable st captures the fact that measures of the input into research display far less low-frequency variation than measures of the output. It grows on average by a factor γs . Estimates of the parameters of equations (2) and (3) tend to yield results that are challenging for ideas-based growth models. First, using patent applications as an indicator of knowledge Tt , Porter and Stern [13] and Abdih and Joutz [1] find that the contribution of ideas to total factor productivity is small. Point estimates of θ lie in the range [0.05-0.2] , and often lack statistical significance. The second challenge concerns the parameter φ. A value of φ > 0 implies that past ideas are useful for the production of new ones, whereas a value of φ < 0 suggests that research uncovers the ideas that are easiest to find, so that discovery becomes progressively more difficult. These effects are known respectively as “standing on shoulders” and “fishing-out.” Endogenous growth models of this class are typically constructed so that φ = 1: for example, this is true of the model in Romer [14], in which increases in capital variety drive growth,

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and of Krusell [10], in which ideas lead to growth through investment-specific technical change as here. However, if φ = 1, then the growth rate depends on the population size (or, more generally, the size of the economy). Jones [9] strongly rejects any empirical growthpopulation link in post-War US data: population rises monotonically, whereas growth rates display no upward trend, implying that φ < 1. Greenwood and Jovanovic [7] argue that this constitutes a key empirical shortcoming of ideas-based growth models. Direct empirical estimates of the ideas production function have recently become available see Porter and Stern [13] and Abdih and Joutz [1]. The estimates suggest that returns are in fact close to constant or even increasing over the post-War period in other words, φ ≈ 1. It is unclear how to square this result with the absence of accelerating growth. A third empirical puzzle also regards equation (3). Estimates of the ideas production function generally detect a downward trend in st . This decline is robust to a diversity of approaches. For example, Caballero and Jaffe [5] use a selection of citation-weighted patent grants. Porter and Stern [13] use aggregate patent application data, also identifying the effects of international patenting. Abdih and Joutz [1] also use patent application data, simultaneously estimating the aggregate production and ideas production functions. The downward trend is perplexing, as it lacks a theoretical basis. For example, if it is the case that “easy” ideas are discovered first, so that ideas become progressively harder to uncover, this is precisely the “fishing out” hypothesis, which should be reflected in a negative value of φ: it should depend on the number of ideas that have already been uncovered, not on the date. To summarize, the evidence is unequivocal: any relationship between R&D/ideas and growth is either weak or non-existent. Which is surprising in light of the role R&D and technology in general has played in growth theory from the get-go. For roughly threequarters of a century, the West has touted R&D to be the prime mover of wealth, the prime cause of enrichment both in general and on a per-capita basis. But is it surprising? With the benefit of hindsight, are we not victims of ourselves, victims of magical thinking, and victims of poor science? After all, the R&D-growth nexus was born of a residual, of what could be termed residual analysis. That is, we factored out what was known of economic growth (i.e. capital and labor) and what was left over (i.e. the residual) was attributed to R&D. Clearly, not solid science by any stretch of the imagination. The problem as it turns out goes beyond the growth debate to production theory per se. Clearly, what was needed and what is needed is a theory of production that is able to incorporate R&D in a more structured way. In other words, a theory of production that can discriminate between productivity-increasing and non productivity-increasing ideas and innovations. In short, what is needed is a theory of production that would move the debate away from the current “residual-based methodology.” That is, away from the zt Ttθ in (2). In the next section, we present just such a theory. Starting with a consilient theory of material processes, we examine the role of technology as well as the role of R&D in production processes.

6.

Underlying Physics

As argued earlier, the “discovery” of the “residual” prompted a number of “lines” of research, including the exhaustive approach (Denison) to the residual approach (Solow) to Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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the Ak approach (Romer). Underlying each is the standard neoclassical production function (capital and labor). Just how R&D and innovation affect production is ignored owing in large measure to the lack of a veritable theory of production (as in physics and mechanical engineering). Classical and neoclassical production functions amount to little more than correlations between inputs and outputs. This has made for and continues to make for a situation in which the effects of innovation and consequently R&D cannot be examined, except in vagaries. In this section, we propose another line of research, one that is consistent with the spirit of Edward Dension’s work, but one that goes further and examines possible sources of output-increasing technological change within the context of a consilient (with physics and process engineering) model of material processes. In other words, instead of working within the confines of neoclassical production theory, we present and use an alternative approach to understanding wealth, one that imposes more structure—and limits—on the relationship between inputs and outputs, the hope being that by doing so, we can shed new light on the role of innovation and R&D on material processes and hence aggregate economic growth. We begin by introducing the Energy-Organization (E-O) approach to modeling material processes [2]. Drawing from material process sciences (engineering, biology), it models wealth in terms of two universal factor inputs, namely broadly-defined energy and broadlydefined organization. Both are necessary conditions in all material processes whether it be in biology, chemistry, engineering or economics. The model is formalized in terms of Equation 4 where Wt , Et , Lt , and St refer to wealth, energy, tools and supervision at time t, respectively. η refers to second-law efficiency, which, as shown, is a function of Lt and St .

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Wt = η(Lt , St )Et

(4)

η(Lt , St ) corresponds to the broadly-defined organization input, while Et corresponds to the broadly-defined energy input. While Et is sometimes referred to as energy consumption per se, technically it refers to available work or negentropy. As energy cannot be created nor destroyed, it follows that energy is not consumed per se, but rather entropy is increased. Second-law efficiency (i.e. η) is assumed to be increasing in tools and supervision. For the sake of discussion, it will be assumed that the latter are qualitative and not quantitative variables. That is, second-law efficiency is increasing in the quality of tools and the quality of supervision. This model is consilient in the sense that it describes virtually all known material processes, be they in process engineering, biology or economics. As such, all material processes are powered by energy. Energy and energy alone is productive in the physical sense. Tools and supervision are necessary factor inputs, but not productive in the physical sense.2 They affect output via their effect on second-law efficiency which is, by definition, bounded from above.3 Lastly, this model and its predictions are consistent with the laws of classical mechanics and thermodynamics, making for a truly consilient model of material processes. 2 According to Betts [4]: Machinery is used to change the magnitude, direction and point of application of required forces in order to make tasks easier. The output of useful work from any machine, however, can never exceed the total input of work and energy. ([4],p.172) 3 Historically, second-law efficiency is highly stable. Few innovations have and can make a significant difference.

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It can be used to study human thermodynamics, industrial processes, celestial motion and/ economic growth. For example, it predicts that growth will be increasing in energy use, with causality running from the latter to the former (Beaudreau [3]). Which brings us to the question at hand, namely the relationship between R&D and growth. Unlike conventional models where the effects of R&D on growth are unbounded, the E-O model imposes structure on the debate. For example, in conventional models, technological change could theoretically double, treble or quadruple output. There are no limits. Such is not the case here. The E-O model, by linking growth to the growth of energy consumption, puts an upper bound on non-energy-related growth. Specifically, R&D can only increase growth via η, second-law efficiency. Examples include less wasteful electrical motors, less wasteful production chains, etc. In short, anything that increases the amount of work that results from a given supply of energy. Other examples include James Watt’s steam engine that raised second-law efficiency manifold, making the steam engine economically viable and ushering in the industrial revolution, Charles Parson’s steam turbine th at further increased second-law efficiency. Any innovation which raises firm level, industry level, aggregate η will increase output. This having been said, it stands to reason that because η is bounded from above and very— extremely—stable over time, process-based R&D will, ceteris paribus, have a limited effect on the growth of material wealth, especially over the long-run. And, in the limit, no effect at all. That is, once η has reached its thermodynamic maximum, then R&D can no longer have an effect on growth. This result has important implications for the question at hand. For example, if R&D does not affect economy-wide second-law efficiency, then ceteris paribus, it cannot increase output. Put differently, if zt Ttθ in (2) does not affect η, then it cannot conceivably increase output and wealth. It is worth noting that this result is consistent with basic physics and process engineering. For a given, stable η, output is increasing in energy consumption. Energy consumption growth, it therefore follows, stands as the key ingredient in the growth recipe, a result that is universal in its scope. To think otherwise is to violate the basic laws of physics. Further, this result is also consistent with the empirical literature on R&D and growth. Specifically, that there is no statistically significant relationship between R&D and growth is consistent with this result, which admittedly casts a pall on half a century of work on growth, specifically on the role of knowledge in growth.4

7.

Conclusions

Perhaps the greatest irony in so far as the R&D-growth literature is concerned, a literature that purports to understand the role of innovation in growth, is the very lack of innovation as far as the analysis is concerned. While the analysis has increased in sophistication, the underlying fundamentals have changed little. One could go as far as to argue that, aside from its technical sophistication, the contributions made by both the exogenous 4

This raises the question, if R&D was not the driving force behind post-WWII U.S., German and Japanese economic growth, then what was? According to Beaudreau [2] and Kummel et al. [11], energy was—more specifically, energy growth. Above-average energy consumption growth combine d with either a stable or increasing η resulted in above-average output growth. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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and endogenous growth literatures can all be found in one form or another in Edward Denison’s pioneering work in the 1950s. There is nothing particularly wrong with this. After all, growth theory is hypothetical in nature. Problems, however, arise when the data fail to support the resulting theory—which is the case here. Studies have failed and continue to fail to confirm the existence of the purported R&D-growth nexus. In this paper, we have examined the science behind the policy. More precisely, we examined the theory of R&D-based growth and the evidence, and came to the conclusion that the underlying science is surprisingly weak. For example, there is little “hard” theory underlying the R&D-growth nexus. When examined using a consilient model of material processes, R&D-growth is found to runs contrary to the physical laws that govern material processes, a result that is consistent with the empirical evidence. Regardless of how one frames the problem, R&D cannot increase growth, ceteris paribus. This is an extremely important finding in so far as the policy debate is concerned. Clearly, if growth is the prime objective, then we as a society are wasting our time and money. Education, economies of scale, institutions, liberty and information cannot create energy, the universal cornerstone of material processes and the ultimate source of all growth.

References [1] Abdih, Yasser and Joutz, Frederick. ”Relating the Knowledge Production Function to Total Factor Productivity.”, International Monetary Fund Staff Papers, 2006.

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[2] Aghion, P. and P. Howitt, Endogenous Growth Theory (Cambridge, MA: MIT Press, 1998). [3] Beaudreau, Bernard C., Energy and Organization: Growth and Distribution Reexamined (Westport, CT: Greenwood Press, 1998). [4] Betts, John E. 1989. Essentials of Applied Physics., Englewood Cliffs, NJ: PrenticeHall. [5] Caballero, Ricardo and Jaffe, Adam. How High are the Giants Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth.” NBER Macroeconomics Annual, 8. (Cambridge, MA: MIT Press 1993). [6] Denison, Edward, The Sources of Economic Growth in the United States and the Alternatives Before Us. Committee for Economic Development, (Washington,DC, 1962). [7] Greenwood, Jeremy; Jovanovic, Boyan. “Accounting for Growth.” New developments in productivity analysis, NBER Studies in Income and Wealth, vol. 63. (Chicago,IL: University of Chicago Press, 2001) 179-222. [8] Griliches, Zvi, The Discovery of the Residual: An Historical Note, National Bureau of Economic Research, Working Paper, 5348, 1995. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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[9] Jones, Charles. “R&D-Based Models of Economic Growth.” Journal of Political Economy, 103, (1995), 759-84. [10] Krusell, Per. “Investment-Specific R&D and the Decline in the Relative Price of Capital”, Journal of Economic Growth, 3 (1998), 131-141. [11] Kummel, Reiner, Dietmar Lindenberger and Wolfgang Eichorn 1998. The Productive Power of Energy and Economic Evolution. University of Wurzburg Working Paper. [12] Maddison, Angus., “Growth and Slowdown in Advanced Capitalist Economies: Techniques of Quantitative Assessment,” Journal of Economic Literature, 1987, 25(2), 649–698. [13] Porter, Michael E. and Stern, Scott. “Measuring the ”Ideas” Production Function: Evidence from International Patent Output” NBER Working Paper, w7891, (2000). [14] Romer, Paul M., “Endogenous Technological Change,” Journal of Political Economy, 98, 1990, s71–s102. [15] Smith, Adam, An Inquiry into the Nature and Causes of the Wealth of Nations (Chicago: Encyclopaedia Britannica, 1990).

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[16] UNESCO, UNESCO Science Report 2010: The Current Status of Science around the World (Paris, 2010).

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Chapter 12

THE DETERMINANTS OF ECONOMIC GROWTH IN EMERGING ECONOMIES: A COMPARATIVE ANALYSIS Pasquale Tridico∗ University of “Roma Tre”, Department of Economics, Rome, Italy

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ABSTRACT Over the past decade Emerging and Transition Economies (ETE) have been experiencing economic growth and a consistent institutional change. The aim of this paper is twofold. First of all, a cross-country analysis of a group of ETE in the period 1998-2008 will be carried out in order to understand what determines economic growth among these countries. Secondly, a comparative analysis will be carried out. The countries will be classified according to their socio-economic models, and I will investigate whether institutions may have an impact on growth. The central hypothesis is that explaining economic growth is a complex issue which needs positive interaction of several socioeconomic and institutional factors. My analysis suggests that countries can grow with their own “style of capitalism”, and the determinant of economic growth is the ability of each country to associate appropriate governance and institutions with education level, export activity and non-income dimensions of human development.

Keywords: economic growth, institutions, human development, socio-economic models. JEL: F430, O430, 0150, G320, I310

1. INTRODUCTION One of the most challenging themes for economists is to explain “how countries become rich”. Adam Smith observed that some nations are richer even if not all the individuals in that society work whereas other nations are extremely poor, even if all the individuals work. He ∗ Tel.: +39 06 57114722; Fax: +39 06 57114771 E-mail: [email protected]

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attributed most of the output differences among countries to better organization and labour division. Recently, there has been burgeoning literature in this field but theories and empirical analyses about economic growth consistently diverge. The aim of this paper is twofold. Firstly, a cross-country analysis of a group of emerging and transition economies during the years 1999-2006 will be carried out. This is a group of 45 countries which includes almost all the emerging economies as defined by the IMF. These countries experienced, in very different magnitudes, economic growth in the past decade and a consistent institutional change. The period between 19989/2008 is not considered a long-run but constitutes a medium-run beyond cycle fluctuations.1 During this period of time Moreover, Spain and Ireland are included in this analysis because they can be considered reference points for emerged economies. The first research question is what determines economic growth among those 47 countries. Secondly, a comparative analysis will be carried out. The 47 countries will be classified according to their socio-economic models and institutional variables. Countries will be classified by taking their financial structures and ownership control of firms into consideration (Levine and Kunt, 1999; La Porta et. al., 1999). A first mapping of countries includes:

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1. 2. 3. 4.

competitive capitalist countries corporative capitalist countries dirigiste economies socialist markets.

I will investigate whether institutions, defined in general as “rule of the game” (North, 1990) have, in some way, an impact on growth and if the type of socio-economic model is one of the determinants of growth. The central hypothesis of the paper is that explaining economic growth is a complex problem which needs positive interaction of several socio-economic and institutional factors. In other words it needs a simultaneous presence of institutions and socio-economic variables. The economic growth literature abounds with papers explaining growth on the basis of four or five factors, often taken singularly, such as human capital (Lucas, 1993; Barro, 1998; Young, 1995; Goldin and Lawrence, 2001), technology (Kuznets, 1966; Landes, 1969; Mokyr, 1990), natural resources (Shaban, 1987; Walker and Ryan, 1990), trade (Lockwood, 1954; Pomeranz, 2000; Galor and Mountford, 2003) and population density (Das Gupta, 1994). In parallel, “market-friendly” economic reforms are advocated as necessary conditions for economic growth. However, such economic reforms in Less Developed Countries (LDC) have failed to deliver the promised economic growth during the 1980s-1990s (Easterly, 2001). Recently, more and more economists have started to take into account the role of institutions for economic growth (North, 1990; Jones 1981; Knack and Keefer, 1995; Mauro, 1995; Olson et al. 1998; Nugent and Lin, 1995; Acemouglu et al., 2001; etc). In parallel, an increasing literature championed by the United Nation of Development Program (UNDP) has 1 Hausmann et.al., (2005) consider that a medium period of time is much useful to analyse turning points in economic growth. They consider as a medium-run a period of 8 years which is not far from our medium-run, i.e., 1999-2006 (7 years altogether).

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been critical of economic growth which does not take into account human development indicators such as life expectancy, infant mortality, literacy, etc. The main problem with most of this literature is the lack of interaction between some relevant socio-economic factors of growth and well-captured institutions. In other words, relevant variables are not considered together. On the contrary, in our paper I maintain that countries which experienced an increase in non-income dimensions of human development during 1970-1998 as a consequence of appropriate institutions, will have sustained economic growth. Secondary school enrolment ratio and Export are included in the cross-country analysis as independent variables. I found that the socio-economic model does not seem to be a determinant of growth and countries can grow with their own “style of capitalism” and economic model. The determinants of economic growth seem to be the ability of each country to associate appropriate governance and institutions with education level, export activity and non-income dimensions of human development (infant mortality reduction in particular, which is supposed to capture the level of a national heath system). The rest of the paper is organized as follow: in section 2 I define emerging economies and the countries that were part of our sample; in section 3, I present briefly the relevant literature on economic growth; in section 4 I describe our variables, Human Capital, Openness, Education, HDI and Institutions; in section 5 I present our model and the first results of a cross-section analysis and in section 6, an institutional analysis is proposed and, on the basis of that, I control for the type of socio-economic model; some final remarks will conclude the paper.

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2. EMERGING ECONOMIES: A MISHMASH OF COUNTRIES The term “emerging economy” (EE) was coined in 1981 by Antoine Van Agtmael of the World Bank, and refer to countries that are “emerging” from under-development, and are restructuring their economies along market-oriented lines.2 Yet those countries are from lowto-middle per capita income economies. They are approximately 80% of the global population and they represent about 20% of the world's economies. Emerging economies are small-, medium- and large- sized, and, in general, they appear on the global scene because they are becoming more open economies, in terms of trade and flows of foreign investments. China and Tunisia, for instance, are part of the category of emerging economies because they have been experiencing a process of reforms over the past decade and opened their markets to the global economy. Hence, openness and market oriented institutional reforms are basic conditions for us in order to consider low-to-middle per capita income economies part of the sample as EEs. In this sense, emerging economies can also be considered transitional economies because they are experiencing a structural and institutional change, moving from closed economies to open economies. Following this definition, some European countries, such as Spain and Ireland, could have been considered emerging economies in the 1980s and 1990s when they experienced fast growth and structural change. For this reason, I include them in our analysis as reference countries for current emerging economies. 2 Cf. Agtmael (2007). Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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According to the World Bank, the five biggest emerging markets are Brazil, Russia, India and China, which are also named as BRIC.3 To these five countries Mexico was soon added.4. The list is continuously updated by international and financial institutions reports and indexes such as Grant Thornton International Report (IBR) on EE, Morgan Stanley Emerging Markets Index, Goldman Sachs papers, and The Economist EE index. According to the latest findings from the Grant Thornton International Business Report (IBR) published on April 19 2007, Mexico, Indonesia, Pakistan, and Turkey are the emerging markets to watch right now. To this list one can easily add Argentina, South Africa, and South Korea and many other Asian countries (Neumeyer and Perri, 2004). Along with this kind of EEs, another category can certainly be added, that of the former communist countries which started the transition from planned economy towards market economy, i.e., Former Soviet Union Republics (FSUR) and Central Eastern European Countries (CEEC). However, not all of them are part of our analysis. I included the countries which, according to the definition above, are generally introducing a program of institutional reforms and are integrating themselves in the world economy. Some countries, such as Uzbekistan, Belarus and Turkmenistan did not start a true transition process and they are still planned and closed economies. None of the financial international organisations mentioned above include those countries among the EEs. Other countries, such as former Soviet Republics of Caucasus (Georgia, Armenia and Azerbaijan) and of Asia (Tajikistan, Kyrgyzstan, Afghanistan and Kazakhstan) currently Countries of the Independent Confederation (CIS) experienced, during transition towards market economies, political troubles and instability. Hence, the path of the program of reforms was often interrupted and impeded. Therefore they are excluded by the most important international financial organisations from the group of EE. A complete list of EE is indeed difficult to make. The definition lying in the reports of international and financial organizations is very general. It says that EEs are countries with low-to-middle per capita income in a process of institutional reforms and integration in the world economy (Mauro, 2000). World Bank and International Monetary Fund share also this definition (IMF, 2001a; World Bank, 1998b). In this paper such a wider definition of EE is adopted in order to include a great number of countries in the sample. To sum up, my sample includes all the countries that are listed in the two indexes i.e., the Morgan Stanley Emerging Markets Index and The Economist Index. The list is made up by the following countries Argentina, Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Israel, Jordan, Malaysia, Mexico, Morocco, Pakistan, Peru, Philippines, Poland, Russia, South Africa, South Korea, Republic of China (Taiwan), Thailand, Turkey, Hong Kong, Singapore, Saudi Arabia. This list is however limited by the fact that it does not consider small countries or countries with limited market liquidity because from a pure financial point of view size and liquidity are important conditions for foreign investors and financial markets. However, from a pure economic point of view may be interesting also to consider small and medium countries even though with little liquidity among EEs. Therefore the list of EEs used in this 3 O’Neill et. al., (2005). 4 « Le Mexique. Si vous appliquez la grille d'analyse des Bric à 11 autres grands pays émergents, il apparaît que le Mexique dispose du même potentiel que la Russie ou le Brésil. Si nous pouvions revenir cinq ans en arrière, nous les aurions appelés les BRIMC ». Le figaro, 23 October 2006, interview with Jim O'Neill, economist at Goldman Sachs.

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paper includes also other countries such as: Slovakia, Estonia, Lithuania, Croatia, Albania, Latvia, Bulgaria, Romania, Slovenia, Vietnam, Botswana, Algeria, Tunisia, Venezuela, Bolivia, Ecuador and Ukraine. These countries are nevertheless open economies with low-tomiddle per capita income and in a process of institutional reforms and integration in the world eonomy. Hence, they fit with the above definition of EEs. Moreover, these countries are considered definitely EEs in National Reports and International Surveys by IMF and WB (IMF, 2001b; World Bank, 1998a). Altogether our sample is made up by 47 countries: 14 former communist countries, 12 Asian countries, 9 Latin American countries, 1 South-east European country, 3 Middle Eastern countries, 6 African countries, and 2 developed economies, old European Union member states (Spain and Ireland), used as reference countries for EEs.

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3. EXPLAINING ECONOMIC GROWTH: A BRIEF REVIEW As I stated above, explaining economic growth is a complex problem because several factors can contribute to growth process. All the theoretical predictions which assume that a single specific factor makes some countries richer than others do not find consistent empirical confirmation. Many exceptions, for instance, can be raised against the idea that human capital is the only factor which is important for growth: some countries such as Poland, Russia, South Korea have education levels which are very close to those in the richest economies yet their GDP per capita is much lower. Another problem with human capital is the possibility of reverse causality between growth and education and it is important to understand which one comes first and which one causes what. Human capital is definitely an important factor for economic growth (Barro and Sala-i-Martin, 1995; Barro, 1998) but it has also been seen that differences in human capital can explain no more that one-fifth of the differences in living standards (Olson, 1996). A similar argument can be put forward with regard to the relation between technology and growth. Richer countries can afford high levels of R&D expenditure and they can enjoy positive returns and spillover from that. Investment in technology is definitely correlated, both theoretically and empirically, with economic growth but the root of the problem seems to be how countries can afford high levels of investment in technology and, consecutively, how some nations have more advanced technology than others (Yeager, 2004). Another factor which is often considered very important for economic growth is natural resources (Shaban, 1987; Walker and Ryan, 1990). United States, Norway, Germany and other richer countries possess abundant natural resources such as oil, cool, land, etc. However, many other better or equally endowed countries such as Russia, Brazil, Nigeria, Venezuela, Saudi Arabia etc. are not as rich while other poorer endowed countries such as Japan, Singapore, Taiwan, Hong Kong are much richer. The same exceptions can be found when considering trade and population density. In the first case, together with the success of some export led countries such as Ireland and the “Asian Tigers”, the history of economies also records successfully cases of inward-oriented countries such as France and other old European Member States after the IIWW. Even the Asian tigers, before entering the global economy, created a strong “infant industry” and promoted import-substitutions policies. From a theoretical point of view, similar

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contradictions can be traced between some economists who support the idea of a strong correlation between trade and growth (Bhagwati, 2004, Galor and Mountford, 2003) and others who minimize the impact of trade on growth (Krevise 2000) arguing that in some cases negative effects such as inequality, wage discrimination and skilled and unskilled inequality seem to prevail (Nayyar, 2000). With regard to population density, today we cannot say that poverty is always associated with high density as some economists, following Malthusian predictions, initially believed. Switzerland, Germany (and in particular the former West Germany) and newly industrialized Asian countries have a high population density and this was not an obstacle to their economic development. In contrast, many Latin American countries such as Brazil and Mexico have a low population density but this did not bring development. Hence, it seems that a comparative analysis reveals many problems and many controversial aspects related to development. Economic growth does not seem to be associated with one single particular factor which is able to bring about development. No single mentioned factor is able to explain economic differences between countries. Moreover, the failure of Washington Consensus during 1990s in several countries such as Mexico, Argentina, Russia, etc. (Stiglitz, 1998; Rodrik, 2004) also showed that there is no single economic policy receipt suitable for all countries while interaction between variables, national institutions and path dependency can explain much more the recent economic success of many countries in Asia or the economic boom of some European countries after the Second World War (Rodrik, 1999). In former communist transitional economies, the transformation from plan to market was mainly perceived by economists and policy makers as a combination of Liberalization, Privatization and Stabilization (LPS). This receipt, associated with democratization, brought about moderate success in some countries such as Poland, Czech Republic, Hungary while in other countries, where LPS receipt was less associated with democratization, such as Russia, Romania, Bulgaria and many other former Soviet Republics, it brought about failures and less income than prior transition. On the contrary, in China and a few other emerging economies where heterodox policies were implemented, there was no consensus on the above mentioned LPS receipt yet China economic growth is defined as “phenomenal” and economic success is real. China’s success occurred without complete liberalization, without privatization and without democratization (Qian 2003). In 1988, China’s GDP was half of Russia’s, in 1998 Russia’s GDP was half of China’s. Markets incentives occurred without liberalization and secure private property rights. China was poor, overpopulated, shorts of human capital and natural resources and was constrained by an ideology which was hostile towards markets. Nevertheless, GDP growth took place and was, under such initial conditions, really surprising (Qian, 2003). GDP in terms of “Purchasing Power Parity” (PPP) in China is about to reach and/or to overcame the ones of the largest European economies (Italy, France, United Kingdom, Germany).

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4. THE DETERMINANT OF ECONOMIC GROWTH: INTERACTION BETWEEN SELECTED VARIABLES As the review of the literature above suggests, there does not seem to be a single receipt with one variable that is able to explain economic growth. On the contrary, empirical evidence in developed capitalist economies and also in the recently emerged economies such as Ireland and Spain, the reference countries in our sample, shows that economic receipt was very different among capitalist countries. Moreover, a consistent part of economic growth comes from a “residual” or “black box” which is not explained by traditional variables such as capital and labour (Solow, 1956). This residual, which is generally associated with technological progress, can be explained by better endowment of some variables such as institutions, infrastructures, social capital, etc. (Knack and Keefer, 1995; Olson et al., 1998; Jones and Hall, 1999). Therefore, in order to explain economic growth, our analysis focuses on the simultaneous presence of some socio-economic factors and institutional indicators. Only when “institutions”, which provide the proper governance, give the right incentives to economic agents, a positive interaction with other socio-economic variables will foster economic growth. Each society can have their own formal and informal rules but what it is important is that they provide a consistent institutional framework for a good business environment, reduce uncertainty, and implement effectively appropriate institutions and policies. Below I will present the relevant factors which can interact positively with each other in order to create economic growth.

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4.1. Human Capital Starting from endogenous growth models, more and more economists included schooling in their growth model. Romer (1986), following seminal works by Young (1928), Kaldor (1957) and Arrow (1962), imputed increasing returns to scale to knowledge. An improvement in the skills of workers increases, ceteris paribus, the final outcome simply because skilled workers are more productive. Knowledge is strictly connected with school and education. Lucas (1988) directly associated the human capital with “learning by schooling” and “learning by doing”, allowing human capital to become reproducible. Physical capital integrated by this definition of human capital is part of a cumulative and reproducible process which avoids decreasing return to scale. Empirically, this model was followed among others by Levine and Renelt (1992), Barro and Sala-i-Martin (1995) and Barro (1998) who showed that convergence between countries is conditional to improvements over time in secondary school enrolment. Moreover, empirical studies show that high education levels are positively correlated with appropriate reform processes in transition and emerging economies (Goel and Budak 2006). At the same time, neoclassical economists argue that human capital only accounts for a fraction of cross-country income differences (Hendricks 2002). Furthermore, reverse causality, according to which growth causes schooling, seems to be, in their crosscountry analysis, more important (Bils and Klenow, 2000). In our model, human capital, expressed by the variable “secondary school enrolment ratio” as an average between 2000-05, contributes to economic growth only when it is associated with appropriate governance,

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captured by political stability and government effectiveness. Of course, policies and incentives, even in politically stable countries with strong governments could be biased. However, political stability and government effectiveness would at least offer a consistent and secure institutional framework which would allow economic agents, both workers and firms, to accumulate knowledge and capital (Jones and Hall, 1999). Economic agents would know that they could get benefits from that better than in a country where political instability and government ineffectiveness prevail.

4.2. Openness

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Lewis (1980), and with him many economists such as Lucas (1993) and Baghwati (2004), believed that trade is the engine of economic growth. Nevertheless, the experience of globalization, so far, has shown that performance of opened economies can vary consistently. The hypothesis that I am supporting in the paper is that openness per se, perceived as export ability, although could be one of the indicators of competitiveness, it is not an engine of economic growth. Integration in the world economy (defined as import and export as GDP percentage) should be accompanied by institutions and state strategies which support internal cohesion and maintain external competitive advantages. According to Rodrik (1999), the best performing countries are the ones that are integrated in the world economy with appropriate institutions which are able to support the impact of globalization on domestic market and social domestic issues. Countries with poor political institutions, weak conflict management institutions and strong social cleavages suffer the external shocks and do not perform well in the world economy. The world market is a source of disruption and upheaval as much as it is an opportunity for profit and economic growth. Without the complementary institutions at home – in the areas of governance, judiciary, civil liberties, social insurance, and education – one gets too much of the former and too little of the later. The weakness of the domestic institutions of conflict management was the Achilles’ heel of the development strategy pursued in Latin America, the Middle East, and elsewhere, and this is what made countries in these regions so susceptible to the external shocks of the 1970s (Rodrik, 1999 p.96).

In Lucas (1993), international trade contributes to stimulate economic growth through a process of structural change and capital accumulation. As in the case of Ireland, where according to Walsh and Whelan (1999) a structural change had already taken place during the 1970s and created conditions which allowed the Irish economy to grow considerably in the 1990s and later in the 2000s.5 Capital accumulation is determined by a “learning by doing” and a “learning by schooling” in a process of knowledge and innovation spillover. A country which protects their goods from international competition by raising tariffs on goods made with intensive skilled work will have as an effect an increase, at home, in the price of goods which use intensive skilled work. Skilled workers’ wages will increase and R&D will be more expensive. Consecutively investments in R&D will decrease and growth will be 5 Similar conditions which are however less marked, took place in Spain which together with Ireland is a reference country in our sample.

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affected negatively. On the contrary, deleting tariffs on those goods will cause a reduction in the price of goods which use intensive skilled work. R&D will cost less and investments in R&D will increase with positive effects on growth (Lucas, 1993). Policies should therefore address such problems and should create conditions for effective and substantial R&D investments. In our model, openness (expressed by the variable “Export” in $US during 2000-05) to world economy is not a condition of economic growth. Following Rodrik’s approach, policies and institutions together with openness and human capital interact positively and can create better conditions for sustainable economic growth. Institutions give the right incentive for knowledge to be accumulated and capital to be invested. This allows firms to be more competitive and export more leading to higher economic growth.

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4.3. Human Development The idea that the GDP is an absolute and reliable measure of development has been widely criticized by development economists (Morris, 1979; Sen, 1985; Noorbakhsh, 1996). A great deal of empirical evidence shows that, both in developing and in developed economies, some countries have relatively high GDP per capita but very low indicators of development such as literacy, access to drinking water, rate of infant mortality, life expectancy, education, etc. This is partly due to the fact that wealth is unequally distributed. Vice versa, there are cases of relatively low GDP per capita and high indicators of development in countries where income is more equally distributed (Ray 1998).6 Human development, which is considered to be a process which allows for an environment where people enjoy long, healthy and creative lives (UNDP, 1990), is a better measure of wellbeing. Human development is measured using the Human Development Index (HDI) of the United Nations Development Programme (UNDP).7 The core idea which is maintained in this paper is that countries that experienced an increase in human development levels will have sustained economic growth. Investments in Human Development increase both aggregate demand and effective quality of life. A better quality of life will generate a better and more skilled labour forces, with positive effects on 6 For instance, Guatemala has a GDP per capita that is higher than Sri Lanka but inequality is much higher in Guatemala. Development indicators are much better in Sri Lanka than in Guatemala. Life expectancy (years): 72 compared with 65; infant mortality rate (per 1000): 18 compared with 48; access to safe water (% of pop.): 60 compared with 62; adult literacy rate (%): 89 compared with 54 (UNDP, 1995). Examples like this are numerous and non-perfect correspondence between GDP and development indicators can be observed even in industrialized countries where there are more resources to distribute. For instance, Ireland has the highest GDP per capita after Luxemburg yet its non-income dimension indicators i.e., education and life expectancy are lower than Italy or Portugal (UNDP 2006). Saudi Arabia has a GDP per capita which is higher than many transition economies such as Poland Czech Republic, Hungary etc, but its non-income dimension indicators are lower. USA has an income per capita which is much higher than most of the countries in the world, yet life expectancy of black American citizens is lower than in China or in the Indian State of Kerala. As a result of all these contradictions and exceptions, the UNDP taxation of Human Development Indexes and GDP rank is not at all coincident (UNDP, 1999). 7 The UNDP Human Development Index is a composite index, ranking between 0-1. It is the combination of two non-income dimensions of people’s lives and one income dimension. The first one is life expectancy at birth which also reflects infant mortality. The second one is educational attainment which is a combination of primary, secondary and tertiary educational level and adult literacy rate. The third element is an adjusted GDP index which reflects income per capita measured in Purchasing Power Parity (PPP) at US$ (UNDP, 1990).

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economic growth, as Barro (1998) showed using improvements in life expectancy from 1960s to 1990s as an explanatory variable in growth regression. I will show that countries which invested during 1970-1998 in non-income dimensions of human development are emerging today (1998-2008) as fast growing economies. As a human development variable I used Infant mortality reduction between 1970 and 1998. Using Infant mortality is useful in order to avoid possible endogeneity problems between human development and GDP.8 However, a non-income dimension of human development is associated with institutional improvements and competitiveness. In other words, human development, together with appropriate institutions and competitiveness of markets, underlined by export ability, and human capital, determine economic growth.

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4.4. Institutions Economic researches showed that institutions and good governance, in some ways, matter in economic organization and rising productivity (i.e., Knack and Keefer, 1994; Olson et al 1998; Jones and Hall 1999; Acemouglu et. al., 2001; etc). Institutions are in general defined as “the rules of the game”. A more sophisticate definition of institutions is “a set of social rules that structure social interactions” (Knight 1992, p. 2). If we consider this definition of institutions, then the explanation of development should be consistent with that of Kuznets (1965, p. 30): “the transformation of an underdeveloped in to a developed country is not merely the mechanical addition of a stock of physical capital: it is a thoroughgoing revolution in the patterns of life and a cardinal change in the relative powers and position of various groups in the population”. Consequently, in order to change institutions, the prevalent social rules need to be changed. In emerging economies, informal economic institutions (i.e. uncodified and prevalent social rules9) can be very resistant towards change and inertia may occur. This is one of the most important problems which inhibit development. Institutional policies and an active State role are therefore needed in order to favour cultural change and foster development. To characterize institutions and institutional reforms is a very difficult task and institutional economists are well aware of this. Recently, Bardhan (2005) suggested that some non-income dimensions of development are better explained by a particular institutional index such as participatory rights and democratic accountability than property right institutions, while according to Rodrik and Rigobon (2005), who explain income gaps among countries, democracy and the rule of law are both good for economic performance. Since 1996 the World Bank has regularly published governance indicators which focus on political institutions and informal institutions.10 I will use these indicators as independent extra-economic variables interacting with other economic variables such as openness and 8 Although Infant Mortality is not an index considered in the HDI, it is a very good proxy of the Life expectancy Index, which is instead considered in the HDI (UNDP, 1999). 9 Cf. Hodgson (2006). 10 World Bank indicators, elaborated by Kaufmann, Kraay and Mastruzzi (2006) reflect the statistical compilation of responses on the quality of governance given by a large number of enterprise, citizen and expert survey respondents in industrial and developing countries as reported by a number of survey institutes, think tanks, non-governmental organizations, and international organizations. Indexes are estimated between -2,5 and +2,5. They concern five fundamental governance dimensions: Voice and Accountability, Political Stability, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption.

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education in order to observe their relation with economic growth. There is one variable which has a positive and statistically significant impact on our cross-country section, that is Political Stability. This result confirms that countries which enjoyed relatively high political stability were able to give effectiveness to appropriate social oriented policies and they had better performance in terms of GDP. Moreover, Voice and Accountability along with Government effectiveness, seem to be important for performance in terms of HDI. Finally, Control of Corruption, Regulatory Quality and Rule of Law which are also taken into consideration, do not seem statistically significant for the GDP or HDI. The point is that if Government is ineffective or the State is politically unstable, the formal economic institutions are weaker and informal institutions and processes of spontaneous forces prevail. This informal institutionalization may also be parastatal or illegal. Examples include the mafia, organized crime, corrupt bureaucracy and an informal economic network among agents, lobbies, etc. These forces fill the vacuum power. These kinds of informal institutions will generate an informal and illegal economy, underdevelopment forces such as inequality and poverty will prevail and human development will be lowered. Moreover, economic relations will be weakened and transaction costs will increase, thus negatively affecting economic growth. Recently the relationship institutionsÆ economic growth has been increasingly investigated both from a theoretical and empirical point of view (e.g., North and Thomas, 1981; Jones 1981; Knack and Keefer, 1995; Rodrik 1999). Olson et al. (1998) show that better governance and quality of institutions are the main sources of economic growth and determine the differences between the output of the various countries. Along the same lines, Jones and Hall (1999) find that “Social Infrastructure” and governmental policies explain the different levels among countries of the residual productivity, which in turn, is on the basis of the GDP level of the countries. However, very often the main problem with this analysis is a reliable estimate of the impact of institutions on economic performance. Usually, rich countries have better institutions. The difficulty is to obtain an instrumental and exogenous variable to compare with income. Acemouglu et. al., (2001) estimate in a cross country section that institutions, expressed instrumentally by settler mortality rates, have a significant effect on economic growth. In the model below, an independent institutional variable (i.e., political stability) will be regressed together with a non-income dimension variable such as infant mortality, which to some extent is an indirect indicator of policies (cf. Easterly, 2001). The first results seem to suggest that only when institutions and policies appear simultaneously in the regression with openness - represented by export capacity of countries - and with education – represented by the secondary school enrolment ratio - the cross country section seem to yield consistent results.11

5. THE MODEL In our model, institutions, measured by the World Bank governance indicators, play a crucial role. On the one hand, institutions, i.e., voice and accountability and government effectiveness explain Human Development. In fact, human development is based on Sen’s 11 Secondary school enrolment ratio is a good indicator, in emerging countries, for skilled workers.

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notion of “capability”, perceived in the sense of what people want and can choose (Sen 1985; Sen 1999). At the same time, choices are determined by institutions and perceived in the sense of policies that give opportunities to people, in other words, capabilities (Fadda, 2003). Increasing human development means increasing both aggregate demand and effective quality of life. A better and healthier quality of life, will generate stronger and better labour forces, with a positive effect on economic growth. On the other hand Political Stability, another World Bank indicator, provides an institutional framework which is useful for reducing uncertainty, ensuring property rights and guaranteeing legality. Moreover, when the institutional variable (Political Stability) and the economic variables (human capital and openness) appear simultaneously in the regression they produce better and significant results. In other words, economic agents receive positive incentives to accumulate human capital (i.e., education), invest in R&D and therefore be more competitive in the world economy, with a positive effect on economic growth (Jones and Hall, 1999). To these three independent variables (political stability, education and openness), a fourth variable is added, that is infant mortality. In order to avoid endogeneity problems we consider as a non income dimension variable and proxy for human development, the infant mortality reduction between 1970-98. In fact, this indicator is not directly included in the calculation of the HDI. Both the first (institutions Æ HD) and the second (institutions + socio-economic variables Æ GDP) relationships will generate high economic growth. Such a model, which is analysed in the cross country regression, is shown in the figure below: Openness and Human capital Economic growth

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Institutions Human development Figure 1.

The equation of such a model would be represented by the following:

Growth = α + β1 PS + β 2 IMR + β 3 EXP + β 4 EDU 2 where economic growth (Growth) is a function of infant mortality reduction (IMR), Political stability (PS), Export flow (EXP) and Secondary school enrolment ratio (EDU2): Following the model presented, investments in education and in the health system are crucial conditions to foster a development process. Therefore, heath and education should be treated as public goods because they can generate collective benefits. In fact, public expenditure in health is crucial for reducing infant mortality and, at the same time, for improving life expectancy; public expenditure in education is important for secondary school enrolment ratio and, at the same time, for R&D which in turn affects competitiveness of firms and therefore exports ability. However, as table A3 in appendix shows, emerging economies have different strategies and levels of public investment in education and health and the

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private sector can play an important role. This depends, on one hand, on the efficiency of the markets to create social benefits and collective advantages. On the other political stability would help public investments and development policies to be more effective. In the cross country analysis, I first regress human development index (2007) with two institutional variables. As table 1 below shows, the HDI is largely explained (R-squared 46%) by Voice and Accountability and Government Effectiveness (average indicators 2000-05). Other variables, such as rule of law, control of corruption and political stability, which are presented in appendix (tables A2 and A4) do not seem to improve the regression and are therefore excluded. These results, which are consistent with Bardhan’s ones (2005), encourage institutional policies which give opportunities to people, allow for pluralism and provide a consistent institutional framework. Table 1. Dependent variable: HDI 2007 Method: OLS Number of obs: 47 Voice and Accountability Government effectiveness Constant R-squared= 0.463399 Adjusted R-squared Durbin-Watson stat Mean dependent var Log Likelihood F-statistic Prob(F-statistic)

Coeff. 0.048551 0.056675 0.759759

Std. Err. 0.016531 0.019677 0.012335

P>|t| 0.0053 0.0062 0.0000

0.438441 1.788478 0.782087 55.70960 18.56703 0.00000

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Source: own elaboration on data in appendix Tables A1-A3-A4

If China had the same level/quality of institutions as Ireland its HDI would be 25% more than its actual level. For Botswana, the HDI would be 68% higher and for Pakistan, it would be 82% higher. A Granger causality test applied to the variables above confirms the direction of the causality between institutions Æ HDI (cf. table 2). Countries which enjoy greater pluralism allow people to participate in political decisions. In this case public choices, such as public investments in health and education, would be better supported. Consecutively, education level and life expectancy would increase and HDI would grow. Illiberal democracies (such as Russia, Venezuela, Malaysia) and authoritarian regimes (such as China, Vietnam) are in a worst position than liberal democracies (such as Ireland and Spain).12 12 Such a classification of countries between liberal democracies, illiberal democracies, and authoritarian regimes is reported in R. Hague and M. Harrop, (2007) Comparative Government and Politics, Basingstoke: Palgrave, p. 8, where a fourth category, i.e., totalitarian states, is added. However, this is a political classification, and does not necessarily correspond to the economic classification which will be used later (cf. chapter 6). Following the political classification, and considering only the countries present in both my sample and the book of Hague and Harrop (2007), it can be observed that average HDI 2004 of liberal democracies is higher than average HDI 2004 of illiberal democracies and authoritarian regimes. Following the economic classification it can be observed that corporative capitalist countries have, in average, higher HDI than all the average values of HDI of the other groups (cf. table 7).

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Pasquale Tridico Table 2. Granger Causality Test

Pairwise Granger Causality Tests Lags: 2; Obs: 47 Null Hypothesis: F-Statistic Voice and Accountability does not cause 0.00196 HDI Government effectiveness does not cause 0.75153 HDI

Probability 0.99805

Rejected

0.47871

Rejected

Source: own elaboration

Better institutions are not only able to improve HDI. Better institutions, together with a set of three socio-economic variables i.e., infant mortality, openness and education, seem to explain most of the recent growth of emerging economies. In the second cross-section, I regress GDP growth (average 1998-2008) with infant mortality change (1970-1998), secondary schools enrolment ratio (average level 2000-05) and Export (average flow 200005). Although statistically significant interaction terms do not appear in the regression, one can observe that when institutions (i.e., political stability, average indicator 2000-05) are included in the regression, the R-squared increases and the coefficients are statistically more significant. This means that all the three socio-economic factors along with political stability are in themselves conductive to growth. The quality of institutions is another variable that explains part of economic growth.

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Table 3. Dependent variable: average rate of economic growth (1998-2008) Regressions with and without the institutional variable(Political stability Av. 2000-05) Method: OLS (heteroskedasticity-consistent) Number of Obs: 47 I Regression with Institutions II Regression without institutions Variables Coefficients Variables 0.034534** Secondary Education Secondary Education (0.017121) Av. 2000-05 Av. 2000-05 9.44E-09* Export Export (3.31E-09) Av. 2000-05 Av. 2000-05 0.025427** Reduction Reduction Infant Mortality 1970-98 (0.011825) Infant Mortality 1970-98 0.750574** Political Stability (0.327082) Av. 2000-05 Constant 2.473991 Constant (1.531082) R-squared 0.429075 0.355747 Adjusted R-squared 0.373375 0.309729 Durbin-Watson stat 1.784644 1.942351 Mean dependent var 4.144954 4.144954 Log Likelihood -82.39311 -85.17228 F-statistic 7.703311 7.730585 Prob(F-statistic) 0.000100 0.000319 Significance level at 1%(*), 5% (**): Standard error in parenthesis Source: own elaboration on data in appendix (table A2) Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Coefficients 0.048903* (0.016724) 1.05E-08* (3.43E-09) 0.024565** (0.012405) 1.341334 1.521164

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The results of our cross-country analysis in Table 3 confirm our model and confirm that growth is a complex process.13 Institutions along with socio-economic variables increase economic performance, yet openness and education alone are no longer enough to explain economic growth. In general, growth seems to be associated with education and integration in the world economy mitigated by appropriate institutions expressed by Political Stability and the improvement of human development, expressed by reduction of infant mortality. In particular, growth (Gro98.08) is a function of infant mortality reduction from 1970 to 1998 (IMR), Political stability (PS - average indicator 2000-2005), Export flow (EXP - average 2000-2005) and secondary school enrolment ratio (EDU2 - average 2000-2005), plus a random error term, e:

Gro98.08 = 2.47 + 0.02 * IMR + 0.75 * PS + 9.44 * EXP + 0.03 * EDU 2 + ε i Once the variables of table A2 in appendix are substituted in the above equation, economic growth in emerging economic will be largely explained. The simultaneous presence of an institutional variable and of the socio-economic variables improves the quality of the regression. Nevertheless, the quality of institutions does not seem to be associated with any particular form of institutions. Political stability is a general concept which is necessary for the economy to work. It provides a consistent institutional framework, allow economic agents to make right choices and manage and mitigate social conflicts. However, institutional forms and reform processes in each country can vary consistently and this does not affect economic performance. In fact, as I will show in the next paragraph, socio-economic models of these countries are very different.

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6. SOCIO-ECONOMIC MODELS AND ECONOMIC GROWTH In general countries can be classified according to their type of economic system which can be characterised by some particular institutional forms and macroeconomic factors such as competition, role of the state, openness, etc. Following this approach Amoroso (2003) and Jessop (2002), identified 4 types of economic systems such as the Anglo-Saxon model (or competitive capitalism), the Corporatist model (corporative capitalism), the Dirigist model, and the social-democratic model. To these models, Choi Chonj Ju (2004) and many others (i.e., Yeager, 2004; Qian, 2003; etc) added the current model of the Socialist Markets represented in particular by China and Vietnam. The table 4 summarizes the main theoretical characteristics of these 5 socio-economic models, and, in parentheses, the main leaders of the model. However, in my sample of countries, four models only are represented because among emerging economies the social democratic model does not appear. Moreover, in order to classify all the 47 countries of the sample I used a type of classification which takes the control of firm ownerships into consideration. This classification was elaborated by Levine

13 The regression model, which is heteroskedasticity-consistent, shows a normality distribution of the residuals with a F-statistic very significant. Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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and Kunt (1999)14 and it is made by considering proxies from financial structures among countries. This type of classification has the advantage of allowing a world-wide comparison among many countries. In some countries, firms are controlled by financial markets, in others the State has several control functions over firms and in others still, the control over firms is shared by State, banks, trade unions, etc. Following this classification the same types of models described in table 4 can be identified. Table 4. Socio-economic models and main characteristics

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Characteristics Competition Economic Regulation Models (leader country) Deregulation, Anglo-saxon Promoting withdrawal of free model competition the State from (USA, UK, the Economy Irland) Decentralized Balancing Corporatist Cooperation model and (Germany) Competition

Main Economic Actors

Relationship International Taxation between Economic public and Relation private actors

Residual Firms, Global Low taxes, Corporations, public sector: competition no or little Markets, Marketprogressive oriented rate PublicTripartite Protection of High private structures taxation to strategic (business partnerships sectors in an finance clubs, Trade open economy Welfare unions, State government) Private and PublicProtectionism High Taxes Dirigist model State Control, National and Accumulation Public sectors private (France) regulated Collective competition and Regulation partnerships Recourses Strategy under State guide PublicPublic and Knowledge State High wages, Social National and innovation Private Firms private controlled career Actors, Democratic liberalization as economic and Ethic model partnership in moderate free perspective, Corporations order to guide for (Scandinavian and competition, High and competition regulation countries) realize Social open economy progressive Cohesion tax rate Public and National State or State Balancing Distributive Socialist Regulation and municipal between markets private actors strategies in a policies, owned firms, with more innovation forms of global context, collective (China, semi-private emphasis on reasonably liberalization Vietnam) services, firms, private collective and free equalitarian free trade foreign firms. goals competition principles. Public Authorities Source: own elaboration and adaptation from Jessop (2002), Amoroso (2003) and Choi Chonj Ju (2004).

This classification is also consistent with the one elaborated by La Porta et al., (1999) who consider different indicators of corporate ownership and financial structures such as State/Families/Financial Institutions/miscellaneous ownerships of firms. Following Levine 14 The debate, in the field of finance about the relation between finance structures and economic growth is very important (see for instance Rajan and Zingales, 1995; Levine and Zervos, 1998). However, this topic remains outside of our analysis.

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and Kunt (1999), a high indicator of “Claims of deposit money bank on private sector/GDP” underlines strong bank activity in the economy. Germany which is the benchmark country for the corporative capitalist model has 0.94 as a value of this indicator. While a high indicator of “Claims of other Financial Institutions on private sector/GDP” underlines market control of the economy. The USA which is the benchmark country for the competitive capitalist model has 0.91 as a value of this indicator. The proxy for the dirigiste capitalist model comes from the “Public share in commercial banks”, and France has the highest values, among advanced economies, for this indicator (0.74). Then countries are classified according to the closeness of their indicators to the benchmarks (cf. table 5). Countries with a higher value of the indicator “Claims of other Financial Institutions on private sector/GDP” will be listed in the model “Competitive capitalism”. Countries with a higher value of the indicator “Claims of deposit money bank on private sector/GDP” will be listed in the model “Corporative capitalism”. Countries with a higher value of the indicator “Public share in commercial banks” will be listed in the model “Dirigiste capitalism”. For instance, Ireland, South Africa, Chile etc have a higher value of the indicator “Claims of other Financial Institutions on private sector/GDP” and they are therefore classified in the model Competitive capitalism. Korea, Malaysia, Hong Kong etc. have a higher value of the indicator “Claims of deposit money bank on private sector/GDP”, and they are therefore classified in the model “Corporative capitalism”. Colombia, Israel, Pakistan, Brazil, etc have a higher value of the indicator “Public share in commercial banks” and they are therefore classified in the model “Dirigiste capitalism”.15 Finally, China and Vietnam are classified as Socialist Markets following the interpretation of Choi Chonj Ju (2004) and many others (i.e., Yeager, 2004; Qian, 2003; etc). This classification is more influenced by long-run strategies than particular policies implemented in a short period. Therefore, even if a country, such as India or Brazil or Turkey, implemented neoliberal policies during 1990s (De Long 2003; Easterly, 2001; Stalling and Peres 2000), there are not automatically classified in competitive capitalism, etc. In a competitive capitalist country, financial markets control and determine shareholder behaviour and this affects corporate governance and performance. Among advanced economies, this model is represented by the USA. This model as well as the others listed below, is not only characterized by the type of control over shareholders. Many other factors are included on the basis of the differences between the models listed such as percentage of public expenditure in health and education; Welfare States, democracy/pluralism; etc., which are indicated in the Table A1 in the Appendix. However, I feel that the control over shareholders synthesises the type of socio-economic model well. Countries in this group, whose benchmark is Ireland, are mainly from Europe and Latin America. In general, these are countries where the economic and cultural influence of the USA, which is the theoretical benchmark of the model, is stronger. In corporative capitalist countries the control and monitoring of shareholders is shared by several agents such as banks, financial markets, Government and employees. This type of socio-economic model, implemented in Germany and Japan, which are the theoretical benchmarks, especially after WWII, is characterized by a particular type of compromise 15 However, whereas the country was not listed in the classification of Levine and Kunt (1999) I refereed to the similar indicators of La Porta et al., (1999). Finally, if the country was not listed also in La Porta et al., (1999) I refereed to the more general macroeconomic classification elaborated by Jessop (2002), Amoroso (2003), Choi Chonj Ju (2004), Yeager, (2004), Qian, (2003).

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between economic agents and organizations. Current benchmarks in the sample are the New Industrialized Countries, NIC, (Hong Kong/Taiwan/Korea S./Singapore). In some Asian countries, such as Indonesia, Thailand, the Philippines and Malaysia, this compromise included a sort of family capitalism because of the stronger power, in those countries, of some families (Hirshmann, 1981). Countries in this group are mainly from Europe and Asia. These are countries where the influence of Germany and Japan is stronger (Wade, 1990). The third group is made up of Dirigiste capitalist countries where State control of the market and some assets in particular is quite consistent, in line with the French model – the theoretical benchmark. However, this is a very heterogeneous group of countries and references to France, in terms of cultural and economic influence, are not clear with the exception of Tunisia and Algeria whose influences could derive from the fact that they were former French colonies. India, which could represent, to some extent, the benchmark of the sample, has a sort of mixed model where State control of markets is quite strong. Russia, Pakistan, Saudi Arabia and Venezuela have a very odd type of socio-economic model which is difficult to include completely in the French model of dirigisme capitalism. The attachment to this model is made rather on the basis of the power and the control that single “State leaders” and/or particular “families” or “organization” seem to have over the economy. Israel, which is also in this group, is a very special case. Because of its history and cultural heritage, the type of socio-economic model seems to fit into this group better. However, economic and cultural influence from France is scarce. In a way, Israel could constitute a benchmark in itself. China and Vietnam represent “Socialist Markets” and seem to be the only two countries which embrace such a model. This represents an evolution and a result of a reform process which started firstly in China in 1978 and was intensified during the 1990s (Yeager, 2004). This transitional process transformed China and Vietnam from planned economies to “Socialist Market Economies”, characterized first by particular forms of property rights which allow: 1) both privates and State to invest, without complete liberalization, privatization and pluralism; 2) integration in the world economy, though quite modest; 3) government control and monitoring of domestic financial markets. Finally, the Social democratic model should also be listed, although I did not find any countries, among emerging economies, which could be closer to such a model. This model is characterized by the traditional compromise between Trade Unions and Industrial organizations (Jessop, 2002; Amoroso, 2003). The State guarantees that this compromise is respected. This compromise allows trade unions and employees to play a role in the economic organization and in the corporate decisions. The Social democratic model follows this scheme: Trade Unions and Markets Æ Shareholder Æ corporate performance. Theoretical Benchmarks of this model among advanced economies are Scandinavian economies such as Sweden, Norway, Denmark and Finland. The fact that I did not find any countries among emerging economies that could be included in the Social democratic model underlines, in a sense, that Scandinavian countries are not very influential and able to “export” their model, although it worked well in their countries and produced very positive results in economic and social terms (Rodhes, 2000).

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Table 5. Type of socio-economic models

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1) Competitive capitalism Financial Markets ⇓ shareholder ⇓ corporate performance

2) Corporative capitalism Banks, Families, Government, Trade Union ⇓ Shareholder ⇓ corporate performance

3) Dirigiste capitalism 4) Socialist Markets State and Financial Market ⇓ Shareholder ⇓ corporate performance

Government and Emerging Markets ⇓ Shareholder ⇓ corporate performance

Theoretical Benchmark: Theoretical Benchmark: Theoretical and actual USA. Actual Theoretical Benchmark: France. Actual Benchmark: Benchmark in the Germany/Japan. Actual Benchmark in the China/Vietnam Sample: Ireland Benchmark in the Sample: India Sample: NIC Ireland Hong Kong India China Bulgaria Taiwan Saudi Arabia Vietnam Romania Korea S. Tunisia Estonia Singapore Russia Czech Republic Indonesia Pakistan Peru Thailand Venezuela Mexico Latvia Egypt Argentina Philippines Algeria Bolivia Lithuania Turkey Chile Malaysia Brazil Botswana Hungary Israel Albania Slovenia Colombia Slovak Croatia South Africa Spain Ecuador Poland Ukraine Average GDP growth Average GDP growth Average GDP growth Average GDP growth 1999-2005 1999-2005 1999-2005 1999-2005 4,33 4,85 2,78 7,95 Source: own elaboration

When I control for the type of socio-economic model of the country by introducing a dummy variable for each of the 4 models above analysed, the results are not significant. First of all, the correlation matrix below (table 4) shows a low correlation between the dummy, which represents the type of model, the other socio-economic and institutional variables, and the average rate of growth (1999-2006).16

16 Each country received a dummy between 1 and 4, according to the model with which they are associated. Competitive capitalism (1), Corporative capitalism (2), Dirigiste capitalism (3), Socialist Markets (4). Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Pasquale Tridico Table 6. Correlation matrix

growth Polit. Stab. export edu_2 inf_mort.red dummy_mod growth99_06 1.0000 Political Stability 0.4487 1.0000 Export 0.3846 0.1829 1.0000 Edu_2 0.4247 0.3765 0.1114 1.0000 Inf. mort. reduc. 0.2020 -0.0321 -0.1825 0.0622 1.0000 dummy_model -0.0077 -0.4418 0.2310 -0.1431 -0.0583 1.0000 Source: own elaboration, data in appendix, Table A2, plus dummy variables as they appear in table 4

Secondly, the regression modified with the dummy variable yields poor results. Hence, the type of socio-economic model does not have an impact on growth. This confirms our hypothesis according to which it is not the model per se which makes countries richer or poorer but the consistency of the institutional framework and the effectiveness of appropriate policies, expressed by the political stability and government effectiveness indicators, which, together with some policy indicators of human development as defined by Easterly (2001) and with some particular variables such as education and export, allow countries to growth. Moreover, these results are consistent with what Rodrik (2003) has shown: different countries require different institutions to support economic growth. The regression table obtained when introducing the dummy variable capturing the type of socio-economic model is shown below. Table 7. Dependent variable: average rate of economic growth (1998-2008)

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Method: OLS Number of Obs: 47 Secondary Education Av. 2000-05 Export Av. 2000-05 Reduction Infant Mortality 1970-98 Political Stability Av. 2000-05 Dummy var Model C R-squared = 0.441761 Adjusted R-squared 0.371981 Durbin-Watson stat 1.771040 Mean dependent var 4.144954 Log Likelihood -81.87629 F-statistic 6.330768 Prob(F-statistic) 0.000204

Coeff. 0.034305

Std. Err. 0.017141

P>|t| 0.0522

8.28E-09

3.53E-09

0.0238

0.025653

0.011840

0.0363

0.922686

0.373910

0.0180

0.288211 1.953444

0.302295 1.627122

0.3461 0.2370

Source: own elaboration, data in appendix, Table A2, plus dummy variables as they appear in table 4

Finally, something concerning other social indicators, such as inequality, poverty and life expectancy, has to be added. First of all, economic growth did not eliminate, so far, poverty among emerging economic (average level in EEs is 21.8% against 15%, in average, among Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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the most developed economies).17 Moreover, inequality level is very high (40% in EEs against 35%, in average, in the most developed economies)18, and life expectancy is, in average, 8 years less than in the most developed economies (71 years in EEs against 79 years in the most developed economies). However, among emerging economies, differences are considerable. In fact as average values show (cf. table 7), competitive capitalist countries, in general, are characterised by the highest inequality and poverty level; however they have higher HDI and GDP levels than socialist markets and dirigist capitalism model’s countries. The group of countries of the corporative model have the best indicators: in average they show lower inequality and poverty level and higher HDI and GDP level than all the average values of the other groups. These considerations are however very general and need deeper analysis and further researches. Table 8. Social indicators, HDI and GDP: average value among type of socio-economic models 1) 2) Competitive Corporative capitalism capitalism 42.47 36.12 28.64 15.93

Gini (%) 2000-04 Poverty (% below national line) 2000-04 HDI 2004 0.791 GDP PPP ($) 2008 11300 Life expectancy 2004 70.2

0.830 14432 72.6

3) Dirigiste capitalism

4) Socialist Markets

41.67 22.11

41 16

Average Emerging Economies 40% 21.8

0.724 7437 70.4

0.729 3860 72

0.783 11048 71.2

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Source: own elaboration, from data in appendix, Table A4

7. FINAL REMARKS In this paper I analysed, through a cross-country analysis, the determinants of economic growth among emerging economies. I found out that both human capital and export capacity are important for economic growth. However, these socio-economic variables increase their explanatory power when associated with a non-income dimension of development which is also policy indicators (i.e., infant mortality reduction between 1970-1998) and with good governance, expressed by a World Bank indicator, i.e., Political Stability. I showed that simultaneous presence of these variables explained growth to a greater extent. In other words, socio-economic variables cause growth when extra-economic institutional variables are able to provide an effective and stable institutional and political framework. In other words if a country has a medium score on institutions, health, education and openess, it can do much better overall, than a country with high scores in some aspects and very low scores in others. On the other hand, Voice and Accountability, together with Government Effectiveness seem to explain the HDI better. Indeed, pluralism and State interventism in non-income dimension such as health public expenditure and education public expenditure would generate more opportunities for people and better capabilities. Increasing human development means 17 Cf. UNDP, 2006. 18 It has to be noticed, however, the very high value of the GINI coefficient in USA i.e., 41% (UNDP, 2006).

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increasing both the effective quality of life and aggregate demand with positive effects on labour forces and economic growth. Furthermore, I found out that the type of socio-economic model (i.e., competitive capitalism, corporative capitalism, dirigiste capitalism and socialist markets) does not have an impact on growth. Emerging economies adopted very different socio-economic models and growth occurred independently, as a cross-country analysis with dummy variables controlling for the type of socio-economic model confirmed. Institutions and socio-economic models may be different among countries. However, is crucial that institutions and the socioeconomic model are able to provide voice and accountability, government effectiveness and political stability, which in turn create security for economic relations, incentives to accumulate knowledge, and create an environment for appropriate public choices in strategic dimensions such as education and health.

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APPENDIX Table A.1 Type of Economy – main institutional dimensions

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Countries

SocioEconomic % Public Expend, Integration model * on gdp (99-04) Glob,Economy (exp+imp as % gdp 9904) Ireland 1 13 167 Competitive Argentina 17 31 Capitalism Bolivia 19 46 Bulgaria 30 113 Chile 18 65 Czech Rep, 31 129 Mexico 13 60 Peru 17 34 Romania 15 74 Albania 19 14,2 Botswana 29 6,4 Ecuador 21 12,8 Estonia 31 14 Slovak 26 10,4 South Africa 24 28,6 Taiwan 2 12 9 Corporative Korea S, 11 12,4 Hong Kong capitalism 6 304 Singapore 9 14,5 Slovenia 22 114 Spain 17 57 Thailand 16 121 Lithuania 28 10,4 Latvia 31 7,5 Egypt 10 45 Hungary 28 137 Indonesia 18 67 Philippines 15 102 Malaysia 18 216 Croatia 28 5,5 Poland 17 65 Ukraine 34 110 India 3 36 28 Dirigist Brazil 22 26 economies Algeria 21 4,9 Turkey 16 57 Venezuela 17 45 Russia 26 63 Saudi Arabia 28 65 Tunisia 14 94 Pakistan 18 30 Israel 25 75 Colombia 28 41 Jordan 48 111 Morocco 18 60 China 4 Socialist 29 46 markets Viet Nam 15 114

-2,5/+2,5 Competitiveness (as Pluralism % export on GDP (Voice&Account,200005) 2000-04) 80 25 31 58 36 72 30 21 37 21 40 27 78 77 27 5 44 193 10 60 26 71 54 44 29 64 31 52 121 47 39 58 19 18 40 29 36 35 53 45 16 44 21 44 33 34 66

1,36 0,35 0,05 0,54 0,94 0,96 0,26 0,03 0,39 -0,04 0,73 -0,13 1,00 0,97 0,83 0,85 0,70 0,1 -0,05 1,06 1,11 0,2 0,94 0,90 -1,01 1,11 -0,43 0,12 -0,36 0,44 1,09 -0,51 0,33 0,37 -1,05 -0,32 -0,43 -0,65 -1,52 -0,97 -1,28 0,63 -0,47 -0,56 -0,56 -1,55 -1,54

Sources: 1st column: own elaboration; 2nd and 3rd column: Heston A., Summers R., Aten B., (2006), Penn World Tables 6.1; 4th columns: UNCDAT, 2006; 5th column: Kaufmann et. al., 2006.

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Table A.2 Relevant variables for growth (as they appear in the OLS regression model) Export (2000-05) Infant mortality Reduction 70- GDP growth Political Stability thousand of $ Secondary School 2000-05(-2.5/+2.5) enrolment 2000-05* 98 1998-08 (%) Albania -0,69 384470 77 -62 5,6 Algeria -1,61 23339337 67 -79 3,6 Argentina -0,30 28510101 79 -47 1,1 Bolivia -0,60 1617243 74 -55 2,5 Botswana 0,78 2743228 54 -62 6,0 Brazil -0,04 68390667 76 -62 2,3 Bulgaria 0,22 6630929 88 -50 4,6 Chile 0,82 21070827 80 -86 3,6 China 0,14 374489899 78 -55 9,0 Colombia -1,00 13435841 55 -64 2,3 Croatia 0,30 5641038 87 -76 3,6 Czech Republic 0,77 43086297 90 -76 3,3 Ecuador 0,95 5631091 50 -66 4,2 Egypt -0,66 4913327 81 -68 4,3 Estonia 0,83 4668674 88 -14 6,1 Hong Kong 1,05 217985619 74 -63 5,1 Hungary 0,82 33808683 91 -72 4,4 India -0,96 51264080 77 -46 6,3 Indonesia -0,90 60228238 64 -62 4,3 Ireland 1,15 89017840 87 -70 6,5 Israel -1,25 32076673 89 -75 2,8 Jordan -0,27 2666001 81 -61 0,2 Korea S. 0,32 186565961 87 -88 5,3 Latvia 0,81 2262015 88 -14 7,0 Lithuania 0,80 6066402 94 -17 6,4 Malaysia 0,29 102299997 76 -80 5,4 Mexico 0,13 162669887 64 -65 2,8 Morocco -0,31 8190657 35 -52 0,1 Pakistan -1,46 10884293 59 -21 1,7 Peru 0,86 8473265 69 -63 3,5 Philippines 0,98 35416858 61 -43 4,5 Poland 0,45 47047873 90 -69 3,4 Romania 0,09 15346125 81 -54 4,2 Russia 0,81 123731454 95 -28 6,7 Saudi Arabia -0,38 71612992 52 -81 3,5 Singapore 1,12 141422468 90 -82 6,1 Slovak Republic 0,72 17712777 88 -64 3,4 Slovenia 1,01 11348061 93 -80 3,8 South Africa -0,25 29781846 66 -40 3,1 Spain 0,44 128394301 97 -78 3,6 Taiwan 0,57 145184607 88 na 4,3 Thailand 0,09 71410257 67 -59 4,9 Tunisia 0,23 7274470 67 -81 4,7 -0,85 Turkey 40990953 59 -75 0,3 Ukraine -0,32 15086560 95 -18 6 Venezuela -1,13 28642994 60 -55 1,7 Viet Nam 0,29 15406011 85 -70 6,9 Notes: * data of China, India and Vietnam refer to gross secondary school enrolment ratio 2000-05, (UNICEF, 2005 ) Source: 1st column: Kaufmann et. al., 2006; 2nd and 3rd column: UNCDAT, 2006; 4th and 5th column: UNDP, 2006; 6thcolumn: WEO, 2008.

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Table A.3 Main economic strategies for growth Edu. Public GovernmentEffectiveness R&D as Health Public Expend. as % of GDP 2000-05(-2.5/+2.5) %GDP 004 Expend. as % of GDP 2003 2003 Albania -0,47 Na 2,7 5 Algeria -0,53 Na 3,3 5 -0,07 Argentina 0,4 4,3 4,2 Bolivia -0,35 0,3 4,3 6,4 Botswana 0,81 Na 3,3 6 Brazil -0,13 1 3,4 4,1 Bulgaria 0,03 0,5 4,1 4,2 Chile 1,09 0,6 3 3,7 China 0,08 1,3 2 2,2 Colombia -0,51 0,2 6,4 4,9 Croatia 0,28 1,1 6,5 4,5 Czech Repub 0,75 1,6 6,8 4,6 Ecuador 0,92 0,1 2 3 Egypt -0,18 0,2 1,5 3,9 Estonia 0,98 0,8 4,1 5,7 Hong Kong 1,22 0,6 2,8 4,7 Hungary 0,82 0,9 6,1 6 India -0,19 0,8 1,2 3,3 Indonesia -0,70 0,6 1,1 0,9 Ireland 1,61 1,1 5,4 4,3 Israel 0,70 1,3 6,1 7,3 Jordan -0,25 Na 4,4 8,1 Korea S. 0,90 2,6 2,8 4,6 Latvia 0,61 0,4 3,3 5,4 Lithuania 0,69 0,7 5 5,2 Malaysia 0,73 0,7 2,2 8 Mexico 0,03 0,4 2,9 5,8 Morocco -0,09 0,6 1,7 6,5 Pakistan -0,68 0,2 0,7 2 Peru 0,46 0,1 2,1 3 Philippines 0,08 0,6 1,4 3,2 Poland 0,60 0,6 4,5 5,8 Romania -0,23 0,4 3,8 3,6 Russia 0,51 1,3 5,3 3,7 Saudi Arabia -0,12 0,5 3 5,8 Singapore 2,28 2,2 1,6 3 Slovak Republic 0,60 0,6 5,2 4,4 Slovenia 0,92 1,5 6,7 6 South Africa 0,65 0,8 3,2 5,4 Spain 1,37 1,1 5,5 4,5 Taiwan 1,15 Na na Na Thailand 0,25 0,2 2 4,2 Tunisia 0,61 0,6 2,5 8,1 Turkey -0,19 0,7 5,4 3,7 Ukraine -0,63 1,2 3,8 4,6 Venezuela -0,88 0,3 2 4,5 Viet Nam 0,21 1 1,5 1,8 Source: first and second column: Kaufmann et. al., 2006; 3rd, 4th and 5th column: UNDP, 2006. Notes: The variables reported in this table are strictly connected with variables found relevant for growth in emerging economies (OLS regression model).

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Table A.4. Comparing models with poverty, inequality, HDI, GDP, Life expectancy, plus indicators of legality

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Countries Ireland Argentina Bolivia Bulgaria Chile Czech Rep Mexico Peru Romania Albania Botswana Ecuador Estonia Slovak South Afr, Taiwan Korea S, HongKong Singapore Slovenia Spain Thailand Lithuania Latvia Egypt Hungary Indonesia Philippines Malaysia Croatia Poland Ukraine India Brazil Algeria Turkey Venezuela Russia Saudi Ara Tunisia Pakistan Israel Colombia Morocco Jordan China Viet Nam

SocioEconomic model 1 Competitive Capitalism

2 Corporative capitalism

3 Dirigiste economies

4 Socialist markets

Poverty* 2000-04 16 27 62 12 17 5 20 49 21 25 30 46 12 21 50 1 2 Na Na 13 14 13 17 20 16 17 27 36 15 11 18 19 28 22 22 27 31 30 Na 7 32 15 15 19 18 4 28

Gini index (0-100) 2000-04 34 53 60 29 57 25 49 45 31 28 63 43 36 26 58 na 31 43 42 28 34 42 36 37 34 27 37 46 49 29 34 29 32 58 35 44 44 40 Na 40 31 39 59 39 39 45 37

Hdi 2004 0,946 0,863 0,687 0,808 0,854 0,874 0,814 0,762 0,792 0,78 0,565 0,759 0,853 0,849 0,658 na 0,901 0,916 0,907 0,904 0,928 0,778 0,852 0,836 0,659 0,862 0,697 0,758 0,796 0,841 0,858 0,76 0,602 0,792 0,722 0,75 0,772 0,795 0,603 0,753 0,527 0,915 0,785 0,631 0,753 0,755 0,704

GDP $ PPP Life 2008 Expectancy 2004 (years) 34551 74 12240 71 2585 75 7355 64 10146 35 15549 71 9222 72 5164 78 6945 72 5405 73 11410 75 4316 76 16414 75 16041 70 12161 72 20590 82 27721 73 27764 64 28368 67 18521 78 22887 80 6972 72 14158 77 12666 72 3817 73 14105 73 3750 75 4271 70 9546 63 12325 70 11000 71 6888 75 2745 72 7698 65 7189 72 4590 79 5485 74 8587 77 13350 47 6982 80 2209 na 21509 70 6509 74 4993 69 4844 66,1 5313 73 2408 71

Rule of law 2000-05 (-2.5/+2.5) -0,53 -0,61 -0,32 -0,12 1,20 -0,40 1,37 -0,78 0,03 0,76 0,05 -0,92 1,62 0,83 0,49 -0,40 -0,77 -0,63 -0,60 0,46 -0,26 -0,88 0,28 0,87 1,18 0,12 0,23 -0,02 -1,12 -0,55 0,64 0,77 -0,47 -0,53 0,81 0,28 -0,92 0,98 0,90 0,61 0,69 2,28 0,60 0,03 0,39 0,65 1,15

Control of Corrupt. 200005(-2.5/+2.5) -0,52 -0,79 -0,08 -0,11 1,39 -0,51 1,52 -0,40 -0,34 0,63 -0,36 -1,02 1,60 0,92 0,29 -0,32 -0,92 -0,32 -0,54 0,32 -0,33 -0,87 0,24 0,97 1,46 -0,31 0,36 -0,25 -0,95 -0,75 0,37 -0,79 -0,76 -0,61 0,95 0,07 -0,90 0,79 0,31 0,19 0,29 2,37 0,32 0,00 0,39 0,42 0,65

Source: UNDP, 2009. Columns Rule of Law and Control of Corruption: Kaufmann et al., 2006. Data on Poverty refers to the most recent year between 2000-04, and the percentage refers to the share of population below national income poverty line

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INDEX # 20th century, 36

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A abatement, 3 access, 35, 43, 44, 47, 106, 109, 114, 129, 144, 153, 155, 156, 161, 163, 166, 251 accessibility, 163 accounting, 9, 44 acid, 24 adaptation, 23 adaptations, 20 adjustment, 162 administrators, 98 adult literacy, 251 advancement, 161, 163 advancements, 161, 163, 165 adverse effects, 14, 107 Afghanistan, 246 Africa, 123, 175, 176 age, ix, 96, 98, 143, 145, 147, 150, 152, 153, 154 aggregate demand, viii, 101, 105, 164 agriculture, 17, 20, 125, 135, 147, 178, 183 air pollutants, 123 air quality, 182 Albania, 184, 247 Algeria, 184, 185, 247 algorithm, 200, 201 alternative energy, 140 alternative hypothesis, 149 alters, 7 American History, 48 amortization, 146, 147 annual rate, 24, 25, 147 appointments, 43

Argentina, 112, 246 Armenia, 246 arrests, 36 ASEAN, 141 Asia, 123, 135, 139, 140, 141, 165, 175, 176, 246 Asian countries, 135, 177, 246, 247 assessment, 112, 115, 136, 140 assets, 109, 144, 146, 147 asymmetry, 14, 153, 154, 155 atmosphere, viii, 123, 124, 130 audit, 130 audits, 131 authorities, 14 authority, 37 Automobile, 44, 50 automobiles, 32 autonomy, 41 awareness, 6, 133, 138 Azerbaijan, 246

B bacteria, 184 ban, 37 Bank of England, 67, 72, 75, 80 banking, 45, 46, 138 bankruptcy, 147, 152, 154, 155, 156 banks, 45, 46 bargaining, 105 barriers, 39, 42, 130, 135, 137, 141 base, 10, 21, 56, 85, 132, 191 behaviors, viii, 101, 102 Belarus, 246 Belgium, 84 beneficiaries, 135 benefits, x, 163, 173, 177, 185, 190 benign, 9, 13, 16 bias, ix, 143, 145, 146, 147, 148, 152

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Index

bibliographic analysis, viii, 53, 55 biodiversity, 17, 181, 183, 184 biofuel, 129, 136 biogas, 128, 135, 136 biological processes, 5 biomass, 5, 23, 128, 129, 135, 136 biotic, 7 birth control, 13 blood, 37 boils, 7, 10, 14, 23 Bolivia, 247 bonds, 33, 35 Botswana, 247 brain, 19 Brazil, 84, 112, 246, 247 breathing, 4, 5, 7, 8 breeding, 8 Britain, viii, 31, 36, 37, 38, 39, 40, 41, 43, 47, 50 budget deficit, 38 Bulgaria, 247 bureaucracy, 41, 43, 46 business cycle, ix, 159, 160 business environment, 39 businesses, 129, 134, 165 buyer, 134 buyers, 133, 162

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C capital accumulation, 91, 103, 110 capital expenditure, 130, 133 capital goods, 5, 8, 19, 174 capital markets, 45, 108, 109, 110, 144 capital productivity, 103 capitalism, xi, 243, 245, 261 carbon, ix, 5, 24, 123, 124, 133, 134, 135, 136, 137, 138, 139, 141, 181, 187 carbon dioxide, ix, 5, 24, 123, 181 carbon emissions, 138, 187 Caribbean, 175, 176 case study, 176, 183 cash, ix, 143, 144, 145, 147, 150, 152, 153, 154, 155 cash flow, ix, 143, 144, 145, 147, 150, 152, 153, 154, 155 catching-up, x, 160, 166, 169 Caucasus, 246 causal inference, 35 causality, 36, 194, 200, 247 causation, 102, 103, 106, 200 censorship, 38 Central Asia, 165 ceramic, 130 certificate, 133

challenges, 33, 125, 140 checks and balances, 35 chemical, 5, 7, 36, 41, 42, 43, 179, 183 chemical industry, 36, 41, 42 chemicals, 32, 36, 42, 43 Chicago, 48, 49, 51, 66, 70, 71, 76, 78, 80, 116, 134, 170 children, 7, 11, 22, 109 Chile, 67, 72, 84, 112, 116, 246 China, 83, 135, 139, 157, 178, 183, 245, 246, 251 circulation, 24 CIS, 246 citizens, x, 6, 159, 251 City, 170 civil war, 36 classes, 35, 39, 40, 42 classification, 56, 65, 71, 79, 86, 93, 255, 259 clean technology, 134 cleaning, 15, 20, 179 climate, x, 7, 9, 12, 18, 123, 138, 139, 140 climate change, xi, 7, 18, 123, 138, 139 CO2, ix, 123, 124, 125, 126, 127, 128, 130, 131, 132, 134, 140, 180 coal, 39, 41, 124, 126, 127, 128 Cold War, 45 Colombia, 69, 84, 112, 246 combustion, 137 commercial, 124, 125, 127, 130, 132, 144, 177 commodity, 13 communication, 106, 165 communist countries, 246, 247 communities, 177, 178 community, 10, 33, 124, 162, 174, 176, 178, 179 comparative advantage, 106, 163, 166 comparative analysis, viii, xi, 101, 113, 243, 244 comparative method, 36 compensation, 10, 11, 12, 14 competition, 6, 7, 8, 42, 45, 144, 152 competitiveness, 162 compilation, vii, 252 complementarity, 105 composition, viii, x, 54, 101, 109, 113, 118, 123, 173, 177, 178, 181 composting, 135, 136 conception, 55 Concise, 48, 49, 50 conditioning, 191 conflict, 2, 3, 5, 7, 15, 20, 21, 92, 110 conformity, 22 consciousness, 179 consensus, 32, 34, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 103, 174

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Index conservation, 10, 17, 18, 19, 20, 21, 25, 130, 132, 137, 178, 184 constant prices, 146 construction, 14, 17, 41, 44, 54, 147 consulting, 56, 129 consumers, 13, 102, 104, 109, 130, 156, 178 consumption, 3, 5, 7, 8, 9, 10, 14, 16, 17, 18, 19, 20, 23, 24, 36, 90, 103, 104, 109, 112, 113, 125, 131, 132, 177, 187 consumption habits, 3 consumption patterns, 10, 109 contaminant, 134 Continental, 51 controversial, 34, 42, 137, 173, 177 convention, 138 convergence, x, 56, 104, 159, 160, 166, 169, 193 conviction, 10 cooking, 163 cooling, 133 cooperation, 15, 33, 34, 184 copper, 7, 24, 25 corporate sector, 135 correlation, 148 corruption, 33, 46, 162 cost, 3, 6, 9, 12, 13, 16, 18, 20, 25, 32, 42, 129, 131, 132, 133, 134, 137, 139, 144, 152, 153, 155, 174, 178 cost curve, 9, 12 cost saving, 131 cotton, 32, 36, 37, 38, 39 covering, 98 creative potential, 33 credit market, 103, 107, 108, 109, 133, 134 creditors, 153, 154, 155 crises, 41 criticism, 36, 38 Croatia, 247 crops, 4, 5, 7, 8, 12, 26 crude oil, 7, 24, 25 cure, 181 currency, 166 cycles, 5, 91, 144, 155, 159, 160 cycling, 10 Cyprus, 69, 84, 166, 184 Czech Republic, 166, 178, 246, 251

D dailies, 38 danger, 194 data availability, 181 data set, 54, 98, 191, 193, 199 database, viii, 53, 54, 55, 60, 145, 182

273

debts, 138 decentralization, 105 decision makers, 139 decomposition, 5 decreasing returns, 108 deduction, 14 defamation, 38 deficit, 113, 156 deforestation, 5, 124, 139, 181, 183 Delta, 116 delusions, 43 delusions of grandeur, 43 demand curve, 8, 9, 11, 12, 13 democracy, 41, 120 Democratic Party, 43 demonstrations, 38 Denmark, 84, 186 dependent variable, 36, 57, 93, 146, 147, 148, 191, 200 depreciation, 146 depression, 32 depth, x, 189, 190, 191, 193, 194, 195, 196, 197, 198, 199, 200 deregulation, 45, 46, 47 derivatives, 11 destruction, 32, 33, 46, 124 developed countries, x, 60, 61, 86, 93, 95, 97, 98, 105, 109, 125, 127, 137, 159, 161, 163, 164, 165, 170, 173, 178, 179, 183, 184, 185, 191, 192, 193, 196, 197 developed nations, 137 developing countries, x, 10, 17, 60, 61, 86, 93, 105, 111, 112, 125, 127, 134, 137, 160, 166, 167, 170, 173, 174, 176, 177, 178, 179, 183, 184, 185, 190, 191, 192, 193, 197, 252 dichotomy, 57 diet, 22 diffusion, 37, 38, 102, 105 dimensionality, 193 diminishing returns, x, 160, 166, 170 direct investment, 163 direct taxes, 112, 113 directors, 43 discharges, viii, 123, 184 discontinuity, 200 dispersion, 113 dissolved oxygen, 184 distortions, 110 distribution, viii, 3, 60, 61, 90, 94, 101, 103, 104, 106, 107, 108, 109, 111, 112, 115, 117, 118, 119, 120, 133, 144, 148, 174, 257 distribution function, 94

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distribution of income, viii, 101, 103, 106, 109, 117, 118 diversification, 128 diversity, 184 domestic demand, 109 domestic issues, 43 domestic policy, 140 drawing, 35 drinking water, 4, 5, 7, 8, 11, 24 dumping, 5, 7, 11, 15 dyes, 42 dynamic panel estimators, ix, 143, 145, 146, 148

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E East Asia, 51, 110 Eastern Europe, 107, 165, 201, 246 ecology, 6, 13, 16 economic activity, x, 2, 102, 103, 104, 111, 114, 159, 162, 176 economic change, viii, 31, 32, 33, 34, 47 economic crisis, 39, 41, 45, 47 economic cycle, 32, 144, 155 economic development, 102, 103, 107, 115, 129, 138, 160, 161, 162, 164, 176, 177, 179, 181, 182, 183, 184, 185 economic downturn, 41 economic efficiency, 109, 114 economic goods, vii, 1, 2, 6, 8, 13 economic growth field, viii, 53, 54, 66, 85 economic growth rate, 104, 109, 162, 165, 175, 176 economic incentives, 174, 178, 181 economic inequalities, viii, 101, 102 economic institutions, 54 economic performance, 160, 163, 169, 190 economic policy, 2, 27, 33, 39, 42, 43 economic problem, 2, 43, 174 economic reform, 244 economic reforms, 244 economic resources, ix, 111, 159, 166, 167, 169, 185 economic theory, 2, 4, 6, 7, 12, 13 economic welfare, 174 economics, vii, 1, 2, 8, 27, 56, 98, 117, 118, 157, 174, 179 economies of scale, 153 ecosystem, 7, 23 Ecuador, 247 editors, 28, 29 education, xi, 10, 42, 43, 44, 98, 104, 106, 109, 113, 116, 161, 163, 166, 167, 169, 243, 245, 247, 251 education reform, 42 educational attainment, 251 educational system, 167

effluent, 136 effluents, 136 Egypt, 184, 185, 246 elaboration, 7 election, 42, 45, 95 electricity, 125, 127, 128, 129, 132, 133, 135, 136, 139, 140 Emerging and Transition Economies (ETE), xi, 243 emerging markets, 139, 246 emission, xi, 12, 14, 18, 123, 124, 127, 128, 131, 133, 134, 135, 137, 138, 139, 141, 178 empirical studies, 61, 103, 106, 111, 112, 114, 165 employees, 21, 107, 146 employers, 105 employment, vii, ix, 1, 3, 10, 18, 20, 21, 22, 139, 144, 156, 160, 162, 163, 166 employment levels, 10, 166 employment, income distribution, vii, 1 encouragement, 22 endogenous theory, viii, 53 endowments, 108, 112 energy, 4, 7, 19, 24, 25, 124, 125, 126, 127, 128, 129, 130, 131, 132, 136, 137, 138, 139, 140, 177, 178, 187 energy consumption, 125, 126, 128, 130, 132, 138, 177 energy efficiency, 25, 124, 140 energy supply, 128, 130 England, 37, 42, 164, 165 entrepreneurs, 107 environment, vii, viii, x, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 26, 27, 34, 123, 128, 129, 132, 138, 139, 140, 141, 152, 173, 177, 183, 185, 186 environmental awareness, 179, 185 environmental degradation, 178, 185 environmental economics, 181 environmental effects, x, 27, 173 environmental impact, x, 173, 176, 177 environmental issues, 22, 174, 176, 177, 178, 181, 183 environmental policy, 10, 18 environmental protection, 20, 22, 178, 179 Environmental Protection Agency, 186 environmental quality, x, 17, 173, 177, 179, 180, 181, 182, 185 environmental standards, 178, 179 environmental sustainability, 3, 4, 7, 11, 15, 16, 18, 21, 23, 27 environmental technology, 18 environmentally sustainable national income (eSNI), vii, 1, 6, 14, 15 EPA, 184, 186

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Index equal opportunity, 33 equality, 104, 107, 108, 164 equilibrium, 3, 4, 5, 13, 112, 116, 162 equipment, 45, 90, 105, 130, 144, 161 equity, 3, 4, 27, 28, 102, 103, 107, 110, 113, 114, 138 erosion, 5, 10, 12, 23, 24, 25, 26 espionage, 38 Estonia, 247 EU, xi, 134 Euro countries, x, 159, 166, 167, 169 Europe, 40, 48, 50, 54, 55, 100, 116, 123, 158, 165, 175, 176, 186 European Central Bank, 157 European Community, 100 European Union, 134, 146, 182, 187, 247 evidence, ix, xi, 32, 35, 37, 47, 54, 56, 114, 118, 119, 143, 145, 150, 151, 152, 153, 154, 155, 156 evolution, viii, 85, 87, 88, 89, 101 execution, 38 exercise, 7, 15, 57 exogenous theory, viii, 53 expenditures, 10, 12, 14, 18, 44, 110, 113 expertise, 130 exploitation, 20, 186 exporter, 178 exporters, 163 exports, 36, 45, 105, 162, 163 external financing, 145, 156 externalities, 110, 183 extinction, 7, 12, 23, 183 extraction, 5, 24, 25, 177

F factor cost, 16 factories, 131, 161 faith, 25 families, 104, 109 family planning, 9 famine, 38, 39, 41 FDI, 91 fear, 40, 47 Federal Reserve Board, 67, 72 feelings, 4, 35 fertility, 108, 109, 118, 119 fertility rate, 108, 109 financial, ix, x, 10, 14, 41, 116, 129, 134, 135, 137, 144, 152, 153, 154, 155, 189, 190, 191, 193, 194, 195, 196, 197, 198, 199, 200, 201, 244, 246 financial development, x, 189, 190, 197, 200 financial institutions, 246 financial intermediaries, 193

275

financial markets, 153, 246 financial resources, 152, 154, 155 financial sector, 191, 193, 201 financial support, ix, 144 Finland, 84 fiscal policy, 102, 103, 104, 105, 106, 110, 111, 112, 113, 114, 117, 120 Fiscal policy, viii, 90, 101, 117, 120 fish, 5 fisheries, 147 fixed costs, 109, 114 flaws, 137 flight, 22 flooding, 11 fluctuations, ix, 13, 15, 156, 159, 160, 169, 179, 182, 201, 244 fluid, 35 food, 7, 11, 20, 38, 39, 42, 130, 177 food security, 177 force, 162, 163, 174 Ford, 44 forecasting, 17 foreign creditor areas, xi, 203 foreign direct investment, 163, 178 foreign investment, 45, 164, 245 foreign policy, 43 forest resources, 182 formation, 12, 23, 25, 26, 144 formula, 24, 25 France, viii, 31, 36, 37, 38, 40, 41, 47, 48, 49, 50, 51, 83, 184, 247 franchise, 40, 42 free goods, 3 free trade, 39, 40, 42 fuel consumption, 25 function values, 200 funding, 138, 179 funds, 109, 185, 190

G game theory, 10, 85 GDP, vii, x, 1, 45, 125, 138, 159, 160, 162, 167, 169, 176, 177, 180, 184, 191, 192, 193, 194, 195, 247, 251 GDP per capita, 247, 251 gene pool, 4, 8, 26 general knowledge, 106, 114 Georgia, 70, 159, 246 Germany, viii, 31, 41, 43, 47, 48, 49, 50, 51, 84, 158, 164, 165, 247 global climate change, x global economy, 46, 245, 247

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global environmental pollution, x, 173 global warming, 24, 123, 124, 127, 138, 139 GNP, ix, 28, 44, 144, 145, 150, 152, 153, 155 goods and services, viii, 3, 11, 14, 22, 101, 160, 161, 163, 165, 174, 176, 177 governance, xi, 17, 33, 169, 243, 245, 252 government expenditure, 104, 112, 118 government intervention, 110 government procurement, 138 government spending, 111, 112, 113, 164, 193 governments, viii, 11, 22, 35, 39, 41, 44, 47, 53, 111, 130, 162 graduate students, viii, 53, 98 graph, 190, 193, 195, 199, 200 Great Britain, 51 Greece, 84, 184 greenhouse, ix, xi, 12, 14, 18, 123, 133, 139, 176 greenhouse gases, 12, 14, 18, 176 gross domestic product, 125, 176, 184 Gross National Product, ix, 143, 146 groundwater, 7, 23, 24, 186 growth rate, x, xi, 45, 102, 104, 107, 108, 109, 112, 130, 159, 160, 162, 165, 167, 169, 176, 189, 191, 193, 198, 199, 200 growth theory, 60, 85, 98, 163 Guatemala, 251 guidance, 129 guidelines, 139

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H habitat, 4, 5, 7 habitats, 7 half-life, 95, 96 happiness, 166, 170 harmful effects, viii, 123 harvesting, 23 Hawaii, 140 hazardous waste, 179 hazardous wastes, 179 hazards, 124, 183 health, viii, 23, 123, 124, 177, 184 health problems, 177 hegemony, 88 height, 46, 183 heme, 98 Henry Ford, 44 heterogeneity, 57, 112 heteroskedasticity, 257 highways, 165 history, viii, 40, 44, 47, 123, 173, 176, 184, 247 Hong Kong, 67, 70, 72, 81, 166, 246, 247 host, 41

hub, 141 human, vii, viii, xi, 1, 3, 4, 5, 7, 11, 12, 13, 14, 17, 19, 23, 32, 33, 91, 104, 106, 107, 108, 109, 110, 114, 117, 123, 124, 139, 161, 163, 174, 177, 184, 185, 186, 191, 193, 243, 244, 245, 247 human capital, 32, 91, 104, 106, 107, 108, 109, 110, 114, 117, 161, 163, 185, 191, 193, 244, 247 human development, xi, 177, 184, 186, 243, 245 human development index, 184 Human Development Index, 251 human health, viii, 123 human resources, 161 Hungary, 84, 246, 251 hypothesis, x, xi, 58, 88, 103, 110, 118, 120, 149, 151, 159, 166, 169, 186, 243, 244

I Iceland, 67, 73, 77 ideal, 169 identification, 56 identity, 35, 37 IMF, 66, 70, 71, 75, 76, 77, 79, 80, 81, 117, 201, 244, 246, 247 immigration, 177 imports, 41, 105, 162, 163 improvements, 24, 25, 88, 113, 130, 174 in transition, 165 inadmissible, 3 income, vii, viii, ix, xi, 1, 3, 11, 12, 13, 14, 15, 16, 18, 21, 39, 90, 93, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 119, 120, 133, 136, 137, 159, 160, 164, 166, 169, 170, 179, 181, 182, 187, 243, 245, 251 income distribution, vii, 1, 3, 11, 102, 103, 105, 106, 107, 109, 110, 111, 112, 113, 114, 117, 119, 120 income inequality, vii, viii, ix, 101, 102, 103, 105, 106, 108, 109, 112, 113, 114, 115, 117, 119, 159, 164, 169, 170, 181 income tax, 39, 90, 108, 111, 113, 119 independence, 129, 164 independent variable, 36, 146, 147, 148, 191, 193, 200, 245 India, 84, 135, 178, 183, 246 individual rights, 38 individuals, vii, viii, 1, 4, 9, 11, 23, 53, 66, 75, 79, 98, 103, 106, 107, 109, 114, 154, 174, 243 indivisibilities, 107, 109 Indonesia, 84, 136, 246 industrial policies, 32 industrial revolution, vii, 32 Industrial Revolution, viii, 31, 32, 36, 47, 49, 50 industrial sectors, 130

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

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Index industrialisation, 119 industrialization, x, 36, 37, 38, 39, 43, 159, 166, 169, 185 industrialized countries, x, 160, 161, 166, 170, 251 industries, viii, x, 14, 16, 17, 18, 21, 31, 32, 33, 35, 36, 39, 41, 42, 43, 44, 45, 46, 47, 107, 129, 130, 136, 173, 178, 186 industry, ix, 20, 22, 32, 33, 35, 36, 37, 39, 40, 41, 42, 43, 44, 47, 107, 109, 123, 129, 130, 135, 138, 140, 147, 176, 178, 247 ineffectiveness, 119 inefficiency, xi inequality, viii, 90, 91, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 117, 118, 119, 120, 159, 164, 165, 251 infant mortality, 177, 245, 251 inferences, 180 inflation, vii, x, 160, 189, 190, 191, 193, 194, 195, 196, 197, 198, 199, 200 information sharing, 44 infrastructure, x, 44, 112, 113, 165, 169, 173, 185, 190 infrastructure investments, x, 173 inheritance, 37 institutional change, xi, 34, 243, 244, 245 institutional innovations, 34 institutional reforms, 245, 246, 247 institutions, vii, viii, xi, 1, 4, 11, 31, 34, 53, 54, 55, 66, 70, 71, 74, 83, 98, 111, 117, 138, 162, 179, 182, 243, 244, 245 integration, 92, 132, 200, 246, 247 intellect, 5 interest groups, 31, 32 interest rates, ix, 143, 144, 145, 146, 152, 153, 155, 156 internal financing, 145, 147, 152, 155, 156 internalised, 16 International Bank for Reconstruction and Development, 28 International Monetary Fund, 88, 169, 246 international trade, 102, 105, 178 intervention, 23 inventions, 42, 161, 167 investment, ix, 90, 103, 104, 106, 107, 108, 109, 110, 112, 113, 114, 115, 120, 130, 137, 143, 144, 145, 146, 147, 148, 150, 151, 152, 153, 154, 155, 156, 164, 165, 166, 167, 191, 247 investment incentive, 110 investment rate, 109 investments, x, 33, 108, 109, 134, 137, 154, 155, 173, 178, 193 investors, 45, 145, 146, 155, 156, 246 involuntary unemployment, 3

277

ionizing radiation, 7 Iowa, 67, 69, 72, 76, 80 Ireland, 69, 77, 80, 83, 244, 245, 247, 250, 251 iron, 32, 36, 39, 40, 41, 46, 47, 130 Israel, 83, 84, 184, 246 issues, 9, 34, 35, 38, 40, 42, 47, 102, 103, 124, 138, 173, 174, 176, 177, 183, 185, 200 Italy, 84, 184, 243, 251

J Jamaica, 84 Japan, viii, 31, 45, 46, 47, 48, 49, 50, 83, 117, 140, 157, 247 joints, 57 Jordan, 246 Joseph Schumpeter, viii, 31 journalism, 38

K Kazakhstan, 246 Keynesian, 99 knowledge economy, 117 Korea, 68, 73, 76, 80, 84 Kuznets Curve, 181, 184, 186, 187 Kyrgyzstan, 246

L labor force, 46, 162, 174 labour conditions, vii, 1, 3 landfills, 184 Latin America, 110, 112, 116, 118, 247 Latvia, 247 laws, xi lead, ix, 3, 5, 6, 9, 11, 18, 22, 24, 26, 35, 36, 39, 104, 105, 110, 124, 137, 147, 152, 154, 155, 159, 162, 163, 183, 196, 197, 198, 199 leakage, 184 learning, 108, 153 legislation, 136, 138 leisure, vii, 1, 3, 19, 104, 112 leisure time, vii, 1, 3 Less Developed Countries, 244 liberalization, 45, 46, 47 life cycle, 121 life expectancy, 177, 245, 251 lifetime, 104, 132 light, 85, 105, 139, 181 liquidity, 108, 246 literacy, 245

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Index

Lithuania, 247 livestock, 8 living conditions, 10, 23 loans, ix, 46, 129, 143 lobbying, 43 locus, 37, 38 Logit model, viii, 53, 94, 95, 96, 97 Louisiana, 68 love, 22, 23 loyalty, 37 Luxemburg, 251 lying, 246

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M machinery, 37, 38, 130, 137, 144, 161 macroeconomic policies, 102 macroeconomic policy, 201 macroeconomics, 117 magnitude, 102, 103, 111, 112, 150, 151, 200 major issues, 22 majority, 35, 58, 103, 110, 114, 154 Malaysia, 84, 123, 124, 125, 126, 127, 128, 129, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 246 man, viii, 12, 26, 123 management, 132, 154, 178 Mancur Olson, viii, 31, 32 manufactured goods, 174 manufacturing, 37, 39, 43, 44, 45, 46, 125, 130, 135, 144, 147 manure, 136 mapping, 244 marginal product, 103, 108, 180 marginal utility, 11 marine environment, 184 market economy, 246 marriage, 37 Maryland, 67, 72, 77, 78 mass, 36, 44, 46 materials, 132, 161 matrix, 193 matter, vii, ix, 1, 2, 4, 6, 7, 10, 37, 56, 103, 143, 145, 146, 159 measurement, vii, 1, 6, 13, 55 measurements, 165 meat, 18, 19, 21, 22, 23 media, 7 median, 110 medical, 15 medicine, 161, 166 Mediterranean, 176, 183, 184, 185, 186 Mediterranean countries, 184, 185

membership, 36 meta-analysis, 96 metallurgy, 41 methodology, 16, 32, 61 metropolitan areas, 177 Mexico, 84, 178, 246 Miami, 69 microelectronics, 32 middle class, 40, 43 Middle East, 247 migration, 190 military, 34, 37, 43 minimum price, 39 minimum wage, 22 Minneapolis, 66, 72, 77, 81 Missouri, 68, 72, 82, 158 models, xi, 24, 53, 61, 92, 93, 94, 95, 96, 97, 98, 102, 104, 107, 108, 109, 110, 111, 114, 115, 124, 148, 160, 184, 190, 243, 244 modernization, 43 mold, 35 monetary policy, 144 moral hazard, 107, 109 Morocco, 184, 246 mortality, 161 mortality rate, 161 MSW, 128 municipal solid waste, 128 mythology, 37

N national identity, 37 national income, vii, 1, 3, 4, 5, 6, 10, 11, 13, 14, 15, 16, 20, 22, 27, 109, 114 national interests, x national policy, 138 nationalism, 35, 42 natural gas, 124, 127, 128 natural growth rate, xi natural resources, x, 3, 4, 5, 7, 17, 18, 19, 23, 24, 25, 135, 136, 161, 173, 174, 177, 178, 185, 244, 247 natural science, 4 negative relation, 96, 110, 144, 152, 154, 155 nervousness, 37 Net Domestic Product, 18 net foreign debtor countries, xi, 203, 222, 225 Netherlands, 1, 15, 18, 27, 28, 29, 83, 84 neutral, 112 New Deal, 48 new growth theories, 106 New South Wales, 68, 73 New Zealand, 84

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Index NGOs, 179 Nigeria, 84, 247 nightmares, 46 nitrous oxide, 130 nobility, 35, 38 nodes, 200 non-renewable resources, 17, 24, 25, 26 normal distribution, 148 North Africa, 175 North America, 176, 186 North American Free Trade Agreement, 186 Northern Ireland, 67, 76 Norway, 84, 247 nuisance, 20 null, 95, 149, 151 null hypothesis, 95, 149, 151 nutrient, 5

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O observed behavior, 85 obstacles, 32, 129 oceans, 15, 123 oil, 7, 9, 15, 17, 24, 26, 32, 124, 126, 128, 135, 136, 139, 140, 163, 177, 247 oil production, 136 omission, 147 openness, 90, 116, 162, 165, 171, 245 operations, 137 opportunities, vii, ix, 44, 108, 109, 129, 144, 145, 147, 150, 152, 153, 155, 156, 160, 161, 162, 166 opportunity costs, 6, 8, 13 ownership, 154, 244 oxygen, 184 ozone, 5

P Pakistan, 84, 246 palm oil, 128, 136 parallel, 54, 102, 244 parallelism, 109 parents, 109 Pareto, 116 Parliament, 37, 38, 40 patents, 42 patriotism, 42 peace, 39 per capita income, 166, 181, 191, 245, 246, 247 permit, 134 Peru, 112, 246 petroleum, 127

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Philadelphia, 28, 67, 72, 77, 78, 82, 189 Philippines, 84, 246 physical environment, 5, 6, 12, 16 physics, xi plants, 4, 7, 130, 135, 137 platform, 44, 46 plausibility, 17 playing, 162 PM, 39, 46 Poland, 246, 247, 251 polarization, 115 police, 10, 38 policy, viii, x, xi, 16, 17, 32, 40, 41, 43, 90, 92, 101, 102, 104, 105, 106, 107, 112, 113, 114, 117, 120, 128, 129, 139, 140, 144, 163 policy instruments, 114, 139 policymakers, 31, 43 political instability, 110, 115, 118 political parties, 34 political power, 111 political problems, 43 politics, 34, 38, 42, 43, 45, 46, 47 pollutants, viii, 123 polluters, 178, 179, 181 pollution, x, 3, 7, 11, 17, 24, 133, 173, 177, 178, 179, 180, 181, 182, 183, 184, 186 poor performance, 111 population, x, 9, 16, 17, 33, 34, 35, 42, 107, 159, 161, 166, 167, 169, 173, 177, 244, 245, 247 population control, 167 population density, 244, 247 population growth, x, 159, 166, 167, 169 Portugal, ix, 84, 143, 144, 156, 251 Portuguese SMEs, ix, 143, 145, 146, 155, 156 positive mental health, 170 positive relationship, 153, 162 Post-Kyoto policies, x, 203 potato, 39 poverty, vii, ix, 112, 159, 160, 162, 164, 165, 169, 170 poverty line, 164 poverty reduction, 164 power generation, 124, 128 power plants, 128 precipitation, 24 preservation, 18, 26 president, 44 pressure groups, 111 prestige, 176 prevention, 20 pre-World War II, 44 price mechanism, 20 primacy, 34

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280

Index

principles, 138 prisoners, 10 private good, 112 private investment, 90, 104, 110, 117, 164, 193 private ownership, 45 probability, ix, 25, 94, 95, 96, 98, 124, 143, 145, 150, 152, 153, 155, 156 producers, 13, 41, 109, 136 production function, 25, 104, 108, 180 productive efficiency, 107 productivity growth, 45 professionals, 55 profit, 120 profitability, 148 progressive tax, 90 project, 15, 56, 128, 132, 133, 134, 135, 137, 140 property rights, 111, 161 proposition, 18, 36 prosperity, 32, 164 protection, 21, 33 protectionism, 42, 43 psychological well-being, 170 public administration, 10 public capital, 112 public expenditures, 44 public goods, 112 public health, 110 public investment, 112, 113, 114 public opinion, 38 public policy, 104 publishing, 38, 56, 182 pulp, 130 purchasing power, 109

Q quality of life, x, 129, 159, 165, 169, 170 quality standards, 9 quantification, 13, 57 quantitative technique, 57 questioning, 9, 137 quotas, 45, 134, 152

R race, 42, 117, 176 radicalism, 36, 42 rainforest, 7 raw materials, 161 reactions, 16 real estate, 37 real national income, 19

real terms, 17, 18 real wage, 39 reality, 174, 179 reasoning, 17 recall, 193 recession, ix, 144, 153, 155, 156 recognition, 6, 38, 46 recovery, 136, 137, 179 recreational, 15 recruiting, 37, 40 recycling, 24, 25 redistribution, 105, 106, 108, 110, 111, 114, 116 redistributive effects, viii, 31, 34, 114 reform, 36, 38, 39, 40, 41, 42, 46 Reform, 40, 50, 116 reforms, 91, 244, 245, 246 regeneration, 23, 24, 185 regenerative capacity, 7, 25 regions of the world, x, 7, 173, 176, 177, 185 regression, 57, 94, 147, 151, 152, 161, 184, 191, 193, 194, 195, 257 regression analysis, 191 regression equation, 57, 94 regression model, 57, 94, 257 regulations, 32, 34, 37, 44, 45, 123, 139, 161, 178, 179, 180 regulatory agencies, 123 reinforcement, ix, 144 reintroduction, 39 relevance, viii, 53, 54, 55, 94, 144, 146, 154, 155 renewable energy, 127, 128, 140 rent, 46, 115 repair, 15 repression, 36, 115 reputation, 153, 154 requirements, 42, 166, 190 research institutions, 182 researchers, 181 reserves, 41, 128 residuals, 193, 194, 195, 257 residues, 128, 129, 136 resistance, 32, 37, 38, 41 resources, 4, 7, 9, 17, 19, 21, 23, 25, 26, 27, 28, 39, 92, 107, 112, 128, 129, 132, 136, 152, 153, 154, 155, 159, 160, 161, 163, 164, 167, 174, 177, 184, 185, 247, 251 response, 39, 93, 94, 103, 105, 113, 157, 177 restoration, 6, 9, 11, 14, 17, 18, 26 restrictions, 10, 39, 45, 146, 149, 152, 153, 154, 190 restructuring, 46, 137, 245 retail, 147 revenue, 107, 135 rewards, 132

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Index rhetoric, 34, 42, 47 rice husk, 128, 136 rights, 14, 91, 161 risk, 9, 91, 107, 110, 139, 152, 153, 154, 155, 156, 162, 190 risks, 3, 9, 11, 24, 107, 137, 179 Romania, 247 root, 247 roughness, 200 rubber, 130, 200 rules, 161 rural areas, 37 Russia, 84, 246, 247

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S Saudi Arabia, 84, 246, 247, 251 savings, 103, 104, 116, 130, 131, 132 savings function, 103 scarce goods, vii, 1, 2, 3, 18, 21 scarcity, 2, 8, 11 school, 191, 193, 195, 245, 253 school enrollment, 191, 193, 195 schooling, 42 science, xi, 4, 42, 43, 54, 55, 56, 59, 88, 140 scientific knowledge, 24 scientific publications, 54, 56 scope, 17, 55, 58, 61, 85, 88, 89, 90, 93, 94, 95, 102, 104, 111, 113 sea level, 123, 124, 140 Secretary of Commerce, 44 security, 3, 92, 127, 128, 130, 137, 139 seller, 134 sellers, 162 semiparametric graphical approach, x, 189 sensitivity, 193, 201 service industries, 147 services, 13, 17, 45, 46, 129, 138, 160, 161, 163, 165, 174, 176, 177, 178, 182 sewage, 184 sex, 23 shadow prices, 11, 13 shame, 47 shock, 41 short supply, 41 showing, 103, 111, 161, 163 SIC, 147 signalling, 152 signals, 41 significance level, 184 signs, 193 simulation, 16 Singapore, 68, 74, 78, 82, 84, 139, 166, 246, 247

281

skilled workers, 105, 106, 166, 253 Slovakia, 166, 247 smoothing, 104 social capital, 33 social class, 37 social consensus, 37 social contract, 33 social fabric, 38 social interests, 179 social responsibility, 137 social sciences, 34, 56 social welfare, 177 socialism, 42 society, viii, 10, 15, 16, 19, 34, 53, 111, 165, 243 soft loan, 138 software, 46, 200 solid waste, 128, 129 solidarity, 34 solution, 25 South Africa, 84, 246 South America, 123, 175, 176 South Asia, 170 South Korea, 166, 246, 247 Southeast Asia, 127 Soviet Union, 33, 107, 246 Spain, 83, 184, 244, 245, 247, 250 specialists, 54 specialization, x, 54, 159, 163, 166, 169 species, 4, 5, 6, 7, 12, 13, 17, 19, 23, 24, 179, 183, 186 specifications, 130 spending, 43, 111, 112, 115, 164 Sri Lanka, 251 stability, 33, 40, 46, 47, 110, 128, 161, 162, 164 stabilization, 24 stakeholders, 138 standard deviation, 149, 150, 151 standard of living, vii, x, 159, 160, 161, 165, 166, 169 standardization, 57 starvation, 42 state, viii, 2, 3, 4, 6, 18, 20, 31, 32, 33, 34, 37, 38, 39, 44, 47, 53, 54, 57, 98, 104, 135, 146, 148, 151, 164, 174, 179, 180, 182 states, x, 32, 111, 159, 163, 165, 166, 169, 184, 247, 255 statistics, 12, 15, 60, 62, 63, 64, 65, 70, 74, 78, 82, 84, 92, 98, 128 statutes, 37 steady-state growth, 104 steel, 32, 130 stimulus, 47 stress, 152, 154, 155, 156, 190

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

282

Index

structural changes, 102, 178 Structural economic change, viii, 31 structure, x, 19, 38, 40, 97, 162, 170, 173, 176, 177, 179, 185, 186, 190, 195 style, xi, 243, 245 subsidy, 44, 112 subsistence, 104 substitutes, 7, 17, 24, 25, 26 substitution, 9, 18, 19, 24, 25, 26 substitutions, 247 sulphur, 181 Sun, 48 supplier, 5 suppliers, 130, 138 supply curve, 9, 12 surplus, 10, 133, 134 survival, ix, 7, 17, 19, 34, 143, 145, 146, 147, 149, 150, 152, 153, 155, 156 sustainability, vii, 1, 3, 4, 12, 13, 14, 15, 16, 17, 21, 23, 24, 25, 26, 128, 130, 137, 139, 152 sustainable development, 4, 11, 134, 183 sustainable energy, 124, 139, 141 sustainable growth, 140 Sweden, 83, 100 Switzerland, 28, 84 synthesis, 140, 186 Syria, 184

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T Taiwan, 166, 246, 247 Tajikistan, 246 tanks, 252 target, 138 tariff, 42 tax cuts, 45 tax policy, 119 tax reform, 38 taxation, 104, 108, 110, 112, 113, 116, 118, 121, 251 taxes, 90, 104, 106, 108, 110, 111, 114, 163, 180 techniques, x, 55, 85, 160, 166, 178, 179, 185 technological advancement, 163 technological change, 32, 33, 34, 35, 37, 105, 106, 108, 114 technological effects, x, 173, 178 technological progress, ix, 15, 17, 18, 24, 33, 105, 106, 114, 159, 161, 169 technologies, 9, 17, 32, 33, 44, 46, 102, 105, 128, 132, 139, 178, 179 technology, x, 4, 5, 6, 15, 18, 19, 20, 21, 24, 32, 33, 34, 37, 38, 39, 42, 44, 106, 114, 129, 132, 137, 138, 140, 160, 161, 162, 163, 164, 165, 166, 167, 173, 178, 179, 180, 185, 244, 247

technology transfer, x, 173, 178, 185 teens, 162 telephones, 165 temperature, 10 tempo, 7 tension, 33, 38, 200 tensions, 43, 200 tertiary education, 251 testing, 185 textbooks, 174 textiles, 32, 36, 37, 38, 39 Thailand, 140, 246 threats, 35, 42 threshold level, 181 time periods, viii, 31, 35, 47, 192, 195, 200 time series, 15, 102, 111, 165, 170 total costs, 12 total energy, viii, 123, 129, 132 total product, 177 trade, 37, 38, 39, 42, 43, 44, 90, 92, 103, 104, 105, 107, 108, 110, 113, 114, 120, 134, 147, 160, 162, 164, 165, 178, 187, 193, 244, 245, 247 trade policy, 163 trade union, 42 trade-off, 103, 104, 107, 108, 110, 113, 114, 120 transaction costs, 33, 135 transfer of money, 134 transition economies, 107, 178, 244, 251 transition period, 13, 15 transmission, 102, 106, 114, 116 transport, 18, 125, 130, 136 transportation, 24, 124, 127, 135, 165 treaties, 134 treatment, 32, 36 tropical rain forests, 10 turbulence, 35 Turkey, 84, 178, 184, 186, 246 Turkmenistan, 246 two-step estimation method, ix, 143, 145, 147, 149, 155

U U.S. Department of the Treasury, 78 UK, 40, 157, 158, 186 Ukraine, 247 unemployment rate, 160, 167 UNESCO, 28 unions, 105 United, 27, 28, 48, 50, 83, 88, 111, 115, 116, 124, 130, 133, 135, 164, 187, 244, 247 United Kingdom, 27, 83, 115 United Nations, 28, 50, 88, 133, 135

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,

Index United States, 48, 83, 111, 116, 164, 187, 247 universities, 42, 43, 54, 83, 84 urban, 38, 177, 181, 184 urban areas, 177 urban population, 177 USA, xi, 140, 159, 184, 186, 189, 251, 263 Uzbekistan, 246

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

V validation, 146 valuation, 8, 9, 27, 57 variables, 6, 22, 35, 54, 55, 57, 58, 90, 92, 93, 95, 97, 103, 111, 145, 146, 147, 148, 149, 150, 151, 154, 162, 164, 191, 193, 200, 244, 245 variations, 35, 119 vector, 102, 111 vegetables, 22 vehicles, ix, 123 vein, 2 Venezuela, 247 vested interests, viii, 31, 32, 33, 34, 35, 39, 40, 41, 43, 44, 45, 46, 47 Vietnam, 247 Viking, 48 violence, 116, 118 vision, 41 volatility, 109 vote, 111 voters, 110 voting, 35, 40, 110 voting record, 35 vulnerability, 111

Washington, 27, 28, 50, 51, 66, 67, 70, 71, 72, 74, 75, 78, 79, 80, 116, 120, 186, 201 waste, 5, 7, 11, 15, 20, 128, 135, 136, 184 waste management, 135 waste water, 20 water, viii, 4, 5, 6, 7, 8, 9, 11, 13, 14, 19, 36, 123, 132, 177, 181, 184, 251 water resources, 177, 182, 184 WD, 60, 61, 63, 65 weak economic structure, x, 173 wealth, viii, 24, 101, 102, 103, 104, 106, 107, 108, 112, 114, 116, 120, 164, 165 wealth distribution, 108, 120 wear, 8 welfare, vii, xi, 1, 2, 3, 8, 12, 13, 14, 19, 45, 112, 164, 165, 174, 176, 177 well-being, 139 West Indies, 69, 78 Western countries, xi Western Europe, 39 Whigs, 37, 39 wholesale, 147 Wisconsin, 66, 71, 76, 77, 80 withdrawal, 7 wood, ix, 11, 23, 41, 123, 128, 130, 136 workers, 37, 39, 105, 106 working class, 43 working hours, 19, 20 World Bank, 27, 28, 51, 62, 63, 64, 65, 66, 70, 71, 74, 75, 76, 77, 78, 79, 80, 81, 116, 118, 119, 134, 170, 182, 186, 187, 191, 245, 246, 247, 252 world order, 46 World War I, 43 worldwide, vii, xi, 24, 26, 56

W wage differentials, 106 wage rate, 21 wage structure, 105 wages, 22, 103, 105 Wales, 140 walking, 48 war, 37

283

Y Yale University, 48, 50, 201 yield, 18

Z Zimbabwe, 84

Theories and Effects of Economic Growth, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook Central,