Progress in Economics Research [1 ed.] 9781622570010, 9781613243947

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Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

PROGRESS IN ECONOMICS RESEARCH

PROGRESS IN ECONOMICS RESEARCH

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

VOLUME 23

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PROG GRESS IN EC CONOMICS S RESEARC CH

PROG GRESS IN ECONOM MICS RESSEARC CH

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VOL LUME 23 2

ALBER RT TAVIDZE EDITOR

Nova Scien nce Publisheers, Inc. N York New Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

Copyright © 2012 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

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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. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

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Published by Nova Science Publishers, Inc. †New York Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

CONTENTS Preface Chapter 1

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Chapter 2

Chapter 3

vii  Regulatory Governance and the Regulatory Framework for Safeguarding Financial Stability Benjamin Mohr and Helmut Wagner 

1 

Mortgage Availability, Qualifications and Risks in Ireland, 2000-2009 Michelle Norris and Dermot Coates 

33 

Home Equity Conversion Mortgages: A Product for an Emerging Demographic Martin Seay and Andrew Carswell 

57 

Chapter 4

Why Is GDP always the Denominator? Stephen Morse 

Chapter 5

The Art of Home Buyer Assistance: Discovering Hidden Treasures Rob Chrane and Andrew Carswell 

Chapter 6

Disruption Management in Distributed Organizations: A Cooperative Repair Approach for Reactive Planning and Scheduling A. Cauvin, S. Fournier and A. Ferrarini

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103 

129 

vi Chapter 7

Chapter 8

Chapter 9

Chapter 10

Contents What Have We Learned From The Real Estate Bubble? Asset Sorting in the Real Estate Investment Market Chihiro Shimizu   Consumers’ Responses to Corporate Social Responsibility: Increased Awareness and Purchase Intention Ki-Hoon Lee  A Test of Perfect Collusion under Imperfect Information Rodrigo Zeidan, Khurshid M. Kiani   and Marcelo Resende Industrial Economics Ofer H. Azar  

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Index

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187 

201 

215  227 

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PREFACE This series spans the globe presenting leading research in economics. International applications and examples of economic progress are invaluable in a troubled world with economic booms bursting like so many penny balloons. Topics discussed include regulatory governance and framework for safeguarding financial stability; home equity conversion mortgages and the elderly; GDP and world economic performance; the art of home buyer assistance; disruption management in distributed organizations; lessons learned from the real estate bubble; unemployment and active labor market intervention; corporate social responsibility and industrial economics. Chapter 1 – The financial crisis of 2007-09 revealed several flaws in the regulatory frameworks across the world. While there is a consensus on the need for regulatory reform, the focus of such a reform is much less clear. This paper argues that the improvement of regulatory governance arrangements should be a key building block of financial reform since the current framework lacks the ability to guard supervisors from being influenced by the financial sector as well as political interference. After contrasting two complementary theories of bank regulation – the helping and grabbing hand view – we thus make a case for regulatory governance. First, the authors explain the key characteristics of this institutional aspect of bank regulation. Second, they systematize empirical studies examining the effects of good regulatory governance on financial sector performance. The evidence surveyed indicates that regulatory governance can indeed have an influence on financial stability. Nevertheless, more robust evidence for supporting the view that good regulatory governance has positive effects on financial stability is needed. Finally, the authors touch upon the issue of whether placing bank regulation

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Albert Tavidze

inside an independent central bank creates a better institutional environment for safeguarding financial stability. Chapter 2 – During the last decade the Republic of Ireland’s underdeveloped, conservative residential mortgage market was radically transformed into a highly developed, flexible sector. This market was traditionally characterized by conservative lending criteria, significant government intervention and the dominance of non-profit providers, but since 2000, the numbers of lenders and the number of mortgage products has expanded radically, repayment terms have become more flexible, commercial banking agencies have come to dominate mortgage provision and the volume of outstanding private mortgage debt has increased fourfold. These developments mirror changes in the mortgage markets of several other European Union member states, particularly the southern countries such as Spain, Greece and Italy, but here the authors argue that they were more extreme in Ireland than the EU norm (European Central Bank, 2009). The transformation of Ireland’s mortgage market made a key contribution to the seemingly perpetual upward trajectory of house prices and new housing output, which, in turn, drove rising employment rates and tax revenues. For this reason, public policy did not attempt to dampen the housing and mortgage boom, but rather stoked it via fiscal incentives for housing development and ‘light touch’ regulation of banks and other mortgage providers. However, the housing boom both drove and masked severe risks at a number of levels in the Irish economy and banking system. From 2000, the Irish economy grew less competitive, but because employment and public finances became disproportionately reliant upon the housing market it appeared deceptively healthy. Household mortgage debt increased radically, particularly among younger homeowners, but low interest rates and ready access to credit enabled growing consumption rates and further non-mortgage debt accumulation. Banks were heavily reliant on housing related lending not only via mortgages but also to the construction industry, but profits remained high. Consequently the Irish economy, government, banking system and households were over-exposed to external macroeconomic shocks and thus the global economic downturn in 2008 had a much more severe impact on all three sectors than in most other western European countries and government implemented particularly radical remedies in response. In the mortgage sector, the government guaranteed all bank lending in 2008, nationalized one mortgage lender in 2009 and effectively part-nationalized all but one of the other major Irish based lenders in the following year. In addition, the volume of mortgage lending fell rapidly from 2008, as mortgage qualification criteria

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ix

became stricter and many mortgage products were withdrawn from the market as did some lenders. This chapter sets out the background to this mortgage boom and bust describes, in terms of the historic trends in mortgage lending in Ireland and the country’s recent ‘Celtic Tiger’ economic boom and downturn post-2007. It then outlines trends in mortgage availability, mortgage qualifications and mortgage finance institutions (MFIs) since 2000 and the associated risks. The conclusions examine the lessons regarding appropriate regulatory and policy responses to a mortgage lending boom which arise from the Irish experience. Chapter 3 – Elderly households increasingly have a significant portion of their wealth tied to their home. As a result, the ability of these individuals to remain financially independent over time while also retaining homeownership is limited. The Home Equity Conversion Mortgage (HECM) program was created in 1987 to help individuals in this situation. HECMs, the most popular version of a reverse mortgage, are ideal products for individuals with high housing equity but with limited non-housing assets. Only available to homeowners age 62 and older, a HECM provides for the use of home equity as collateral in the creation of a loan with repayment deferred until the owner dies, the home is sold, or the home is no longer the owner’s primary residence. HECMs allow access to home equity, while still allowing elderly individuals to maintain residence in their home and, unlike similar mortgage products, have no income requirements or credit qualifications. After limited demand in the early years, high levels of homeownership combined with limited nonhousing savings have provided for the dramatic expansion of the HECM market over the last decade. The arrival of the Baby Boomers into the retirement years looks to continue this growth into the foreseeable future. This chapter provides an overview of the HECM program, a review of its expansion over the years, and its potential growth in the future. Chapter 4 – Gross Domestic Product (GDP) is often employed in indicators and indices, typically as a denominator which implies a return (in environmental health, well being etc.) per unit of national wealth. GDP is itself often divided by population to provide a proxy measure of income per capita, and this too often finds its way into indices such as the Human Development Index (HDI). For example, the Holy Grail of sustainable development is in many ways represented by the so-called Environmental Kuznets Curve, a plot of environmental degradation as a function of national wealth. While there have been efforts to promote alternatives to the GDP, such as the Genuine Progress Indicator (GPI), GDP still dominates. But why should GDP feature so prominently in such measures? Why is it so prevalent as a denominator and

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what are the alternatives? This chapter aims to discuss some of these key questions that rest behind so many of the indicators and indices we commonly use today. The chapter provides a number of examples where GDP or GDP/capita are the denominators and discusses the assumptions and limitations that rest behind them. Chapter 5 – Home buyer assistance programs proliferated throughout the U.S., starting in the early 1990s. Despite the recent housing downturn, several areas of the country offer borrowers some form of home buyer assistance. This reality runs counter to the belief among many that such programs had been eliminated or phased out after the subprime mortgage crisis of the mid-2000s. This type of assistance usually comes in the form of down payment assistance, and is subject to tighter controls than existed with assistance programs in the past. Still, evidence suggests that a communication gap exists between various factions of the housing and real estate communities as to the availability and applicability of such programs to prospective buyers. Consumers subsequently are shut out of these opportunities due to various information gaps that still exist within the housing counseling industry, depriving them of an increase in consumer welfare in the process. The authors conclude by providing a series of case studies that help illustrate the increase in housing affordability that working households can attain through the adoption and layering of these home buyer assistance programs. Chapter 6 – In the current financial and economic hyper-competitive context, the control of disruptions is becoming a major issue to tackle in the management of organizations. Problems from industrial organizations are getting more and more complex according to their topographic distribution and the variety of tasks to be achieved. This complexity makes solving organizational problems difficult, especially tasks planning. The first aspect of this issue concerns the complexity of disruption management in order to be closer to the reality of industrial systems. The second aspect deals with human factors. Indeed, most current methods of scheduling management mainly deal with clearly defined physical and temporal constraints. The human factor in rescheduling is generally not considered as essential and therefore is not taken into account. The first objective of the approach consists in minimizing the organizational impact on the existing plans or schedules. The second objective consists in minimizing impacts on human resources by changing as little as possible their working organization and their forecast frameworks.

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Usual solutions propose to dynamically revise schedules or plans. However online generation of plans for dealing with environment uncertainty does not usually dynamically integrates the degree of impact of the new plans on the organisation of industrial systems. Consequently the need for a specific approach for managing disrupting events appears. This approach must take into account the distributed nature of the new forms of organizations, respecting the actors' autonomy. Moreover, it must focus on the impacts of the disruption recovery solutions, particularly on the human organizational aspect. Both these aspects lead the solving process to “fix” the actual schedule rather than to compute a completely new solution. The search for minimizing the disruption impacts involves the implementation of cooperative decision processes that actors would naturally develop. This process is based on cooperative strategies between actors using various arrangements of repair operations on task attributes. Scheduling repair operations and solving strategies are adapted to this growing complexity. The resulting multi-agent system operates the repair behaviours in order to determine the solution which minimizes the disruption impact and proposes it to the final human decision maker. This method has been applied to production workshops inside a company, in the context of inter-enterprise situations, to topographically distributed systems such as building site organization and to maintenance operations in aeronautics. Actors, resources, and disruptions were defined at each level according to the problem specific needs. Chapter 7 – The advent and collapse of real estate bubbles, or the sharp rises and falls in real estate prices, have posed major economic issues in many nations. Real estate prices soared sharply in Japan and Sweden in the 1990s and recently in many Western countries (until the mid-2000s), until plunging in the wake of the financial crisis in the United States. The rapid rise and fall of real estate prices in Japan from the mid-1980s to the 1990s is said to represent the most significant real estate bubble of the 20th century. Following the collapse of this bubble, Japan experienced a long period of economic stagnation, often cynically described as the “lost decade.” What have we learned from these ups and downs in the real estate market? Have recent real estate investment risk management efforts incorporated these lessons? To answer these questions, the author would like to pay attention to the severalty of each real asset. The lesson learned from last century’s economic bubble and from the expansion and shrinkage of the real estate market in the wake of the latest financial crisis is that “real estate investment risks cannot be

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dispersed by diversifying investments, and major risks will remain unless assets are carefully selected.” In the 1980s bubble, many real assets were the subject of speculative transactions whose purpose was not actual use. The investors in these assets ultimately suffered from devastating losses. Based on this lesson, the latest expansion of the real estate investment market was based on real assets already in use that would provide the investors with certain profits. However, as the market overheated, investments were diversified into various types of property to disperse risk, became smaller in size, and were geographically expanded beyond urban centers into suburban areas, then into regional cities. As a result of such market expansion, it is likely that market selection will be spurred again by market shrinkage in the wake of the financial crisis. Bearing these issues in mind, the author in this paper will look back on the period of adjustment following the collapse of the economic bubble in the 1990s; elucidate how assets were sorted in the Tokyo 23 wards office market, taking macroscopic changes in the real estate market in the Tokyo 23 wards office market into account; and suggest possible major considerations for future investments in office buildings. Chapter 8 – Competitive business environments in recent years have put pressure on firms to examine their corporate social responsibility (CSR) activities. Importantly, it is observed that a transitional movement has begun from traditional CSR (i.e. giving back to society without any expectation of return) to strategic CSR (socially and economically win-win) in many corporations. A fundamental belief among business academics and practitioners is that CSR pays off for the firm as well as for the firm’s stakeholders and society in general. A failure to find strong empirical support for the relationship between CSR activities and financial performance has, however, been troubling to those advocating CSR. This lack of empirical relationship between CSR activities and financial bottom line is perceived by some businesses as evidence that these activities not relevant for successful business performance. Past studies have investigated how consumers perceive and respond to various CSR activities including corporate sponsorship, corporate donations, corporate voluntarism, and community involvement. Some important findings are related to attributions developed by consumers about motives of the corporation that conducts CSR activities, and whether these attributions exert a positive or negative influence on consumer attitudes toward the corporation. However, previous studies have not characterized corporate behaviors in terms of their perception by consumers as significant CSR, and researchers have paid

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little attention to consumers’ understanding of this notion of CSR. The present study explores the relationship between consumer awareness of CSR activities and the consumer’s purchase intentions. To this end, a questionnaire survey involving Korean consumers is employed. For the analysis, measurement scales for CSR activities and consumers’ purchase intention scales are respectively developed. From the results it is found that there is a significant positive relationship between these two parameters. This study finds that, as CSR activities, corporate social contribution and local community contribution affect consumers’ purchase intention while corporate environmental protection and contribution have no effects on purchase intention. Chapter 9 – This paper presents an empirical investigation of a gametheoretical model of an infinitely repeated game with imperfect information and trigger strategy. One of the main difficulties with game-theoretical models in economics is the fact that they hardly end up with a few empirically testable hypotheses. The theoretical model that is the basis of our analysis is due to Abreu, Pearce and Stachetti (1986), which in turn extended the model of Green and Porter (1984). Following Berry and Briggs (1986) and Briggs (1988), we test the behavior that leads to periods of collusion and punishment periods that precisely follow a first-order Markov process. The study results should provide insights for regulatory agencies in terms of analyzing market interactions and the exercise of tacit collusion, since it provides a testable framework for one specific case of market structure. Chapter 10 – Industrial economics has been one of the major fields of economics for the last few decades. The main interest in the early days of the field was in empirical research, later in the 1970s and 1980s there was a shift towards more interest in theoretical research, and afterwards empirical research gained again interest, but involved more sophisticated research that was different from the empirical research in the early days of the field. More recently, sub-fields that were traditionally very small, such as behavioral industrial economics and experimental industrial economics, have become much more popular than in the past. The chapter reviews some of the history and content of the field of industrial economics. It then identifies the five top journals in industrial economics (RAND Journal of Economics; Journal of Economics and Management Strategy; Journal of Industrial Economics; International Journal of Industrial Organization; and the Review of Industrial Organization) and examines their relative impact. The development in the number of articles published in these journals and covered by the Social Science Citation Index is also analyzed. The chapter then considers the articles published in these five journals since 1965, ranking the most-cited articles in

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each decade. The RAND Journal of Economics is clearly the leading journal, but the Journal of Economics and Management Strategy, the Journal of Industrial Economics and the International Journal of Industrial Organization also include highly-cited articles and their recent impact factors are not far behind that of the RAND Journal of Economics.

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In: Progress in Economics Research. Volume 23 ISBN 978-1-61324-394-7 Editor: Albert Tavidze © 2012 Nova Science Publishers, Inc.

Chapter 1

REGULATORY GOVERNANCE AND THE REGULATORY FRAMEWORK FOR SAFEGUARDING FINANCIAL STABILITY Benjamin Mohr and Helmut Wagner

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University of Hagen, Germany

ABSTRACT The financial crisis of 2007-09 revealed several flaws in the regulatory frameworks across the world. While there is a consensus on the need for regulatory reform, the focus of such a reform is much less clear. This paper argues that the improvement of regulatory governance arrangements should be a key building block of financial reform since the current framework lacks the ability to guard supervisors from being influenced by the financial sector as well as political interference. After contrasting two complementary theories of bank regulation – the helping and grabbing hand view – we thus make a case for regulatory governance. First, we explain the key characteristics of this institutional aspect of bank regulation. Second, we systematize empirical studies examining the effects of good regulatory governance on financial sector performance. The evidence surveyed indicates that regulatory governance can indeed have an influence on financial stability. Nevertheless, more robust evidence for supporting the view that good regulatory governance has positive effects on financial stability is needed. Finally, we touch upon the issue of whether placing bank regulation inside an independent

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Benjamin Mohr and Helmut Wagner central bank creates a better institutional environment for safeguarding financial stability.

Keywords: Bank Regulation, Financial Stability, Governance, Institutions, Central Banks, JEL Classification Code: G21, G28, L51, E58.

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1. INTRODUCTION “Political interference is the Achilles’ heel of any regulatory system.” During the financial crisis of 2007-09 this quote from Honohan (1997) was impressively confirmed. By now, the origins of the financial crisis of 2007-09 are well understood – with regulatory shortcomings put at center stage (see Wagner, 2010). While macroeconomic causes comprise the build-up of imbalances in international claims and difficulties related to the long period of low real interest rates, the microeconomic origins consist of flawed incentives, failures of risk measurement and management and particularly regulatory failures (BIS, 2010). As regards regulation and supervision, systemic repercussions due to the failure of non-banks as well as the systemic risks entailed by the interaction between regulated and unregulated institutions, financial activities and markets were not appropriately recognized. Furthermore, regulatory authorities did not have sufficient powers to limit the build-up of highly concentrated credit risk in unregulated entities, and market discipline was not sufficient in terms of constraining excessive risk-taking. Closely related to this, regulatory arbitrage has not been addressed properly so that financial institutions shifted their business into unregulated or lightly regulated sectors (Carvajal et al., 2009). Many commentators view governance failures as a key contributing factor to the global financial crisis. The evidence provided by Levine (2010) indicates that regulatory agencies apparently were aware of the build-up of risk in the financial sector associated with their policies, but chose not to modify those policies. Mian et al. (2010) lend support to this finding by showing that vested interests influenced the financial sector policy-making of the US government in the wake of the financial crisis. Buiter (2008) argues that “cognitive regulatory capture” of the Federal Reserve by the financial industry led to a policy stance that excessively considered concerns and fears of vested interests by those being regulated. Igan et al. (2009) find that financial institutions which lobbied more intensely originated mortgages with

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Regulatory Governance and the Regulatory Framework …

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higher loan-to-income ratios, securitized more intensively and had faster growing mortgage loan portfolios In light of these observations, we make a case for regulatory governance as an essential building block regarding reforms to strengthen bank regulation with the objective of safeguarding financial stability. The issue of independence and accountability for regulatory authorities has received an increasing attention. The Basle Committee on Banking Supervision has recognized the importance of independence and accountability for regulatory authorities by including these two governance arrangements in the Basel Core Principles for Effective Banking Supervision. Today, the implementation of an independent regulatory authority is viewed as a key principle for prudential regulation, being a common financial-sector policy recommendation in the IMF’s Financial Sector Assessment Programmes. However, recent studies have shown that there still is a serious lack of regulatory independence across all countries and regions (see Seelig und Novoa, 2009). The aim of this paper is to discuss the theoretical foundations of regulatory governance and more importantly, to examine and systematize the empirical evidence on the financial stability effects of regulatory governance and related aspects thereof. This review is basically motivated by the fact that many regulatory authorities still lack the mandate, sufficient resources and independence to effectively contain systemic risk and to implement early action in the run-up to a financial crisis (see Claessens et al., 2010). We also turn to the question of whether locating the regulatory function inside the central bank might be preferable to other institutional regulatory arrangements, since the central bank could be in a better position to regulate and supervise the financial sector when evaluated against the background of governance aspects such as independence, professionalism and remuneration (Cukierman, 2011). The remainder of the article is organized as follows: section 2 puts regulatory governance into proper perspective by discussing two contrasting views of bank regulation. Section 3 makes the case for regulatory governance as an institutional mechanism for improving the functioning of the financial sector and explains the key characteristics of this institutional aspect of bank regulation. The subsequent section reviews the empirical literature on the impact of regulatory governance on the stability of the financial sector and related aspects. In light of the issues raised in this article, section 5 asks the question of whether bank regulation should be undertaken by the central bank. The last section concludes.

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2. TWO VIEWS OF BANK REGULATION In general, economists emphasize the conflict between public and private interests in determining policy outcomes. In this section we will discuss two contrasting approaches to bank regulation.1 We begin by outlining the traditional approach to explaining the existence of financial regulation– the helping hand view of regulation. Doing so, we first have to distinguish between objectives and the rationale for regulation.2 The key objectives of a bank regulator are the promotion of economic development, the prevention of financial crises and the protection of consumers (see, e.g., Herring and Litan, 1995). The main objective is the proper functioning of the financial system which is presumed to significantly contribute to economic development (see, e.g. Levine, 2005). A related objective is the prevention of financial crises, which can entail significant costs for the economy (see, e.g., Reinhart and Rogoff, 2009). Finally, consumer protection is also a core duty of a bank regulator. By establishing rules and regulations concerning the appropriate practices and business models in the financial sector, the regulatory agency should ensure that there is a fair and open competition in the financial sectors. The rationale for a constructive and more active role for governmental regulation goes back to Pigou (1938) who argues that market failures impede the proper functioning of the financial market so that the market would produce a sub-optimal outcome when left to itself. The helping hand view assumes that there are serious market failures, that the government has the incentives to maximize social welfare and wishes to prevent or correct these market imperfections (Shleifer and Vishny, 1998). In this view, bank regulation can enhance the functioning of the financial system by intervening in the banking sector and thereby promote economic growth. There are basically three reasons for government intervention in the financial sector – asymmetric information, negative externalities and monopoly power – which we do not want to dwell on here. For a detailed discussion of the market failures that impair social welfare and distort market mechanisms, we refer to, e.g., Goodhart et al. (1998), and Llewellyn (1999). 1 2

See also Barth et al. (2006) for an extensive review. Typically the term “regulation” refers to the setting of rules and guidelines, while “supervision” describes the process of enforcing these rules and monitoring the banks’ activities. Note, that we use the term “bank regulation” in a rather broad sense. Hence, “regulatory agency” or “regulatory authority” will refer to all institutions involved in the process of bank regulation and supervision.

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While governmental solutions to correct market imperfections rest upon the assumptions that governments are better informed than the markets and always act in the public interest, such assumptions seem to be ill-founded because regulators are subject to political and regulatory capture (Beck, 2006). According to the grabbing hand view, regulators do not implement rules and supervise the financial sector to overcome market failures. The involved interest groups – the regulatee (financial industry), politicians and regulatory agency officials – rather interact to maximize their ability to extract rents from economic activity (Shleifer and Vishny, 1998). Even in situations in which regulatory authorities try to maximize social welfare, they may fail due to a lack of competence or limited expertise (see, e.g., Claessens, 2006). Hence, this view predicts that regulators give priority to private interests and are scarcely guided by public interests. Consequently, no improvement in the functioning of the financial system or bank stability may evolve. The theoretical literature on the economics of regulation starts with the work by Stigler (1971), Posner (1974) and Peltzman (1976). Their results suggest that regulators are subject to regulatory capture, i.e. regulated firms put great pressure on regulators so that rules and guidelines are implemented in a way suiting their interests. Large financial institutions may influence the regulatory agency directly by offering a “revolving door” in exchange for being cooperative (Hardy, 2006). Furthermore, powerful financial institutions may capture regulators indirectly through politicians via lobbying and influence peddling (see, e.g., Kane, 2002) so that the regulator supports the interests of the financial industry, rather than promoting social welfare. As elaborated by, e.g., Krozner (2001), interest groups from the financial industry may influence politicians through campaign contributions, donations or votes who in turn pressure regulators to act in the interest of the financial industry. Usually the financial sector represents a compact, well-organized group, which is able to use coercive powers of the government and impose their interests at the expense of other groups which have more diffuse membership. Or as Kane (1997) puts it: “(…) regulators and regulatees may connive to allocate the costs and benefits of regulation to other parties, with taxpayers and unsophisticated financial-services firm customers being strong candidates for getting the short end of regulatory deals”. As pointed out by Olsen (1965), Stigler (1971), Peltzman (1976) and Becker (1983), more cohesive groups will find it easier to organize themselves, and the effectiveness of groups rises with the concentration of benefits among group members. Furthermore, regulation

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is less likely to be successful when deadweight costs are high.3 Finally, marginal costs and benefits to different groups play an important role, as the benefits of regulation are dispersed among many different groups (see also Krozner, 1998 for a more detailed discussion). Krozner and Strahan (1999) argue that the balance of power between various interest groups shifts over time so that different political or regulatory outcomes are achieved, depending on which interest group is most successful in pursuing their interests. Politicians have incentives to participate in the regulatory game and serve self-interests, too, in that they facilitate the financing of government expenditures, direct credit to politically attractive ends and politicize resource allocation. Especially in emerging and developing countries the banking sector is the primary source of domestic financing so that the control of the sector via regulations is of vital interest (Barth et al., 2006). Recent studies have shown that economies with weakly constrained governments are characterized by an alliance between political and economic elites enjoying special benefits (see Haber and Perotti, 2008 for an extensive survey). While the government tends to influence regulations so as to promote political constituencies (Djankov et al., 2002), such political connections can matter through the suppression of competition and the delay of reform in the financial sector (Rajan and Zingales, 2003). Through government-owned banks or concentrated ownership, the government can have influence on the allocation of credit, so that state-owned or politically connected enterprises can gain preferential access to finance. Empirical work has shown that regulators are heavily influenced by politicians and financial industry lobbyists alike. In spite of the fact that close links between the political, financial and corporate sector are rather common and there often is an increase in state ownership in the aftermath of financial crises, government ownership of banks tends to be rather inefficient. An influential study by Djankov et al. (2002) finds that government ownership is associated with lower subsequent growth of per capita income and less financial development. Government ownership is particularly pervasive in countries with low levels of per capita income and interventionist governments. Claessens et al. (2000) show that the majority of East Asian enterprises is controlled by a single shareholder. The concentration of corporate control in the hands of a few interest groups or families provides the basis for preferential treatment by public officials, i.e. through preferential 3

Krozner (1998) describes deadweight costs as the difference between the winner’s benefit and the loser’s cost arising from a regulatory measure.

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access to finance or preferential contracts, as enterprises with more concentrated ownership structures are more likely to establish close political ties. A wave of empirical studies examines the interplay of the political, financial and corporate sector and provides cross-country and country-specific evidence that political connections play a crucial role in obtaining access to external financing and matter for increasing firm value. Dinc (2005) studies whether government-owned banks behave differently around election years and shows that state banks increase their lending in election years, relative to private banks. Faccio (2006) finds in a cross-country study that connected firms have higher leverage, lower taxes and stronger market power than otherwise similar firms. Several recent papers take an event-study approach and find similar results for countries such as Indonesia (Fisman, 2001), Malaysia (Johnson and Mitton, 2003), Mexico (La Porta et al., 2003), Italy (Sapienza, 2004), Pakistan (Khwaja and Mian, 2005), Thailand (Charumilind et al., 2006) and Brazil (Claessens et al., 2008). Besides preferential access to finance, political connections may generate other, substantial benefits to the financial industry. Recent empirical work by Faccio et al. (2006) illustrates that in case of economic or financial turbulences, politically connected enterprises are more likely to be bailed out by their home country in comparison with their non-connected firms. Brown and Dinc (2005) demonstrate that government interventions in the banking sector are often delayed due to political concerns. While politicians tend to avoid costly interventions in the banking sector before elections, most government takeovers or closings of failing banks occur in the first half of the electoral cycle. Finally, there is strong evidence that less democratic regimes suppress entry and competition (see, e.g., Djankov et al., 2002) and that such barriers matter for financial development and economic growth (see, e.g., Rajan and Zingales, 1998).

3. REGULATORY GOVERNANCE TO THE RESCUE? The upshot from the theoretical considerations regarding the grabbing hand behaviour of bank regulation and the empirical evidence that regulators sometimes do not maximize social welfare is that there seem to be substantial reasons for the search for an institutional mechanism limiting the regulatory authorities’ leeway in fulfilling their mandate. We argue that regulatory

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governance can be an important institutional mechanism for safeguarding financial stability and review its basic characteristics.4 The increasing popularity of this topic can be attributed to financial liberalization that changed the financial landscape and the challenges to bank regulators (Goodhart, 2007). More importantly, recent banking crises have brought the discussion about the appropriate institutional framework for regulatory agencies to the forefront. Following Williamson (2000), governance “(…) is an effort to craft order, thereby to mitigate conflict and realize neutral gains. So conceived, a governance structure obviously reshapes incentives”. In the case of bank regulation, Das and Quintyn (2002) distinguish four defining pillars of regulatory governance: independence, accountability, transparency and integrity. The most discussed and probably most important pillar tends to be the independence of the regulatory agency. Reflecting the discussion in the previous section, independence of regulatory agencies has two dimensions: independence from political interference and freedom from regulatory capture by the regulated industry (Quintyn and Taylor, 2007). While the case for central bank independence (CBI) is well established (see, e.g., Cukierman, 2008), the discussion of independence in the sphere of bank regulation is relatively new; with Goodhart (1998) as well as Das and Quintyn (2002) being among the first drawing the attention on this important institutional aspect. As put forth by Majone (2005), the willingness of politicians to delegate powers to independent authorities can be explained in various ways. First, specialized authorities with neutral experts are characterized by a higher level of expertise in carrying out regulatory policies and have the capacity to adapt to changing conditions. Second, delegating regulatory powers contributes to reducing the costs of decision-making since policy makers can economize on time and effort in identifying desirable refinements to legislation. Third and probably the main reason for delegating powers to an independent institution, there is a strong need to achieve credible long-term policy commitments. In this regard, Quintyn and Taylor (2007a) draw two analogies between CBI and the independence of regulatory agencies. First, short-term policy objectives do not always coincide with the requirement of a stable, long-term regulatory framework. And second, politicians could also face the well known time inconsistency problem when making decisions in the field of bank regulation. Accordingly, politicians have incentives to keep insolvent financial 4

See, e.g., Quintyn and Taylor (2002; 2007a) for an in-depth treatment of the theoretical foundations of regulatory governance.

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institutions alive by organizing a bailout or granting exceptions from regulatory requirements, thereby delaying the unpopular decision because they want to avoid the short-term costs in form of lost campaign contributions or lost votes (see Brown and Dinc, 2005). Thus, the logic of Rogoff’s conservative central banker could be extended to the area of regulation. By insulating regulators from policy makers whose objectives may differ from the regulators’ objectives, the credibility of regulatory commitments could be enhanced (Majone, 2005). Furthermore, the delegation of regulation powers to an independent agency is desirable to the extent that it is given a clear mandate in the form of a financial stability objective because independence is easier to achieve when there is a single, widely-shared objective (see, e.g., Bini Smaghi, 2007). Alesina and Tabellini (2007; 2008) make a more formal case for regulatory independence by building a model to investigate the criteria that guide the allocation of policy tasks to elected politicians versus independent bureaucrats. They find that it is preferable to assign tasks rather to bureaucrats than politicians if these tasks require certain abilities relative to effort and if there is uncertainty about the abilities of the politician, if time inconsistency is a relevant issue, and if vested interests have large stakes in the policy outcome. Having elaborated the case for agency independence, we now turn to the four dimensions of independence – namely institutional, regulatory, supervisory and budgetary independence. First of all, institutional independence refers to the status of the regulatory authority as an institution operating separately from the executive and legislative branches. Quintyn et al. (2007) identify three critical components of institutional independence. First, there should be clear rules regarding the terms of appointment and dismissal of senior personnel. Second, collegial decision-making in multi-member commissions are considered superior to decision-making by one individual chairperson. And third, the decision-making process should be open and transparent so as to minimize the risk of political interference. Regulatory independence, the second dimension, refers to the ability of the regulatory authority to have an appropriate degree of autonomy in setting fundamental prudential rules and regulations for the financial sector which is a crucial prerequisite for ensuring that the financial sector complies with international best practices (see, e.g., Masciandaro et al., 2009). As Quintyn and Taylor (2003) point out, especially the growing complexity and internationalization of financial markets give rise to the importance of regulatory independence since regulators need to be able to adapt rules and

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regulations quickly and flexibly in response to changing conditions and the build-up of risk in the financial sector. The most difficult component of independence to achieve is supervisory independence. With supervisory independence, the agency is in the position to exercise its judgment and powers in supervisory activities such as licensing, on- and off-site monitoring, sanctioning and the enforcement of these sanctions, which are the regulatory agencies’ main tools to safeguard banking sector stability (Quintyn and Taylor, 2002). The difficulty stems from the fact that in order to preserve its effectiveness, the supervisory function involves private ordering between the regulator and the regulatee. However, this “invisibility” makes the agency vulnerable to political and industry interference (Masciandaro et al., 2009). Finally, budgetary independence refers to the role of the executive and legislative branch in the determination of size and use of the agency’s budget. This component is of importance since regulatory agencies with a higher degree of autarky in terms of source, size and use of their budget are better equipped to restrain from interference by the government, attract competent staff and adapt prudential regulations quickly in response to changing conditions (see, e.g., Quintyn and Taylor, 2003). Independence of regulatory authorities cannot deliver the desired results in terms of policy outcomes if it is not accompanied by accountability arrangements (see Quintyn and Taylor, 2003). As Majone (1993) stresses, policy makers are rather concerned about an independent regulatory authority virtually acting as an unelected fourth branch of government without any checks and balances. Accordingly, Quintyn (2009) characterizes accountability as the other, indispensable side of independence. Accountability can be defined as the obligation owed by the accountable to the accountee according to which the former must giver account of, explain and justify his actions and decisions and take responsibility for any fault or damage (Lastra, 2001). Hence, there is no trade-off between accountability and independence. Rather, these two institutional arrangements should be seen as complementary. Accountability arrangements reinforce the independence of a regulatory authority by giving its actions and decisions legitimacy and enabling the authority to build a reputation, thus improving agency governance and performance. Equally important, an agency with a good reputation is seen as more reliable and trustworthy by the public; consequently, a good reputation bolsters the agency’s independence (see Hüpkes et al., 2006).

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Hüpkes et al. (2005) identify at least four functions that a well structured accountability arrangement fulfils: first, to provide public oversight; second, to provide and maintain legitimacy; third, to enhance integrity of public sector governance; and finally, to enhance agency performance. Nevertheless, holding regulators accountable tends to be a rather complex task since much of their operations is cloaked with commercial confidentiality (Goodhart, 2001) and unlike monetary authorities, regulatory authorities have to be accountable to the industry they regulate and to the executive/legislature (Hüpkes et al., 2006). While independence and, to a lesser degree, accountability are the most debated pillars in the regulatory governance literature, transparency and integrity are equally important because the four pillars are mutually reinforcing and hold each other in balance. Weakening one of the four pillars thus means that the balance between the pillars is undermined. Transparency, the third pillar of regulatory governance, is increasingly recognized as an institutional arrangement for mitigating uncertainty in financial markets in general (see, e.g., Cady and Pellechio, 2006; Glennester and Shin, 2008). According to the IMF’s Code of Good Practices on Transparency in Monetary and Financial Policies, transparency refers “(…) to an environment in which the objectives of monetary and financial policies, their legal, institutional, and policy framework, monetary and financial policy decisions and their rationale, data and information related to these policies, and the terms of central bank and financial agencies accountability are provided to the public in a comprehensible, accessible, and timely manner” (IMF, 2000). Transparency and accountability are closely interrelated since they both share the provision of information as a common requirement. Whereas accountability constitutes the obligation to give account of, explain and justify the regulatory authorities’ actions, transparency is the degree to which information on such actions is available in comprehensible, accessible, and timely manner. Thus, transparency directly supports accountability and vice versa. The provision of information in the context of accountability facilitates a transparent economic and political environment, while transparency promotes accountability by making the regulatory policy clear to the outside world (see Lastra and Shams, 2001; Das and Quintyn, 2002). Furthermore, transparency protects the independence of the regulatory authority by revealing when the authority is under political or industry pressure thereby discouraging politicians and financial industry lobbyists from interfering in the regulatory process (Quintyn and Taylor, 2002).

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Integrity, the last but no less important pillar, refers to institutional mechanisms that ensure that the staff of regulatory agencies can pursue the goals of good regulatory governance without compromising them by falling victim to self-interests (Das and Quintyn, 2002). This pillar comprises institutional arrangements such as appointment procedures of heads, internal audit arrangements or legal protection against law suits. Taken together, good regulatory governance enhances the ability of the financial system to withstand unsound market practices and the occurrence of moral hazard and hence, improves the system-wide risk management capabilities. By contrast, dysfunctional government arrangements undermine the credibility of the regulatory authority and lead to the spread of unsound practices, jeopardizing the stability of the financial system (Das et al., 2004). In this regard, Quintyn (2007) argues that weak regulatory governance promotes weak financial sector governance in general, which in turn impairs the smooth functioning of the financial system, curbing economic performance and growth. According to Barth, Nolle, Phumiwasana and Yago (2003), there are particularly three common practices that undermine regulatory governance. First, credit granted due to directed lending might not be justified under safe banking standards because it is more likely that it turns out to be nonperforming. Such practices could undermine the credibility of the regulatory authority and the development of a sound loan base and consequently restrict economic growth. Second, government ownership of banks could threaten the stability of the banking system in a similar vein since the regulatory authority might not be allowed to apply the regulatory standards to state-owned banks. Accordingly, the credibility of the agency could be impaired and solvency problems at poorly managed state-owned banks could lead to a liquidity crisis. Finally, the protection of weak regulations by politicians and governmentencouraged regulatory forbearance are the most common types of undermining the integrity of the regulatory authority and exacerbating banking crises, with Japan (see, e.g., Hoshi and Kashyap, 2001) and the US (see, e.g., Kane, 1989) being the most prominent casualties. Rochet (2008) concludes that many recent banking crises were largely amplified or even provoked by political interference and the key to successful financial reform lies in ensuring the independence and accountability of regulatory authorities. Indeed, there is ample evidence that the policies described undermined the independence of the regulatory authority, contributing to the emergence of banking crises (see, e.g., Caprio and Klingebiel, 1997; Lindgren et al., 1999; De Krivoy, 2000).

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4. THE IMPACT OF REGULATORY GOVERNANCE Having reviewed the theoretical case for independent and accountable regulatory agencies, we now turn to the empirical evidence regarding the impact of regulatory governance on the functioning and stability of the financial system. In doing so, we concentrate primarily on those studies which examine the effects of regulatory governance (and related aspects) on economic performance and on the stability of the banking sectors or financial stability more generally. We also collect the empirical work which deals with the organizational structure of the regulatory agency and the determinants of regulatory governance.5 We grouped the empirical work on regulatory governance into eight categories; table 1 provides an overview of the relevant studies. Two studies examine the determinants of regulatory governance. Following Quintyn et al. (2007), Masciandaro et al. (2008) construct a regulatory governance index to evaluate the independence and accountability of the regulatory authority. Using a wide set of control variables, their analysis indicates that public sector governance has a decisive impact, but more on accountability than on independence arrangements. They also found that placing the regulator inside the central bank has a negative impact on governance arrangements. Neyapti and Dincer (2005; 2008) build an index measuring the legal quality of bank regulation and supervision and show that prevailing financial crises, EU membership and higher levels of financial development and foreign direct investment inflows exert a positive influence on the quality of a legal regulatory framework. Dalla Pellegrina and Masciandaro (2008) belong to the second category as they estimate the relationship between public sector governance and the institutional structure of the regulatory authority. Their main finding is the crucial role public sector governance plays in determining the unification of the regulatory agency. Concretely, there is a positive relationship between good governance performance and the degree of unification. A “helping handpolicy maker” will tend to prefer a unified regulatory authority different from the central bank, while a “grabbing hand-policy maker” will choose a single

5

See Quintyn (2007) for a comparable systematization of empirical studies on the impact of regulatory governance. In contrast to Quintyn’s survey, we added a few more categories and examined a broader range of studies since we cover a longer period of time.

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regulatory authority.6 These results are more or less corroborated by the work of Freytag and Masciandaro (2007) and Masciandaro (2007; 2009). Table 1: Systematization of empirical studies on regulatory governance 1 Impact of financial, macro, institutional factors on regulatory governance Masciandaro, Quintyn and Taylor (2008) Neyapti and Dincer (2005; 2008) 2 Impact of public sector governance on institutional structure Dalla Pellegrina and Masciandaro (2008) Freytag and Masciandaro (2008) Masciandaro (2007; 2009) 3 Impact of public sector governance on financial stability Breuer (2006) Kaufmann (2002) 4 Impact of regulatory governance on financial stability Beck, Demirgüc-Kunt and Levine (2003; 2006) Das, Quintyn and Chenard (2004) Donze (2006) Ponce (2009) 5 Impact of regulatory framework on financial stability and development Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

Angkinand (2009) Barth, Caprio and Levine (2004, 2006) Barth, Caprio and Levine (2008) Boudriga, Boulila and Jellouli (2009) 6 Impact of compliance with principles of financial stability Das, Iossifov, Podpiera and Rozhkov (2005) Demirgüç-Kunt, Detragiache and Tressel (2008) Demirgüç-Kunt and Detragiache (2010) Podpiera (2006) Sundararajan, Marston and Basu (2001) 7 Impact of regulatory governance on compliance with standards and codes Arnone, Darbar and Gambini (2007) 8 Impact of institutional structure on compliance with standards and codes Arnone and Gambini (2007) Čihák and Podpiera (2006; 2007)

6

The authors explain this by pointing out that the helping hand-kind of policy maker does not need to please vested interests and fear political pressure from an influential single agency.

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Next, we turn to the empirical studies concerning the impact of different forms of governance on banking or financial stability and economic performance. In spite of the compelling evidence that institutions and governance have a strong impact on economic development and stability (see, e.g., Carmichael, 2002; Rodrik et al., 2004), there currently exist only two studies that analyse the impact of public sector governance on financial stability. Kaufmann (2002) measures financial stability by using the microeconomic firm level data of the World Bank Global Competitiveness Survey. Regressing the variable against several governance indicators, his analysis reveals that the “control of corruption” significantly influences banking sector stability. In a more recent study, Breuer (2006) also finds that a higher degree of corruption raises banking sector instability, proxied by nonperforming loans as a share of bank assets. More surprisingly, she finds that a lack of property rights reduces and improvements in law and order and government stability increase problem bank loans. Five studies analyse the relationship between regulatory governance and financial stability. Beck et al. (2006) investigate the impact of different regulatory policies on the integrity of bank lending. Using the World Business Environment Survey, they approach the term financial stability by asking to which degree firms face obstacles in obtaining external finance. Their results are consistent with the “political/regulatory capture view”; that is, powerful official supervision may increase the flow of credit to well connected firms while it will hurt the availability of credit to firms in general. In an earlier study, Beck et al. (2003) take account of the “independent supervision” view. They find that creating an independent supervisory agency mitigates the negative effects of having a powerful official regulator by lowering the obstacles in obtaining external finance. Specifically, a higher degree of regulatory independence seems to reduce the likelihood that politicians or the financial industry will capture the agency. Das et al. (2004) construct an index of regulatory governance based on the four pillars mentioned in the previous section. Banking sector stability is proxied by data on the capital adequacy ratio and the ratio of non-performing loans the authors collected from the IMF’s Financial Sector Assessment Program (FSAP). The estimation results suggest that regulatory governance has a positive impact on the stability of the banking sector. Ponce (2009) also uses data collected by the FSAP to capture regulatory governance arrangements but only uses the ratio of non-performing loans to total loans as an indicator for the degree of risk in the banking sector. His main findings are that regulatory independence significantly reduces the average probability of

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banks’ loan default, and that legal protection and accountability seem to be of even more importance. Ponce therefore concludes that regulatory authorities should have political independence but that independence should be complemented by legal protection and accountability arrangements. Donzé (2006) reaches a similar conclusion. His findings indicate that better regulatory governance tends to improve banking sector soundness. While regulatory governance is captured by aggregate measures of personnel, goal, instrument, and budgetary independence, he proxies banking sector stability by using financial strength ratings developed by the credit rating agencies Fitch and Moody’s. The next group of empirical studies takes a somewhat broader perspective, analysing the influence of the regulatory framework on financial stability and development. In this vein, Barth et al. (2004; 2006) conduct a comprehensive study on the impact of regulatory practices on the development, efficiency and stability of the banking sector as well as the occurrence of a banking crisis. Similar to Beck et al. (2003; 2006), the authors do not estimate the influence of regulatory governance directly. Instead, they test the validity of two contrasting approaches to bank regulation set out earlier in this article – the public and the private interest approach to regulation – by examining an extensive array of regulations and supervisory practices. In sum, their findings provide no support for greater official supervisory powers and are rather consistent with the private interest view of regulation. Supervisory independence is not related to bank development, efficiency and stability. In Barth et al. (2008) the authors present microeconomic evidence on the impact of the two competing views by using two microeconomic indicators on bank efficiency – bank-level data on overhead costs and the degree to which firms need corrupt ties with banks for obtaining external finance. Again, the empirical evidence is inconsistent with the public interest view, as empowering supervisors tends to increase corruption in bank lending. Following the approach of Barth et al. (2004; 2006), Boudriga et al. (2009) estimate the impact of the regulatory framework on credit risk exposure. They introduce aggregate non-performing loans data as the dependent variable for which the data is drawn from the IMF Financial Soundness Indicators. Although their results indicate that higher capital adequacy ratios and higher provision seem to reduce the level of nonperforming loans, regulatory practices have no significant impact. Only the level of independence of the regulatory authority seems to reduce the level of non-performing loans in countries with little corruption. Finally, Angkinand (2009) also uses a range of indexes from the database provided by Barth et al.

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(2004; 2006). He examines the effects of regulatory practices on the severity of banking crises measured in terms of output costs. According to his results, bank capital requirements and fewer restrictions on bank activities tend to mitigate crisis severity. While the empirical work reviewed so far typically assesses the compliance with standards and codes like the Basle Core Principles for Effective Banking Supervision (BCP) in order to construct indexes as proxies for regulatory governance arrangements, five studies have examined the impact of the compliance with standards and codes on financial stability directly – thereby implicitly estimating the influence of regulatory governance. Sundararajan et al. (2001) were the first who attempted to test the impact of BCP compliance on banking stability. Utilizing the non-performing loan ratio as a proxy for bank soundness, they do not find a direct impact of BCP compliance. Das et al. (2005) resort to more sophisticated methods. They construct two indexes; an index of the quality of financial policies based on BCP and IOSCO assessments and a financial stress index that builds on the work by Illing and Liu (2003) and encompasses the banking sector and the foreign exchange and equity markets. Their main finding is that economies characterized by a higher quality of financial policies are more able to mitigate the adverse effects of macroeconomic pressure on the financial system. Podpiera (2006) explores in how far the adherence to BCP standards creates an environment supportive of a well-functioning banking sector. His work shows that higher degrees of BCP compliance tend to increase the asset quality and reduce the net interest margin. This finding is consistent with the results of Demirgüc-Kunt et al. (2008) who use Moody’s Financial Strength Rating as a proxy for the soundness of the banking sector. However, their results indicate that the positive relationship between bank ratings and BCP compliance is rather weak. Accordingly, they attempt to estimate the impact of distinct aspects of the regulatory framework by distinguishing different core principles and find that compliance with information provision is significantly and positively associated with bank soundness. Demirgüc-Kunt and Detragiache (2010) extend this work by utilizing the z-score7 instead of Moody’s rating. On the basis of these data, they fail to find any relationship between bank soundness and compliance with specific groups of principles or BCP compliance in general. 7

The z-score is defined as the ratio of the sum of the average return of assets and the assetequity-ratio, and the standard deviation of the return on assets. The z-score is inversely related to a bank’s probability of default (see, e.g., Demirgüc-Kunt and Detragiache, 2010).

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Arnone et al. (2007) represent the only paper that studies the relationship between regulatory governance and compliance with standards and codes. They examine simple bivariate correlations between indexes of regulatory independence, transparency and BCP compliance or sub-indexes of various BCP chapters. The correlation coefficients indicate that there is a strong and significant relationship between the independence of the regulatory authorities and the quality and effectiveness of banking supervision. Furthermore, transparent authorities show a high degree of BCP compliance. The last category of empirical studies comprises two papers. Arnone and Gambini (2007) conduct bivariate correlation analyses to analyse the influence of the institutional structure on the compliance with standards and codes. The descriptive analysis suggests that the organizational model of an integrated regulatory authority has a statistically significant advantage compared to a central bank-dominated multiple agency regime. Moreover, they run a regression analysis showing that a higher degree of BCP compliance is associated with a more integrated regulatory authority (responsible for the banking, insurance and securities sector) inside the central bank. Thus, their study provides hints in favour of placing regulation inside the central bank. Cihák and Podpiera (2006; 2007) follow the approach of Arnone and Gambini (2007), but include the IOSCO and IAIS standards and codes (for the securities and insurance sector respectively) in addition to the BCP. Their results lend support to the notion that integrated regulatory authorities seem to be characterized by a higher degree of regulatory governance and a higher overall quality of supervision. However, their study does not provide any support for locating regulation inside or outside the central bank. Looking at the big picture, the empirical evidence surveyed here indicates that regulatory governance seems to lead to better regulatory practices which in turn have a positive impact on financial stability. To be sure, the evidence on the impact of regulatory governance on financial stability is far from conclusive. Hence, more robust evidence for supporting the view that good regulatory governance has positive effects on financial stability is needed. Some points are worth noting. First, there is a need for clarification of what constitutes a good regulatory framework that promotes bank development, efficiency, and stability; especially, what range of official regulatory and supervisory powers an agency should be given. Second, due to a lack of theoretical guidance, any construction of an index that tries to capture regulatory governance arrangements relies on some certain degree of judgment. Evidently, this is reflected in the wide range of different proxies used for capturing regulatory

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governance in the studies surveyed in this section. Finally, because there currently is no widely accepted measure, quantification or time series for measuring financial stability (see, e.g., Segoviano and Goodhart, 2009), similar difficulties relate to the dependent variable that should proxy financial stability. Most often utilized for capturing financial (in)stability is the ratio of nonperforming loans to total loans. However, statistics regarding the nonperforming loans in a banking sector may suffer from measurement problems which are likely to increase the noise in the data analyzed, since national regulatory authorities still often follow national guidelines that are not necessarily aligned (see Cihák and Schaeck, 2010).

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5. WHAT ROLE FOR THE CENTRAL BANK? The question of whether the central bank should be the bank regulator is still open to debate and has attracted great interest in academic circles. For the sake of brevity, we only brush over the main arguments briefly since the arguments for assigning some or all responsibilities to the central bank have been extensively debated elsewhere (see, e.g., Goodhart and Schoenmaker, 1993; 1995; Briault, 1999; Peek et al., 1999; Abrams and Taylor, 2000; Barth, Dopico, Nolle and Wilcox, 2002). The main argument in favour of locating the regulatory function inside the central bank is the better access to information. Furthermore, central banks often possess a high degree of independence which insulates the regulator from outside pressures and enhances the regulators’ ability to enforce regulations (see the discussion in section 3). Finally, the central bank has a comparative advantage in attracting the best staff. On the other hand, concerns with regard to granting central banks greater regulatory responsibilities are mainly based on the potential conflict of interest with monetary policy. Moreover, if bank failure or even banking crises occur, the central banks’ reputation may be at risk. And finally, the central banks’ independence may be compromised, since a wider financial stability mandate could politicize the central bank when being involved in supervision or the resolution of ailing financial institutions (see Barth, Nolle, Phumiwasana and Yago, 2003). In contrast to the theoretical literature, there has been rather little research on the institutional structure of bank regulation. According to Barth, Dopico, Nolle and Wilcox (2002), Barth, Nolle, Phumiwasana and Yago (2003) as well as Barth et al. (2004; 2006), the institutional structure only has a weak influence on bank performance. Frisell et al. (2008) find that central banks

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tend to be less independent and more subject to discretionary political control when bank supervision is assigned to the central bank. Estimating the relationship between central bank independence and financial instability, Klomp and De Haan (2009) conclude that political central bank independence is negatively associated with financial instability. As elaborated in the previous section, recent empirical evidence by Arnone and Gambini (2007) provide some hints for locating the regulatory and supervisory function inside the central bank whereas Masciandaro et al. (2008) show that the likelihood for more elaborate accountability arrangements is higher when the regulatory function is located outside the central bank although bank regulators inside the central bank have been granted the highest degree of autonomy. Consequently, it is fair to say that up to the recent financial crisis, there is no consensus on what constitutes an optimal institutional architecture of bank regulation – neither on conceptual nor empirical grounds. To be sure, central banks around the world serve as the sole bank regulator or as one of several regulatory agencies (see Barth et al., 2006). Especially in emerging and developing economies central banks play a key role in the field of bank regulation. The foremost reason for this seems to be the fact that in less developed countries, central banks often are one of the few credible and reputable institutions with a certain degree of independence. Thus, regulators located inside the central bank are expected to “piggyback” a comparable degree of independence (Arnone, Laurens, Segalotto and Sommer, 2007). Furthermore, there are sufficient financial resources and a greater availability of skilled staff at the central bank. Additionally, developing countries typically face problems in financing the establishment of another agency (see Quintyn and Taylor, 2007b). However, more recently, the balance has tipped in favour of assigning the central bank more responsibilities in bank regulation. The depth and severe consequences of the financial crisis of 2007-09 led to a reconsideration of the financial stability frameworks around the world and the role of central banks in bank regulation, in particular. As the importance of systemic risk and the need for the adoption of a macroprudential approach to bank regulation come to the fore, many commentators see the central bank as the natural candidate to be put in charge of systemic regulation and oversight (see, e.g., Blinder, 2010; Cukierman, 2011). As pointed out by Nier (2009), an expanded regulatory role for central banks may increase the effectiveness of bank regulation since central banks have incentives to reduce the occurrence of systemic crises as the realization of systemic risk incurs substantial costs for central banks. Moreover, the central banks’ expertise in financial infrastructure could prove

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to be useful in crisis management. Caruana (2010) argues that central banks typically are the first public institution to act when a crisis occurs. Furthermore, they already perform two tasks that qualify them for the role as a systemic regulator. Central banks have got the responsibility for the oversight of payment and settlement systems and they are concerned with the analysis of macroeconomic and financial trends as well. In addition, central banks have to take into account that monetary policy decisions affect financial conditions and a regulatory authority other than the central bank might not consider macroeconomic considerations in its decisions. Thus, Blinder (2010) notes that central banks seem to be more in the position of finding the right balance between financial stability considerations and monetary policy objectives than leaving the job to two independent agencies. As such, the often cited conflicts of interest should rather be interpreted as a rational balancing of competing objectives. Summing up, there seems to develop a certain consensus that central banks are suited for the regulation and supervision of systemically important financial institutions. In fact, central banks now are increasingly put in charge of overseeing the financial system as a whole – two recent examples being the creation of the European Systemic Risk Board at the ECB and the Financial Stability Oversight Council in the US (Hannoun, 2010).

6. CONCLUSION In this article, we have argued that the performance of bank regulation could be improved by properly designed government arrangements. Since regulatory authorities exercise important powers with distributional consequences they are subject to pressures from the financial sector as well as political interference. Accordingly, the development of independent and accountable regulatory authorities seems to be of utmost importance. We took the two contrasting approaches to bank regulation as a starting point and learned that sometimes involved interest groups may interact to maximize their ability to extract rents from economic activity. Thus, regulators may give priority to private interests and thus, no improvement in the functioning of the financial system or bank stability may evolve. We proceeded to examine the four essential elements of regulatory governance – independence, accountability, transparency and integrity. These pillars are mutually reinforcing and hold each other in balance.

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Most importantly, we asked the question of whether regulatory governance provides any measurable benefits in terms of financial stability. The empirical evidence surveyed indicates that regulatory governance seems to leadp to better regulatory practices which in turn have a positive impact on financial stability. Nevertheless, more robust evidence for supporting the view that good regulatory governance has positive effects on financial stability is needed since the evidence on the financial stability effects of regulatory governance is far from conclusive. Finally, we touched upon the issue of whether placing bank regulation inside an independent central bank creates a better institutional environment for safeguarding financial stability. Even though there was no consensus prior to the recent financial crisis, there now seems to develop a certain consensus that central banks are best suited for the regulation and supervision of systemically important financial institutions. Yet, the exact design of the corresponding macroprudential toolkit still has to be specified. The financial crisis of 2007-09 has shown that governance failures in the regulation and supervision of the financial sector can contribute significantly to the severity of a crisis. The recent experience has shown that regulatory authorities should be equipped with clear mandates and adequate tools to take early action and deal with unacceptable build-ups in systemic risk. On the positive side, European officials have recently recognized the need for an improvement of the governance arrangements in bank regulation as they note in the De Larosière report (2009) that “the supervisory authority must be empowered and able to make its own independent judgements (…), without authorities or the industry having the right or possibility to intervene. Moreover, the supervisor itself must base its decision on purely objective and non-discriminatory grounds.” However, one should take it as a cautionary note that a recent study by the IMF (Cihák and Tieman, 2008) has shown that most frequent weaknesses in bank regulation are related to the potential for political interference in day-to-day supervision, the lack of budgetary independence, and the need to strengthen the legal protection of supervisors. Thus, there are still considerable gaps in the regulatory frameworks that need to be addressed by policy makers around the world.

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Chapter 2

MORTGAGE AVAILABILITY, QUALIFICATIONS AND RISKS IN IRELAND, 2000-2009 Michelle Norris1 and Dermot Coates2

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1

School of Applied Social Studies, University College Dublin, Belfield, Dublin 4, Republic of Ireland 2 Senior Manager, FGS Partnership, Republic of Ireland

ABSTRACT During the last decade the Republic of Ireland’s underdeveloped, conservative residential mortgage market was radically transformed into a highly developed, flexible sector. This market was traditionally characterized by conservative lending criteria, significant government intervention and the dominance of non-profit providers, but since 2000, the numbers of lenders and the number of mortgage products has expanded radically, repayment terms have become more flexible, commercial banking agencies have come to dominate mortgage provision and the volume of outstanding private mortgage debt has increased fourfold. These developments mirror changes in the mortgage markets of several other European Union member states, particularly the southern countries such as Spain, Greece and Italy, but here we argue that they 1 2

T: +35317168203; E: [email protected] T: +3534086933; E: [email protected]

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Michelle Norris and Dermot Coates were more extreme in Ireland than the EU norm (European Central Bank, 2009). The transformation of Ireland’s mortgage market made a key contribution to the seemingly perpetual upward trajectory of house prices and new housing output, which, in turn, drove rising employment rates and tax revenues. For this reason, public policy did not attempt to dampen the housing and mortgage boom, but rather stoked it via fiscal incentives for housing development and ‘light touch’ regulation of banks and other mortgage providers. However, the housing boom both drove and masked severe risks at a number of levels in the Irish economy and banking system. From 2000, the Irish economy grew less competitive, but because employment and public finances became disproportionately reliant upon the housing market it appeared deceptively healthy. Household mortgage debt increased radically, particularly among younger homeowners, but low interest rates and ready access to credit enabled growing consumption rates and further non-mortgage debt accumulation. Banks were heavily reliant on housing related lending not only via mortgages but also to the construction industry, but profits remained high. Consequently the Irish economy, government, banking system and households were over-exposed to external macroeconomic shocks and thus the global economic downturn in 2008 had a much more severe impact on all three sectors than in most other western European countries and government implemented particularly radical remedies in response. In the mortgage sector, the government guaranteed all bank lending in 2008, nationalized one mortgage lender in 2009 and effectively partnationalized all but one of the other major Irish based lenders in the following year. In addition, the volume of mortgage lending fell rapidly from 2008, as mortgage qualification criteria became stricter and many mortgage products were withdrawn from the market as did some lenders. This chapter sets out the background to this mortgage boom and bust describes, in terms of the historic trends in mortgage lending in Ireland and the country’s recent ‘Celtic Tiger’ economic boom and downturn post-2007. It then outlines trends in mortgage availability, mortgage qualifications and mortgage finance institutions (MFIs) since 2000 and the associated risks. The conclusions examine the lessons regarding appropriate regulatory and policy responses to a mortgage lending boom which arise from the Irish experience.

Keywords: Ireland, mortgages, risks.

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BACKGROUND Compared to many other western European countries the Republic of Ireland is distinguished by historically high rates of home ownership. In 1971, 61 per cent of Irish households were home owners compared to 50 and 35 per cent of their counterparts in Britain and Sweden, respectively (Kemeny, 1981). By 1991 homeownership rates in Ireland had expanded to 80.2 per cent while the proportion of households living in private rented accommodation declined from 10.9 to 7.0 per cent of households between 1971 and 1991, and households accommodated by state subsidized social landlords fell from 15.9 to 9.7 per cent concurrently (Norris and Winston, 2004). In addition to a strong cultural commitment to home ownership, for most of the 20th Century this tenure model was underpinned by extensive government support for home buying, compared to other tenures and a mortgage lending regime dominated by a small number of public and nonprofit sector providers and characterized by conservative lending practices (Murphy, 2004). Until the 1980s, lending to lower income home buyers was dominated by the local government sector, which provided 30 per cent of mortgages by value in the 1970s, while lending to middle to higher income households was dominated building societies. These, state subsidized, nonprofit agencies were legally restricted to the mortgage market and provided around 65 per cent of mortgage loans by value during the 1970s (Fahey, et al, 2004; Murphy, 1994). Insurance companies made up the bulk of the remaining 5 per cent of the market during the 1970s, but did not remain involved in mortgage lending over the long-term. Although local government lenders were characterized by higher loan to value ratios and more flexible qualification criteria, the maximum loans available were strictly constrained by government order at around three times borrowers’ incomes and significantly below average contemporaneous house prices (Baker and O’Brien, 1979). Baker and O’Brien’s (1979: 41) examination of building societies in the 1970s concludes that they ‘tend to set fairly stiff criteria with regard to the size of the deposit required, the minimum income in relation to the size of the loan and the type of property involved... generally it is impossible to get a loan greater than two and a half times income’. In the context of these conservative lending criteria and also low real interest rates for several decades (due to high inflation), the rate of mortgage holding was low and only one third of homeowners had mortgages in the 1970s and growth in private sector credit growth more broadly was very low during this period (Fahey, et al, 2004; Kelly and Everett,

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2004). Direct government support for home ownership, including grants, tax deductibility of mortgage interest and sales of social housing to tenants at below market value and indirect support in the form of lack of property or capital gains taxes on principal private residences, also reduced the need to borrow (O’Connell, 2005). These supports appear particularly generous in view of the relatively modest funding available for other tenures, particularly private renting and also the poor performance of the Irish economy, which stagnated or declined for much of the 20th Century (Kennedy, et al, 1998). An acute fiscal crisis in the early 1980s, generated by a particularly serious and prolonged economic downturn, led to the abolition or scaling back of most of the universalist, direct public supports for home ownership and their replacement with less expensive programmes targeting low income home buyers (Norris, et al, 2007). At the same time a public debt crisis forced local government to radically scale back their involvement in mortgage lending and since then this sector has provided less than two per cent of mortgage loans by value (Norris and Winston, 2004). In order to enable it fill this breach and encourage competition, the commercial mortgage sector was deregulated as part of a wider process of financial liberalization (including: abolition of quantitative restrictions on credit growth; lowering of banks’ reserve requirement ratios; dismantling of capital controls and the removal of all restrictions on interest rates) which mirrored, but lagged developments in the rest of western Europe and more particularly in other English speaking countries (Ball, et al, 1988; Kelly and Everett, 2004). The Building Societies Act (1989) allowed these agencies to operate in the wholesale money market, gave them freedom to develop a wider range of property and financial services and provided for their conversion to public limited status (Murphy, 1994). During the 1990s, three building societies became PLCs and two remain mutualised currently. Commercial banks commenced mortgage lending in the mid-1970s but their involvement in this market remained modest for the next decade. This changed following the withdrawal of fiscal subsidies for building societies and the decline of some of the banks traditional areas of investment, and between 1985 and 1987 their percentage of the mortgage market grew from 8.3 to 36.9 per cent (Murphy, 1995). According to Murphy (1995), this development radically increased competition in the sector and resulted in the introduction of some new mortgage products (such as endowment mortgages), but failed to promote the liberalisation of lending criteria. A minimum deposit of 10 per cent and evidence of a strong savings record remained the norm in the sector.

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From the mid 1990s, Ireland’s economic fortunes changed radically following the arrival of the ‘Celtic Tiger’ economic boom (Honohan and Walsh, 2002). GDP per capita increased from 10 per cent below the EU15 average in 1995, to 35 per cent above in 2007 (see Figure 1) (Eurostat, 2009). Together with sharp falls in taxation, rising employment and other mortgage market related factors discussed below, this contributed to equally dramatic demographic and housing market changes. The population rose by 17 per cent and the number of households expanded by 14 per cent between 1996 and 2006 (Central Statistics Office, 2007a). After a slow start, rates of new house building expanded significantly to meet this demand – to 13 dwellings per 1,000 inhabitants in 2003 compared to an average of 5 per 1,000 in the EU15, but despite this house price inflation remained stubbornly high. It jumped from 8 per cent per annum between 1990 and 1993 to 22 per cent per annum between 1996 and 2002, and continued to rise (albeit at a lower rate) until 2006 (see Figure 2 ) (Norris and Shiels, 2007). Since mid-2007, however, the Irish economy, government finances and housing market have declined even more sharply than in most other western European countries. As Figure 1 demonstrates, GDP per capita grew by 5.3 per cent in 2007, but declined by 4.2 per cent in 2008 and by 7.1 per cent in 2009. The unemployment rate rose from 4.6 per cent in 2007 to 13.1 per cent in the fourth quarter of 2009, and the public balance of payments, which had been positive for most of the 1997-2007 period, fell sharply to -7.1 per cent of GDP in 2008 (Central Statistics Office, various years). This economic downturn has depressed rents and house prices, but the full extent of its impact on the housing market is as yet unclear. The most robust house price data available, presented in Figure 2 indicates that prices nationally fell by 26 per cent between the fourth quarters of 2007 and 2009. However, several commentators have suggested that these data radically underestimate the true extent of price decline (see: Duffy, 2009) due to the relatively low volume of sales recorded over this period.

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Michelle Norris and Dermot Coates

Source: Central Statistics Office (various years).

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Figure 1. Unemployment and GDP in Ireland, 1996-2009.

Source: Permanent TSB/ ESRI (Various Years) and Department of the Environment, Heritage and Local Government (various years). Note: Data on house prices refer to December of the relevant year, with the exception of the data for 2009 which refer to August. Figure 2. House Prices and Housing Output in Ireland, 1996-2009.

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MORTGAGE AVAILABILITY Over the seven years between end-2000 and end-2007, the amount of mortgage credit outstanding in Ireland rose by over 300 per cent (almost €94bn) and from 31.1 to 75.3 per cent of GDP (see Table 1). Although mortgage lending and private sector credit more broadly increased across the European Union and across most developed countries concurrently, the extent of growth in Ireland was particularly strong (Doyle, 2009). The rate of expansion in outstanding mortgage credit in Ireland between 2000 and 2007 was four times that of the 27 current EU members (EU27) (80.3 per cent), and even further above the equivalent rate for the fifteen, mainly western European, longstanding EU members (EU15) (79.2 per cent) and among the latter group, the expansion in Irish mortgage lending was outpaced only by Greece. As a result, in 2007 the Irish mortgage debt to GDP ratio was over one third higher than the EU average of 50.2 per cent (European Mortgage Federation, various years). Table 1 reveals that this dramatic growth was concentrated in the 2002 to 2005 period when mortgage credit outstanding rose by 117 per cent. This growth slowed significantly in 2006 and 2007 and mortgage credit outstanding contracted by 3.8 per cent between December 2008 and September 2009. Therefore, at the close of the decade, total mortgage credit outstanding stood at €110bn. Table 1 also demonstrates that this development was driven both by a rise in the number of mortgages granted and in the size of loans. The number of mortgages granted per annum rose from 57,300 in 2000 to a peak of 111,300 in 2006 before falling back to 53,600 in 2008. However, residential mortgage debt per capita rose even faster concurrently - from €8,620 in 2000 to €33,570 in 2008. Between 2000 and 2007, the total Private Sector Credit (PSC) requirement – that is lending to the private sector by all credit institutions – rose by some 240 per cent. The PSC continued to raise post-2007 and peaked at €404bn in November 2008 before easing back to €378bn in 2010. This development was influenced strongly by the growth in mortgage lending. In 2000, mortgage lending outstanding accounted for 27 per cent of the PSC but this rose to almost 37 per cent in 2004 before easing back to 33 per cent in 2007 and 29 per cent in 2009. Over the entire period, the rise in the outstanding mortgage loans accounted for 35 per cent of this additional PSC.

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Table 1. Key Macro Trends in Mortgage Lending in Ireland, 2000-2009 Year Total Mortgage Credit to Irish Residents

New Mortgages

Private Sector Credit (PSC)

N (000)

% Change

€m

€m

% Change

€000

% Change

2000

29,474

n/a

8.62

n/a

Mortgag e Debt to GDP Ratio (%) 31.1

74.3

n/a

111,207

26.5

Change in Mortgage s as a % of PSC n/a

2001

34,025

15.4

10

16.0

32.8

66.8

-10.1

129,571

26.3

24.8

4.72

79.3

18.7

142,691

30.4

71.6

4.69

Mortgage Debt per Capita

Mortgage s as a % of PSC

Representativ e Interest Rates on new Mortgages 6.17

2002

43,416

27.6

12.11

21.1

36.3

2003

54,614

25.8

14.98

23.7

42.7

84.7

6.8

160,429

34.0

63.1

3.50

2004

73,120

33.9

19.12

27.6

55.2

98.7

16.5

199,595

36.6

47.3

3.47

2005

94,259

28.9

24.08

25.9

61.4

107.6

9.0

258,810

36.4

35.7

3.68

111.3

3.4

317,776

34.8

27.7

4.57

2006

110,602

17.3

29.29

21.6

70.1

2007

123,002

11.2

32.2

9.9

75.3

84.3

-24.3

376,796

32.6

21.0

5.07

2008

114,290

-7.1

33.75

4.8

80.0

53.6

-36.4

395,070

28.9

n/a

5.33

2009

109,917

-3.8

Nav

Nav

Nav

Nav

Nav

371,879

29.6

26.6

Nav

Note: Year refers to position as at December (except 2009; September. N/a means not applicable, Nav means not applicable. Source: Central Bank (various years) and European Mortgage Federation (Various Years)

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The contribution of mortgage lending to the rising PSC is even more striking when examined on an annual basis. In 2000, the volume of total mortgage credit outstanding increased by €4.5bn; this accounted for onequarter of the rise in the PSC over the same period. However, the share of the rise in the PSC attributable to additional mortgage lending rose sharply thereafter. For instance, new mortgage lending accounted for 72 per cent and 63 per cent of the rising PSC in 2002 and 2003, respectively. The decline in interest rates and therefore lower borrowing costs were a key enabling factor in the radical growth in the volume of mortgage lending in Ireland. Table 1 reveals that this decline was significant in nominal terms, but its impact was further magnified by particularly low real interest rates (due to high inflation over the period 1999-2004, the average real interest rate in Ireland was –0.9 per cent) and a historic context of high and also volatile interest rates (Honohan and Leddin, 2006). This fall in nominal interest rates was driven by two factors. First by Ireland’s entry to European Monetary Union in 1999, the adoption of the Euro as her national currency and the resultant transfer of interest rate setting powers from the Irish Central Bank to the European Central Bank and second, by very intense competition in the Irish mortgage market, particularly post-2003. As is explained later in this chapter, this competition was in turn related to a marked increase in the number of mortgage firms serving the Irish market. From 2007, declining competition, rather than an increase in Eurozone interest rates drove a rise in nominal interest rates.

MORTGAGE QUALIFICATIONS Table 2, which details key trends in mortgage qualifications between 2000 and 2009, elucidates some of the drivers of the radical increase in mortgage borrowing during the first half of this decade. This Table demonstrates that residential landlords made a very marked contribution to this development. The proportion of outstanding mortgage lending accounted for by owner occupiers also fell steadily in recent years, from 82 per cent in 2003, to 72.7 per cent in 2007 as a result owner occupation between 2002 and 2006 for the first time in the history of the Irish state, from 79.7 to 77.2 per cent of households (Central Statistics Office, various years). Since the beginning of housing market bust in the latter year, total mortgage lending to this sector has continued to fall, albeit at a much lower rate.

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Lending for second home purchase has remained steady since 2003 at just over one per cent of outstanding mortgages, while lending for buy-to-let properties increased radically during the period under review from 16.7 per cent of outstanding mortgages in 2003 to 26.1 per cent in 2007. Interestingly, total mortgages to this sector have actually increased during the house market collapse to 27.4 per cent of outstanding mortgages in 2009. The proportion of interest only mortgages also increased significantly between 2003 and 2007, and the available evidence indicates that this trend is directly related to the growth in buy-let-mortgages as the vast majority of these mortgages were taken up by investors (Doyle, 2009; Duffy, 2009). These data also confirm that the increase in the number of mortgages drawn down by residential borrowers post-2000 was accompanied by an increase in their size. Mortgages of over €250,000 increased from 2.3 per cent of the total in 2000 to 41 per cent of total in 2006. One hundred per cent mortgages first became available around 2004 and between then and 2008 rose from 4 to 12 percent of all mortgages granted. Furthermore, mortgages with terms of 30 years plus increased from 10 to 39 per cent of mortgages drawn down during this period in contrast to the historic norm of 20 year long mortgage repayment terms (Department of the Environment, Heritage and Local Government, various years; Doyle 2009). The data presented in Table 2 indicates that these trends have reacted slowly to the post-2007 correction in house prices. The proportion of mortgages of €250,000 + increased from 37 to 41 per cent of mortgages granted between 2006 and 2007 and remained at the latter level in 2008, 100 per cent loans fell from 14 to 10 per cent of mortgages granted between 2006 and 2007, but rose again to 12 per cent in 2008 and mortgages with a term of > 30 years increased from 31 per cent of loans granted in 2006 to 39 per cent in 2008. However the available evidence indicates that these trends are likely to change in the near future. Following the housing market correction from 2007, banks began to remove their interest only mortgage and 100 per cent mortgage products from the market (Doyle, 2009).

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Table 2. Key Micro Trends in Mortgage Lending in Ireland, 2000-2009

Type of Residence (%)1

Interest Rates

Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Variable (%)1 68.9 71.6 76.3 80.6 82.8 84.6 81.7 75.3 80.0 86.3

Fixed (%)1 31.1 28.4 23.7 19.4 17.2 15.4 18.3 24.7 20.0 13.7

Principal Private Nav Nav Nav 82.0 80.0 77.4 73.7 72.7 71.9 71.4

Buy-toLet Nav Nav Nav 16.7 18.8 21.5 25.1 26.1 26.9 27.4

Holiday/ second Nav Nav Nav 1.3 1.1 1.1 1.2 1.1 1.2 1.2

Type of Mortgage Loan (%)2 Term of > 30 years 100% > €250,000 loans 2.3 Nav Nav 4.6 Nav Nav 5.9 Nav Nav 9.1 Nav Nav 18.0 4.0 10.0 27.0 7.0 23.0 37.0 14.0 31.0 41.0 10.0 35.0 41.0 12.0 39.0 Nav Nav Nav

Interest only 2.4 2.1 2.7 3.3 5.7 8.4 12.6 Nav Nav Nav

Note: Year refers to position as at December. 1: refers to outstanding residential mortgage lending. 2: refers to new mortgages granted. Source: Central Bank (various years) and Department of the Environment, Heritage and Local Government (various years).

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Despite the radical rise in the total mortgage credit borrowed by Irish households the proportion of Irish homeowners with mortgages actually fell from 62.9 per cent in 2000 to 46.2 per cent in 2007, which indicates that the radical increase in mortgage debt between these years was concentrated among a minority of households (Norris and Winston, 2009). Detailed analysis of the data presented in Table 2 indicates that very large mortgages are overwhelmingly concentrated among recent first-time buyer households based in Dublin – Ireland’s capital and largest city. In 2006, 74 per cent of this group drew down mortgages of over €250,000, compared to 38 per cent of first time buyers in the country as a whole and in the same year 64 per cent of repeat home buyers and property investors in Dublin also borrowed on this scale. Also in 2006, 31 per cent of first time buyers in Dublin took on 100 per cent mortgages, compared to 34 per cent of first time buyers in the country at large and just 5 per cent of repeat buyers/ investors in Dublin. In the same year, 70 per cent of mortgages drawn down by first time buyers in Dublin had terms of over 30 years, compared to 20 per cent of loans granted to repeat buyers/ investors in this city and 60 per cent of those granted to first time buyers in the country as a whole (Department of the Environment, Heritage and Local Government, various years). Table 2 also highlights a marked change in the types of mortgages which have been drawn down by Irish borrowers since 2000. For instance, fixed rate mortgages accounted for almost one in three loans in 2000, this had fallen back to less than 15 per cent by 2010. This situation, which contrasts with the norm in several EU15 countries (Belgium France, Germany and the Netherlands) and also in the United States, reflects the significant variance in the rate of take-up of fixed compared to variable rate mortgages as the decade progressed (European Central Bank, 2009). Whilst outstanding credit under the latter expanded by 360 per cent over these 10 years, the equivalent rate for the former was just 78 per cent (Central Bank, various years). This was in turn driven by a particularly large spread between fixed and variable rate mortgages during this period, as the latter were significantly more expensive than the new variable, ‘tracker’ mortgages (pegged to a premium above the European Central Bank (ECB) refinancing rate) which first became available around 2003 (Doyle, 2009). Recent research by O’Donnell and Keeney (2009) reveals that the interest rate is the principal determinant of Irish borrowers choice of mortgage product. In addition, the decline in fixed rate mortgages also reflects the unusually short fixation period generally available to Irish mortgage holders, of two or three years, which means that the majority of loans revert to the variable rate quite quickly (Doyle, 2009).

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There is some evidence that the popularity of variable mortgages in Ireland may decline as a result of the housing bust and financial crisis. Doyle (2009: 81) reports:

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Following the inception of the financial turmoil in August, 2007, banks began removing tracker mortgages from their product range… By April 2009 the tracker mortgage had effectively disappeared for new borrowers… In addition banks have introduced more fixed rate products and reduced the number of variable rate products. Some institutions have introduced 10-year fixed rate products.

According to her calculations the number of fixed rate products available on the Irish mortgage market increased from 71 to 82 between 2006 and 2009, while the number of variable rate products fell from 78 to 45 currently. However, despite this the Irish mortgage market remains overwhelmingly dominated by variable rate mortgages and the international research evidence indicates that the prevalence of mortgages of this type and of large borrowings greatly increases the risks to borrowers associated with interest rate fluctuations (eg. Borio, 1995). The extent of these risks are underscored by data on take-up of mortgage interest supplement – the principal, means tested government support for unemployed home owners, which subsidises the interest portion of their mortgages. Take-up of this benefit has increased significantly since the Irish economy moved into recession in 2008. It grew from 3,318 households in 2004 to 8,091 in 2008, and data for the latter year indicates that claimants are strongly concentrated in Dublin (28 per cent of claimants) and among the 2549 year age group (78.9 per cent of claimants) (Department of Social and Family Affairs, various years). To date however the recent increase in take-up of mortgage interest supplement and in unemployment does not yet seem to have translated into very widespread repossessions of dwellings, although repossessions have risen. Data from the Courts Information Service (various years) indicates that court cases for the possession of lands/ dwellings/premises (disaggregated data are not available) rose from 140 in 2004 to 490 in the first half of 2009. Industry sources indicate that this relatively low level of repossessions is the result of short-term factors – specifically a 12 month moratorium on repossession of dwellings on the part of the major Irish banks which was agreed as part of the government recapitalization of these institutions which is discussed below (Duffy, 2008). Repossession rates are likely to rise after the moratorium expires and also if, as

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expected, Eurozone interest rates rise from their current historic low (Duffy, 2008).

MORTGAGE FINANCE INSTITUTIONS

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Over the decade covered by this review, the number of credit institutions operating in the Irish mortgage market has increased significantly. In 2000, 12 banks were registered with the Central Bank as mortgage lenders, but by 2010 this number of lenders had risen to 17 (Central Bank, various years). The drivers of this development were threefold: the propensity for the major domestic mortgage lenders to spin-off specialist mortgage lenders - Bank of Ireland and Allied Irish Bank (AIB) respectively launched Bank of Ireland Mortgage Bank in 2006 and AIB Mortgage Bank in 2008; the entry of Anglo Irish Bank - an established domestic bank – into the mortgage lending market for the first time, and the entry of a number of number of foreign lenders into the Irish residential mortgage market, such as Bank of Scotland and Danske Bank A/S, which established Irish subsidiaries for this purpose in 2004 and 2008, respectively. In 2007, these foreign lenders accounted for approximately 30 per cent of mortgage loans advanced in Ireland (European Central Bank, 2009). Mortgage lenders registered with the central bank accounted for 99 per cent of mortgage lending by value in 2007 (Doyle, 2009). The remainder is accounted for by lending by local authorities and also four sub-prime lenders (Start, GE Money, Nua Homeloans and Stepstone) which entered the Irish market between 2004 and 2007 (Coates, 2008). Although the radical increase in the volume of mortgage lending, described above, was already an established trend prior to this expansion in the number of lenders, the increased competition reinforced this trend by driving the financial product innovation highlighted in the previous section. For instance, the number of interest only mortgage products on the market increased radically from 2004, which obviously contributed to the growth in take up of these mortgages, 100 per cent mortgages first became available at this time as did mortgage equity withdrawal products and by 2007, these

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accounted for 10 per cent of new mortgages issued (Hogan and O’Sullivan, 2007; Doyle, 2009). In addition increased competition led to marked reductions in the margins charged by Irish lenders on their mortgages compared to both the western European norm and the margins charged on other bank products (McElligott, 2007). An initial round of cuts in these margins was sparked by the entry of Bank of Scotland into the mortgage market. It had bought an Irish bank (ICC) in 2001, commenced mortgage lending in 2004, and charged significantly lower margins than other lenders. These low margins were copper fastened by the arrival of tracker mortgages which, as mentioned above, were generally fixed at a very low margin above ECB refinancing rates. Tracker mortgages are estimated to account for approximately 60 per cent of the outstanding variable rate mortgage stock (Doyle, 2009). Concurrent with this institutional change in the mortgage market, the sources employed by lenders to fund mortgage lending changed significantly, which in tandem with the marked increase in mortgage lending and other property related loans had significant implications for their aggregate balance sheet position. The key features of these developments are sketched in Tables 3 and 4 below. Traditionally, retail deposits by households and private institutions were the principal funding source for Irish mortgage lenders, Table 3 demonstrates that in 2000 they accounted for 50.2 per cent of funding. Although total retail deposits in Irish mortgage lenders grew by 76.2 per cent between 2003 and 2007, lending expanded faster resulting in a funding gap which was filled by borrowing from the wholesale money markets via interbank lending and debt securities. Reliance on these two funding sources grew from 30.2 per cent in 2000 to 55.8 per cent in 2007 (see Table 3). The European Central Bank (2009) reports that a similar funding gap emerged in all Eurozone countries, with the exception of Germany between 1999 and 2007, but this gap was largest in countries such as Spain, Ireland, the Netherlands and Portugal which experienced the greatest expansion in mortgage lending during this period.

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Table 3. Aggregate Balance Sheet of Irish Mortgage Lenders, 2000-2009

Liabilities

2000 %

2001 %

2002 %

2003 %

2004 %

2005 %

2006 %

2007 %

2008 %

2009 %

Capital and reserves

10.6

10.3

9.0

7.4

6.5

6.2

5.7

5.7

4.9

6.6

Inter-bank lending Government and Central Bank deposits

27.4 3.5

25.9 3.8

27.1 3.2

28.5 4.4

34.5 3.6

35.7 3.7

36.4 2.8

39.2 4.1

44.9 7.6

43.4 7.4

Deposits from the private sector

50.2

50.1

48.8

45.5

38.7

37.0

32.1

29.2

26.0

25.9

Debt securities

2.8

4.5

5.4

8.2

11.5

12.5

17.1

16.6

11.7

12.1

Additional liabilities

5.5

5.3

6.4

5.9

5.1

4.9

6.0

5.2

4.9

4.6

Source: Central Bank (Various Years). Note: These data refer to mortgage lenders registered with the Central Bank only and do not include local authorities or sub-prime lending agencies.

.

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Table 4. Real Estate Related Lending by Irish Credit Institutions, 2000-2009

Real Estate Related Lending Construction Real Estate activities

Households

Year

€m

€m

€m

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

3,630 4,269 4,497 6,075 9,547 14,000 25,137 25,980 22,164 15,042

7,697 10,077 12,897 18,259 25,015 39,582 90,840 79,839 89,748 87,280

30,048 34,705 44,120 55,189 73,636 94,887 111,963 124,226 115,108 110,581

Source: Central Bank (Various Years). Note: These data refer to resident non-government credit only. Year refers to position as at December.

Real Estate Related Lending as % of Total Lending 37.4 38.0 43.3 49.7 54.4 57.5 72.0 61.3 58.0 57.8

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Table 4 demonstrates that the vulnerability caused by this funding gap was reinforced by the over exposure of the banks to the real estate sector of the economy, including not only mortgage lending, but also loans for property development and real estate acquisition. In 2000, real estate related lending by all Irish banks totaled €41.375m (or 37.4 per cent of total lending). Lending to this sector increased steadily as the decade progressed to a high of 72 per cent of total lending (€111.963m) in 2006 at the height of the house price boom. Lending to this sector rose slightly in absolute terms in the following year, but declined as a proportion of all lending, and in 2008 and 2009 real estaterelated lending declined in both absolute and relative terms. A Central Bank financial stability report published in 2006 raised concerns that the ‘Share of the banking sector’s loan book in property related lending continues to grow and is high by historic standards’ (Kearns and Woods, 2006: 133). The fact that in five of the thirteen credit institutions surveyed over 80 per cent of the loan book related to real estate in 2005 was emphasized in particular. Furthermore, some institutions were over exposed to particular sectors of the property market at this time – the reports highlights three banks in which over 90 per cent of property-related lending is in residential mortgages and a small number of institutions in which commercial property accounts for more than 50 per cent of real estate-related loans (Kearns and Woods, 2006). By late-2008, these concerns were borne out after financial institutions were unable to raise money on international markets in the wake of the collapse of Lehman Brothers in the United States. In response, the Irish government introduced a number of measures to stabilise the banking sector. These initiatives commenced when on the 28th of September, it put in place a guarantee agreement to safeguard the full value of all deposits, covered bonds and senior debt and some categories of subordinated debt in all Irish, headquartered banks and their subsidiaries. Since then, the scope of the guarantee was extended to include the Irish operations of a number of foreign banks and its duration was also extended. It is currently due to lapse in September 2010 (Department of Finance, 2008). On the 14th of December 2008, the government announced the initiation of a recapitalization programme for all Irish headquartered banks which would be implemented via the purchase of shares and as part of which banks were required to abide to the moratorium on the repossession of primary residences mentioned above (National Treasury Management Agency, 2008). Early the following year, the government announced that the recapitalization programme was inadequate to stabilize Anglo Irish Bank, which had specialized in lending for property

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development, so this institution was fully nationalized (National Treasury Management Agency, 2009). Also in 2009 the government passed legislation to establish the National Asset Management Agency (NAMA) – a government agency tasked with acquiring ‘toxic assets’; the vast majority of the property development-related loan books (including all loans of €5m and above, which collectively total €81 billion) from five of the six Irish banks (Daly, 2010). These were acquired at a discount, calculated on the current market value of the underlying loans (and taking cognizance of expected long-term values) and in return, these institutions were issued with government bonds senior and subordinated bonds. The purpose of this initiative is to augment the wider recapitalization programme as the government bonds can be used as security to enable the banks raise loans from the European Central Bank and the market. According to its Chairman, ‘NAMA’s core commercial objective will be to recover for the taxpayer whatever it has paid for the loans in addition to whatever it has invested to enhance property assets underlying those loans’ (Daly, 2009: 2). In order to achieve this, borrowers will be liable for the repayment of the full value of their loans and the associated assets will be sold to the market over an extended period, currently estimated to be in the region of a decade.

CONCLUSION This chapter has sketched the autonomy of the boom and subsequent bust in mortgage lending in Ireland between 2000 and 2009. During the first half of this period, the extent of the growth in lending and the development of new mortgage products and new markets such as the buy-to-let investors was even stronger in Ireland than in other western European countries (European Central Bank, 2009). This was driven by intense competition created by expansion in the number of MFIs operating in the Irish market and facilitated by the availability of new funding sources such as inter-bank lending and debt securities. This lending boom in turn drove unprecedented house price inflation and a construction boom, which skewed both employment and government revenues. Between 2000 and 2007, construction employment grew from ten to fourteen per cent of the workforce, compared to an average of between five and seven per cent in other advanced economies in the latter year. The share of capital taxes and stamp duties (dwelling sales tax) in total tax revenue grew from eight per cent in 2000 to sixteen per cent in 2006

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(O’Leary, 2010). Consequently, when the international credit crunch commenced in 2008 it had particularly severe repercussions not only for Irish banks, but also for the Irish government and households, as all sectors were over exposed to property lending. The key policy lessons arising from the Irish mortgage boom and bust are threefold. Firstly they relate to the importance of retaining fiscal policy levers to control property price booms. When Ireland acceded to economic and monetary union in 1999, national government lost control of interest rates – traditionally the key mechanism to curtail house price booms. But Ireland, and many other Eurozone countries failed to counter the loss of this policy instrument by introducing any alternatives (Honohan and Leddin 2006). Notably Ireland lacks the most obvious fiscal instrument for controlling house price inflation - residential property taxes, which were abolished for the majority of dwellings in 1977. Second, they relate to the dangers for good economic governance which are inherent in windfall revenues from a property boom such as that experienced in Ireland. In the Irish case the short term nature of these ‘transactional’ revenues was not factored into policy decisions and when this income dried up it precipitated a severe fiscal crisis. Furthermore reliance on these windfall revenues encouraged government to introduce pro-cyclical policies such as tax incentives for new housing and commercial property development which were radically expanded in the late 1990s (Goodbody Economic Consultants, 2005). Notably, despite the obvious nature of these dangers (at least in retrospect) the sustainability of tax revenue is not factored into European Union arrangements for the surveillance of Eurozone economies under the Stability and Growth Pact which governs such matters (O’Leary, 2010). Third they relate to the regulation and governance of the mortgage industry. Ireland’s arrangements in this regard were significantly reformed in 2003, when the Central Bank of Ireland was replaced by a new integrated Central Bank and Financial Services Regulatory Authority of Ireland (CBFSRAI). This arrangement attempted to align a non-supervising central bank with a new Financial Regulator within a combined framework with oversight provided by a single board. In effect, Ireland had adopted a half-way house between, on the one hand, a regulatory model comprising of a nonsupervising central bank alongside a separate unified financial regulator (for instance the Bank of England and the separate Financial Services Authority in the UK) versus a model which retained banking supervision within the ambit

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of the central bank (see the Federal Reserve in the US) (Regling and Watson, 2010). One of the two recent reviews of banking crisis commissioned by the Irish government concluded that this structure was the result of a policy compromise which sought to deliver stronger banking competition and more high-profile consumer protection and which ultimately undermined the credibility of the new organisation and failed to encourage a sufficient focus on macorprudential risk (Regling and Watson, 2010). In tandem with the establishment of the CBFSRAI, Ireland, like many other western countries, adopted a light-touch supervisory regime based upon a ‘principles-based’ approach which de-emphasised the importance of specific rules and emphasized the importance of key principles of operation, derived from market risk assessment. However the second government commissioned review of Ireland’s banking crisis links regulatory failings not principally to the use of this principles-based approach (although it is criticized) but rather to the manner of its implementation (Honohan, 2010). Thus Honohan (2010: 8) concludes: The style of supervision adopted did not generate the most relevant or useful information to anything near the extent required. By relying excessively on a regulatory philosophy emphasising process over outcomes, supervisory practice focused on verifying governance and risk management models rather than attempting an independent assessment of risk, whether on a line-by-line or whole-of-institution basis. This approach involved a degree of complacency about the likely performance of well-governed banks that proved unwarranted. It was not just a question of emphasising principles over rules, it was the degree of trust that well-governed banks could be relied upon to remain safe and sound.

REFERENCES Ball, M, Harloe, M and Martens, M (1988), Housing and social change in Europe and the USA, London: Routledge. Baker, T and O’Brien, J (1979), The Irish Housing System a Critical Overview, Dublin: Economic and Social Research Institute. Borio, C (1995), The structure of credit to the non-government sector and the transmission mechanism of monetary policy: a cross-country comparison, Basel: Bank for International Settlements Working Paper no 24. Central Bank (various years), Quarterly Review, Dublin: Central Bank.

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Central Statistics Office (2007a), Census 2006: Principal Demographic Results, Dublin: Stationery Office. Central Statistics Office, (various years), Measuring Ireland’s Progress, Dublin: Stationery Office. Coates, D (2008), ‘The Irish sub-prime residential mortgage sector: international lessons for an emerging market’, Journal of Housing and the Built Environment, 23(2):131–144. Courts Information Service (various years), Courts Service Annual Reports, Dublin: Courts Information Service. Department of Finance (2008), Credit Institutions (Financial Support )Scheme, 2008: Market Notice – Confirmation of Statutory Guarantee, Dublin: Department of Finance. Department of the Environment, Heritage and Local Government (various years), Annual Housing Statistics Bulletin, Dublin: Department of the Environment, Heritage and Local Government. Daly, F (2010), ‘NAMA – the objectives, progress and challenges’, unpublished paper presented to the to the CPA Annual Conference, Dublin, 4th of June. Doyle, N (2009), ‘Housing Finance Developments in Ireland’, in Central Bank, Quarterly Bulletin, 09(04): 75-88. Duffy, D (2009), Negative Equity in the Irish Housing Market, Dublin: Economic and Social Research Institute Working Paper No 319. European Central Bank (2009), Housing Finance in the Euro Area, Frankfurt: European Central Bank, Occasional Paper Number 101. European Mortgage Federation (Various Years), Hypostat, Brussels: European Mortgage Federation. Fahey, T., Nolan, B. and Mâitre, B. (2004) Housing, Poverty and Wealth in Ireland. Dublin: Institute of Public Administration. Goodbody Economic Consultants (2005), Review of Area-based Tax Incentive Renewal Schemes, Dublin: Goodbody Economic Consultants. Hogan, V. and O’Sullivan, P (2007), Consumption and House Prices in Ireland, in Economic and Social Research Institute, Quarterly Economic Commentary, 2007(3): 46-61. Honohan, P (2010), The Irish Banking Crisis - Regulatory and Financial Stability Policy, 2003-2008. A Report to the Minister for Finance by the Governor of the Central Bank, Dublin: CBFSAI Honohan, P and Leddin, A (2006), ‘Ireland in EMU: More Shocks, Less Insulation?’, Economic and Social Review, 37(2): 263-294.

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Kearns, A and Woods, M (2006), ‘The Concentration in Property-Related Lending – a Financial Stability Perspective’, in, Central Bank, Financial Stability Report, 2006, Dublin: Central Bank. Kelly, J and Everett, M (2004), ‘Financial Liberalisation and Economic Growth in Ireland’, in Central Bank, Quarterly Bulletin, 04(03): 91-112. Kemeny, J (1981), The Myth of Home Ownership: Private Versus Public Choices in Housing Tenure, London: Routledge. Kennedy, K, Giblin, T and McHugh, D (1988), The Economic Development of Ireland in the Twentieth Century, London: Routledge. National Treasury Management Agency (2008), Government Announcement on Recapitalisation, 21st of December, 2008, Dublin: NTMA, unpublished press release. National Treasury Management Agency (2009), Minister’s Statement regarding Anglo Irish Bank, 2008, Dublin: NTMA, unpublished press release. Norris, M and Winston, N (2004), Housing Policy Review: 1990-2002, Dublin: Stationery Office. Norris, M, Coates, D and Kane, F (2007) 'Breaching the Limits of Owner Occupation? Supporting Low-Income Buyers in the Inflated Irish Housing Market'. European Journal of Housing Policy, 7 (3):337-356. Norris, M and Winston, N (2009) ‘Housing Wealth, Debt and Stress Before, During and After the Celtic Tiger’ paper presented to conference on Housing Markets and the Global Financial Crisis; The Uneven Impact on Households City University Hong Kong, 8th-9th of December. McElligott, R (2007), ‘Irish Retail Interest Rates: Why do they differ from the rest of Europe?’, in Central Bank, Quarterly Bulletin, 07(01): 137-252. Murphy, L (1994), ‘The Downside of Home Ownership: housing change and mortgage arrears in the Republic of Ireland’, Housing Studies, 9(2): 183198. Murphy, L (2004), ‘Mortgage Finance and Housing Provision in Ireland, 1970- 90’, Urban Studies, 32(1): 135-154. O’Connell, C (2005), ‘The Housing Market and Owner Occupation in Ireland’, in Norris, M and Redmond, R (eds), Housing Contemporary Ireland: Policy, Society and Shelter, Dublin: Institute of Public Administration, pp. 21-43. O’Donnell, N. and Keeney, M (2009), Financial Capability: New Evidence for Ireland. Dublin: Central Bank, Research Technical Paper1/RT/09

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O’Leary, J (2010), External Surveillance of Irish Fiscal Policy During the Boom, Maynooth: NUI Maynooth, Accounting Working Ppaers Series, N210-10 Permanent TSB/ ESRI (various years), Permanent TSB/ ESRI House Price Index, Dublin: Economic and Social Research Institute. Regling, K and Watson, M (2010), A Preliminary Report on The Sources of Ireland’s Banking Crisis, Dublin: Stationery Office.

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Chapter 3

HOME EQUITY CONVERSION MORTGAGES: A PRODUCT FOR AN EMERGING DEMOGRAPHIC Martin Seay and Andrew Carswell

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1

Doctoral Candidate at the University of Georgia’s Department of Housing and Consumer Economics, Athens, Georgia, U.S.A. 2 Associate Professor at the University of Georgia’s Department of Housing and Consumer Economics, Athens, Georgia, U.S.A.

ABSTRACT Elderly households increasingly have a significant portion of their wealth tied to their home. As a result, the ability of these individuals to remain financially independent over time while also retaining homeownership is limited. The Home Equity Conversion Mortgage (HECM) program was created in 1987 to help individuals in this situation. HECMs, the most popular version of a reverse mortgage, are ideal products for individuals with high housing equity but with limited non-housing assets. Only available to homeowners age 62 and older, a HECM provides for the use of home equity as collateral in the creation of a loan with repayment deferred until the owner dies, the home is sold, or the home is no longer the owner’s primary residence. HECMs allow access to home equity, while still allowing elderly individuals to maintain residence in their home and, unlike similar mortgage products, have no income requirements or credit qualifications. After limited demand in the

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Martin Seay and Andrew Carswell early years, high levels of homeownership combined with limited nonhousing savings have provided for the dramatic expansion of the HECM market over the last decade. The arrival of the Baby Boomers into the retirement years looks to continue this growth into the foreseeable future. This chapter provides an overview of the HECM program, a review of its expansion over the years, and its potential growth in the future.

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INTRODUCTION The prevalence of the dream of homeownership in America has led to a society where many households have a significant portion of their wealth tied to their home. This trend is increasingly more common in elderly households (Apgar & Di, 2005). According to the 2007 Survey of Consumer Finances, an estimated 15.6 million households were headed by an individual age 62 or older with home equity greater than or equal to 95% of their home values. For an estimated 4.8 million of these households, home values represented more than 75% of their net worth. With less than a quarter of their net worth in nonhousing assets, the ability of these individuals to remain financially independent over time while also retaining homeownership is limited. A study conducted in 2000 by the American Association of Retired Persons indicated that 90% of individuals age 65 and older preferred to remain living in their homes, indicating that the sale of the home is not desirable (Bayer & Harper, 2000). The Home Equity Conversion Mortgage (HECM) program was created in 1987 to help individuals in this situation. Authorized by Congress and administered by the U.S. Department of Housing and Urban Development, HECMs are by far the most popular version of a reverse mortgage (Shan, 2009). HECMs, and reverse mortgages in general, are ideal products for individuals with high housing equity but with limited liquid assets. Only available to homeowners age 62 or older, a HECM provides for the use of home equity as collateral in the creation of a loan. Similar to a Home Equity Line of Credit (HELOC), the homeowner is permitted to borrow against this equity. The distinguishing factor is that the homeowner's obligation to repay a HECM loan is deferred until the owner dies, the home is sold, or the home is no longer the owner’s primary residence. This delayed repayment acts to mitigate any obligations or restrictions resulting from the loan that might compel individuals to sell their homes to satisfy loan obligations. After the

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recent economic issues, HECMs currently represent nearly 100% of all reverse mortgages on the market (Shan, 2009). The aging of the Baby Boom generation provides for a significant expansion of the market for reverse mortgages. According to the 2007 Survey of Consumer Finances, an estimated 7.3 million households were headed by an individual age 54 to 65 with home equity greater than or equal to 90% of their home values. For an estimated 2.1 million of these households, home values represented more than 75% of their net worth. This age group in large part reflects individuals who have not yet retired, or have done so only recently. The use of non-housing assets to cover living expenses in retirement has yet to take its toll, indicating that a significant number of households will face liquidity issues over time. The importance of reverse mortgages for Americans moving forward appears to be significant.

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THE HECM PROGRAM Typical mortgage products provide for a loan to be used to purchase a home. The borrower receives a lump-sum payment up front and agrees to a repayment plan spanning a finite time period. The home acts as collateral for the loan, and if payments are not met, the lender can assume ownership. The initial equity requirements for the borrower are limited, with loans in recent years being offered with no down payment. Over the period of the loan, the borrower’s equity in the home increases as the loan principal is paid off. These products act as a gateway to homeownership, allowing borrowers to purchase homes that they otherwise would not have been able to afford. In many ways, HECMs are the opposite of traditional mortgages. With a HECM, a lender provides access to home equity through a lump-sum payment, an annuity stream, a line of credit, or some combination of the three. In return for these payments, the lender gains equity in the home. As opposed to a traditional mortgage, the flow of money during the life of the mortgage is in the direction of the homeowner. The homeowner's obligation to repay is deferred until the owner dies, the home is sold, or the home is no longer the owner’s primary residence. Similar to traditional mortgages, the home acts as collateral; however, the homeowner’s liability extends only to the value of the home, and the homeowner is not responsible for loan amounts in excess of this value. Conversely, the homeowner will keep any additional equity if the home value is larger than the loan amount.

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Three basic requirements must be met for an individual to qualify for a HECM: a homeowner must be age 62 or older, must have fully paid off their homes or be able to repay outstanding debt with the proceeds of the HECM, and must claim the home as their primary residence. In addition to homeowner requirements, only certain types of property are eligible. Property must fall into one of the following categories: a single family home, a 1-4 unit home with one unit occupied by the borrower, a HUD-approved condominium, or an FHA qualified manufactured home or residence within a Planned Unit Development. Also, homeowners must receive counseling from a HUDapproved counselor. Counselors work for independent agencies to avoid conflicting interests and seek to clarify the legal and financial implications of a HECM. Unlike traditional mortgages, there are no credit qualifications for a HECM, although a credit check is performed to ensure the homeowner has no other liens on the home or any outstanding debts to the federal government (Stevens, 2009a).

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HECM Structure The amount available to a homeowner through a HECM is dependent upon several factors and is computed through a three-step process. First, the Maximum Claim Amount (MCA) is determined. It is equal to the lesser of the fair-market value of the home or a nationwide ceiling that adjusts annually with inflation. The 2010 nationwide ceiling for the MCA is $625,500, with a higher limit of $729,750 for designated high-cost areas (Stevens, 2009b). The MCA is set to be the maximum balance for the loan at termination. The next step is to determine the Initial Principal Limit (IPL). The IPL is the amount of money that, if assumptions hold, will grow to be the MCA at the expected loan termination. The Principal Limit Factor (PLF) is derived from the age of the borrower and the interest rate at the time of closing. This factor, which ranges from zero to one, is multiplied by the MCA to yield its present value, the IPL. The PLF is positively correlated with homeowner age and negatively correlated with interest rates (Szymanoski, 1994). Table 1 provides an example of how PLF changes given varying borrower ages and interest rates. Finally, the Net Principal Limit (NPL) is determined. The NPL is simply the IPL reduced for upfront costs and an amount set aside for a monthly servicing fee. Fees can range from about $6,000 for a $100,000 home to over $16,000 for a $400,000 home (National Council on Aging, 2009). The NPL represents the initial loan amount that a homeowner can borrow.

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Table 1. Principal Limit Factors Based on Borrower Age and Expected Interest Rate

62 67 72 77 82 87

4% 0.562 0.598 0.635 0.675 0.714 0.752

6% 0.507 0.549 0.593 0.639 0.685 0.729

8% 0.333 0.386 0.444 0.509 0.576 0.643

10% 0.222 0.272 0.333 0.403 0.481 0.561

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Source: Table constructed from data provided by U.S. Department of Housing and Urban Development (2010a).

HECM loans are available with both fixed and adjustable interest rates. The interest rates for adjustable rate HECMs are based on either the London Inter-Bank Offered Rate (LIBOR) or the 1- Year U.S. Treasury Constant Maturity Rate (CMT) and can take on several different forms. For example, both monthly and annually adjusting interest rate HECMs are available based on the CMT. The interest rate for the monthly adjustable option is equal to the current CMT rate plus a margin of 1.5%, with a lifetime adjustment cap of 10%. The interest rate for the annually adjustable option is equal to the current CMT rate plus a margin of 2.1%. Changes to the annual interest rate are limited to 2% per year with a 5% lifetime adjustment cap. There are several fees that must be taken into account when a homeowner is considering a HECM. The largest single cost incurred by a HECM is the origination fee, which is bounded by the Housing and Economic Recovery Act of 2008. The act limits origination fees to the greater of $2,500 or 2% of the first $200,000 of the MCA plus 1% of any amounts over $200,000, with a maximum fee of $6,000. For example, the origination fee for a loan with a MCA of $300,000 would be capped at $5,000. In addition to this, common fees include a monthly servicing fee, home appraisal fees, title insurance and escrow fees, county taxes and recording fees, inspections/certifications, credit check, flood certification, property taxes, and homeowner’s insurance (U.S. Department of Housing and Urban Development, 2009). The majority of these can be paid for out of the body of the loan, limiting out-of-pocket expenses. FHA insurance premiums represent a significant additional cost to homeowners. FHA insurance provides coverage to both the lender and the borrower. As with all annuity products, the borrower faces the risk of lender default if the contract holder is unable to make scheduled payments. FHA

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insurance removes this risk by providing for the continuation of payments in the case of lender default. Additionally the lender faces crossover risk, which is the risk that the loan value will become greater than the home value. In this situation where the collateral value of the home is less than the loan value, the lender faces certain losses upon the repayment of the loan. This risk is mitigated by FHA insurance, which provides for the assignment of mortgages whose loan balances rise to 98% of the MCA to HUD. Premiums are collected through a one-time upfront payment and recurring monthly payments. The upfront payment is equal to 2% of the MCA, and the monthly premiums annualize to equal .5% of the current mortgage balance. These premiums are financed into the loan balance and do not require any out-of-pocket expenses.

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Payout Options The homeowner has the choice of five different methods to receive the proceeds of a HECM loan. By far the most popular payout option, representing 87% of all HECM loans originated in 2007, is the Line of Credit plan (Bishop & Shan, 2008). This option provides for the creation of a line of credit similar to that of a HELOC. The homeowner is able to take disbursements at times and in amounts of their choosing. In addition to being the most flexible of the payment plans, it provides immediate access to the largest sum of money possible. In contrast to the Line of Credit plan, both the Tenure and Term plans provide for no initial payment. The option most often associated with reverse mortgages is the Tenure plan. With this option, an annuity is created to provide a stream of equal monthly payments for the duration of the loan. This option provides the greatest hedge against longevity risk, as the payments will continue until death, assuming residency in the home is maintained. Similarly, the Term plan provides for the creation of an annuity, but only for a fixed period. The homeowner determines the length of these payments and, due to the restricted number of payments, will typically receive larger amounts each time. Although the payments will end at a specified time, repayment is still deferred until death, the sale of the home, or such time that the home is no longer the primary residence. The last two options are a combination of the Line of Credit plan and one of the two annuity plans. The Modified Tenure provides for a guaranteed stream of equal payments for the duration of the loan with the flexibility of a line of credit portion. A portion of the loan amount is used to fund the annuity,

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with the remainder available as a line of credit. The Modified Term similarly provides for the combination of the annuity and line of credit options, with the limitation that the annuity ends after a set period of time. It is important to note that the homeowner may elect to alter his or her payment option during the course of the loan with minor additional costs. Table 2 provides an example of payout amounts for the Tenure and Line of Credit plan given varying borrower ages and home values. Table 2. HECM Payouts Options Based on Borrower Age and Home Value

Borrower Age 62

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67 72 77 82 87

$200,000 Tenure Line of Credit $491 $79,943

$400,000 Tenure Line of Credit $1,033 $168,083

$600,000 Tenure Line of Credit $1,587 $258,223

$569 $668 $800 $996 $1,326

$1,190 $1,388 $1,655 $2,049 $2,715

$1,823 $2,122 $2,524 $3,119 $4,125

$89,317 $99,361 $109,903 $120,785 $130,862

$186,657 $206,501 $227,243 $248,525 $268,002

$285,997 $315,641 $346,583 $378,265 $407,142

Source: Calculations provided by AARP Reverse Mortgage Calculator. Loan amounts based off a 1-month adjustable LIBOR HECM at prevailing interest rates in June 2010.

HECMs and the Concept of Aging in Place Besides the direct financial impact of receiving transformed equity from the home, one of the benefits most commonly associated with a reverse mortgage is the ability to “age in place”. “Aging in place”, which originated from discussions about the need for home improvements for the elderly, refers to the ability of an individual to remain living in their own home as they age (Pynoos, 1993). Most elderly individuals indicate that they wish to live independently as long as possible (Kendig & Pynoos, 1996). Due to the alleviation of financial burdens through a reverse mortgage, homeowners may now be able to maintain residence in the family home. The ability to remain living at home allows the aging individual to retain independence and autonomy in a manner consistent with previous stages of their life, allowing the individual to better manage impairments and perform daily activities

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(Lawton, 1989; Mann, 2001). Marek, Popejoy, Petroski, Mehr, Rantz, and Lin (2005) showed that individuals who aged in place, as compared to those in nursing homes, had higher levels of cognition, decreased occurrence of depression, increased ability to complete daily activities, and better health outcomes. Rosel (2003) and Rowles (1981) indicate a strong psychological benefit of aging in place, as the elderly feel a connection with their environment and their intangible connections within the community. Another benefit offered by aging in place is the removal of anxiety associated with the relocation process. The relocation process can cause stress, increased feeling of isolation and grieving, and instigate a decline in both physical and psychological abilities (Karmali, 1999). Chapin and Dobbs-Kepper (2001) found that relocation for elderly individuals increases the likelihood of depression and suicidal tendencies. The homeowner’s physical relocation is not even necessary for this stress to exist; as Frank (2001) points out, the fear of being forced to move causes increased stress levels. This forgone stress provides a distinct benefit for those homeowners who are able to retain homeownership through the use of a reverse mortgage. Aging in place offers cost advantages as well. An industry survey conducted in 2009 by Genworth Financial (2010) found the median cost of assisted living facilities and nursing homes to be $38,000 and $75,000 a year, respectively. While certainly not all individuals who are forced to sell their homes will move to a facility, there are obviously large monetary benefits to postponing transfer into one of these facilities. Despite these substantial benefits, there have been some criticisms of aging in place as associated with the use of a reverse mortgage. One of the most uncertain costs for the elderly population is that of health care. In the event of a high cost medical occurrence, large unexpected expenses could necessitate the sale of the home. Additionally, there may be reason to reconsider the optimal living situation for the homeowner (Feinstein, 1996). The constraints of a reverse mortgage limit the desirability for the sale of the home, providing incentives for the homeowner to act in a way contrary to his optimal choice. There is also some concern about whether HECMs provide incentives for homeowners to continue living in substandard homes. Given that HECMs can only be taken out on homes with little to no mortgage debt, often owners have lived in the home for a substantial amount of time. Golant and LaGreca (1994) find that the length of residence was a poor predictor of housing quality. While this seems to refute this argument, it does note that building age was negatively associated with housing quality. This is of significant concern, as HECMs could act to both enable and trap elderly

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individuals in substandard housing. However, innovations in universal design and the application of technology to the home have brought increased hopes for the viability of aging in place. Numerous studies (Cheek, Nikpour, & Nowlin, 2005; Fisk, 2001; Mace, 1998; Peterson, 1998) have indicated the increased ability of an individual to remain self-sufficient in a private residence through the application of universal design or smart-home technologies. However, neither of these will help an individual that is in need of constant medical care, and the argument still persists that an individual may feel trapped in the home.

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THE EARLY YEARS OF THE HECM PROGRAM From its inception, the potential market for reverse mortgages has been projected to be vast. Using data from the 1989 American Housing Survey (AHS), Merrill, Finkel, and Kutty (1994) indicate that over twelve million elderly homeowners own their residences with no encumbering mortgage. Of this demographic, an estimated 800,000 homeowners could see a significant increase in their financial well-being through the use of a reverse mortgage. Similarly, Rasmussen, Megbolugbe, and Morgan (1995) use data from the 1990 Census to estimate the potential market, but use slightly less stringent criteria. The researchers conclude that 6.7 million households spread across the United States fit the target profile. This analysis is continued in Morgan, Megbolugbe, and Rasmussen (1996), which indicates that 1.8 million elderly women would see a significant increase in their income through the use of a reverse mortgage. Using data from the AHS, Kutty (1998) estimates that 621,820 elderly homeowners could be raised above the poverty line with the use of a reverse mortgage, providing for a reduction in the elderly poverty rate of 2.4%. Despite the overwhelming research indicating a vast pool of potential borrowers, the early years of the HECM program saw very little action as illustrated in Table 3. Although authorized in 1987, the first HECM was not made until late 1989. From that point through the end of 1995, a total of 11,060 HECM loans were originated. The loan volume did increase towards the latter half of the 1990s, but the first ten years of the HECM program, ending in the year 2000, saw a grand total of 42,319 loans. Even with this limited participation, the HECM program has originated 90% of all reverse mortgages in the U.S. (Shan, 2009).

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Table 3. HECM Loans Originated from 1990 – 2000 Year

# Originated

1990

157 389

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Active Loans as of 3/2010 2

1,019 1,964

1 4 23

3,365 4,166

35 110

3,596 5,208

114 292

7,895 7,923

785 1,060

6,637

1,335

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Source: Table constructed from data provided by U.S. Department of Housing and Urban Development (2010b).

MARKET CONSTRAINTS Various reasons were proposed for this lack of growth. From the demand side, the presence of a strong bequest motive was indicated. The desire to bequeath property to heirs among elderly homeowners would limit the applicants for reverse mortgages, as homeowners would be reluctant to create a claim against property that they wished to pass down to their heirs. However, Caplin (2002) finds that, except for the extremely wealthy, the bequest motive for individuals is not overwhelming and its magnitude is not large enough to affect decisions. In addition to this, Mayer and Simons (1994) estimate that more than 1.3 million homeowners have no living children to whom they could leave an inheritance, a number that far overshadows the number of loans created. Lastly, the remainder value of the house above the final loan amount will remain in the estate and still be available for desired recipients. Venti and Wise (1989, 1990, & 2004) revealed that the elderly avoid diminishing housing equity. They found that, in the absence of a precipitating event, elderly homeowners did not tap into their housing wealth to cover

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expenditures. The hesitance to tap into home equity was further explored by Leviton (2002), who conducted a series of open-ended interviews of homeowners who had received reverse mortgage counseling. The interviews identified a number of factors that played a key role in the decision to receive a reverse mortgage, including an individual’s attachment to their home, family input, and financial attitudes. Overall, homeowners indicated that they avoided taking a reverse mortgage unless it was the only viable option for them to maintain their independence. In most cases, the decision to receive reverse mortgage counseling was instigated by an inability to survive financially in the current situation. A series of interviews conducted by Munnell, Soto, and Aubry (2007) found similar sentiments. The number one reason identified by households age 50-65 for not planning on accessing home equity is that it provided insurance against living and health expenses. Without the need to access the equity to meet these purposes, the use of a reverse mortgage is viewed as undesirable. The inherent financial complexity and innovation presented by HECMs might also act to deter potential borrowers (Bishop & Shan, 2008). The adoption rates of new products by the elderly is consistently lower than that of other age groups (Kerschner & Chelsvig, 1984; Gilly & Zeithaml, 1985) The low adoption rates have been explained by arguing the elderly have negative perceptions of new products and these products being relatively harder for them to understand (Pommer, Berkowitz, & Walton, 1980; Adams & Thieben, 1991). This avoidance of new products and innovation could represent a significant limiting factor to the expansion rate of HECMs. For low-income households, the use of a HECM might be avoided given its implications on eligibility for government programs (Bishop & Shan, 2008). For example, taking a HECM may disqualify an individual from receiving Medicaid (National Council on Aging, 2009). In many states the home’s value is exempted in the qualification process for Medicaid as long as the applicant, their spouse, or their dependent maintains residence. If the house is transformed into income or cash, however, it can disqualify an individual from benefits. A HECM could cause the homeowner to pay thousands of dollars in medical expenses that would have otherwise been covered by Medicaid. For individuals in situations such as this, the use of a HECM would be less than ideal. There is significant concern from the supplier perspective of the possibility of an adverse selection bias. Adverse selection would occur if borrowers were more likely to be in good health with a longer expected life span than population averages. This issue is addressed by Davidoff and Welke

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(2007) who determined that, rather than being hurt by adverse selection, the reverse mortgage market has been a beneficiary of advantageous selection. Upon analyzing the length of reverse mortgage loans, the researchers find that the opposite is true and reverse mortgage purchasers are more likely than their demographic counterparts to sell their home. The proposed reason is that individuals that have severe liquidity constraints are the most likely to take a reverse mortgage in the first place. In the event of a high-cost occurrence, these individuals are more likely to need to access additional equity in the home through its sale. While this relieves concerns about adverse selection pertaining to borrower characteristics, it does not take into consideration home characteristics. For example, homeowners who expect either low appreciation rates or a decrease in home value may be more likely to enter into a reverse mortgage. Davidoff and Welke (2007) find evidence to support this, as the mobility rates between HECM borrowers and non-borrowers is much smaller in areas with historically low home appreciation rates. The longer duration of loans on low appreciation property provides for an increased likelihood of the convergence of home values and loan values is more likely. There are significant moral hazard risks with reverse mortgages. Moral hazard arises when homeowners realize that market risk is borne by investors rather than themselves. Given that the borrower is the active caretaker of the home, they may be less likely to take care of the property as the ownership transfers (Shiller & Weiss, 2000). If the homeowner has significant equity in the home this risk is minimized, as they are the remainder beneficiary. However, there is a risk that a homeowner in a reverse mortgage situation will reduce maintenance expenditures as their home equity becomes smaller (Miceli & Sirmans, 1994). Even without the moral hazard concerns, Davidoff (2006) showed that homeowners age 75 and older spend less on home repairs than younger homeowners. The property must meet certain minimum standards for the loan to remain in good standing, but there are significant concerns from the lenders’ perspective about the attention the property will receive. Lenders must also contend with crossover risk: the risk that an individual will remain in his home after the loan balance exceeds the value of the house (Chinloy & Megbolugbe, 1994). With no mechanism to trigger repayment of the loan other than the death of the homeowner or the voluntary sale of the house, the lender is limited in its ability to manage this risk. It is important to recognize that there are two variables in the equation: the home price and the loan balance. The recent downturn in the housing market has acted to increase the possibility that the home value will exceed the loan balance. This risk is

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mitigated for HECMs with FHA insurance, but helps explain the dearth of comparable products. The possibility that other methods could potentially be utilized to achieve the effects of a reverse mortgage was explored by Hammond (1993), who identified two possible alternatives: the sale of the home and a sale-leaseback agreement. The sale of the home is found to be lacking, as it fails to accomplish the main purpose of facilitating continued home residence. However, this objective is accomplished with a sale-leaseback agreement. The sale typically consists of a one-time lump sum payment as well as a continued annuity from the buyer to the homeowner. Foote (2007) notes that the cost of property taxes, home insurance, and maintenance are shifted to the buyer, diminishing the total out of pocket costs for the homeowner. The saleleaseback does require rent payments, which incurs an expense previously nonexistent. There continues to be interest in the sale-leaseback structure, but at this point no large scale programs have been attempted. A major problem is identifying investors that are willing to take an active role in property upkeep while accepting the limits of the leaseback restrictions. While the saleleaseback approach is promising, these options have shortfalls and are limited in their viability as alternatives. Various reasons accounted for the limited demand for HECMs in their first decade of existence. While the market has since expanded, these issues must still be considered, as they remain present in the marketplace. Both the current market demand and the characteristics of consumers are shaped by these issues innate within HECMs . Additionally, many of the mortgages originated in this period are still active and represent a small portion of the market.

THE CURRENT MARKET Since the beginning of the 21st century the demand for HECMs has exploded. Loan originations have increased steadily, as indicated in Table 4. In fact, originations experienced double digit growth from 2001 – 2007 before leveling off in 2008 and 2009. The total number of HECMs skyrocketed 1252% from 42,319 at the end of 2000 to 572,418 by the end of 2009. This growth period for HECMs was capped in 2009, which saw a record 114,641 loan originations.

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Table 4. HECM Loans Originated From 2001-2009 Year 2001 2002 2003 2004 2005 2006 2007 2008 2009

# Originated 7,789 13,049 18,084 37,790 43,082 76,281 107,368 112,015 114,641

Active Loans as of 3/2010 1,978 4,387 7,593 19,430 29,233 62,165 96,613 106,013 111,210

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Source: Table constructed from data provided by U.S. Department of Housing and Urban Development (2010b).

Figure 1 provides information about the geographic distribution of HECM borrowers. The Western region leads all others with 201,923 loans. California and Florida claim by far the most originations by state, with 110,793 and 69,957 respectively (U.S. Department of Housing and Urban Development, 2010b). The combination of a heavy retirement community presence and historically high home values in these two states is likely the cause of the consistently heavy loan activity. Texas trails considerably as the next most active state, with 30,933 originations. In stark comparison, North Dakota has the smallest number of HECMs originated with a grand total of 329. 250,000 200,000 150,000 100,000 50,000 0 Midwest

Northeast

South

West

Source: Figure constructed from data provided by U.S. Department of Housing and Urban Development (2010b). Figure 1. Total Loan Originations Through 2009 by Census Regions.

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The market for HECMs has been consistently headed by single females since its inception, as illustrated in Figure 2 (U.S. Department of Housing and Urban Development, 2010b). Given women’s longer life expectancies, this is to be expected. However, in recent years the percentage of joint borrowers has increased significantly and, if the trend continues, will soon become the prevailing demographic group.

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

70% 60% 50% 40% 30% 20% 10% 0%

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Single Female

Single Male

Joint

Source: Figure constructed from data provided by U.S. Department of Housing and Urban Development (2010b). Figure 2. Borrower Demographics By Orginantion Year.

The average age of borrowers has decreased significantly over the years from 76.7 to 73 as demonstrated in Figure 3 (U.S. Department of Housing and Urban Development, 2010b). This means that homeowners are taking out HECMs earlier, increasing the period of life after loan origination. Given that the majority of individuals select the line of credit pay out option, they now must stretch out funds over a longer period without the longevity hedging offered by the Tenure payout structure. The combination of the line of credit pay out option and decreased borrower age raises concerns that homeowners will face tough financial times towards the end of their lives when they have run out of both non-housing assets and those provided through the HECM.

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72 78 77 76 75 74 73 72

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

71

Source: Figure constructed from data provided by U.S. Department of Housing and Urban Development (2010b).

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Figure 3. Average Borrower Age By Year of Origination.

POTENTIAL MARKET OUTLOOK FOR HECMS While HECMs have exploded onto the scene in recent years, originations are still dwarfed by the potential market. The arrival of Baby Boomers into retirement represents a vast new pool of potential borrowers. Lusardi and Mitchell (2007) indicate the median “Early Baby Boomers”, those born between 1948 and 1953, has roughly half of their wealth in the form of home equity, with 79.9% owning a home. Conversely, only 41.5% reported owning an IRA and 30.9% stock ownership. With limited participation in retirement and growth vehicles, the ability to access home equity for many of these individuals will be important to their future financial livelihood. Besides the growth in demand for traditional HECM products, the HECM program continues to evolve to meet the needs of the elderly. The Housing and Economic Recovery Act of 2008 provided for the creation of the HECM for Purchase Program (Montgomery, 2008). This program provides for the simultaneous purchase of a home and creation of a HECM loan. The proceeds from the HECM can be used to pay the purchase price. This innovative program allows individuals who do not meet the income qualifications of other mortgages to purchase a home they would have otherwise been unable to

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afford. Individuals must still have a significant amount of cash in order to be able to pay the difference between the home value and the loan amount. Montgomery (2008) provides an example of how this mortgage might be used. A 67-year-old is considering the purchase of a $300,000 home. Assuming a Principal Limit Factor of .665 and loan costs of approximately $15,500, the homeowner would be able to receive a lump sum payment of $184,000. With the use of a HECM For Purchase, the homeowner would only be required to come up with $116,000. The use of this loan provides the financing to make this purchase possible that would have been impossible otherwise. While this program is still new, it appears that its future is bright. As the HECM market looks to the future, it must address several misconceptions that have become prevalent among elderly households (Freedom Financial, 2007). The first of these myths is that the homeowner turns over ownership to the lender, leading to concerns that the homeowner could be kicked out of the home. However, the homeowner retains full ownership with the home acting as collateral for the loan. The relationship between the home and loan leads to the next myth, which is that the home must be sold upon loan termination. Although the home is often sold to generate the cash needed to pay off the loan, it is not required. Additionally, the belief persists that debt could be passed down to heirs if the loan becomes more than the house is worth. However, the liability for a HECM extends only to the value of the home and any additional debt is forgiven. Additional misconceptions include restrictions upon how loan proceeds are spent and that loan money is taxable. As prospective borrowers flock to the HECM market, they should remain cautious. Reilly (1997) cautioned about the abuse that occurs in the reverse mortgage market toward the exploitation of individual borrowers. Meanwhile, one of the largest increases in mortgage fraud in recent years has been specifically within the reverse mortgage market (Tergesen, 2009). Making matters worse, owner-occupant seniors are also more likely to become financially exploited when compared against renters (Choi, Kulick & Mayer, 1999). Further complicating the decision to borrow is the presence of numerous reverse mortgage online calculators. For the regular primary mortgage market involving the entire population of potential home buyers, research has shown that there are inconsistencies regarding homebuyer costs across online calculator options (James, Robb, Carswell, & Atiles, 2010). The possibility exists that similar problems will exist for the plethora of online calculators for reverse mortgage products as well. The borrower must keep in

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mind that HECMs are not for everyone, and be careful to fully understand the product before selecting it.

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REFERENCES Adams, A.S., & Thieben, K.A. (1991). Automatic teller machines and the older population. Applied Ergonomics, 22(2), 85-90. Apgar, W.C., & Di, Z.X. (2005). Housing wealth and retirement savings: Enhancing financial security for older Americans. Cambridge, MA: Joint Center for Housing Studies of Harvard University. Bayer, A., & Harper, L. (2000). Fixing to stay: A national survey on housing and home modification issues. American Association of Retired Persons. Retrieved May 21, 2010 from http://assets.aarp.org/rgcenter/il/home _mod.pdf Bishop, T., & Shan, H. (2008). Reverse mortgages: A closer look at HECM loans. National Bureau of Economic Research. Retrieved June 21, 2010 from http://www.nber.org/programs/ag/rrc/08Q2%20Bishop,%20Shan %20 FINAL.pdf Caplin, A. (2002). Turning assets into cash: Problems and prospects in the reverse mortgage industry. In O. Mitchell, Z. Bodie, P. B. Hammond & S. Zeldes (Eds.), Innovations in retirement financing. Philadelphia, PA: University of Pennsylvania Press. Chapin, R., & Dobbs-Kepper, D. (2001). Aging in place in assisted living: Philosophy versus policy. Gerontologist, 41(1), 43-51. Cheek, P., Nikpour, L., & Nowlin, H. D. (2005). Aging well with smart technology. Nursing Administration Quarterly, 29(4), 329-338. Chinloy, P., & Megbolugbe, I. F. (1994). Reverse mortgages: Contracting and crossover risk. Journal of the American Real Estate and Urban Economics Association, 22(2), 367-386. Choi, N.G., Kulick, D.B., & Mayer, J.(1999). Financial exploitation of elders: Analysis of risk factors based on county adult protective services data. Journal of Elder Abuse and Neglect, 10 (3/4), 39-62. Davidoff, T. (2006). Maintenance and the home equity of the elderly. Fisher Center Working Papers (No. 03-288). Retrieved June 21, 2010 from http://www.escholarship.org /uc/item/3m59r3tv Davidoff, T., & Welke, G. (2007). Selection and moral hazard in the reverse mortgage market (Working Paper). University of California-Berkley.

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Retrieved June 21, 2010 from http://strategy.sauder.ubc.ca/davidoff/ RMsubmit3.pdf Feinstein, J. (1996). Elderly health, housing, and mobility. In D. Wise (Ed.), Advances in the economics of aging (pp. 275-320). Chicago, IL: University of Chicago Press. Fisk, M.J. (2001). The implications of smart home technologies. In S.M.H. Peace & C. Holland (Eds.), Inclusive housing in an ageing society (pp. 101-124). Bristol, UK: The Policy Press. Foote, B.E. (2007). Reverse mortgages: Background and issues. In H. Sentowski (Ed.), Mortgages: Fundamentals, issues and perspectives (pp. 49-70). New York, NY: Nova Science Publishers, Inc. Frank, J. (2001). How long can I stay? The dilemma of aging in place in assisted living. Journal of Housing for the Elderly, 5(29), 5-30. Freedom Financial. (2007). Top ten myths about reverse mortgages debunked for senior citizens. Retrieved June 21, 2010 from http://seniorjournal .com/NEWS/ ReverseMortgage /2007/7-08-09-TopTenMyths.htm Genworth Financial. (2010). Genworth 2010 cost of care survey: Home care providers, adult day health care facilities, assisted living facilities, and nursing homes. Retrieved May, 21 2010 from http://www.genworth.com /content/products/long_term_care/long_term_care/cost_of_care.html?WT. svl=YMABIIMAP&mlink=YMABIIMAP Gilly, M., & Zeithaml, V. (1985). The elderly consumer and adoption of technologies. Journal of Consumer Research, 12(3), 353-357. Golant, S.M., & LaGreca, A. (1994). Housing quality of U.S. elderly households: Does aging in place matter. The Gerontologist, 34(6), 803814. Hammond, C.M. (1993). Reverse mortgages: A financial planning device for the elderly. Elder Law Journal, 75(1), 75-112. James, R.N., III, Robb, C.A., Carswell, A.T., & Atiles, J.H. (2010, in press). Housing costs among low-income renters and homeowners: 'Rent vs. buy' and the hidden costs of low-income homeownership. In F. Columbus (Ed.), Housing, housing costs and mortgages: Trends, impact and prediction. Hauppauge, NY: Nova Science Publishers Karmali, S. (1999). Assisted living in BC: Effects of organizational factors on residents’ satisfaction. (Unpublished master’s thesis). Simon Fraser University, Burnaby, British Columbia, Canada. Kendig, H., & Pynoos, J. (1996). Housing. In Encyclopedia of gerontology: Age, aging and the aged (Vol. 1, pp. 703-713). San Diego, CA: Academic Press.

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Kerschner, P., & Chelsvig, K. (1984). The aged user and technology. In R. Dunkle, M. Haug & M. Rosenberg M. (Eds.), Communications technology and the elderly: Issues and forecasts (pp.135-144). New York, NY: Springer Publishing Company. Kutty, N. (1998). The scope for poverty alleviation among elderly homeowners in the United States through reverse mortgages. Urban Studies, 35(1), 113-129. Lawton, M.P. (1989). Environmental proactivity and affect in older people. In S. Scpacapan & S. Askamp (Eds.), The social psycology of aging (pp. 135-163). Thousand Oaks, CA: Sage Publications, Inc. Leviton, R. (2002). Reverse mortgage decision-making. Journal of Aging & Social Policy, 13(4), 1-16. Lusardi, A., & Mitchell, O. S. (2007). Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth. Journal of Monetary Economics, 54(1), 205-224. Mace, R.L. (1998). Universal design in housing. Assistive Technology, 10(1), 21-28. Mann, W. C. (2001). Potential of technology to ease the care of provider’s burden. Generations, 25(1), 44-48. Marek, K.D., Popejoy, L., Petroski, G., Mehr, D., Rantz, M., & Lin, W.C. (2005). Clinical outcomes of aging in place. Nursing Research, 54(3), 202-211. Mayer, C.J., & Simons, K.V. (1994) Reverse mortgages and the liquidity of housing wealth. Journal of the American Real Estate and Urban Economics Association, 22(2), 235-255. Merrill, S.R., Finkel, M., & Kutty, N.K. (1994). Potential beneficiaries from reverse mortgage products for elderly homeowners: An analysis of American Housing Survey data. Real Estate Economics, 22(2), 257-299. Miceli, T.J., & Sirmans, C.F. (1994). Reverse mortgages and borrower maintenance risk. Journal of the American Real Estate and Urban Economics Association, 22(2), 433-450. Montgomery, B. (2008, October). Home equity conversion mortgage (HECM) for purchase program (Mortgagee Letter 2008-33). U.S. Department of Housing and Urban Development. Retrieved June 21, 2010 from http://www.hud.gov/offices/adm/hudclips/letters/ mortgagee/2008ml.cfm Morgan, B., Megbolugbe, I., & Rasmussen, D. (1996). Reverse mortgages and the economic status of elderly women. Gerontologist, 38(3), 400 -405. Munnell, A., Soto M., & Aubry J. (2007). How people think about their house in planning for retirement (Issues Brief No. 7-7). Center for Retirement

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Research at Boston College. Retrieved May, 17 2010 from http://crr.bc.edu/images/stories/Briefs/ib_7-7.pdf?phpMyAdmin= 43ac483c4de9t51d9eb41 National Council on Aging. (2009). Use your home to stay at home: A guide for older homeowners who need help now. Retrieved June 21, 2010 from http://www.ncoa.org/news-ncoa-publications/publications/ncoa_reverse _mortgage_booklet_073109.pdf Peterson, W. (1998). Public policy affecting universal design. Assistive Technology, 10(1), 13-20. Pommer, M.D., Berkowitz, E.N., & Walton, J.R. (1980). UPC scanning: An assessment of shopper response to technological changes. Journal of Retailing, 56(2), 25-44 Pynoos, J. (1993). Strategies for home modification and repair. Generations, 16(2), 21-26 Rasmussen, D.W., Megbolugbe, I.F., & Morgan, B.A. (1995). Using the 1990 public microdata sample to estimate potential demand for reverse mortgage products. Journal of Housing Research, 6(1), 1-23. Reilly, J. (1997). Reverse mortgages: Banking into the future. Elder Law Journal, 5, 17-18. Rosel, N. (2003). Aging in place: Knowing where you are. The International Journal of Aging and Human Development, 57(1), 77-90. Rowles, G. D. (1981). The surveillance zone as meaningful space for the aged. The Gerontologist, 21(3), 304-311. Shan, H. (2009). Reversing the trend: The recent expansion of the reverse mortgage market (Finance and Economics Discussion Series 2009-42). Washington, D.C.: Federal Reserve Board. Shiller, R.S., & Weiss, A.N. (2000). Moral hazard in home equity conversion. Real Estate Economics, 28(1), 1-31 Stevens, D. (2009a, November). Home equity conversion mortgage program: Subordinate Liens (Mortgagee Letter 2009-49). U.S. Department of Housing and Urban Development. Retrieved June 21, 2010 from http://www.hud.gov/offices/adm/hudclips/letters/ mortgagee/2009ml.cfm Stevens, D. (2009b, November). 2010 FHA Maximum Loan Limits (Mortgagee Letter 2009-50). U.S. Department of Housing and Urban Development. Retrieved June 21, 2010 from http://www.hud.gov/ utilities/intercept.cfm?/offices/adm/hudclips/letters/mortgagee/files/0950ml.pdf Szymanoski, E.J. (1994). Risk and the home equity conversion mortgage. Real Estate Economics, 22(2), 347-366.

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Tergesen, A. (2009, August 27). Mortgage fraud: A classic case’s latest twists. Wall Street Journal. Downloaded June 28, 2010 at: http://online. wsj.com/article /SB10001424052970204044204574362641338197748.html U.S. Department of Housing and Urban Development. (2009). FHA reverse mortgages (HECMs) for consumers. Retrieved June 21, 2010 from http://www.hud.gov/offices/hsg/sfh/hecm/ hecmabou.cfm U.S. Department of Housing and Urban Development. (2010a, April). Principal limit factors. Retrieved June 21, 2010 from http://www.hud.gov/ offices/hsg/sfh/hecm/hecmplf.xls U.S. Department of Housing and Urban Development. (2010b, March). HECM cases endorsed for insurance by fiscal year: Also selected loan and borrower characteristics. Retrieved June 21, 2010 from http://www.hud. gov/offices/hsg/comp/rpts/hecm/hecmmenu.cfm Venti, S.F., & Wise, D.A. (1989). Aging, moving and housing wealth. In D.A. Wise (Ed.), The economics of aging (pp. 9-48). Chicago, IL: University of Chicago Press. Venti, S.F., & Wise, D.A. (1990). But they don’t want to reduce housing equity. In D. A. Wise (Ed.), Issues in the economics of aging (pp. 13-29). Chicago, IL: University of Chicago Press. Venti, S.F., & Wise. D.A. (2004). Aging and housing equity: Another look. In D. A. Wise (Ed.), Perspectives on the economics of aging (pp.127-180). Chicago, IL: The University of Chicago Press.

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Chapter 4

WHY IS GDP ALWAYS THE DENOMINATOR? Stephen Morse*

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Centre for Environmental Strategy, University of Surrey Guildford Surrey GU2 7XH, UK

ABSTRACT Gross Domestic Product (GDP) is often employed in indicators and indices, typically as a denominator which implies a return (in environmental health, well being etc.) per unit of national wealth. GDP is itself often divided by population to provide a proxy measure of income per capita, and this too often finds its way into indices such as the Human Development Index (HDI). For example, the Holy Grail of sustainable development is in many ways represented by the so-called Environmental Kuznets Curve, a plot of environmental degradation as a function of national wealth. While there have been efforts to promote alternatives to the GDP, such as the Genuine Progress Indicator (GPI), GDP still dominates. But why should GDP feature so prominently in such measures? Why is it so prevalent as a denominator and what are the alternatives? This chapter aims to discuss some of these key questions that rest behind so many of the indicators and indices we commonly use *

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Steephen Morse todaay. The chaptter provides a number of examples whhere GDP or GD DP/capita are the t denominattors and discuusses the assuumptions and limiitations that rest behind them m.

E l Kuznets Curvve, Keyworrds: GDP, Huuman Developpment Index, Environmental Deebt, Economic Growth.

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GDP: A BRIEF OVE ERVIEW oss Domestic Product (GDP P), also calledd the Gross Domestic D Incoome Gro (GDI), is one of thee main measurres of econom mic performannce in the woorld H it has h not been without w its crritics as manyy have soughtt to today. However identify y GDP as thhe quintessenntial embodim ment of an all a too comm mon emphasis on wealth and economicc growth. Thee argument iss a simple onne – human experience shhould be mucch more thann accumulationn of finance but DP amongst those t in goverrnment and thhe private secctor popularrity of the GD constan ntly works aggainst such a broader perrspective. Buut is this a fair criticism m? This paper will exploree that questioon by setting out the case for GDP an nd give exam mples as to itts continued popularity within a rangee of contextss. The paper will w then go on to explore the t most curreent articulationn of criticism m of GDP andd ask whether it i will make anny difference. GD DP is designedd to measure the t level of ecconomic activvity in a counntry, region or o even smalleer spatial unitss such as a citty. A more tecchnical definittion of GDP P, taken from thhe World Devvelopment Repport (2000/01)) is as follows: “GDP is the gross value added, a at purchhaser prices, byy all resident prod ducers in the economy plus any taxes annd minus any subsidies not inclluded in the valuue of the products.”

ws within GDP. The two baasic Theere are a numbber of componnents and flow ones are that people earn income from wages and spend it on goods (foood, g machines, TVs T etc.) and services (wateer supply, inteernet connectiions washing etc.). Th herefore to asssess such floows one couldd measure purrchases of goods and serv vices or moneey paid out inn wages. Takking the expennditure approaach, GDP is often summarrised as follow ws:

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GDP = Gross Domestic Product C = consumers’ expenditure on goods and services G = government expenditure on goods and services I = investment EX = exports IM = imports Thus GDP is the sum of what is spent by consumers (C) and the government (G) on productive goods and services along with expenditure on investment. The investment (I) component of GDP is complex. It refers to ‘private domestic investment’ since government investment in infra-structure such as roads is included within G. Much of the savings lodged by households is invested by banks into the private sector, and is therefore a ‘sink’ which locks up capital. Liquidating that investment will put cash back into the system. Also note that non-productive expenditures (social security benefits, unemployment compensation, welfare benefits, interest payments on the national debt) are not included in G. The final term (EX – IM) allows for the countries trade balance (exports – imports) to be taken into account. Note that a good or service doesn't actually have to leave the country to be counted as an export. Tourists spend money on hotel rooms, local travel and food and while these goods have been ‘produced’ locally they are paid for by foreigners and hence considered as an export. The higher the value of the GDP then the greater the level of economic activity. GDP was born out of the maelstrom of the recession (‘Great Depression’) in the 1930s with the work of Simon Kuznets in the US and Colin Clark in the UK and Australia to establish systems of national accounting that allow for an assessment of change over time and for Clark the ability to make comparisons between countries. However, there are many complicating factors at play. Looking at trends in GDP over time can be misleading as inflation increases the quality of money circulating in an economy without any increase in economic activity (Maddison, 1983). Thus an apparent increase in GDP can be caused not by an increase in the number of items being purchased but by an increase in their unit price. This problem can be addressed by calculating what is called ‘real GDP’, whereby all transactions are calculated relative to a single year. An example of the impact this re-jigging has on the value of GDP is shown in Figure 1 for the UK economy from 1900 to 2011. Employing ‘real’ GDP values fixed (or ‘chained’) to currency value of a particular reference year has the effect of smoothening out the increase over time relative to GDP

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which includes inflation. It should also be noted that the quantity of money flowing in an economy will in part be a reflection of the number of people in that economy; more people means more expenditure and wages and hence a higher GDP. Part of the increase in ‘real’ GDP shown in Figure 1 is due to the increase in the UK population between 1900 and 2011. However, providing the size of the population is known then this can be easily accounted for by dividing national GDP by the number of residents.

UK economy from 1900 to 2011.Also included is a plot of national debt. Source of data: www.ukpublicspending.co.uk Figure 1. Comparison of GDP with and without inflation.

A further complication with GDP rests with comparison across space (e.g. between countries). Two economies may be identical in terms of the type and quantity of goods being traded, but if prices are higher in one country relative to the other then its GDP will be much higher. Also, the GDP in one country could be lower than the other even when there is a greater volume of goods and services being exchanged. Indeed Kuznets was sceptical about making such cross-country comparisons as he felt national accounts reflect to some extent the socio-cultural nature and history of the ‘place’ and this will inevitably vary from place to place. Others saw it differently and worked to arrive at national accounts that could be compared across time and place, but while ‘real’ GDP can accommodate temporal issues such as inflation comparison between places is a more complex problem. This is not just a currency exchange rate issue. Even when a currency is converted there can

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still be very different prices across national borders for the same good. Money is easily traded across the globe but many goods are not so easily traded and there are market frictions which induce a “band of inaction” (Peel and Venetis, 2003). There may be various reasons for this such as their bulk to price ratio making transportation uneconomic, perishability or because of inducements to production (such as tariffs) which provide advantages for local producers. Therefore while many goods may be virtually identical across countries in terms of ingredients their prices may be quite different as they are produced locally rather than transported. One answer to this problem is to apply the notion of ‘purchasing power parity’ (PPP; Taylor, 1995; Rogoff, 1996). PPP is one of the most widely tested economic hypotheses (Holmes, 2000) and is a commonly employed method for calibrating GDP to allow for comparison across countries (Dowrick and Quiggin, 1997). It is usually estimated by collecting the prices of specified items (typically grouped within categories, or ‘basic headings’) that are representative of typical expenditure but at the same time comparable across countries. As Kuznets warned, given the diversity between cultures in what a household would normally purchase this is certainly not a straightforward feat. The PPP adjusted GDP values are normally given in terms of some international monetary unit such as ‘international dollars’, and lists of PPP adjustments are published on a regular basis (Vachris and Thomas, 1999). One of the first such comparative tables of GDP adjusted for purchasing power was provided by Clark (1940) and a summary is presented as Table 1. While some of the countries no longer exist (e.g. Czechoslovakia, Yugoslavia) and some of the geographical phrases (e.g. ‘Rest of Africa’, ‘Rest of Asia’) are perhaps suggestive of the biases of the time there is nonetheless a similarity with more modern rankings.

GDP AS A COMPONENT OF OTHER INDICES As well as being a powerful indicator in its own right, GDP often crops up as a component of other indices. GDP often appears as a denominator. An example that is very much being quoted at present is the debt:GDP ratio. It needs to be noted (and is sometimes forgotten) that the value of this ratio depends upon both the denominator and the numerator. The debt:GDP ratio is sometimes equated as being solely a measure of debt. Figure 2 is a plot of the year-to-year percentage change in GDP for the UK economy (i.e. the year-toyear change in the real GDP figures shown in Figure 1). GDP fell at various times from 1990 to 2011, most notably during or just after world wars, but also

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during the ‘Great Depression’ of the early 1930s; an event that helped provide a spur for economists to get a better set of measures for economic performance and thereby avoid the same thing happening again. Between the 2nd WW and more recent years the ‘downturns’ in the UK economy have been relatively few and indeed quite mild compared to those of earlier times. The exception, of course, has been the financial crisis of 2008 and 2009 which ranks alongside that of the 1st WW in terms of decline in GDP.

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Table 1. One of the first published rankings of countries based upon income/capita where income has been adjusted for purchasing power Average yearly income/capita * 1300 – 1400 1200 – 1300 1100 – 1200 1000 – 1100 900 – 1000 800 – 900 700 – 800 600 – 700 500 – 600 400 – 500 300 – 400

200 – 300 Under 200

USA, Canada New Zealand Great Britain, Switzerland, Argentina Australia Holland Ireland France, Denmark, Sweden, Germany, Belgium, Uruguay Norway, Austria, Spain, Chile Czechoslovakia, Yugoslavia, Iceland, Brazil Greece, Finland, Hungary, Poland, Latvia, Italy, Estonia, USSR, Portugal, ‘Rest of America’, Japan, Palestine, Philippines, Algeria, Egypt, Hawaii, Guam Bulgaria, Rumania, Lithuania, Albania, Turkey, Syria, Cyprus, South Africa, Morocco, Tunis China, British India, Dutch Indies, ‘Rest of Asia’, ‘Rest of Africa’, ‘Rest of Oceania’

After Clark, 1940; page 54. * 1925-34. Artificial unit which has been adjusted for ‘purchasing power’.

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Why Is GDP always the Denominator?

Negative values are indicative www.ukpublicspending.co.uk

of

a

recession.

Source

of

data:

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Figure 2. Percentage change (year-to-year) in UK GDP (chained to 2005).

Source of data: www.ukpublicspending.co.uk Figure 3. Debt:GDP ratio for the UK economy.

A plot of national debt (chained to 2005) over the same period (Figure 1) shows how UK governments have often borrowed money during times of poor economic performance. The surges in debt match the economic downturns. However, it may be a surprise to the reader to see in Figure 3 how the trend in debt:GDP ratio has fared over the same period. The financial crisis of recent years has increased the debt:GDP ratio but only to the level seen in the late 1960s/early 1970s. The ratio is nowhere near as bad as it was for the period

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spanning the 1st and 2nd WW, including the inter-war years and indeed for the 1950s and 1960s. But, of course, these graphs tell only part of the story – the national finances. They do not tell the story of the political, social and environmental consequences of the changes, and indeed they are not designed for that purpose. Thus the recessions in Figure 2 had major repercussions for many families in the UK via loss of earnings and unemployment, and this can become hidden if one looks at these graphs in pure economic terms. But GDP as a measure is only designed to measure monetary flow within an economy and was not designed to gauge happiness or quality of life. Another examples of the use of GDP as an ‘additive’ component within an index is provided by the Human Development Index (HDI). The HDI is an attempt to go beyond the pictures shown in Figures 1 to 3 by encapsulating something called ‘human development’ or what many refer to more simply (if not accurately) as ‘quality of life’ (Kelly, 1991; Anand and Sen, 1994; Moldan, 1997). The HDI has three components; one for education, one for health (proxied by life expectancy) and one for income. The HDI is the average of these three components, each having equal weight (Booysen, 2002) It was created by the United Nations Development Programme (UNDP) and values for countries are presented each year in its Human Development Reports (HDR). One of the key rationales given by the UNDP for the creation of the HDI was a perceived need to counter the dominance of economic growth (proxied by changes in GDP and related indicators over time) in development and typified by the early work of Clark shown in Table 1. The rationale is summed up in the first paragraph of the first chapter of the first HDR published in 1990: “People are the real wealth of a nation. The basic objective of development is to create an enabling environment for people to enjoy long, healthy and creative lives. This may appear to be a simple truth. But it is often forgotten in the immediate concern with the accumulation of commodities and financial wealth.” HDR 1990 page 9

The report even invokes the writings of Aristotle as support: "Wealth is evidently not the good we are seeking, for it is merely useful and for the sake of something else."

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As a result the UNDP concludes: “But excessive preoccupation with GNP growth and national income accounts has obscured that powerful perspective, supplanting a focus on ends by an obsession with merely the means”.

Ironically, the GDP (real and adjusted in terms of PPP) per capita is used as the measure of income in the HDI. The rationale for including a measure which was regarded as engendering an “excessive preoccupation” is set out on page 12 of Chapter 1 of the 1990 HDR. While the text may be quite dry it does make for sober reading:

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“The third key component of human development - command over resources needed for a decent living - is perhaps the most difficult to measure simply. It requires data on access to land, credit, income and other resources. But given the scarce data on many of these variables, we must for the time being make the best use of an income indicator. The most readily available income indicator - per capita income – has wide national coverage.”

Thus the intention appears to have been to use GDP/capita (adjusted for PPP) as an income indicator on a temporary basis with the intention that it be replaced. However this has not happened in the 20 year history (at the time of writing) of the HDI, presumably because the required datasets on land, credit etc. have not become available. Indeed it is often forgotten how dependent indices such as HDI and, for that matter, GDP are upon the availability of good quality data (Murray, 1991; Loup et al., 2000). The persistence of GDP within an index that was created to dethrone is both remarkable and ironic. The components of the 2007 HDI are set out in Table 2 along with the mean, standard deviation (SD) and coefficient of variation (CV) of the data under each heading. Of the variables the GDP/capita component has much the greater CV. The UNDP have argued consistently for a diminishing return in human development from GDP/capita and so that high values of that component should not dominate within the HDI (Sagar and Najam, 1998). As a result GDP/capita is adjusted to reduce its relatively large variation. Indeed arguably the most significant change in calculating the HDI from 1990 onwards has been in the handling of the GDP/capita component. In the first HDR of 1990 this was achieved by simply taking the logarithm of the GDP/capita, but between 1991 and 1998 the method of transformation was changed to the more complex Atkinson formula (UNDP HDR, 1991). However, this approach has the effect of severely penalizing real GDP/capita.

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Above a notional target adjusted GDP/capita more or less levels out whereas with the logarithmic-based transformation it continues to increase, albeit more slowly, and never levels off completely. Between 1999 and the present there was a return to the logarithm method as it was felt by the UNDP that the Atkinson formula was too severe on middle-income countries (UNDP HDR, 1999). One further point of interest regarding the inclusion of GDP/capita within the HDI is its high degree of correlation with the other components of the index. The method of aggregation employed by UNDP collapses the four variables shown in Table 3 into three. This is achieved by combining the two education elements into one. However, keeping the variables separate the Pearson correlation coefficients between them are shown in Table 3. All of the HDI components are significant correlated with each other. At one level this is encouraging as even if the components are measuring quite different characteristics of ‘development’ they at least must have something in common, even if the mechanisms involved are complex. Even GDP/capita in its ‘raw’ form is highly correlated with the other components. Indeed values of GDP/capita transformed by logarithms have correlation coefficients greater than 0.7 with the other HDI components. But this degree of correlation begs the question as to why they are all needed in the HDI? The UNDP counter this by reiterating the importance of these wider concerns in human development that the HDI is attempting to encapsulate. In an empirical sense the use of the HDI in league tables rather than say the GDP/capita does result in a different ranking; something which the UNDP tends to stress and indeed illustrate in the HDRs. It is interesting to note the extent to which this occurs. Table 4 presents a set of correlation coefficient between the ranks of the variables. In this case the figures are Spearman rank correlation coefficients; a non-parametric version of the Pearson correlation coefficient which employs ranks of the variables. While the ranks of all the four components of the HDI have statistically significant correlations with the ranks of the HDI, the correlation between the HDI and GDP component was, if anything, higher than for the other three variables. Maybe, and despite all of the protestation to the contrary, GDP/capita is not such a bad proxy for human development after all, at least in terms of the data, index and assumptions employed by UNDP.

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Table 2. Summary statistics for the dataset employed in the 2007 HDI

Life expectancy at birth

Mean SD CV Minimum Maximum

HDI 2007 0.74 0.17 24 0.34 0.97

(years) 2007 69 10 15 44 83

Adult literacy rate (% aged 15 and above) 1999–2007 84 19 23 26 100

Combined gross enrolment ratio in education

GDP/capita

(%) 2007 72 17 24 26 114

(PPP US$) 2007 13,482 15,827 117 298 85,382

As published in the Human Development Report of 2009. Note: in the HDI calculation a number of countries having GDP/capita greater than $40,000 are ‘flattened’ down to $40,000, thereby also reducing variation. However, the values used in the above table are the ‘raw’ data without such flattening.

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Table 3. Pearson correlation coefficients for the components of the HDI 2007

Life expectancy Literacy Gross enrolment GDP/capita

Life expectancy 1

*** P < 0.001 Note: GDP/capita figures are in their ‘raw’ (untransformed) form

Literacy 0.74*** 1

Gross enrolment 0.77*** 0.8*** 1

GDP/capita 0.6*** 0.49*** 0.59*** 1

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Table 4. Spearman rank correlation coefficients between HDI (2007) rank and the ranks of its four components LE 0.933***

Literacy 0.802***

GER 0.874***

GDP 0.951***

*** P < 0.001 Note: in the HDI Literacy and gross enrolment are combined into ‘education’

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GDP AS AN EXPLANATORY VARIABLE While GDP often appears as a component within ‘aggregate’ or ‘composite’ indices such as the HDI it is also often used as a dependent or independent variable for comparison. The assumption is typically that a variable will have an effect on GDP or alternatively that GDP will have an influence on a variable. In the HDI, for example, it is not unreasonable to assume that the education and life expectancy components will be influenced by GDP as this will govern the amount of resource available to a government to spend on schools, hospitals and the skilled staff that would work in these institutions. Indeed both of these ‘cause - effect’ assumptions for GDP can be applied in a wide range of contexts and an example is the theory behind the Environmental Kuznets Curve (EKC; Stern et al., 1996; Khanna and Plassmann, 2004; Hartman and Kwon, 2005; Nahman and Antrobus, 2005). The EKC explores how GDP is related to the environment. It is named after Simon Kuznets (1901-1985), a Russian-born economist and Nobel Prize winner famous for his work on estimating national income. Kuznets also worked on the assumed linkage between national wealth and inequality of the distribution of that wealth (Kuznets and Simon, 1955). His conclusion was that inequality increases with wealth but at a point of inflection inequality declines as social support systems such as a minimum wage, better education etc. take effect (the Inequality Kuznets Curve, IKC). The EKC borrows from this idea by suggesting that as a country (or for that matter any geographical region) passes through a process of industrialisation so the environment inevitably becomes degraded. But as with the IKC it is theorised that at some point the curve turns down – a further increase in wealth leads to a lessening of environmental degradation rather than worsening. There are a number of assumed reasons for this. The population of the region may begin to value the environment more once a degree of wealth is exceeded and as a result of this public concern pressure is placed (legal, moral or otherwise) on the polluters

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to reduce the damage which they are inflicting or to stop altogether (Ekins, 1997; Stern, 2004; Dinda, 2005). Thus new technology and processes are introduced to address environmental damage. Thus in theory the relationship between GDP (or perhaps more appropriately (GDP/capita) and environmental degradation is set out as Figure 4. Once the inflection point is passed there is a ‘delinking’ of economic growth with environmental degradation. Indeed the challenge for a country is to be able to ‘tunnel’ across from the positive slope of the curve to the negative, thereby bringing the point of inflection down. The EKC continues to be an attractive concept in sustainable development, largely because it is a ‘good news’ story. While a country may have to pass through some pain (in environmental terms) there is hope in that continued increases in wealth bring about an improvement in the environment. It is not a theory that discounts or devalues economic growth. On the contrary economic growth is the force that leads to an improvement in the environment.

Environmental damage

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Point of inflection

Worsening environmental damage with wealth

Lessening environmental damage with wealth

Wealth (e.g. GDP/capita)

Figure 4. Environmental Kuznets Curve; the theory.

Perhaps because of the attraction of the EKC theory there have been many attempts to try and see whether it is true but unfortunately the story is a mixed one. There are the expected caveats given that much depends upon the quality of the data and defining what environmental damage means and how it is measured so as to be able to use it as a dependent variable. There are also time lag effects as ‘observed’ environmental damage may be the result of accumulated economic growth in previous years but which years should one choose? There is also a question as to whether the spread along the wealth axis is large enough so as to be able to pick up a point of inflection. In other words, maybe all countries are still on the ‘increasing’ damage segment and statistical tests would not be able to distinguish whether a point of inflection has been

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reached. Unsurprising the attempts to prove EKC have painted many pictures depending upon how these issued are addressed; from proof of EKC at one end of the spectrum to disproof at the other. In order to illustrate the conundrum Figure 5 is an example using data from the 2010 version of the Environmental Performance Index (EPI; epi.yale.edu). The EPI is a somewhat complex composite index that combines a total of 25 indicators, each having a different weighting with regard to influence on the final index. Thus the indicator entitled ‘Greenhouse gas emissions per capita’ has a weighting of 12.5% on the EPI while ‘Agricultural water intensity’ has a weighting of only 0.8%. By way of contrast the HDI has only four basic components although two of them are collapsed into one (‘education’). The three main components of the HDI have equal weighting. The end product of the aggregation in the EPI is a ‘score’ for each country with a maximum of 100 and higher values representing better ‘environmental performance’. The EPI results are presented in league table format akin to that used for the HDI. 8.0

EPI 2010 1st Principal Component

6.0

Singapore Bahrain Iceland Qatar

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4.0

2.0

0.0 0.0

2.0

4.0

6.0

8.0

10.0

Zimbabwe

‐2.0

12.0

14.0

Logarithm GDP/capita Equatorial Guinea

‐4.0 Angola Niger

‐6.0

Predictor Constant LN GDP/capita

Coef -11.8605 1.36146

SE 0.5939 0.06741

t-value and significance -19.97*** 20.20***

R2 (adjusted) = 72% Durbin-Watson statistic (autocorrelation) = 1.32 Figure 5. Environmental Performance Index (2010) as a function of GDP/capita (2007).

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Table 5. Components of the Environmental Performance Index (2010) Objectives

Environmental Health

Policy Categories

Indicators

Environmental burden of disease Air pollution (effects on humans) Water (effects on humans)

Environmental burden of disease

Air Pollution (effects on ecosystem) Water (effects on ecosystem)

Biodiversity & Habitat Ecosystem Vitality Forestry Fisheries

Agriculture

Climate Change Total

Indoor air pollution Outdoor air pollution Access to water Access to sanitation Sulphur dioxide emissions per populated land area Nitrogen oxides emissions per populated land area Non-methane volatile organic compound emissions per populated land area Ecosystem ozone Water quality index Water stress index Water scarcity index Biome protection Marine protection Critical habitat protection Growing stock change Forest cover change Marine trophic index Trawling intensity Agricultural water intensity Agricultural subsidies Pesticide regulation Greenhouse gas emissions per capita (including land use emissions) CO2 emissions per electricity generation Industrial greenhouse gas emissions intensity

Indicator Weight in EPI % 25 6.3 6.3 6.3 6.3 2.1 0.7 0.7 0.7 2.1 1.0 1.0 2.1 1.0 1.0 2.1 2.1 2.1 2.1 0.8 1.3 2.1 12.5 6.3 6.3 100

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The decisions as to what indicators to include, the datasets employed to populate them and the weightings were made by the creators of the EPI. Hence inevitably there is much subjectivity and the EPI is not purely a derivative of the initial datasets but is also a product of human judgement. In order to help minimise the latter the results shown in Figure 5 are based upon a principal component (PC) analysis of the EPI 2010 ‘raw’ datasets rather than the published EPI values. Hence the subjective weightings of the 25 indicators are no longer a consideration. The vertical axis of Figure 5 is the 1st principal component of the analysis. The 1st PC is related to the published EPI values in the sense that higher values of the 1st PC equate to higher values of the EPI (= better environmental performance). The results in Figure 5 suggest a very good statistical fit (R2 more than 70%) between the 1st principal component of the EPI datasets and wealth (GDP/capita), but in this case environmental performance is positively linked to wealth i.e. more wealth brings better environmental performance. A number of ‘outlier’ countries are shown in Figure 5 to give the reader a sense of the geography. However the reader should note that there is no message here which suggests that environmental performance first worsens with wealth before improving as suggested by the EKC. Indeed if anything the picture is about as positive as one could possibly get as any increase in wealth results in better environmental performance, of, if one wishes to take the flip side of this, any increase in environmental performance results in higher wealth. If the EKC is a good news story that Figure 5 must be close to euphoric!

BEYOND GDP? As illustrated in the above sections the GDP has proven to be a useful and robust measure of economic performance. It does what its creators set it out to do – it measures monetary flow within an economy. Some have chosen to use this as a proxy of wealth by dividing GDP by the population size, and in turn this has been a useful input into a variety of scenarios such as human and sustainable development. GDP clearly remains a popular measure for a variety of reasons, even amongst those who purposely create indices such as the HDI to provide an alternative vision of human existence to that which they regard as being encapsulated by GDP. While UNDP initially regarded their use of GDP/capita as being a temporary measure of income it would appear that they

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have not be able to dispense with it some 20 years after the HDI was first created. Thus GDP is a part of an index meant to depose it! The fact that GDP is purely an economic indicator and says nothing in itself about social or environmental aspects of a society has not been lost on many people, and indeed was a central concern in the creation of the HDI. The argument is a straightforward one – managing so as to maximise GDP as a sort of proxy indicator of societal ‘well being’ can be achieved by causing damage to the fabric of society (e.g. by creating great wealth amongst relatively few people and driving others into poverty) and/or the environment (e.g. by widespread pollution and degradation of resources). In practice, of course, governments do not seek to maximise GDP as their only concern but it can indeed be a prime consideration. This perceived dominance of GDP has led to various initiatives to provide modified forms of the index or to adjust the GDP in some way to accommodate other considerations (Bartelmus 1987). An example is the Index of Sustainable Economic Welfare (ISEW) and its more modern relative – the Genuine Progress Index (GPI; Lawn 2003; Talbeth et al. 2007). The success of these initiatives is a matter for much debate, but they are far from replacing GDP. The latest manifestation of this oft-repeated concern is the ‘Beyond GDP’ theme currently being promoted by a variety of international agencies (Fleurbaey, 2009). In 2007 a high-level conference was hosted by the European Commission, European Parliament, Club of Rome, OECD and WWF (www.beyond-gdp.eu) and out of this conference emerged a report and press statements which echoed earlier statements from UNDP (quoted above) when it created the HDI. The following is an excerpt from a press release (IP/09/1286) of the 8th September 2009 available on the ‘Beyond GDP’ website “GDP is used in economic forecasting and allows comparisons of countries and of developments over time. It is conceptually well defined, clear and has stood the test of time. GDP was not intended to be a measure of well-being. It doesn’t pick up on issues that are vitally important to the quality of our lives such as a clean environment, social cohesion or even how happy people are. It is not in itself a sufficient guide for modern policy making that covers social and environmental objectives. This becomes a problem when GDP is understood as the unique yardstick for progress.”

In February 2008 the French President Nicholas Sarkozy appointed a committee, chaired by Joseph Stiglitz and including Amartya Sen as an Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

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advisor, entitled “The Commission on the Measurement of Economic Performance and Social Progress” (CMEPSP; www.stiglitz-senfitoussi.fr/en/index.htm). The work of Amartya Sen, a Nobel Prize wining economist, was one of the prime inspirations behind the creation of the HDI. The CMEPSP produced a report in September 2009. A major spur for this more recent surge in interest of dethroning GDP is not unconnected with the economic collapse of 2008-2010. This was typically associated by some with the greed of those who sought to maximise economic return without contemplation as to what the future might bring. Thus GDP has almost become the symbolic embodiment of this greed with the result that society needs to move beyond it – to somehow leave it behind. Indeed perhaps GDP has replaced the fictional Gordon Gekko from the 1987 film Wall Street who once said “The point is ladies and gentlemen that greed, for lack of a better word, is good”. Gekko was rated as 24th in the table of the top 50 film villains of all time by the American Film Institute (2005) so any association with his sentiment is quite an achievement. But is this fair? Despite all of the points made in this paper it has to be said that the dominance of GDP as a measure of ‘success’ has to be challenged. A narrow focus on maximising GDP can result in many negative impacts within society, although whether these assumed impacts are real or indeed whether they are necessarily negative are admittedly points for discussion. But is this the fault of GDP per se? It has to be remembered that GDP was designed by people to measure something which they thought to be important. It is also worth remembering the obvious - that it is people, and not only politicians, who made the decision to regard economic growth as the priority. As the CMEPSP report puts it on page 8: “GDP is not wrong as such, but wrongly used. What is needed is a better understanding of the appropriate use of each measure.”

Indeed this statement or indeed the arguments and messages within the entirety of the CMEPSP report and associated documentation is extraordinary not so much for what it says but the fact that the authors felt they had to say it yet again given the long history of the GDP and its alternatives (including the HDI, ISEW and GPI). There are so many echoes to the early HDRs written nearly 20 years prior to the CMEPSP that a sense of déjà vu is overwhelming. Yet none of this appears to address the reasons as to why GDP has remained so dominant over that time and ironically the use of GDP in the clarion call of those who question this emphasis on maximising economic growth illustrates

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its continued power. While the GDP may be a key measure employed by governments worldwide the HDI receives far less attention despite its extensive promotion by the UNDP for two decades. How many governments have a stated and practised priority of maximising their HDI? One suspects very few. Will the latest surge in ‘beyond GDP’ change matters? One hopes that it will but the lesson of history to date suggests the opposite. This point was certainly not lost at the ‘Beyond GDP’ conference as the following quotation illustrates: “We should put more emphasis on the fact that there are strong economic interests involved in pursuing economic growth without restriction and in keeping GDP as proxy to well-being.” European Communities (2009 page 180).

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Barriers to going beyond GDP were briefly discussed at the conference and they are indeed formidable. In fact the answer which was promoted to deal with this was also not new – to create new indicators that can be used alongside GDP. Thus for example in the same press release as mentioned above (IP/09/1286) there is a statement that: “A pilot of an environmental index will be proposed in 2010 that will assess progress in the main fields of environmental policy and protection. The index will cover areas such as greenhouse gas emissions, loss of natural landscapes, air pollution, water use and waste generation.”

A sentiment of intention that sounds very similar to the already-existing EPI. But will these ‘parallel’ indicators succeed in providing a balance to the GDP? After all, alternative indicators to the GDP have been around for some time and yet have not been able to change the balance of emphasis in favour of economic growth. Indicators do help to crystallise complexity into simplicity, not by accident but by design. What perhaps does need to be addressed is why some indicators are more successful in terms of their ‘use’ or influence than are others. GDP was born at a time when economies, especially those of the more developed world, were in serious trouble in terms of recession and the threat of another world war and there was a strong and urgent demand for more information to help with management. Thus GDP had an organic birth out of a very clear ‘demand’. By way of contrast the HDI was created to help promote an idea. It did not have a ‘demand-driven’ birth but was the result of a desire

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by a group to promote their vision of human development. Thus the HDI was ‘supply’ driven. The CMEPSP report could also arguably be regarded as ‘supply’ driven even if it was promoted by a senior world leader. Maybe the same can be said of the ‘Beyond GDP’ conference. This contrasting dynamic of demand and supply with regard to indicators has received little if any attention from researchers but maybe that is the angle that needs to be explored rather than repeating the same message and expecting it to succeed this time around. Given that so many indicators exist in the world today it would be interesting to explore the range of influences at play during creation and indeed ‘use’ by policy makers and managers.

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CONCLUSION The reification of indicators is a story of the world today, and GDP is perhaps one of the most successful indicators in terms of its influence. Not only is it employed in its own right but also finds its way into composite indices and provides a convenient means of exploring relationships between other characteristics, such as environmental performance, and wealth. Whether GDP should be included in such indices or whether it should be employed so much as a dependent and independent variable when looking for relationships is another matter. Also one has to question to what extent indicators reflect values or influence them. The dynamic of supply and demand for indicators is an area in need of urgent attention by researchers.

REFERENCES Anand, S. and Sen, A. K. (1994). Human Development Index: Methodology and Measurement. Human Development Report Office Occasional Paper. UNDP, New York. Bartelmus, P. (1987), Beyond GDP: New approaches to applied statistics. Review of Income and Wealth, 33: 347–358 Booysen, F. (2002). An overview and evaluation of composite indices of development. Social Indicators Research, 59 (2): 115-151. Clark C (1940). The Conditions of Economic Progress. McMillan and Co., London.

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Stiglitz JE, Sen A and Fitoussi J-P (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress. Available at www.stiglitz-sen-fitoussi.fr/en/documents.htm Dinda, S. (2005). A theoretical basis for the environmental Kuznets curve. Ecological Economics, 53(3): 403-413. Dowrick, S and Quiggin, J (1997). True measures of GDP and convergence. The American Economic Review, 87(1): 41-64. Ekins, P. (1997). The Kuznets curve for the environment and economic growth: Examining the evidence. Environment and Planning A, 29(5): 805-830. European Communities (2009). Beyond GDP. Measuring progress, true wealth and the well-being of nations. Conference Proceedings19-20 November 2007. Available at www.beyond-gdp.eu Fleurbaey, M (2009). Beyond GDP: The Quest for a Measure of Social Welfare. Journal of Economic Literature, 47(4): 1029-1075 Hartman R and Kwon OS (2005). Sustainable growth and the environmental Kuznets curve. Journal of Economic Dynamics & Control, 29(10): 17011736. Holmes, MJ (2000). Does purchasing power parity hold in African Less Developed Countries? Evidence from a panel data unit root test. Journal of African Economies, 9(1): 63-78. Kelly AC (1991). The Human Development Index: ‘Handle with care’. Population Development Review, 17(2): 315-324. Khanna N and Plassmann, F (2004). The demand for environmental quality and the environmental Kuznets Curve hypothesis. Ecological Economics, 51(3-4): 225-236. Lawn P (2003). A Theoretical Foundation to Support the Index of Sustainable Economic Welfare (ISEW), Genuine Progress Indicator (GPI) and Other Related Indexes. Ecological Economics, 44: 105 - 118. Loup J, Naudet D and Developpement et Insertion Internationale (DIAL) (2000). The state of human development data and statistical capacity building in developing countries. Human Development Report Office Occasional paper. UNDP, New York. Maddison A (1983). A comparison of levels of GDP per capita in developed and developing countries, 1700-1980, The Journal of Economic History, 43(1): 27-41. Moldan B (1997). The Human Development Index. In B. Moldan, S. Billharz and R. Matravers R (Editors), Sustainability Indicators: A report on the

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Project on Indicators of Sustainable Development, John Wiley and Sons, Chichester, pp. 242-252. Murray CJL (1991). Development data constraints and the Human Development Index. Discussion paper no. 25, May 1991. UNRISD, Geneva. Nahman A and Antrobus G (2005). The environmental Kuznets curve: A literature review. South African Journal of Economics, 73(1): 105-120. Peel, DA and Venetis, IA (2003). Purchasing power parity over two centuries: trends and nonlinearity. Applied Economics, 35: 609-617. Rogoff, K (1996). The purchasing power parity puzzle. Journal of Economic Literature, 34: 647-668. Stern DI (2004). The rise and fall of the environmental Kuznets curve. World Development, 32(8): 1419-1439. Stern DI, Common MS and Barbier EB (1996). Economic growth and environmental degradation: The Environmental Kuznets Curve and sustainable development. World Development, 24(7): 1151-1160. Talbeth J, Cobb C and Slattery N (2007). The Genuine Progress Indicator 2006. A tool for sustainable development. Redefining Progress. Oakland, California. . Taylor, MP (1995). The economics of exchange rates. Journal of Economic Literature, 33:13-47. United Nations Development Programme (UNDP). Human Development Reports published annually between 1990 and the present. UNDP, Human Development Report Office, New York. Available at hdr.undp.org/en Vachris MA and Thomas J (1999). International price comparisons based on purchasing power parity, Monthly Labour Review. October 1999: 3-12. World Bank. World Development Reports, published annually between 1977 and the present, World Bank, Washington DC. Available at econ.worldbank.org

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In: Progress in Economics Research. Volume 23 ISBN 978-1-61324-394-7 Editor: Albert Tavidze © 2012 Nova Science Publishers, Inc.

Chapter 5

THE ART OF HOME BUYER ASSISTANCE: DISCOVERING HIDDEN TREASURES Rob Chrane* and Andrew Carswell†

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University of Georgia, Department of Housing and Consumer Economics, Athens, Georgia U.S.A.

ABSTRACT Home buyer assistance programs proliferated throughout the U.S., starting in the early 1990s. Despite the recent housing downturn, several areas of the country offer borrowers some form of home buyer assistance. This reality runs counter to the belief among many that such programs had been eliminated or phased out after the subprime mortgage crisis of the mid-2000s. This type of assistance usually comes in the form of down payment assistance, and is subject to tighter controls than existed with assistance programs in the past. Still, evidence suggests that a communication gap exists between various factions of the housing and real estate communities as to the availability and applicability of such programs to prospective buyers. Consumers subsequently are shut out of these opportunities due to various information gaps that still exist within the housing counseling industry, depriving them of an increase in *

Rob Chrane is currently the President of Workforce Resource, LLC, an online service to housing professionals to promote awareness of, increase access to, and simplify prospective home buyers’ applications for downpayment assistance programs . † Andrew Carswell is currently an Associate Professor at the University of Georgia’s Department of Housing and Consumer Economics.

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Rob Chrane and Andrew Carswell consumer welfare in the process. The authors conclude by providing a series of case studies that help illustrate the increase in housing affordability that working households can attain through the adoption and layering of these home buyer assistance programs.

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INTRODUCTION From the mid-1990s through the mid-2000s, American society experienced a renaissance of sorts, as millions of American households which had previously been excluded from opportunities of obtaining mortgage credit suddenly experienced the benefits of homeownership. These previously “underserved” populations were somewhat stymied by the so-called “barriers to homeownership” that many low- to moderate-income borrowers faced when seeking mortgage credit. Due to the proliferation of subprime and Alt-A mortgage products (those that are above “subprime”, but not considered to be of prime quality) which began in the mid-2000s, many potential home buyers found these so-called barriers torn down to allow for a period in which low- to moderate-income households were given more opportunities for homeownership than had ever been made available before at any point in American history. There seem to be three myths prevalent in the post-subprime world. The first is that the ability for low- and moderate-income populations to achieve homeownership, or more accurately to obtain mortgage financing, have largely dried up. The second myth is that those who actually can obtain credit will not be affected by affordability concerns due to the subsequent house price declines that followed the subprime mortgage crisis. The third myth paints legitimate and successful affordable homeownership programs with the same subprime brush claiming that these programs have played a significant role in the current housing crisis. While these prevailing narratives are attractive to the public, we attempt to lay out the case that there are several opportunities for would-be homeowners with limited means in the post-subprime world, largely through the use of homebuyer assistance programs available through both government and nonprofit sources. Meanwhile, we also make the case that while the stagnation of house prices has helped homebuyers somewhat, other forces have helped to negate any affordability gains that households might have gained through the potential calming influences engendered by declining house prices. The bulk of the rest of the article is comprised of

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illustrations of how such home buyer assistance can provide a jump start to critical households seeking homeownership.

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WORKFORCE HOUSING’S ROLE WITHIN THE AFFORDABILITY DEBATE Despite the housing crisis, it is unlikely to assume that low- to moderateincome households will abandon the prospects of becoming homeowners, given the well-documented salient societal benefits that emanate from becoming a homeowner (Rohe, Van Zandt, & McCarthy, 2002; Rossi & Weber, 1996). It is undoubtedly difficult for such households to gain homeownership opportunities, as well as simply housing opportunities in general. According to the National Low Income Housing Coalition, every county in the United States has a fair market rent higher than that which can be afforded by a family earning the equivalent of the minimum wage for that particular area. In several areas of the country, the problem has become so acute that so-called “living wage” campaigns have sprouted, in part to address the housing affordability issue (Reynolds, 2001). While the discussion which prevailed concerning the subprime mortgage crisis centered largely on lower-income populations, it is undeniable that affordability pressures also are a concern for moderate- and middle-income earners as well. Perhaps recognizing that housing affordability was not simply limited to low-income populations, housing policy makers coined a new term to recognize the affordability concerns of moderate- and lower-middle class households – workforce housing (Bell, 2002; Urban Land Institute, 2009). Members of this group, comprised of civil servants, teachers, firemen, policemen and those within the service industry are often forced to live in outer communities and travel long distances to and from work (Joint Center for Housing Studies, 2006; Schofield and Brown-Graham 2004). Other research has shown the erosion of purchasing power for such critical working sectors over time and the differentials that occur across geographic areas (Walden, 2002, 2001; Walden & Newmark, 1995; Walden & Sogutlu, 2001). Lack of affordable housing close to work makes it difficult for school systems, hospitals and police departments, as well as corporations and small businesses to recruit and retain employees. Those protectors, educators, healthcare and other service workers who are willing to “drive until they qualify” often endure long daily commutes that exacerbate traffic congestion, create air

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pollution and otherwise diminish their quality of life and that of their families and communities. In many metropolitan areas, the amount of households that live outside the central city area and within the outer suburbs create an extra layer of expenses that can prove excessively burdensome to households. When one factors in the volatility of energy prices that it takes to heat and cool the house, the household budget gets stretched even further. On the income side, there are even indications that the salaries of college graduates are going to remain stagnant for several years to come (Murray, 2009), providing an indication once again that some of the populations most traditionally associated with homeownership opportunities in the past may struggle to attain such status in the future. While high loan-to-value (LTV) mortgage originations are usually associated with subprime populations, it is not necessarily the case that the market no longer originates low down payment loans. For the most part, the effect can still be achieved for low- and moderate-income homebuyers with good credit, fully documented incomes and assets. In fact, some households may even be eligible for more than one down payment assistance (DPA) programs. To avoid some of the controversy that accompanied some of the earlier low down payment programs from the subprime mortgage era (Kelly, 2008; Shlay, 2006), the down payment assistance programs made available by states and localities have tighter restrictions attached to them. In order to qualify for such programs, borrowers must have demonstrated good credit, have good jobs and have money left over each month after paying their mortgage, the car and their other living expenses. They usually have savings. They were required to prove they attended certified homebuyer education and they financed their home with a 30 year fixed rate mortgage. Even if they were not required to make a down payment because they qualified for down payment assistance, they were not servicing debt on 100% of the sales price. While the provision of housing credit for low- and moderate-income households has come more to the forefront over the past 15 years, thanks to political support for government programs to support low and moderateincome households and the unfortunate rise (and inevitable fall) of the subprime mortgage market, it is instructive to note that the issue of providing homeownership opportunities for marginalized populations has a long and complicated history. The Community Reinvestment Act, commonly referred to as CRA, was originated in 1977 by the U.S. Congress as a way of forcing banks to address credit-starved areas within their jurisdiction, essentially redressing inequities of such credit provision between low- and high-income

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areas, and rolling back the effects of “redlining” practices carried out by lending institutions within their own communities. Going one step further following the savings and loan crisis of the late 1980s, Congress also forced Fannie Mae and Freddie Mac, the two secondary mortgage market providers serving the housing industry, to allow for an increasing percentage of its mortgage purchase activities within its own portfolio to be within low- and moderate-income neighborhoods. While these provisions were initially intended to bolster the provision of credit to these previously “underserved” populations, these actions quickly became convenient scapegoats for various critics in the wake of the subprime mortgage crisis of the mid- to late 2000s, whether justified or not (Pinto, 2009, U.S. Department of Housing and Urban Development, 2010). Despite that belief, however, Herbert, et. Al (2008) shows that foreclosure rates among homebuyers assisted through respected programs such as the HOME Investment Partnerships Program and the 1 American Dream Downpayment Initiative are not excessive, especially when compared against both subprime borrowers and FHA-insured homebuyers overall, and by all appearances the HOME/ADDI program was successful at helping low-income families to achieve and, most importantly, sustain homeownership.

MARKET REALITIES Despite the best intentions of these programs and initiatives by the federal governments to incentivize opportunities for low-income homeownership, recent events have forestalled efforts at advancing this goal. The tight credit availability brought about by the recent housing crisis, plus the media frenzy which accompanied it, has effectively served to sideline consumers, perhaps even some households that might have been prime candidates for home ownership in more steady times. The First Time Home Buyer Tax Credit, initiated late in the Bush Administration and extended twice by the Obama 1

HOME Investment Partnerships Programs provide formula grants to States and localities that communities use-often in partnership with local nonprofit groups-to fund a wide range of activities that build, buy, and/or rehabilitate affordable housing for rent or homeownership or provide direct rental assistance to low-income people. Each year it allocates approximately $2 billion among states and localities nationwide. The American Dream Downpayment Initiative (ADDI) was created in 2003 to assist low-income first-time homebuyers in purchasing single-family homes by providing funds of up to $10,000 for down payment, closing costs, and rehabilitation carried out in conjunction with the assisted home purchase.

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Administration, expired on April 30, 2010 further depressing housing demand for the low- to moderate-income population. Ironically, in some cases, the federal government itself has proven to be the obstacle to advancing such opportunities for first-time home buyer assistance (Sterngold, 2010). Real estate professionals and most economists agree that entry level home sales will lead the real estate recovery by breaking the gridlock in the move-up market. Sellers of those homes can’t trade up without buyers (National Association of REALTORS, 2009). The number one barrier to homeownership for entry-level borrowers is the lack of sufficient funds for a down payment. As a result, the value of down payment assistance still remains high for many households.

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THE BENEFIT OF HOME BUYER ASSISTANCE PROGRAMS Down payment assistance (DPA) programs began to proliferate in the early 1990s (George K. Baum & Company, 2004). Some programs originated for the primary purpose of increasing the area’s homeownership rate, perhaps cognizant of the social benefits derived from a high home ownership rate (Haurin, Dietz, & Weinberg, 2002). While the notion of housing assistance programs seems confined to the days when local governments’ budgets were flush with tax revenues and housing markets were robust, the truth remains that there are still several billions of dollars of down payment assistance that borrowers have available to them. Even more beneficial, the possibility of layering different types of assistance programs provides the potential borrower with even more potential purchasing power. It is still possible to finance 100% of a home’s sales price minus any minimum cash required by the rules of the assistance program which can range from $500 to perhaps 1% or more of the sales price. Such assistance is made available to low- and moderateincome homebuyers who qualify for a mortgage. Down payment assistance is offered by local and state housing finance agencies, and includes federal funding through the U.S. Department of Housing and Urban Development (HUD) which is then distributed to state and local governments or HUDapproved non-profit organizations. Many times, a 30 year first mortgage (usually an FHA insured loan) can be combined with one or more down payment assistance programs. Such programs are called “soft seconds”, meaning that they require low or no monthly payments and carry very low interest rates. In most cases the loan is

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simply paid in full upon one of three events: a) refinancing the home; b) selling the home; or c) giving up the home as a primary residence. Sometimes these programs involve a conditional grant. The condition to be met usually involves an occupation time limit of a specified number of years. When the condition is met, the loan is then forgiven. There are also innovative methods of receiving assistance that go beyond the simple notion of providing a transfer payment to the new home buyer. The just-concluded home buyer tax credit succeeded in aiding between 200,000 and 400,000 households, according to some estimates (Calmes, 2009; Joint Center for Housing Studies, 2010; Mullins, 2009). Equity sharing programs allow prospective home buyers the opportunity to get into a home that they otherwise could not afford. While more common in Europe, particularly in the U.K., the widespread introduction and proliferation of such programs within the U.S. are hampered by several factors, including the moral hazard inherent in such programs (Caplin, Chan, Freeman, & Tracy, 1997). Community land trusts, originated in the latter part of the 20th century, also offer innovative methods of introducing low- to moderate-income families into decent home ownership opportunities by allowing nonprofit institutions to purchase land meant exclusively for the use of providing affordable housing within the community (Swann, Gottschalk, Hansch, & Webster, 1972). Mortgage credit certificates are another mechanism that state and local governments can allow to encourage homeownership, in that they allow homebuyers to claim a tax credit for some portion of the mortgage interest paid per year. It is a dollar for dollar reduction against their federal tax liability. Because it is a tax credit and not a tax deduction, mortgage lenders will often use the estimated amount of the credit on a monthly basis as additional income to help the potential borrower qualify for the loan. The USDA Rural Development is a guaranteed loan program that allows for no down payment on the part of the buyer, as well as no monthly mortgage insurance.Housing advocates also point out the benefits of employer-assisted housing programs (EAHPs) as a form of employment benefit, noting in particular its attraction to both workers and management in terms of potential reduced turnover, increased productivity and improved quality of life due to decreased transportation time (Snyderman, 2005). While the concept showed much promise in the early 1990s among housing policy advocates (Schwartz, Bartelt, Ferlauto, Hoffman, & Listokin, 1992), the widespread proliferation of EAHPs has never really materialized. It is important to note that there are a number of factors that determine a homebuyer’s eligibility for buyer assistance. Nearly all such programs are distributed primarily by local governmental entities so they are very location-

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specific. They may be restricted to certain census tracts, zip codes, townships, cities, counties, states and even specific neighborhoods or other arbitrary polygons. Most programs also require the sales price of a subject property not to exceed a maximum dollar amount. Almost all programs limit the annual household income, and that limit may be determined in part by the household size. Most programs are designed for first-time homebuyers as defined by HUD. HUD’s definition of first-time homebuyers includes: an individual who has had no ownership in a principal residence during the 3-year period ending on the date of purchase of the property. This includes a spouse (if either meets the above test, they are considered first-time homebuyers. a single parent who has only owned with a former spouse while married. an individual who is a displaced homemaker and has only owned with a spouse. an individual who has only owned a principal residence not permanently affixed to a permanent foundation in accordance with applicable regulations. an individual who has only owned a property that was not in compliance with State, local or model building codes and which cannot be brought into compliance for less than the cost of constructing a permanent structure. For the millions of homeowners who lost their homes to foreclosure, that means that once they rebuild their credit rating, they will be considered firsttimers for these purposes. Other exceptions to the literal meaning of first-time buyer are displaced homemakers who owned a home within the last three years with an ex-spouse. As mentioned earlier, a strong motivation for creating homeownership incentives is to provide affordable housing for those who serve their communities. That includes protectors, educators and medical care personnel, among other critical personnel. Other housing assistance programs are available for special purposes and under certain circumstances tied to relevant public policy concerns. These include such things as energy efficient homes (Energy Star™, EarthCraft™) homes and those with high “visitability” such as “Easy Living”™ certified homes. There have also been programs for Transit Oriented Developments (TODs) and properties within tax increment financing and tax allocation districts (TIFs and TADs). Regarding the property itself, many real estate professionals have a misperception of what type of home qualifies, just as some have

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misperceptions about who these buyers really are. These housing professionals are surprised to learn how many homes may be eligible for one or more assistance programs in a particular community. In fact, according to the 2007 American Housing Survey, about 50% of all the owner-occupied homes in the U.S. could be eligible if listed today. Based on information on single family owner-occupied housing as reported by AHS, and using as a rough guidelines what is known about buyer assistance programs, one can estimate that this translates to roughly 37.5 million units. Savage (2009) determined that 7.6% of renter households, roughly 2.5 million, could afford to buy a home in 2004 but instead opted not to. Some of the most obvious reasons that cause potential home buyers to struggle to afford market-rate housing, include not having enough cash to close, holding too much debt, or not having enough income. These reasons are displayed in Exhibit 1. Taking advantage of down payment assistance programs, however, can have maximum impact for potential home buyers. The study stated that down payment assistance of $7,500 increased the percentage of renters qualifying for a mortgage by 8 percentage points and $10,000 by 12 percentage points. While such outlays definitely come at a cost to local, city, county, and state governments, the outward benefits of stable homeownership communities translates into vast economic development potential. In addition, municipal governments can expect increased tax revenue from the new home buyers. It is also important to note that the housing assistance programs and opportunities mentioned here are not newly proposed initiatives, but rather are already-existing, programs which are currently underutilized. The study first considered modifying the down payment requirement from 5% to 2.5% and even 0%. The reason that this does not have the same efficacy as providing down payment assistance is that, when the down payment is reduced, the amount borrowed must go up, the payments go up and more income is necessary for service and therefore one must qualify for the higher debt. With down payment assistance, however, the mortgage amount remains the same. Reducing the interest rate, even by as much as 3%, has a only a marginal impact on affordability because the single greatest obstacle to homeownership is lack of a sufficient funds for a down payment and closing cost.

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Three Ways to Increase Home Affordability 12% 11% 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% Modify Down Reduce Payment Interest Rate by 3% Who Could Afford a Home in 2004 by Howard A. Savage, US Census Bureau Survey of Income and Program Participation, 2004 American Housing Survey US Census Bureau

1.05M additional households

2.73M additional households

4.16M additional households

Offer Down Payment Assistance ($5,000)

Offer Down Payment Assistance ($7,500)

Offer Down Payment Assistance ($10,000)

Percent Increase

Proprietary and confidential © 2008-2010 Workforce Resource, LLC

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Exhibit 1.

CHALLENGES AND OPPORTUNITIES TOWARD REACHING CONSUMERS There are a lot of moving parts in the U.S. housing supply chain and they fall into one of two categories. There is the real estate business, whose primary function is to execute real estate transactions. The most obvious are real estate agents who market and sell homes, home builders and lenders who finance the purchase of homes. There are also appraisers, home inspectors, title agents and real estate attorneys. These industry actors are extremely competitive, and success is defined by closed sales volume and customer satisfaction. Meanwhile the housing industry includes local development and redevelopment authorities, state and local housing finance agencies, governmental entities, affordable housing advocates, housing counselors, nonprofits, policy makers, regulators, the Federal government and education driven trade organizations. They share in the ultimate goal of housing people. Some even straddle both worlds, but, at times their motivations and attitudes

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clash. There are models of cooperation, but pockets of mistrust based on both experience and misperception remain. One of the most logical ways to communicate these types of programs to the home buying public is through the services of housing counselors. The housing counseling industry has been around for over three decades and has even shown that it can help potential home buyers in various aspects of budgeting and financial preparation over time (Carswell, 2009). In 2008, there were roughly 1.7 million households served by nearly 1,800 counseling agencies located throughout the country, but usually within metropolitan areas (Herbert, Rodger, & Turnham, 2008). Because many low- to moderate-income home buyers rely on these service providers at the initial point of contact, housing counselors presumably reach clients at the right time. Given the recent woes within the housing market, however, many counseling agencies struggle to receive funds for marketing and outreach on these types of assistance programs. It is reasonable to assume also that many counselors themselves do not know about the breadth and scope of these types of programs to begin with, which further dampens public awareness. With proper knowledge of such homeowner assistance programs, the housing counseling community can continue to demonstrate the value of their operations, which would logically allow them to receive more federal funding in the future. Housing counselors will tell you they don’t reach enough home buyers before they commit to a home and a mortgage. Home buyer education classes are filled with accidental beneficiaries of one DPA or another, but they are in attendance only because an education certificate is required for closing. There are many hard working, mission-driven professionals devoted to educating and counseling first-time homebuyers. There can also be an institutional resistance to adopt new technologies for delivering their services in the way that consumers expect to be served today. The counseling industry relies too much on outmoded and inefficient methods to reach not only its clients, but the primary influencers of its clients, real estate agents and mortgage lenders. The current state of the housing industry presents a unique opportunity for housing counselors and program administrators to re-engage real estate professionals. Because of the housing downturn, commissioned sales people are looking for more business. They are looking for new solutions and open to revisiting ones forgotten during the boom years. Cost-effective and efficient tools are available to overcome some of the challenges that discouraged REALTORS® and lenders from serving this market. Counseling agencies and buyer assistance program administrators need to repackage their offerings and

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make them more user friendly, which can then translate to more real estate traffic as well. CredAbility (formerly Consumer Credit Counseling Service of Greater Atlanta). a national, non-profit consumer credit agency, serves as a model for the counseling industry in this regard. The agency provides counseling and education around the clock in both English and Spanish, both online and by telephone. The agency also offers in-person counseling at 25 offices located across the southeastern U.S. CredAbility just launched a nationwide online pre-purchase certification program also providing 24/7 bilingual toll free support. This represents what today’s consumers want and expect. For those agencies that are not as well-heeled financially as CredAbility, there are other avenues toward providing outreach. Another way for housing counselors to reach their target audience is to leverage the power of Web 2.0 including social networking tools. There are more free and low cost tools to communicate on a massive scale than ever before. First-time home buyers are wired and so are their primary influencers, REALTORS®. Because nearly nine out of ten consumers start their home search online, according to the National Association of REALTORS® (2009), the opportunity to use social networking and other online technologies to help better communicate these opportunities to first-time home buyers has never been more within reach.

CASE STUDIES To demonstrate the power of these types of home buyer assistance programs, a series of case studies have been created. These case studies intend to show that several borrowers can boost their purchasing power through utilization of programs currently at their disposal. The situation portrayed in Exhibit 2 shows the finances of a situation that typifies several households in America. In this example, an 88 year-old woman lives on a limited fixed income of only $965 per month. Her 60 year-old daughter lives with her and works as a housekeeper. She makes $1,275 per month. Their current apartment is being condemned and they have 60 days to vacate the premises. They have found a home nearby and closer to public transit, but the purchase price is $180,000.

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This scenario is an extreme example of layering a number of DPAs to significantly increase the amount of equity into the transaction thereby reducing the amount of mortgage financing along with the principal and interest payment. This many programs were available due to both the buyer’s circumstances and the property location. The buyer was relocated from public housing slated to be demolished and household income was low. The subject property is located in a targeted Census tract and a former enterprise zone. This structure also has the effect of enhancing the first mortgage lender’s risk positions by its low loan to value (LTV) ratio.The buyer assistance programs included:

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a 30-year fixed rate mortgage equal to 38% of the sales price with a grant 2 equal to 4% of the sales price to be used for prepaid expenses and closing cost funded through mortgage revenue bonds (MRBs) issued by the City of Atlanta. (Home Atlanta from Atlanta Authority/Urban Residential Finance Authority (URFA)); down payment assistance through a program called Opportunity Down 3 Payment Assistance Program equal to 20% of the sales price in the form of a soft second mortgage, meaning 0% interest and no monthly payments until the home is refinanced, sold or no longer owneroccupied; down payment assistance through the Atlanta Affordable Homeownership Program of $10,000 in the form of another soft second mortgage with the same terms. This funding was made possible through HUD’s American Dream Downpayment Initiative (ADDI). Technically there can only be one “second” so one of the program administrators agrees to be in a third or lower lien position.

2

Pre-paid expenses include current property tax pro-rations, first year’s homeowners insurance policy and escrow deposits for future property taxes and insurance. 3 This program is now capped at 10% of sales price. Progress in Economics Research, edited by Albert Tavidze, Nova Science Publishers, Incorporated, 2011. ProQuest Ebook

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Exhibit 2 WITH ASSISTANCE

WITHOUT ASSISTANCE

SALES PRICE

$180,000

$180,000

LESS: 4% GRANT OF LOAN AMOUNT

$2,752

$0

LESS: OPPORTUNITY BOND ASSISTANCE

$36,000

$0

LESS: AAHOP/ADDI DOWN PAYMENT

$10,000

$0

LESS:OTHER- AHA ($20,000), MAP ($35,000), EDI ($12,500)

$67,500

$0

AMOUNT FINANCED * funds applied first to CC & Pre-paids

$69,200

$174,600

INTEREST RATE

6.50%

7.125%

FIRST MORTGAGE TERM

30

30

MONTHLY P & I PAYMENT

$437

$1,176

MONTHLY PMI

NA

$86

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MONTHLY T&I ESCROW

$285

$285

MONTHLY MORTGAGE PAYMENT

$722

$1,547

MINIMUM INCOME REQUIRED (33% DTI)

$26,255

$54,600

CLOSING COST AND PRE-PAIDS

$5,452

$7,938

CASH TO CLOSE

$116,252

$13,338

LESS AVAILABLE DPA AND GRANTS

$116,252

$0

NET CASH TO CLOSE

$0

$13,338

118

Rob Chrane and Andrew Carswell Additional equity was provided in the form of soft seconds through: o the Atlanta Housing Authority (AHA) of $20,000; o the City of Atlanta Mortgage Assistance Program (MAP) funding of $35,000 through a grant to the city by the Enterprise 1 Foundation (a non-profit low-income housing advocate) ; and o EDI funding of $12,500, which was comprised of relocation funds available to residents of public housing who are being relocated due to the planned demolition of their long-term RESIDENCE.

In the second case study (shown in Exhibit 3), a public school teacher lives fairly comfortably on her $47,500 annual salary in a one-bedroom apartment. She has been living within her means, and has been able to save about $12,000. Her elderly parents moved to the U.S. from their homeland on the other side of the world to live with her. In conducting a home search that can accommodate all parties involved, the teacher finds a suitable home which includes space for an office, at a price of $249,900. This represents a scenario more commonly seen in urban areas. The programs utilized here include: Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

a 30 year fixed rate mortgage equal to 80% of the sales price with a grant equal to 4% of the sales price to be used for prepaid expenses and closing costs funded through mortgage revenue bonds (MRBs) issued by the City of Atlanta; down payment assistance equal to 10% of the sales price in the form of a soft second mortgage, meaning 0% interest and no monthly payments until the home is refinanced, sold or no longer owneroccupied; and down payment assistance through ADDI of $10,000 in the form of another soft second mortgage with the same terms. Technically there can only be one “second”, so one of the program administrators agrees to be in a third lien position.

1

At one point the City of Atlanta Bureau of Housing issued an RFP to market this program because the funds were not being used.

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Exhibit 3 WITH ASSISTANCE

WITHOUT ASSISTANCE

SALES PRICE

$249,900

$249,900

LESS: 4% GRANT OF LOAN AMOUNT

$7,996

$0

LESS: OPPORTUNITY BOND ASSISTANCE 2nd

$24,990

$0

LESS: ADDI DPA

$10,000

$0

LESS:

$0

$0

AMOUNT FINANCED * funds applied first to CC & Pre-paids

$199,900

$242,400

INTEREST RATE

6.50%

7.125%

TERM OF FIRST MORTGAGE

30

30

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PRINCIPAL AND INTEREST PAYMENT

$1,264

$1,633

MONTHLY PMI

NA

$119

MONTHLY T&I ESCROW

$365

$365

MONTHLY MORTGAGE PAYMENT

$1,629

$2,117

MINIMUM INCOME REQUIRED (43% DTI)

$45,875

$57,350

CLOSING COST AND PRE-PAIDS

$8,996

$10,271

CASH TO CLOSE

$58,996

$17,771

LESS AVAILABLE DPA AND GRANTS

$42,986

$0

NET CASH TO CLOSE

$16,010

$17,771

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In the final case study (Exhibit 4), an Atlanta city municipal worker and single father earning $45,500 per year decides to become a first-time homebuyer. He wants to live close to work and enroll his son in a new charter school located just blocks from his office. He finds a condominium downtown where he can walk his son to school on his way to work. The sales price is out of his range at $249,000, but he is considering borrowing against his 401K plan in hopes of qualifying for a smaller mortgage. This also represents another typical urban scenario and includes the following solutions: a 30-year fixed rate mortgage equal to 58% of the sales price with a grant equal to 4% of the sales price to be used for prepaid expenses and closing cost funded through mortgage revenue bond (MRBs) issued by the City of Atlanta; ADDI down payment assistance of $10,000 in the form of another soft second mortgage with the same terms. Technically there can only be one “second” so one of the program administrators agrees to be in a third lien position. (Atlanta Affordable Homeownership Program; equity of $94,000 (58% of the sales price) that was funded by the Eastside Tax Allocation District program. This funding was provided by the City of Atlanta as part of a tax incentive package to encourage development in targeted areas. This incentive includes funds to produce mixed income housing (an affordable housing component within a market rate development). In this case, the sales price was bought down to $155,000 from a market rate price of $249,000. Because the $94,000 subsidy is credited to the developer, the contract terms reflect a market rate transaction. The details of the transaction are fully transparent to all parties including the first mortgage lender.

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Exhibit 4 WITH ASSISTANCE

WITHOUT ASSISTANCE

SALES PRICE

$249,000

$249,000

LESS: 4% GRANT OF LOAN AMOUNT

$5,576

$0

LESS:

$0

$0

LESS: AAHOP/ADDI DOWN PAYMENT

$10,000

$0

LESS: EASTSIDE TAD FUNDS

$94,000

$0

AMOUNT FINANCED * funds applied first to CC & Pre-paids

$144,000

$241,500

INTEREST RATE

7.00%

7.375%

TERM OF FIRST MORTGAGE

30

30

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PRINCIPAL AND INTEREST PAYMENT

$958

$1,668

MONTHLY PMI

NA

$120

MONTHLY ESCROW (Condo- Taxes & HOA only)

$630

$630

MONTHLY MORTGAGE PAYMENT

$1,588

$2,418

MINIMUM INCOME REQUIRED (43% DTI)

$44,316

$57,433

CLOSING COST AND PRE-PAIDS

$7,379

$7,379

CASH TO CLOSE

$112,379

$32,279

LESS AVAILABLE DPA AND GRANTS

$109,576

$0

NET CASH TO CLOSE

$2,803

$32,279

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CONCLUSION AND DISCUSSION Too many of qualifying households are simply unaware that they have options at very attractive terms. By making home buyer assistance more accessible, the pool of qualified homebuyers can be greatly expanded and these buyers – mostly first-time, low and moderate-income individuals and families – will be able to find homes they can afford to buy and keep. It is fairly easy to see that a large collection of actors benefit from such homeownership assistance programs. Consumers not only increase their purchasing power, but position themselves nicely to become a stable part of a community through a homeownership opportunity. Real estate professionals benefit through consummating sales transactions that otherwise could not have taken place without the presence of such programs. These beneficiaries also include manufacturing plants that have a direct stake in the housing industry, such as gypsum, concrete and lumber producers, just to name a few. Small businesses benefit from the peace of mind in knowing that a stable population dominated by strong communities of long-term homeowners can become customers of their products. Local and state governments benefit from the extra property taxes generated by a higher homeownership rate, as well as the social and economic benefits associated with the ability to recruit major corporations to their communities. These major employers benefit by being able to recruit and retain a skilled workforce. Hospitals remain viable because they can attract nurses and medical technicians and schools have more teachers they can hire. Better public schools in the urban core attract families back to the city who can now afford a home of their own. Less time spent commuting relieves traffic congestion and pollution and provides parents more time to participate in their children’s school and recreational activities. The case has been made for the importance of providing affordable workforce housing. This need has been around for quite some time and will continue to be an issue long after the housing market recovers from its current doldrums. The need for qualified buyers to absorb the overwhelming supply of housing has never been greater than today.

REFERENCES Bell, C.A. (2002). Workforce housing: The new economic imperative? Housing facts and findings, 4(2), 3-4. Retrieved June 21, 2010 from

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http://www.knowledgeplex.org/kp/text_document_summary/article/relfile s/hff_0402_complete.pdf. Calmes, J. (2009, October 7). Democrats may extend tax credit for homes. New York Times. Downloaded June 28, 2010 at: www.nytimes.com/2009/10/08/us/politics/08stimulus.html?_r=2. Caplin, A., Chan, S., Freeman, C., & Tracy, J. (1997). Housing partnerships: A new approach to a market at a crossroads. Boston, MA: MIT Press. Carr, K., Herbert, C., Lam, K., & Makhkamov, Y. (2008). Rates of foreclosure in HOME and ADDI Programs. Washington, DC: Concentrance Consulting Group. Carswell, A.T. (2009). Does housing counseling change consumer financial behaviors? Evidence from Philadelphia. Journal of Family and Economic Issues, 30(4), 339-356. George K. Baum & Company. (2004, February 15). The history of down payment assistance. Downloaded June 2, 2010 at: www.gkbaum. com/housing/topicalReports/history_of_downpayment_assistance.pdf. Haughey, R.M. (2001). Challenges to developing workforce housing. Washington, DC: Urban Land Institute. Available at: http://www.uli.org/ResearchAndPublications/Reports/~/media/Documents /ResearchAndPublications/Reports/Workforce%20Housing/DevWorkforc eHousing.ashx Haurin, D.R., Dietz, R.D., & Weinberg, B.A. (2002). The impact of neighborhood homeownership rates: A review of the theoretical and empirical literature. Housing Policy Debate, 13(2), 119-151. Herbert, C.E., Rodger, C.N. & Turnham, J. (2008). The state of the housing counseling industry. Rockville, MD: Abt Associates. Herbert, C.E., & Tsen, W. (2007). The potential of downpayment assistance for increasing homeownership among minority and low-income households. Cityscape, 9(2), 153-184. Joint Center for Housing Studies. (2010). State of the nation’s housing 2010. Cambridge, MA: Harvard University. Joint Center for Housing Studies. (2006). America’s rental housing: Homes for a diverse nation. Cambridge, MA: Harvard University. Kelly, A. (2008). “Skin in the game”: Zero downpayment mortgage default. Journal of Housing Research, 17(2), 75-99. Mullins, L. (2009, November 6). Expanded first-time home buyer tax credit becomes law. U.S. News and World Report. Downloaded June 28, 2010 at: money.usnews.com/blogs/the-home-front/2009/11/06/expanded-firsttime-home-buyer-tax-credit-becomes-law.html.

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Murray, S. (2009, May 9). The curse of the class of ’09. Wall Street Journal. Available at: http://online.wsj.com/article/SB124181970915002009.html National Association of REALTORS. (2009, November 13). NAR survey shows first-time home buyers set record in past year. Downloaded June 28, 2010 at: www.realtor.org/press_room/news_releases/2009/11/ survey_record National Low Income Housing Coalition. (2009, April). Out of reach 2009: Persistent problems, new challenges for renters. Washington, DC: NLIHC. Downloaded June 28, 2010 at: www.nlihc.org/oor/oor2009/oor 2009pub,pdf. Pinto, E. (2009, Autumn). Yes, the CRA is toxic. City Journal, 19(4). Reynolds, D. (2001). Living wage campaigns as social movements: Experiences from nine cities. Labor Studies Journal, 26(2), 31-64. Rohe, W., Van Zandt, S., & McCarthy, G. (2002). Social benefits and costs of homeownership, in Retsinas, N. (ed.), Low-Income Homeownership, Examining the unexamined goal. Boston, MA: Harvard University Joint Center for Housing Studies. Rossi, P.H., & Weber. E. (1996). The social benefits of homeownership: Evidence from empirical surveys. Housing Policy Debate, 7(1), 1-36. Savage, H.A. (2009, May). Who could afford to buy a home in 2004? Current Housing Reports. Washington, DC: U.S. Census Bureau. Schofield, J. H., and Brown-Graham, A.R. Locally initiated inclusionary zoning programs. Report, School of Government, University of North Carolina, Chapel Hill, NC: UNC Chapel Hill, 2004. Schwartz, D.C., Bartelt, D.W., Ferlauto, R., Hoffman, D.N., & Listokin, D. (1992). A new urban housing policy for the 1990s. Journal of Urban Affairs, 14(3-4), 239-262. Shlay, A. (2006). Low-income homeownership: Dream or delusion? Urban Studies, 43(3), 511-531. Snyderman, R. (2005). Making the case for employer-assisted housing. NHI Shelterforce, 141. Available at: http://www.nhi.org/online/issues/141/ EAH.html. Sterngold, J. (2010, January 21). Reviving down-payment assistance faces opposition. Bloomberg BusinessWeek. Available at: http://www. businessweek.com/news/2010-01-21/reviving-down-payment-assistanceprogram-faces-fha-opposition.html. Swann, R., Gottschalk, S., Hansch, E.S., & Webster, E. (1972). The community land trust: A guide to a new model for land tenure in America. International Independence Institute.

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U.S. Department of Housing & Urban Development. (2010). Report to Congress on the root causes of the foreclosure crisis. Washington, DC: Author. Urban Land Institute. (2009). Priced Out: Persistence of the workforce housing gap in the San Francisco Bay Area. Washington, DC: Urban Land Institute. Walden, M. (2002). Absolute and relative consumption of married U.S. households in 1960 and 1996: The Cleavers meet the Taylors. Journal of Consumer Affairs, 36(1), 77-99. Walden, M. (2001). Are two incomes needed to prosper today? Evidence from the 1960s to the 1990s. Journal of Consumer Affairs, 35(1), 141-161. Walden, M., & Newmark, C.M. (1995). Interstate variation in teacher salaries. Economics of Education Review, 14(4), 395-402. Walden, M., & Sogutlu, Z. (2001). Determinants of intrastate variation in teacher salaries. Economics of Education Review, 20(1), 63-70.

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In: Progress in Economics Research. Volume 23 ISBN 978-1-61324-394-7 Editor: Albert Tavidze © 2012 Nova Science Publishers, Inc.

Chapter 6

DISRUPTION MANAGEMENT IN DISTRIBUTED ORGANIZATIONS: A COOPERATIVE REPAIR APPROACH FOR REACTIVE PLANNING AND SCHEDULING

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A. Cauvin∗, S. Fournier† and A. Ferrarini‡ LSIS UMR CNRS 6168 – Paul Cézanne University Domaine Universitaire de St Jérôme, Marseille 13 397, France

ABSTRACT In the current financial and economic hyper-competitive context, the control of disruptions is becoming a major issue to tackle in the management of organizations. Problems from industrial organizations are getting more and more complex according to their topographic distribution and the variety of tasks to be achieved. This complexity makes solving organizational problems difficult, especially tasks planning. The first aspect of this issue concerns the complexity of disruption management in order to be closer to the reality of industrial systems. The second aspect deals with human factors. Indeed, most ∗

Tel : +33 (0)4 91 05 60 21 – Fax : +33 (0)4 91 05 60 33 Email: [email protected] † Email: [email protected] ‡ Email: [email protected]

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130

A. Cauvin, S. Fournier and A. Ferrarini current methods of scheduling management mainly deal with clearly defined physical and temporal constraints. The human factor in rescheduling is generally not considered as essential and therefore is not taken into account. The first objective of the approach consists in minimizing the organizational impact on the existing plans or schedules. The second objective consists in minimizing impacts on human resources by changing as little as possible their working organization and their forecast frameworks. Usual solutions propose to dynamically revise schedules or plans. However online generation of plans for dealing with environment uncertainty does not usually dynamically integrates the degree of impact of the new plans on the organisation of industrial systems. Consequently the need for a specific approach for managing disrupting events appears. This approach must take into account the distributed nature of the new forms of organizations, respecting the actors' autonomy. Moreover, it must focus on the impacts of the disruption recovery solutions, particularly on the human organizational aspect. Both these aspects lead the solving process to “fix” the actual schedule rather than to compute a completely new solution. The search for minimizing the disruption impacts involves the implementation of cooperative decision processes that actors would naturally develop. This process is based on cooperative strategies between actors using various arrangements of repair operations on task attributes. Scheduling repair operations and solving strategies are adapted to this growing complexity. The resulting multi-agent system operates the repair behaviours in order to determine the solution which minimizes the disruption impact and proposes it to the final human decision maker. This method has been applied to production workshops inside a company, in the context of inter-enterprise situations, to topographically distributed systems such as building site organization and to maintenance operations in aeronautics. Actors, resources, and disruptions were defined at each level according to the problem specific needs.

Keywords: Disruption management, Reactive scheduling, Repair operations, Distributed organizations, Multi-Agent.

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1. INTRODUCTION

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1.1. Context and Problematic Within a more competitive financial and economic environment, the survival of companies request better effort and harshness in management of operations planning and organization. Moreover, the current economic context leads companies to deal with highly restrictive deadlines and labour fall (Clausen et al., 2001). In this context, the management of disruptions becomes a major issue to tackle in management of socio-technical systems (Yu and Qi, 2004). Disruptions lead to important cost increase. Socio-technical organization problems are mostly complex due to their topographic distribution and the variety of tasks to be achieved. This complexity increases the difficulty of solving organizational problems especially on tasks planning. It also highlights the interest of helping decision makers in disruption management of pre-established planning. Decision making in planning, management and organization becomes then closer to the production operations themselves. This trend can be noticed in large companies as well as in small businesses, for workshops, supply chains and also for building site organization. The complexity of the disruption management problem needs to be taken into account in order to be closer to the reality of industrial systems (tasks with nonlinear constraints, human management, interruptibility - or not - of undertaken actions ...). This complexity increases the difficulty of solving organizational problems especially on tasks planning. This complexity also highlights the interest of helping decision makers in disruption management of preestablished planning. In order to minimize disruptions impact, an approach based on agent paradigm is proposed. This approach implements an agent-based modelling of socio-technical organizations, and a distributed cooperative problem solving method leading to the proposal of solutions minimizing disruption impacts, through a multi-agent simulation. This approach was initially developed for workshop rescheduling, and has then been extended and applied to the supply chain management problem (Cauvin et al., 2009). The first point concerns the development of the method of disruption management based on the distributed recovery of the planning. Such recovery consists in defining cooperative repair behaviours between actors. The second point concerns the modelling of problems resulting from disruptions based on

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the agent paradigm. Finally, a third point is based on the simulation of repair behaviours by a multi-agent system in order to determine the solution which minimizes the disruption impact on the system. The solution will be proposed to the human decision-maker to make the final decision.

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1.2. Objectives of the Works The approach presented in this chapter is based on previous work about a Distributed Cooperative Problem: the problem is transposed and modelled using the multi-agent paradigm (Ferber, 1999). This approach is based on an organizational model of industrial systems whereas all the actors and resources of the system have a sufficient decisional autonomy to manage the occurrence of disruptions as soon as possible. This method has been applied on production shops inside enterprises (Tranvouez et al. 2001) and in the context of inter-enterprise level (for the management of supply chains) (Tranvouez and Ferrarini 2006). Actors, resources, and disruptions were defined at each level according to the problem specific needs. This chapter presents a method to deal with complex rescheduling or replanning problems, focusing more particularly on taking into account the specific context of distributed and complex organizations. The increased complexity results from several factors. The first one is the intrinsic complexity of operating tasks: they can be interruptible or not. The second factor relies on the diversity of resources that support the realization of the task: raw materials, tools, human resources (workers), etc.

2. DEFINITION OF “TASK” AND “DISRUPTION” Before presenting repair operations and associated strategies, it is necessary to define the seminal concepts used in the method of disruption management and in the model developed for solving the problems resulting from disruptions in the context of complex organizations.

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2.1. Task Definition

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Let us consider a task as an action to be carried out in order to achieve the organization objectives. A Task is defined as an atomic element. A task Ti is identified by a name and several attributes: ID( task name, unique) Temporal attributes: o Length: the time necessary to perform the task o Achievement interval: period during which the task should be performed o Programmed schedule ƒ Start date ƒ End date o Temporal margins ƒ Start date at the earliest/latest (startdateearliest/startdatelatest) ƒ End date at the earliest/latest (enddateearliest/enddatelatest) o Constraints of precedence (successive tasks) Physical attributes (capacity and resources required): o Resources ƒ Tools (for example: hammer, wrench, etc.) ƒ Working facilities (for example: lift truck, scaffolding, etc.) ƒ Consumables (for example: water, fuel, detergents, etc.) ƒ Materials / components (for example: metal blooms, paint, cement, electric cables, etc.) Actors: o Skills: necessary to perform the task o Number: actors needed for performing the task Structural attributes: o Quantity: the amount of products the task has to process / has processed o Interruptible: can the task be interrupted without affecting the result of its execution? (yes / no) It can be noticed that the Structural Attributes are particular ones: a qualitative attribute defines the capacity of task to be interrupted (ex.: assembling a motor) or not (ex: casting a concrete slab). Moreover, a task produces a quantifiable result. This result can be used to size up task achievement.

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Theen, a task caan be represented as thee following n-uplet: n { ID D; [ time{len ngth , achievement intervaal, programmeed schedule { Start date, End E date}, temporal t marggins {(startdaateearliest / sttartdatelatest, enddateearliest / enddateelatest}, consttraints of prrecedence }] resources {ttools , faciliities working g , consumables , materials }; {actor(s) ( skill(s), numbber) }; quantitty { to achieeve, processedd}; interruptibble (Boolean) }. } Figure 1 presentss the temporaal margin conccept. A task must m be execuuted inside itts achievemennt interval. Thhis interval cannnot be modiffied. A task must m begin between b startddateearliest annd startdatelateest. A task must m end betw ween enddateeearliest and ennddatelatest. Tem mporal constraaints are consiidered:

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[ Ti.startdateearliiest, Ti.enddateelatest] ⊆ Ti.A AchievementInnterval Ti.sstartdateearliesst ≤ Ti.startdattelatest Ti.sstartdate ∈[ Ti.startdateearliest, Ti.startdattelatest] Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest] Ti.sstartdateearliesst + Length ≤ Ti.enddateearliest Ti.sstartdatelatest + Length ≤ Ti.enddatelatestt

Figure 1. Definition of temporal t margiins.

2.2. Deefinition and d Types of Disruptions D s d is defined d as a situation duriing the executtion of a taskk in A disruption which th he deviation of o the original planning is siignificant enouugh to amend the

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schedule. Disruption is not necessarily the result of a specific event (Clausen et al. 2001); it may result from a slow drift of certain parameters in the supervision of operations (unusual slowness of some workers, deviation of technical performances of machines ...) or a combination of multiple factors not always identifiable (difficulty of achieving a task with return multiple search tools or materials …). The following types of disruptions are considered as internal or external. Internal disruptions result in failures occurring in the organization and consequently affect the performance of tasks, depending on actors (absence, lack of skills …) and resources (broken tools, equipment failure, lack of consumables, lack of materials ...). External disruptions are not due to the organization of the complex system but due to external constraints from outside the system such as weather (weather too bad to complete tasks done in the open air), regulation and codes (refusal for non-compliance with safety rules …) or other (strike, theft of material ...). (Cauvin, 2005) classifies possible events that may occur during the life of complex systems. She points out five categories. Disruptions that affect the operational process result mainly from problems in the availability or the reliability of resources the process uses. Disruptions caused by the suppliers of the operational process result in defects in the procurement of material or immaterial inputs. Disruptions caused by the customers of the operational process result from variations of the customer demand. Disruptions in the operation of the information system affect the transmission of data. Disruptions in the operation of the decision system result in untimely decisions. In the regular operating mode, the behaviour of the system follows the forecasts. As soon as a disruption is detected until the end of the implementation of the reaction, the system works in a disturbed mode. In fact, the system deviates from the initial objectives. It is thus necessary to confer recovery capacities to the system in order to allow it to deal efficiently and quickly with the disruptions which occur. These capacities involve repair operations.

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3. REPAIR OPERATIONS A repair operation can be defined as a local and limited modification of a previously computed schedule (Zweben et al. 1993). Initially these operations consisted in time shifts (right or left) or tasks permutations within one or more production plans. Repairing scheduling is particularly adapted to solve incomplete scheduling problems (not taking into account tasks) or partially deficient (violation of time constraints), resulting for example from disruptions of the system. Furthermore, this approach has already been applied to distributed scheduling (Neiman and Lesser 1996). Repair operations make it possible to limit the re-scheduling to a minimal number of actors by favouring co-operation and negotiation. As regards disruption management in industrial systems (from production shops to supply chains), six types of repair operations are characterized in two classes: local operations (left or right shifts, left or right moves, permutation, decomposition, trade) or co-operative operations (transfer, exchange, parallel permutation, collaborative trade) (Cauvin et al., 2009). These operations mainly take into account the temporal dimension (modification of the planning) and the level of the end product inventory. To extend this point of view, repair operations that take into account additional dimensions are defined. In fact, these operations must be differentiated according to characteristics of tasks (qualitative or quantitative) and to disruption typologies. The enlargement of the scope and then of repair operations concerns more particularly the qualitative characteristic (interruptible or uninterruptible tasks) and physical attributes (resources, tools, equipment, materials, indirect materials) according to the level of their stock. Repair operations depend on: 1) time: shift, move, permutation, transfer, exchange, parallel permutation, decomposition; 2) actors: transfer, exchange 3) level of stock of material resources: local operations (picking in a local stock: trade), then in the stock from another site (co-operation: collaborative trade); 4) level of performed quantities: trade, collaborative trade, decomposition.

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Thee following suub-sections describe the diffferent operators that have been defined. Each sectionn presents thee operator andd explains brieefly its algoritthm he names of thhe task attributtes previously defined. using th

3.1. Riight Shift

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a to a value α on the Thee operator shiifts a task Ti to the right according temporaal axis, in the limit of its achievement a innterval. It is a very small shift inside the t defined teemporal marggins. The task attributes startdate s and the enddatee are modifiedd. The operattor returns thee modified task. As shownn in Figure 2, 2 in this exam mple, the operaator RightShift ft is applied onn the task T1.

Figure 2. Right Shift.

R α Ti RightShift Ti.sstartdate = Ti.sstartdate + α Ti.eenddate = Ti.ennddate + α h with [Ti.startdate, Ti.enddate] ⊆ Ti.A AchievementIInterval and d Ti.sstartdate ∈ [Ti.startdateearliest, Ti.startdattelatest] d and Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest]

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3.2. Leeft Shift Thee operator shiifts a task Ti to the left according to a value α on the temporaal axis, in the limit of its achievement a innterval. It is a very small shift inside the t defined teemporal marggins. The task attributes startdate s and the enddatee are modifiedd. The operattor returns thee modified task. As shownn in Figure 3, 3 in this exam mple, the operaator LeftShift is i applied on thhe task T5.

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Figure 3. Left Shift.

L α Ti LeftShift Ti.sstartdate = Ti.sstartdate - α Ti.eenddate = Ti.ennddate – α h with AchievementIInterval [Ti.startdate, Ti.enddate] ⊆ Ti.A d and Ti.sstartdate ∈ [Ti.startdateearliest, Ti.startdattelatest] d and Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest]

3.3. Riight Move t the right onn the temporal axis, in the liimit Thee operator movves a task Ti to of its acchievement intterval but outsside its temporral margins. The T task attribuutes

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startdatte and the ennddate are moodified as weell as temporral margins. The T operatorr returns the modified m task.. As shown inn Figure 4, in this t example, the operatorr RightMove is applied on thhe task T1.

Figure 4. Right Move.

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Thee function Preev (Tj) gives the t previous taask of task Tj on the tempooral axis. Thee function Nexxt (Tj) gives thhe next task off task Tj on thee temporal axiis. Forr example, in Figure F 4: Prevv (T2) = T1 andd Next (T2) = T3 R α Ti RightMove Ti.sstartdate = Ti.sstartdate + α Ti.eenddate = Ti.ennddate + α Ti.sstartdateearliesst =Prev (Tj).eenddate Ti.sstartdatelatest = Next (Tj).beegindate - Ti.leenght Ti.eenddateearliest =Ti. startdateeearliest + Ti.llenght Ti.eenddatelatest = Tj. startdatellatest + Ti.lengght h with [Ti.startdate, Ti.enddate] ⊆ Ti.A AchievementIInterval d and Ti.sstartdate ∈ [Ti.startdateearliest, Ti.startdattelatest] d and Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest]

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3.4. Leeft Move Thee operator moves a task Ti to the left on the temporal axis, in the liimit of its acchievement intterval but outsside its temporral margins. The T task attribuutes startdatte and the ennddate are moodified as weell as temporral margins. The T operatorr returns the modified m task.. As shown inn Figure 5, in this t example, the operatorr LeftMove is applied on thhe task T5.

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Figure 5. Left Move.

L α Ti LeftMove Ti.sstartdate = Ti.sstartdate - α Ti.eenddate = Ti.ennddate - α Ti.sstartdateearliesst =Prev(Tj).ennddate Ti.sstartdatelatest = Next(Tj).begindate - Ti.leenght Ti.eenddateearliest =Ti. startdateeearliest + Ti.llenght Ti.eenddatelatest = Tj. startdatellatest + Ti.lengght h with [Ti.startdate, Ti.enddate] ⊆ Ti.A AchievementIInterval and d Ti.sstartdate ∈ [Ti.startdateearliest, Ti.startdattelatest] and d Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest]

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3.5. Peermutation Thee operator perrmutes task Ti with task Tj on the tempporal axis, in the limit off their achieveement intervall. The task atttributes startddate, the endddate and tem mporal marginn (startdateeaarliest, startdaatelatest , endddateearliest and enddateelatest) are moodified. The operator o returnns the two moodified tasks. As shown in i Figure 6, inn this example,, the permutattion is done onn tasks T3 and T5.

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Figure 6. Permutation.

Ti Permutation P Tj Ti.sstartdate = Tj.sstartdate Ti.eenddate = Tj.ennddate Tj.sstartdate = Ti.sstartdate Tj.eenddate = Ti.ennddate Ti.sstartdateearliesst =Prev(Tj).ennddate Ti.sstartdatelatest = Next(Tj).begindate - Ti.leenght Tj.sstartdateearliesst =Prev(Ti).ennddate Tj.sstartdatelatest = Next(Ti).begindate - Tj.leenght Ti.eenddateearliest =Ti. startdateeearliest + Ti.llenght Ti.eenddatelatest = Tj. startdatellatest + Ti.lengght Tj.eenddateearliest =Tj. startdateeearliest + Tj.llenght Tj.eenddatelatest = Tj. startdatellatest + Tj.lengght h with for Ti and respecttively for Tj, [Ti.startdate, Ti.enddate] ⊆ Ti.A AchievementIInterval and d

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Ti.sstartdate ∈ [Ti.startdateearliest, Ti.startdattelatest] d and Ti.eenddate ∈[ Ti.enddateearliesst, Ti.enddatelatest] d and AchievementInnterval [Ti.startdateearlieest, Ti.enddateelatest] ⊆ Ti.A

3.6. Deecompositioon

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h Thee operator deccomposes a taask in n other tasks. All theese subtasks have the sam me achievemennt interval andd the same ow wner. The operator returnss all the creaated subtaskss. As shown in Figure 7, in this exam mple, task T4 is decomp posed in two suubtasks (T41 and a T42).

Figure 7. Decompositioon.

Ti Decomposition D nn Forr j = 1 to n Tij.sstartdate = Ti.startdate+ (Ti.lenght/n)*(j-1 . 1) Tij.eenddate = Ti.sstartdate+ (Ti.llenght/n)*(j) h with for Tij . tInterval [Tij.startdate, Tij.eenddate] ⊆ Ti.Achievement

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and d Tij.sstartdate ∈ [Ti.startdateearliiest, Ti.startdaatelatest] d and Tij.eenddate ∈[ Ti.enddateearlie . est, Ti.enddatellatest]

3.7. Trrade

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Thee operator traddes a resourcee from Tj to Ti in the limit of the resouurce quantity y that belongss to TJ. The operator o returnns the two moodified tasks. As shown in i Figure 8, inn this example, the trade is done d between task T4 and Task T T5 .

Figure 8. Trade.

Ti Trade T Tj Ti.rresource = Tj.rresource

3.8. Trransfer t a new owneer, keeping all other attribuutes. Thee operator trannsfers task Ti to This operator returns the modified task. As show wn in Figure 9, in this exampple, i a) that becom mes owner b. the operrator changes the task owneer (the owner is

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Figure 9. Transfer.

Ti Transfer T actor Ti.aactor = actor

3.9. Ex xchange b task Ti and task Tj, Thee operator exxchanges the task owner between keeping g all other attrributes. The operator o returnns the two moodified tasks. As shown in i Figure 10, in this exampple, the operaator exchanges the task ow wner between n both tasks T3.

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Figure 10. Exchange.

Ti exchange e Tj Ti.aactor = Tj.actoor Tj.aactor = Ti.actoor

3.10. Parallel P Perm mutation c context. Simuultaneously, two t Thiis operator iss used in a collaborative actors permute, p on thhe temporal axxis, task Ti witth task Tj and task Tk with task t Tl, in th he limit of their achievemeent interval. Consequently, C the attributess of each tassk, such as sttartdate, endddate and tempooral margins (startdateearliiest, startdateelatest ,enddaateearliest andd enddatelatest) are modifieed. The operaator returns two couples of modifiedd tasks. As shown s in Figgure 11. Paraallel Permutaation. Thee Parallel Peermutation opperator uses a compositionn of Permutattion operatorrs. (Ti ,Tj) Parallel Permutation P (Tk ,Tl)

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he permutationn is processed on task T1a and a task T4a foor Actor 1 andd on , th task T2bb and task T4b for Actor 2.

Figure 11. Parallel Perm mutation.

Thee Parallel Peermutation opperator uses a compositionn of Permutattion operatorrs. (Ti ,Tj) Parallel Permutation P (T Tk ,Tl) Ti Permutation P Tj Tk Permutation P Tl

3.11. Collaborativ C ve Trade Thee operator traddes a resourcee from Tj to Ti in the limit of the resouurce quantity y that belonggs to TJ, wheere TJ belonggs to a differrent owner. This T

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operatorr returns the two modified tasks. t As show wn in Figure 12. 1 Collaborattive Trade. Ti CollaborativeT C Trade Tj Ti.rresource = Tj.rresource

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d between task t T3a and Task T T5b. , in this example,, the trade is done

Figure 12. Collaborative Trade.

Ti CollaborativeT C Trade Tj Ti.rresource = Tj.rresource

4. COOPE ERATIVE DISTRIBUTE ED METHO OD FOR MANAGIN NG DISRUP PTIONS o the propossed method comes from the cooperattive Thee principle of methods of distributted solving off disruptions implementedd in the areass of

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production and logistics. The proposed method is based on the development of solutions by the actors themselves for limiting the impact of disruptions while ensuring the achievement of objectives. Rather than implementing a planning calculation, the repair of the existing situation is studied (Cauvin et al., 2009). In order to achieve this goal, several strategies have been defined for answering disruptions consisting in a sequence of repair operations applied on the disrupted planning.

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4.1. Strategies for Solving Disruptions Solving strategies require sequences of repair operations in order to limit the impact of disruptions on the system actors. Each implemented strategy will evaluate the solution in order to decide (or not) for using a more costly strategy in terms of impact on the system. The evaluation of each solution is based on a multi-criterion function measuring its effectiveness (degree of success in the absorption of the disruption), its complexity (the extent of changes to the original scheduling) and its agility (decrease of time margins for manoeuvre of actors). As shown in Figure 13, when a disruption occurs during a task, the actor (Act1) first tries to solve it by a local strategy implementing one or more operation(s) of time repair (1) and in case of failure (after evaluation of solutions) one or more local repair operations on resources of the site (1’). In case of failure a strategy of bilateral cooperation (2) is first initiated and then a cooperative multilateral strategy intra site is implemented (3) in case of failure of previous strategies. In case of failure of all local strategies, the impact of the disruption is then propagated to the other sites simultaneously (4). This requires cooperation and uses the same previous strategies but within the concerned site(s). This call goes through the head (Act6) and induces a disruption in the sites it manages.

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Figure 13. Distributed solving s strategiees.

4.2. Meta-Model M o the Meth of hod m the study of o supply chain managem ment Thee meta-modell results from domain abstraction prrocess. Beforee implementinng the methodd, the meta-moodel o be extended. This abstracttion process reequires identifying what in the needs to previou us domain meethods (worksshop and suppply chain management) m w was domain dependent froom what was not. n model presenteed in Figure 13 1 synthesizess it and confirrms Thee new meta-m the degrree of genericcity of the metthod. As alreaady expected, concepts c of taasks or capaacities can be differently interpreted depending d off the applicattion domain: e.g. a resourrce in workshoop scheduling can be a machhine, as well as a a

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compan ny can be a resource in a suupply chain, and a a tool cann be a resourcee in Building and Construuction site mannagement.

Figure 13. Cooperative Repair problem m solving meta--model.

Forr example, in a Building Site S organizatiion the trade repair operattion results from the suupply chain extension. e It represents thhe possibility of ng a task or att least reducinng its length, with w its equivvalent of capaccity replacin (i.e. stock seen here as a a capacity). The case stuudy has addedd a new operattion pose which geeneralizes the possibility of interruptingg a task and thus t decomp considers it as 2 different d taskks: one comppleted and the t other to be resched duled. Resourcces have been detailed (hum man and operaative) as buildding site req quires. Efficieency costs havve also been detailed as the t multi-criteeria evaluatiion of the currrent solutions that t must takee into account specific needss. Theese changes do not “disruptt” the methodd but rather givve new meanss to reduce the t impact of a disruption on o a system where w Resourcces can locallyy or coopera atively changee tasks allocaated realizationn time in ordder to give soome agility and reactivityy to the envvironment chaanges. The following fo secttion m is implemented on the details more thorougghly how the conceptual model mple with an agent a based modelling m approach. domain from the exam

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5. AGENT BASED MODELLING AND SIMULATION APPROACH FOR DISTRIBUTED PROBLEM SOLVING: IMPLEMENTATION ON BUILDING RENOVATION

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The agent based modelling paradigm used for industrial systems considers systems as composed of autonomous entities. These entities are pro-active and defined by their behaviours (i.e. their interactions according to their roles and competencies). The agent based modelling paradigm has already been successfully applied on distributed scheduling (Neiman and Lesser, 1996). Indeed, the actors involved in construction sites (head managers, technicians, skilled tradesmen, workers, etc.) have means, resources, skills and competencies which software agents exhibit as well. All these abilities make it possible to perform tasks or functions in an individual or collective way in an organisation. This analogy between agents and actors already used for industrial systems modelling (Nwana 1996) (Parunak 1999) (Brueckner et al 2003) naturally leads to consider the agent-based approach as relevant for the building renovation issue.

5.1. The Isomorphism between Construction Field and AgentBased Modelling Consequently, similarities between the properties of both agents and actors enable us to make a bijection between construction site actors and agents of multi-agent systems. This bijection thus generates an isomorphism of structure between construction field and agent-based modelling. Moreover, agent-based modelling allows us to easily take into account (Wooldridge and Ciancarini, 2001): the natural distribution of the construction sites organisation (several actors from the same trades working together, several sites managed simultaneously, etc.), the dynamic changes in the environment through the addition or suppression of resources or actors, the decisional complexity and variability of construction sites management.

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The natural ability of multi-agent systems to solve distributed problems makes it possible to manage these requirements. The Building and Construction site management field specifically introduces a supplementary complexity level which requires an extension of the previously defined methods. This supplementary complexity level takes its roots remarkably in a greater anthropisation of the modelled system. This fact is notably noticed in task realisation and in resources utilisation (as much in the notion of quantity as in the notion of availability) and induces the reinforcement of the temporal aspect. This anthropisation result of the main characteristic of this new field: tasks are quite exclusively realised by human (tradesmen) and not by machines. In the aim to fully take into account this complexity, the basic axioms of the method are redefined as well as new dimensions are added in both tasks and disruption modelling. Thus, following sub-sections show how the notions of tasks and resources are redefined for this new application domain, in the scope of the distributed cooperative problem solving method. The extension of the approach also needs adjustments such as redefinition of disruptions, repair operations, disruption management strategies, and at last who are the implied actors in the process (and thereby in fine who (or what) the agents represent).

5.2. The Description of the Case Study The case study deals with the renovation of a small building. The implied trades are thus more of light work type than main walls works type. First the case study is described and specified. Secondly, the developed method is implemented on this case. The different issues raised by such domain are manifold and rely on many dimensions: Type and number of jobs involved in the building site (painter, plumber, electrician, …) together with specific tasks Numerous involved resources (tools, raw materials, equipment, …) Number and type of stock (plasterboard, cables, paint …). In our case study, the building is distributed in two sites: two flats on the same floor. The company in charge of the building site employs eleven employees.

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4 plasterers called Pt1, Pt2, Pt3 and Pt4 2 plumbers called Pb1 and Pb2 2 electricians called El1 and El2 2 painters called Pa1 and Pa2 1 manager called Ma1.

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Let us consider kitchen renovation. Plumber must install a water pipeline connected to a sink. In order to install it, the partition must be laid down. Afterwards, depending on sink position, the electrician will install a plug. Finally, a painter will paint a coat of primer. Two others tasks must be done: verification of the soundness of walls and wiring. Workers can work regardless of the site. Ten workers realize six tasks by building site using finite stocks (meters of copper pipe, number of plasterboard, meters of electric cable, etc.) and appropriate tools for each task. In order to simplify the problem, let us consider that a task Ti uses up a certain amount of stocks Si and uses only one tool Oi. All workers have a work capacity equal to one. Then, the task length (in hour) is equal to the work capacity to achieve it. A task can be done only if: Necessary tool/s is/are available Worker(s) assigned to the task are available Stocks are available in sufficient amount. If during the task realization, one of these resource or capacity becomes unavailable, the task cannot be finished repair solution must be found in order to end the task. Table 2 shows tasks and resources distribution by jobs. Thus, two plasterers by building site are provided. They have three resources in stock and two tools. They must achieve two tasks. One of these tasks must be done by two workers. The ten employees are split between both construction sites as shown in Table 2. The manager works within both building sites. As shown in Figure 14, the second site begins after the first one.

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Table 2. Resource con nfiguration in n the buildingg site bs Job

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r Tk & res. tasks actors stockss tools

Pt plasterrer

Pb plum mber

El E ellectrician

Pa painter

2 4 6 4

1 2 1 3

2 2 3 3

1 2 1 1

Figure 14. Global site planning p according to the sites.

Too ols are spreadd between bothh building sitees as shown in i Table 3. Toools can be shared betweeen several workers and poossibly between several tassks. They arre reusable. Tablee 3. Tools rep partition betw ween both sitees Tool Opt1 Opt2 Opbl1 Oel1 Oel2 Opa1

Siite 1 2 2 1 1 1 1

Site 2 2 2 1 1 1 1

Figure 15 showss a task scheddule that must be done withhin both buildding sites. Th he task “fixinng coat of prim mer” relies onn the task "insttalling plug" that t relies on the task "innstalling sinkss" that relies on o "installing partition". Taasks

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“electriccal diagnosis”” and “humidity diagnosiis” are indepeendent from the others and a can be donne in parallel.

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Figure 15. Dependency graph of tasks.

Tab ble 4 shows thhe real schedulle of the first building b site. For F instance, task t "Tpt1" is done by woorkers “Pt1” and a “Pt2” and begins on dayy 14 at 8 am and a n the same dayy at 12 am. Tabble 4 also show ws the amounnt of work needed ends on for each h task. The am mount of workk allocated to the second buuilding site is the same. A worker beginns at 8 am andd stops at 6 pm m. The table shhows the num mber of work kers a task needs. Table 4. 4 Task sched dule Tpt1 Tpt2 Tpb1 Tel1 Tel2 Tpa1

Pt1 + Pt2 Pt2 Pb1 El1 El1 Pa1

4h 4h 6h 3h 4h 5h

day 144 at 08 :00am day 144 at 12 :00am day 144 at 12 :00am day 155 at 08 :00am day 144 at 08 :00am day 155 at 11 :00am

a 12 :00am day 14 at day 14 at a 04 :00pm day 14 at a 06 :00pm day 15 at a 11 :00am day 14 at a 12 :00am day 15 at a 04 :00pm

5.3. Illlustration off the Methood on the Caase Study d occcurs during rennovation of thhe kitchen. Moore precisely, the A disruption disruptiion occurs durring the task “installation “ of partition". Inn fact, one of the plasterb board cannot be b used to creaate the partitioon.

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In order o to continnue the tasks needed to finiish the work, it is necessaryy to solve th his disruption. As evoked inn previous secttion the approoach tries to soolve such a problem p at thee more local level. l In the example, e one way to deal with w the disru uption is to reeplace the deffective plasterbboard. Two caases are possibble. In the first fi one, an opperator takes new n plasterboard in the stocck or the stockk is insufficient and a dellay must be seettled. In the second case, it is necessaryy to mension. In fact, f an interrval must be allocated insside modify temporal dim t obtain new plasterboard. planning in order to take into accouunt the delay to portunities to solve the disruuption includee the followingg solutions: Opp

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Shifting task Tptt1 to the righht to get enouugh time in orrder to insert the delay. Tak king plasterbooard in the second buildinng site. The problem is thhen shifted to thee second buildding site. Beg ginning immeediately the work w on the seecond buildingg site in orderr to gain the timee to obtain the plasterboard for the first buuilding site. Following the priinciples presennted in this chhapter, the soluution must be the s actors. In most local in order too avoid disrupption propagaation to other system the casee study, if the plasterboard is not in stockk, the more loocal solution iss to shift tassk Tpt1. In facct other tasks have h a dependdence link witth “installationn of partition n". Furthermoore, these taskss cannot be modified m indiviidually. Then, the most lo ocal solution is to wait befoore performing Tpt1 in ordder to reconstrruct the stocck of plasterbooard. The shiftt right operatioon modifies thhe planning. Figure 16 presentts the new taskk layout. No global g calculuss is necessary..

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5.4. Test Platform

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The system is developed using ECLIPSE and the framework JADE. Thanks to JADE (JADE, 2007). The prototype is FIPA compliant and uses the normative ACL-FIPA communication language (FIPA, 2000). Each agent performs a behaviour that defines its actions (execution of a task, communication) during the simulation. These behaviours are modelled using ABD diagrams developed at LSIS lab. The system uses different kinds of agents. Few of them are used for simulation management like clock agent in order to synchronize simulation agents. Simulation agents are built on the same pattern. They are defined using an isomorphism between them and actors of the real system. During the simulation, such agents can play different behaviours depending on agent interactions and environment changes. One behaviour allows agents to deal with planned tasks in order to attend their goals. Another behaviour deals with disruptions. It allows agents to cooperate in order to find a solution for the problem resulting from such a disruption. All agents use JADE framework and work using same pattern except the clock agent. They are able to perform two behaviours that are mutually exclusive.

6. CONCLUSION This chapter presents a method of cooperative management of disruptions which uses agent based modelling. It is an extension of the approach developed for production systems and then extended to the issue of supply chain management. This extension mainly focuses on the consideration of new dimensions (such as organization distribution and human factors) and on the development of repair planning in order to reduce the impact of the disruption on complex systems. The increased complexity results from an enhanced typology of tasks (interruptible or not …), from the ability to take into account inventory levels (of material, of produced items …) and the availability of inventory level of identified resources (tools, operators …). The proposed approach copes with the enlargement of the dimensions of the problem, set in new repair operations enabling to adjust the resolution process to this complexity.

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These new concepts are integrated in the management of construction sites and implemented on the case of renovation. A Multi Agent system prototype based on JADE platform has been developed to verify and test this method of disruption management. The future work will focus on: the extension of the metric for evaluating the impact of disruptions (the shift of a task that does not use a stock does not have the same cost as a task requiring stocks) in order to better tackle the distributed dimension; the improvement of the model in order to better consider all the dimensions of complex distributed systems and organizations like the diversity of skills, know-how, corporate culture ... the collaboration with social science researchers to better define the axiomatic corpus (tasks / disruptions / measurement of the impact on men).

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REFERENCES Brueckner, S., Baumgaertel, H., Parunak, V., Vanderbok, R., & Wilke, J. (2003). Agent models of supply network dynamics: Analysis, design and operation. In T. P. Harrison, H.L. Lee, & J. J. Neale (Eds.), The practice of supply chain management: Where theory and application converge. USA: Springer. Cauvin, A. (2005). Analyse, modélisation et amélioration de la réactivité des systèmes de décision dans les organisations industrielles: vers une aide à la conduite des processus d’entreprise dans un contexte perturbé. Habilitation à Diriger des Recherches, University of Aix-Marseille III, France. Cauvin, A., Ferrarini, A., & Tranvouez, E. (2009). Disruption management in distributed enterprises: A multiagent modelling and simulation of cooperative recovery behaviours. International Journal of Production Economics, vol. 122, 429-439. Clausen, J., Hansen, J., Larsen, J., & Larsen, A. (2001). Disruption management. OR/MS Today, vol. 28, 40-43. Ferber, J. (1999). Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. London, UK: Addison Wesley.

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FIPA (2000). FIPA Agent Management Specification, Foundations of Intelligent Physical Agents. www.fipa.org/ Jade (2007). JADE: Java Agent DEvelopment Framework. http://jade. tilab.com/ Neiman, D., & Lesser, R. (1996). A Cooperative Repair Method for a Distributed Scheduling System. In B. Drabble (Ed.), Proceedings of the Third International Conference on Artificial Intelligence Planning Systems: AIPS-96 (pp. 166-173). Edinburgh, Scotland. Nwana, N.H. (1996). Software Agents: An Overview. Knowledge Engineering Review, vol. 11(3), 1-40. Parunak, V. (1999). Industrial and Practical Applications of DAI. In Weiss G. (Eds), Multi-agents Systems: A Modern Approach to Distributed Artificial Intelligence. Cambridge, Massachusetts: MIT Press. Tranvouez, E., & Ferrarini, A. (2006). MultiAgent Modelling of Cooperative Disruption Management in Supply Chains. In IEEE – International Conference on Service System and Service Management (ICSSSM'06). Troyes, France: IEEE. Tranvouez, E., Ferrarini, A., & Espinasse B. (2001). Multiagent modelling and simulation of workshop disruptions management by cooperative rescheduling strategies. In Workshop on Multiagent Based Modelling and Simulation in Industry and Environment - 13th European Simulation Symposium and Exhibition. Marseille, France. Wooldridge, M., & Ciancarini, P. (2001). Agent-Oriented Software Engineering: The State of the Art. New York: Springer-Verlag. Yu, G., & Qi, X. (2004). Disruption management: framework models and applications. Singapore: World Scientific Publishing Co. Pte. Ltd. Zweben, M., Davis, E., Daun, B., & Deale, M. (1993). Scheduling and Rescheduling with Iterative Repair. IEEE Transactions on Systems Man and Cybernetics, vol. 23(6), 1588-1596.

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In: Progress in Economics Research. Volume 23 ISBN 978-1-61324-394-7 Editor: Albert Tavidze © 2012 Nova Science Publishers, Inc.

Chapter 7

WHAT HAVE WE LEARNED FROM THE REAL ESTATE BUBBLE? ASSET SORTING IN THE REAL ESTATE INVESTMENT MARKET 1)

Chihiro Shimizu*

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Reitaku Institute of Political Economics and Social Studies Reitaku University, Japan

1. INTRODUCTION The advent and collapse of real estate bubbles, or the sharp rises and falls in real estate prices, have posed major economic issues in many nations. Real estate prices soared sharply in Japan and Sweden in the 1990s and recently in many Western countries (until the mid-2000s), until plunging in the wake of the financial crisis in the United States. The rapid rise and fall of real estate prices in Japan from the mid-1980s to the 1990s is said to represent the most significant real estate bubble of the 20th century. Following the collapse of this bubble, Japan experienced a long period of economic stagnation, often cynically described as the “lost decade.” What have we learned from these ups and downs in the real estate market?

1)

*

The original academic research of this paper is Shimizu and Karato (2010).

Associate Professor (PhD), The International School of Economics and Business Administration

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Have recent real estate investment risk management efforts incorporated these lessons? To answer these questions, the author would like to pay attention to the severalty of each real asset. The lesson learned from last century’s economic bubble and from the expansion and shrinkage of the real estate market in the wake of the latest financial crisis is that “real estate investment risks cannot be dispersed by diversifying investments, and major risks will remain unless assets are carefully selected.”2) In the 1980s bubble, many real assets were the subject of speculative transactions whose purpose was not actual use. The investors in these assets ultimately suffered from devastating losses. Based on this lesson, the latest expansion of the real estate investment market was based on real assets already in use that would provide the investors with certain profits. However, as the market overheated, investments were diversified into various types of property to disperse risk, became smaller in size, and were geographically expanded beyond urban centers into suburban areas, then into regional cities. As a result of such market expansion, it is likely that market selection will be spurred again by market shrinkage in the wake of the financial crisis. Bearing these issues in mind, the author in this paper will look back on the period of adjustment following the collapse of the economic bubble in the 1990s; elucidate how assets were sorted in the Tokyo 23 wards office market, taking macroscopic changes in the real estate market in the Tokyo 23 wards office market into account; and suggest possible major considerations for future investments in office buildings.

2. COLLAPSE OF THE BUBBLE AND DEVELOPMENT OF THE OFFICE MARKET 2.1. Diversification of the Real Estate Market In the 1980s bubble, repeated rounds of speculative real estate transactions targeted urban areas in particular, and numerous lots were converted in poor ways. As Tokyo grew as an international financial center, demand for office 2)

Mr. David Bucke, UBS Asset Management, said the lessons learned from the recent financial crisis are that we should be aware that as real estate investment risks, there are appraisal risks as well as liquidity risks and that we have to select real estate very carefully (in his presentation at the IPD/IPF Property Investment Conference 2009 held in Brighton on 26 November, 2009).

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spaces increased significantly, official forecasts pointed to potential shortages of office floors, and many financial institutions helped finance the construction of office buildings. In urban centers, small office buildings, called “pencil buildings” were built where residences once stood, and many office buildings and commercial facilities were also developed in suburban areas. A large amount of space was introduced to the market in the temporary expectation of strong demand. However, upon the collapse of the bubble, land of no use became unmarketable, and poorly located office spaces and the pencil buildings built on residential tracts suffered high vacancy rates, with the result that even the 23 wards of Tokyo ended up with a vast store of unused assets. Assets supplied in excess of demand were finally forced off the market and converted into totally different types of property, as occupancy rates failed to improve no matter how far rent fell. Economically, this constitutes a maldistribution of land resources in urban cities that created strong inefficiencies. Where we find inefficiency in the land use market, market adjustments cannot be achieved simply by reducing rent or by rising vacancy rates, but by moving toward a new balance based on changes in land use and redevelopment. In other words, real estate exposed to strong inefficiencies is forced off the market, and those investing in such properties or whose portfolios include such properties would end up with high risks. What types of real estate were forced out of the market in the 1990s postbubble period and in which regions? Analysts argue that during the bubble period, many residences were converted into office buildings given the high rent for the latter in urban areas. The author will examine these conversions and their consequences below.

2.2. The Microstructure of the Office Market To answer this question in terms of data, the author estimated the hedonic function for office and residential house rents3) and examined the difference between rents for office spaces in the 23 wards of Tokyo and the rents that would be charged if they were converted to residential use. Office rents are generally higher than residential rents in urban centers, but if the latter is

3)

See Appendex for the details of the estimation.

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higher, office buildings have the optional value of conversion to residential use. That is, such assets cannot produce adequate profits as office buildings. Examining this phenomenon, Shimizu and Karato (2010) argued office buildings are likely to be converted to another use if the rents gained when used as office buildings is lower than rents that would be earned if used in a different way (e.g., as residences). A series of studies in the United States reached the same conclusion.4) Given large differences between proceeds from the current land use and from possible conversion, the current land use cannot produce sufficient profits, increasing the chances that the owner will be compelled to change the use of the land. Investors in these assets would end up with high risks given the high possibility that such assets will go unused, a more serious possibility than potential increases in vacancy rates or declines in rent.

Figure 1. Spatial distribution of office buildings in 1991. 4)

See Wheaton (1982), Rosenthal and Helsley (1994), Munneke (1996), and McGrath (2000).

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According to surveys of land and building use conducted by the Tokyo metropolitan government in 1991, the 23 wards of Tokyo contained some 52,890 non-wooden office buildings at the peak of the economic bubble. Figure 1 shows the spatial distribution of these buildings.The author made estimates for each of these buildings, defining excess return as the total sum of the difference between the office rent (RO) and the residential rent (RC), estimated as models, ( Excess Return(ER )it =

∑ (RO

it

− RCit ) ). A higher

i

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rent for residential use means an opportunity loss. If this situation persists, the office building is likely to be converted to another use, as discussed above.

Figure 2. Spatial distribution of office spaces for which residential rents exceed office rents in the 23 wards of Tokyo in 1995 (residential rents > office rents).

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Table 1. Percentage of buildings with opportunity losses: by ward and by year Ward Chivoda Chuo Minato Shinjuku Bunkyo Taito Sumida Koto Shinagawa Meguro Ohta Setagava Shibuya Nakano Suginami Toshima Kita Arakawa Itabashi Nerima Adachi Katsushika Edogawa Average

1991 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

1995 2.00% 12.00% 19.00% 11.00% 3.47% 66.00% 20.00% 4.51% 5.07% 14.80% 8.03% 5.23% 0.00% 1.19% 3.48% 1.19% 1.21% 70.00% 79.00% 1.96% 0.00% 0.00% 31.02% 2.33%

1999 4.62% 77.00% 3.24% 1.52% 13.95% 11.36% 13.68% 28.48% 22.56% 48.82% 26.82% 23.12% 34.00% 7.25% 25.85% 6.12% 11.74% 8.70% 10.36% 15.11% 1.21% 3.18% 53.94% 10.58%

2000 10.35% 2.68% 8.41% 3.95% 23.45% 20.44% 32.37% 44.94% 33.87% 60.66% 37.24% 37.63% 1.12% 15.80% 37.94% 10.69% 22.83% 18.93% 22.18% 28.59% 4.84% 7.26% 65.95% 17.89%

2001 10.48% 2.83% 8.63% 3.95% 23.81% 20.78% 32.89% 45.40% 34.30% 60.92% 37.84% 38.27% 1.19% 16.45% 38.26% 10.92% 23.30% 19.35% 22.64% 29.08% 4.96% 7.49% 66.47% 18.16%

2002 10.75% 3.02% 9.02% 4.06% 24.12% 21.13% 34.41% 46.16% 35.35% 61.45% 38.29% 39.20% 1.22% 16.99% 38.81% 11.15% 24.14% 19.92% 23.42% 29.82% 5.25% 7.72% 66.99% 18.58%

2003 9.76% 2.37% 7.72% 3.52% 22.53% 19.59% 29.54% 42.74% 32.51% 59.34% 36.09% 36.02% 1.02% 14.94% 36.60% 10.24% 21.34% 17.11% 20.95% 26.63% 4.27% 6.47% 64.41% 16.98%

2004 18.24% 8.36% 16.74% 8.38% 36.11% 31.61% 53.16% 60.42% 48.33% 69.74% 49.65% 51.37% 3.15% 29.65% 50.43% 18.51% 37.65% 34.92% 40.32% 43.87% 13.55% 14.76% 76.93% 27.58%

# of Offices 6,365 6,532 5,895 3,745 1,642 3,195 1,520 2,370 1,618 760 2,006 2,046 2,949 924 1,265 2,188 1,073 713 888 1,224 1,734 881 1,357 52,890

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Table 1 shows the changes during 1991-2004 in the percentage of office buildings located in each ward associated with opportunity losses. In 1991, for all of the 52,890 buildings, office rents were higher than residential rents. Thereafter, opportunity losses emerged as office rents declined faster than residential rents. In 1995, 1,226 buildings, or 2.33%, were associated with opportunity losses. By 2004, this figure had risen to 14,577 buildings, or 27.58%.

Figure 3. Spatial distribution of office spaces for which residential rents exceed office rents in the 23 wards of Tokyo in 2000 (residential rents > office rents).

In 2004, from a regional aspect, the percentage of buildings associated with opportunity losses exceeded 50% in Sumida, Koto, Meguro, Setagaya, Suginami, and Edogawa. These wards had many lots that were proactively converted from residential to office use during the economic bubble beginning

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in the early 1980s.1) Figures 2 to 4 show the changes in the spatial distribution of buildings associated with opportunity losses in selected years. These office buildings were first observed in suburban areas, then expanded to urban centers.

Figure 4. Spatial distribution of office spaces for which residential rents exceed office rents in the 23 wards of Tokyo in 2005 (residential rents > office rents).

The author examined the relationship between excess returns in 2005 and three conditions, of which the first two are locational conditions: (a) distance 1)

Chapter 14 of Shimizu (2004) includes an analysis of land use changes from 1991 to 1996 by purpose of use and ward, based on the surveys of land and building use conducted by the Tokyo metropolitan government.

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to the nearest railway station; (b) time distance to the urban center; (c) building size (total floorage). The results of the estimates are shown below. ERit = 846.380 - 915.559・lnWK it - 188.483・lnACCit + 335.767・lnTAit (23.578) (-130.749) (-23.614) (87.103) Adjusted R-square=0.387 Number of observation=52,890 Excess returns tend to fall (meaning opportunity losses are more likely to occur) as the distance from the nearest railway station (WK) or from the urban center (ACC) increases, tending to increase in proportion to building size (TA). Thus, most opportunity losses are found in small, less conveniently located buildings.

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2.3. Withdrawal From the Office Building Market Next, let’s examine how these office buildings associated with opportunity losses were converted during the post-bubble period. Table 2 shows the percentage of all of the 52,890 buildings in the 23 wards intended for office use as of 1991 that suffered opportunity losses in later years leading up to 2004 by pattern of change in building use. The author examined building conversions occurring in three points at quinquennial intervals (i.e., 1991, 1996, and 2001) to identify land use changes in the office market in these wards, classifying building use as O (office), R (condominium), or S (other than office or condominium) and observed the subsequent conversion of the buildings intended for office use in 1991. For example, if a building intended for office use (O) in 1991 was still used as offices (O) in 1996 but was converted into a condominium (R) by 2001, the change pattern is O-O-R. This gives us five possible patterns of change over the 1991-1996-2001 period: O-O-O, O-O-S, O-O-R, O-R-R, and O-S-S. Of all 52,890 buildings, 38,974 buildings, or 74%, were used for office purposes at all three observed points in time, 1991, 1996, and 2001. This means 26% of the properties were eventually forced off the market and converted to a different use: 1,091 buildings, or 2%, had been converted into residences by 2001, while 2,808 buildings, or 5%, had been converted to residential use by 1996.

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Table 2. Distribution of office buildings associated with opportunity losses by land use change pattern: 1991 to 2001 Change Pattern

1991

1995

1999

2000

2001

2002

2003

2004

# of Offices

O-O

0.00%

1.93%

9.40%

16.24%

16.51%

16.93%

15.37%

25.52%

38,974

O-O

0.00%

2.24%

10.18%

17.68%

17.99%

18.30%

16.67%

26.42%

2,279

O-O

0.00%

3.48%

15.31%

25.75%

26.03%

26.76%

24.75%

38.22%

1,091

O-R

0.00%

5.09%

20.48%

30.41%

30.84%

31.27%

29.42%

43.13%

2,808

O-S

0.00%

3.11%

12.37%

20.63%

20.87%

21.26%

19.59%

31.04%

7,738

Total

0.00%

2.33%

10.58%

17.89%

18.16%

18.58%

16.98%

27.58%

52,890

Note: “O” stands for offices, “R” for condominiums, and “S” for other uses.

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This data shows that office buildings representing the glut created during the bubble period were forced off the market in the post-bubble market adjustment process. In the post-bubble office market, we see only declines in contract rents if we look only at the macroscopic changes; but when we analyze the microstructure in terms of buildings, we find that market sorting has occurred in the form of conversions.

3. WHAT HAPPENS IN THE OFFICE MARKET? What are the current levels of returns in the office and residential markets? How will the real estate investment market change in the future?

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3.1. Deterioration of Fundamentals in the Office Market The financial crisis was not just a headache for property markets, but had considerable impact on the real economy. The economic bubbles that began and ended in Japan and Sweden in the 1990s were confined to those countries. However, the latest real estate bubble and its collapse took place simultaneously around the world, changing its economic landscape entirely. The collapse of this particular bubble led to lower results for Japanese enterprises and forced them to change their global management strategies. The resulting recession and revisions of management strategies have had a major impact on the real estate market. First, the recession implies a considerable decline in quantitative demand for office spaces. Long before this problem took shape, observers had already pointed out that the office market would experience a significant drop in demand when the retirement of the baby-boom generation began on a large scale. However, others opined that given a period of economic expansion, extending the term of employment and creating new jobs would maintain quantitative demand for office spaces. The recession that emerged instead caused enterprises to forgo employment extensions, discontinue the employment of non-regular workers, and even curb new hires. This indicates a decline in demand for office spaces as a macroscopic sum. Lower business results imply lower per capita productivity. Corporate productivity affects employee income and per unit office payment. In other words, a fall in corporate productivity after the financial crisis not only led to declining employee income, but pushed down rents paid per unit of

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space. Even a company located in one of the highest-grade office buildings at a prime location in the urban center will reduce the leased area it holds and seek to cut rent payments per unit if productivity declines. We would expect changes in a company’s management strategy to trigger a restructuring of the properties it currently uses. Rather than carrying out temporary measures like consolidating or reorganizing its business sites, it would review management resources to change its production systems or product lineup, affecting the allocation of real estate resources. In particular, the fundamentals of the office market will undergo major changes.

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3.2. Adjustment of Income Return on Office Investment This change in the fundamentals of the office market will result in higher vacancy rates and lower rent per unit. Shown below (Figure 5) are long-term trends in office and house rents in the Tokyo 23 wards, indicated by a rent index based on contracted rents as estimated above.1) The reader may expect to see clear trends in the real estate market, but no statistical data currently available shows by how much real estate prices and rents rose during the bubble period, when the bubble reached its peak, or how far adjustments progressed after the bursting of the bubble.2) Office rents were \5,500/m2 in the first quarter of 1986, reaching a peak of \12,000/m2 in the third quarter of 1991, a 2.4-fold increase.3) However, after the bursting of the bubble, rent adjustments proceeded for five years, reducing rents to \5,000/m2 by 1996, 60% down from 1991 levels. Thereafter, office rents continued to decline until 2004; began to rise in 2005, returning to \6,100/m2 by the second quarter of 2008; but took a sharp downturn with the Lehman Shock in 2008, being adjusted to \5,000/m2 by the second quarter of 2009. The recent rent fluctuations in the wake of the financial crisis are approximately 25%⎯about half those of the bubble period, in which fluctuations exceeding 40% were experienced. 1

The rent index was estimated by the hedonic approach. Data on contracted rents for residential spaces and office spaces were provided by Recruit Co., Ltd. and by the member companies of Zentakuren, respectively. 2 See Nishimura and Shimizu (2002) for this issue. 3 This theoretical value is the average level including small buildings. Since small buildings are far greater in number in terms of the stock level, the observation looks lower in terms of the absolute level.

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14000

12000

Office Residentia l

10000

8000

6000

4000

2000

Y1986Q1 Y1986Q4 Y1987Q3 Y1988Q2 Y1989Q1 Y1989Q4 Y1990Q3 Y1991Q2 Y1992Q1 Y1992Q4 Y1993Q3 Y1994Q2 Y1995Q1 Y1995Q4 Y1996Q3 Y1997Q2 Y1998Q1 Y1998Q4 Y1999Q3 Y2000Q2 Y2001Q1 Y2001Q4 Y2002Q3 Y2003Q2 Y2004Q1 Y2004Q4 Y2005Q3 Y2006Q2 Y2007Q1 Y2007Q4 Y2008Q3 Y2009Q2

0

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Figure 5. Macro-trends in office and residential rents.

Residential rents, on the other hand, have not fluctuated as sharply as office rents. Residential rents were \3,400/m2 in the first quarter of 1986, reaching a peak in the second quarter of 1991, almost at the same moment as office rents, for a 1.35-fold increase, or over \4,700/m2. Given the 2.4-fold increase in office rents, the rise in residential rents was relatively less pronounced, even during the bubble period. Residential rents bottomed out in the first quarter of 1996, at the same time as office rents, and were adjusted to \3,400/m2, nearly equal to the first quarter of 1986. Thereafter, residential rents have remained between around \3,400/m2 and \3,500/m2. Office rents rose from 2005 until they began declining once again in 2008 through 2009, but residential rents remained proof to these fluctuations. In short, residential rents have proved quite stable even in the wake of the financial crisis. The recent drop in office rents in the Tokyo 23 wards is not an immediate aggravating factor in the performance of office investments. As discussed by Shimizu (2009), we know that income returns from real estate investment have a tendency to resist movement, and rapid and sweeping adjustments do not occur in response to market changes. Income returns from real estate already in use do not change unless contractual rent figures are renewed; that is, they vary according to the probability of contract renewal and the amount by which rent rises or falls.

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Given the ordinary practice in Japan of renewing lease contracts every other year, 2010 will mark a year of contract renewal for tenants who signed contracts when rents were highest in 2008. Negotiations for such contract renewals are expected to be based on and reflect the recent drops in rents. In other words, income returns will likely decline considerably due to possible downward rent revisions following contract renewals and the increases in macroscopic vacancies resulting from lower demand. However, it would appear that this period of market adjustments is now almost at a close. Office rents cannot go lower than now, given the close proximity to the record lows of the past 25 years, including the post-bubble period, although we should not forget lagging effects. The impact of market adjustments will be limited compared with the post-bubble period in terms of the extent of market change.

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3.3. Sorting Office Buildings Income returns will decline temporarily, while the deterioration in fundamentals depends on economic recovery. However, it is important to note that not all office buildings will undergo average, similar fundamental changes. As the analysis in the preceding section suggests, many office buildings maintained certain performance levels and survived the post-bubble period. The line between such office buildings and those that will be forced off the market will grow clearer. In this context, how will office buildings be sorted? The major differences from the 1990s bubble period are higher office stock levels and larger office spaces. Many large buildings were constructed in the Tokyo 23 wards after 2000 in a phenomenon called the “year 2003 problem.” Given a sharp increase in office floorage and a decline in absolute demand for office spaces, it is easy to predict the market adjustment that occurred upon the collapse of the economic bubble. In such cases, adjustments will affect not just pencil buildings and peripherals, as with the post-bubble period. Rather, the sorting criteria will grow even more diverse. The criteria used to be building location, size, and specifications. Now, there will be a growing tendency to differentiate office buildings by management skill. Such differentiation cannot be derived from the present analysis. It should be noted that even similar buildings located in similar areas

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will demonstrate significantly varying performances due to differences in the skill of their management. No matter how large and conveniently located, office buildings may face rising vacancy rates and declining rents if they are poorly managed. Attention should be paid to the fact that more than ever before, mid-/small-sized buildings are likely to be sorted out as unused assets by the market.

3.4. Declines in Capital Return If the office market changes as depicted above, capital returns will inevitably drop. Since this is determined as the discounted present value of a future return, if the return declines, there will be greater pressure to reduce prices. In addition, the discount rate has been raised due to growing liquidity risks. All this points to a further decline in capital returns.

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4. WHAT HAVE WE LEARNED FROM THE REAL ESTATE BUBBLE AND THE FINANCIAL CRISIS? What have the players in Japan’s real estate market learned from the advent and collapse of the real estate bubble? Have they incorporated these lessons when managing risks related to real estate investments? When the economic bubble collapsed in the 1990s, as discussed in this paper, many assets were forced off the market. This implies the severalty of each real property; individual assets may have undergone various phenomena that cannot be estimated based on macroscopic changes alone, such as rising vacancy rates and declining rents. he lesson learned by those who witnessed the generation and collapse of the bubble is that we can diversify our investments in periods of market expansion in terms of property type, size (asset class), and region, but we should select our assets carefully. Some have argued dispersing effects would arise from the increasing diversity of the market. In fact, these effects did not materialize, and we were required to select individual assets carefully. The recent fund bubble began with major office buildings in urban centers and expanded to encompass mid- and small-sized ones. Property types included not just office buildings, but residences, commercial facilities, logistics facilities, hotels, and the industrial infrastructure. The geographical scope of

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investment extended beyond Tokyo and other large cities to reach core and smaller cities in other regions. In essence, real estate investments should be made from a long-range perspective. In particular, if long-term funds are to be used, it is important to carefully select real estate that is highly resistant to change over time, rather than investing in a wide variety of assets for the sake of reducing the related risk. Differentiation will be spurred not merely by changes in fundamentals, but by building characteristics such as earthquake protection and the ability to conform to global environmental policies and regulations, as well as tightening of financial restrictions. Failure to properly control these risks will result in a higher cap rate, hence lower capital returns. In short, it will grow increasingly more important to identify and to invest with care in certain types of real estate. The past real estate bubble and the recent financial crisis have demonstrated the diversity and severalty of real estate properties and the conditions investment properties must meet to be highly resistant to change over time.

REFERENCES Brueckner, J. K. (1980), A vintage model of urban growth, Journal of Urban Economics, Vol.8, 389-402. Baltagi, B. H. (2008), Econometric Analysis of Panel Data 4th ed., John Wiley & Sons Ltd. Munneke, H. J. (1996): Redevelopment Decisions for Commercial and Industrial Properties, Journal of Urban Economics, Vol.39, 229-253. McGrath, D. T. (2000), Urban Industrial Land Redevelopment and Contamination Risk, Journal of Urban Economics, Vol.47, 414-442. Rosenthal S. S. and R. W., Helsley (1994), Redevelopment and the urban land price gradient, Journal of Urban Economics, VOL.35, 182-200. Nishimura, K and Shimizu, C (2002), Distortion in Land Price Information, Economic Analysis of the Real Estate Market edited by K. Nishimura, Nihon Keizai Shimbun, Inc., pp.19-66. Shimizu, C (2009), Characteristics of Housing Investment, Research Paper by Tokio Marine Property Investment Management, Inc, No.1.

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Shimizu, C and K.Karato (2010), Estimation of Redevelopment Provability using Panel Data-Asset Bubble Burst and Office Market in Tokyo-, CSIS Discussion Paper(The University of Tokyo), No.104. Shimizu, C, K.G. Nishimura and Y. Asami (2004), Search and Vacancy Costs in the Tokyo Housing Market: An Attempt to Measure Social Costs of Imperfect Information, Regional and Urban Development Studies, Vol.16, No.3, 210-230. Shimizu,C, K.G.Nishimura and T.Watanabe(2008), Residential Rents and Price Rigidity: Micro Structure and Macro Consequences, RIETI Discussion Paper Series 09-E -044./Paper Wheaton, W. C. (1982), Urban spatial development with durable but replaceable capital, Journal of Urban Economics, Vol.12, 53-67.

APPENDIX

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Data Land Uses and Use Conversions This study uses the building-based GIS (geographical information system) polygon data from a land and building use survey by the Bureau of Planning of the Tokyo Metropolitan Government to observe how buildings that existed in 1991 were redeveloped and converted by 1996 and 2001. The number of office buildings in 1991 stood at 40,516, excluding those used for both stores and housing. Of the 40,516 office buildings that existed in 1991, 2,607 were redeveloped or converted into housing by 1996, with the remaining 37,909 buildings used still for offices. Of office buildings that existed in 1996, 3,576 were redeveloped or converted into housing by 2001. The remaining 34,333 office buildings remained as offices. Office and Housing Rents Office rent RR and housing rent RC must be specified to estimate the model. We used rent data provided by the National Federation of Real Estate Transaction Associations, known as “Zentakuren”, for the period between January 1991 and December 2004. The data covered 13,147 rent contracts during the period.

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Meanwhile, we used “Weekly residential listing magazine—Rental Homes” from Recruit Co. to collect housing rent data4. From the data in the magazine, we selected data that were deleted because contracts had been concluded. Rent prices upon their deletion from magazines represent first offers in the reverse auction process where landlords send house quality and rent information through magazines and continue to cut rents until they find tenants. These figures can be characterized as the highest prices for tenants, but may be taken as market prices because few tenants successfully negotiate reductions in rents from offered levels5. Between 1991 and December 2004, there were data on 488,348 rents. Office and housing rent databases are shown in Table 1 and a statistical summary in Table 2. Each database covers a 14-year period in which bubbles formed and burst, including volatile rent data. The average office rent was 4,851 yen per square metre with a standard deviation of 1,925 indicating strong volatility. The average housing rent was 3,248 yen per square metre with a standard deviation of 8246. We use the above data to estimate floor rents. Office rents are determined through business location, based on the convenience of business communications and employees’ commutation as well as workplace conditions such as space. Because the data for this study cover 14 years from 1991 to 2004, we make next pooling regression model as follows:

log RitO = xiO ' θO + diO ' δO + vitO

(6)

O where Rit stands for office rent per unit of floor area for property i at

time t, xi for the vector of property i characteristics (including floor space, distance to the nearest station, age, proximity to an urban centre, and a O O regional dummy variable), θ for the relevant implicit price vector, d i for a

time dummy variable vector that takes the value of 1 at time t and 0 at any O O other time, δ for the time effect vector, and vit is the disturbance term.

4

Steel apartments account for most rental housing stock. Because our study was designed to compare housing with office buildings, however, we limited data for our analysis to RC (reinforced concrete) and SRC (steel reinforced concrete) buildings. 5 On a weekly basis, Recruit monitors whether contracts are concluded on advertised rents and how rents failing to meet tenant requests are lowered. As a result of monitoring, it has been found that final rent levels offered just before their deletion from the magazine are equal to contract levels (as confirmed with data from the period 1996 to 2001). 6

Office rents ranged from the minimum at 1,815 yen to the maximum at 13,310 yen and housing rents from 600 yen to 13,300 yen. Both rents were distributed in the same area.

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Table 3. Rent Data Outline Symbols WK

FS TA

Variables Distance to nearest station Accessibility to central business district Floor space/ square metres Total floor space/ square metres

BY

Number of years after construction

BS NU

Balcony space/ square metres Number of units

RT

Market reservation time

MC

Management cost

WD

Walk dummy

FF

First-floor dummy

HF

Highest floor dummy

SD

South-facing dummy

SD2

South-facing dummy2

TK

Ferroconcrete dummy

ACC

Contents Time to the nearest station (walking and bus). Average of railway travel time in daytime to the most crowded 40 stations in 1988 weighted by the number of passengers at the stations*. Floor space Total floor space Period between the date when the data are deleted from the magazine and the date of construction of the building. Balcony space (as shown in Jutaku Joho magazine). Total number of units in the condominium. Period between the date when the data appear in the magazine** for the first time and the date when the data are deleted Management fee. Whether the travel time includes time on bus 1, not including time on bus 1 but including time on bus 0. The property is on the ground floor 1, on other floors 0. The property is on the top floor 1, on the other floors 0. Windows facing south 1， other directions 0. Fenestrae facing south, south west or south east 1, other directions 0. Steel reinforced concrete frame structure 1, other structure 0.

Unit minutes minutes m2 m2 year m2 unit date YEN/ month (0,1) (0,1) (0,1) (0,1) (0,1) (0,1)

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Table 3. (Continued) KD LDj (j=0,…,J) RDk (k=0,…,K) TDl (k=0,…,L)

Housing Loan Corporation dummy Location (Ward) dummy Railway line dummy Time dummy (monthly)

Eligible for Housing Loan Corporation loan 1, not eligible 0. j th administrative district 1, other district 0. i th railway line 1, other railway line 0. (10 railway lines appeared in the magazine) k th month 1, other month 0.

(0,1) (0,1) (0,1) (0,1)

* Shinjuku station is the busiest station. The busiest 40 stations include main terminal stations of the Yamanote Line such as Shinagawa, Ikebukuro and Shibuya as well as Yokohama, Kawasaki, Chiba, Omiya and Kashiwa stations. We have established a 73,920 railway line network database, which is worked out of 1,848 stations that appeared in the magazine for the 40 stations. This database is updated every six months. ** Weekly residential listing magazine by Recruit Co.

Table 4. Descriptive Statistics of Office and Housing Rent Data

Rent (yen/m2) Contractual space (m2) Distance to Tokyo centre (minutes) Number of years after construction (years) Distance to station (minutes) Total floor space (m2) Number of observations=

Office Average 4,851.48 264.02 12.46 16.19 4.13 3,426.36 13,147

Standard deviation 1,925.12 309.87 6.25 10.29 2.91 4,520.41

Housing Average 3,248.26 41.03 10.53 9.26 6.76 – 488,348

Standard deviation 824.90 20.63 7.17 7.28 3.89 –

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Housing rents are assumed to be based on commutation convenience, indicated by proximity to the urban centre, the distance to the nearest station, building age, structure and other characteristics such as window and door aspects. Prices of one-room apartments mainly for singles, compact houses for DINKS (double income no kids) and other small families, and family-type houses for large households are structurally different. Housing preferences for small households including singles and DINKS are different from those for large households including parents and their children. Therefore, their bid prices are structurally different (Shimizu et al., 2004). The model is given in next equation:

log RitH = xiH ' θ H + d iH ' δ H + vitH

(7)

where RitH stands for the housing rent per unit area for property i at times t and xi for the vector of property i characteristics (including space occupancy,

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age, distance to the nearest station, time to the urban centre and a regional dummy variable).

Estimation Results Rent Functions for Office and Housing Uses Table 5 indicates estimation results for office and housing rent functions. Regarding the office rent function, age, or number of years since construction, was estimated at –0.093 and the distance to the nearest station at –0.219. As for age, the rent per square metre was estimated to decline by 9.3% every year. Although the decline appears too fast, the age variable apparently accounts for fast economic and technological deterioration of old office buildings amid the advancement of office buildings (for adaptations to office automation equipment, higher ceilings and earthquake resistance) and building methods (for features such as columns). Given the average age of 16 years for buildings in our analysis, we believe that the tendency may be strong. Distance to the nearest station indicates how business communication and workers’ commutation is convenient. Regarding the housing rent function for the standard compact type, age is estimated at –0.070, distance to the nearest station at –0.034, the First-floor dummy(Table.1) at –0.042 and proximity to the urban centre at –0.066. All of

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these variables are negative, consistent with the general tendency, but space occupancy is given as –0.197 in contrast to a positive figure for the office rent model. We must pay attention to the sign difference. Here, the constant term dummy and the cross term are also observed. Among constant term dummies, the one-room dummy is estimated at +0.706 and the family-type dummy at –1.581. Regarding cross terms between the one-room dummy and the variables, space occupancy is estimated at – 0.263, distance to the nearest station at –0.011, age at +0.025 and time to the urban centre at –0.040. The estimation results indicate that the tendency to avoid age for the one-room type is weaker than for the compact type. Oneroom apartment residents may give priority to convenience rather than environment, demonstrating strong preferences for shorter distance to the nearest station and a shorter time to the urban centre. For the family-house type, space occupancy is estimated at +0.043, distance to the nearest station at +0.004, age at –0.002 and time to the urban centre at –0.035. Family-type house residents have stronger preferences than compact or one-room house residents for newer and wider buildings. If +0.004 of the cross term is taken into account, the distance to the nearest station is then –0.030. This tendency indicates that residents in relatively wide rental condominiums give less priority to traffic convenience than do one-room and compact house residents. This suggests that better residential environments for houses are associated with longer distances to the nearest station. In Tokyo’s special wards, railway stations and their vicinities feature greater convenience and commercial concentration while lacking greenery, playgrounds or security. At locations that are more distant from railway stations, the natural environment, park development and security may be better. This may be interpreted to mean that households in larger houses might have given priority to natural environmental quality rather than convenience associated with shorter distances to railway stations. Therefore, family-type house residents who demonstrate stronger preferences for better residential environments are expected to be less sensitive to distances to railway stations than one-room or compact house residents.

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Table 5. Office and Housing Rent Function Estimation Results Method of Estimation

OLS

Dependent Variable

OR: Rent of Office (in log)

RC: Rent of Condominium (in log)

Property Characteristics (in log)

Coefficient

t-value

Coefficient

t-value

Constant FS: Contractual space BY: Number of years after construction WK: Distance to nearest station ACC: Time distance to Tokyo centre TA: Total floor space SRC: SRC building dummy

8.374 0.190 –0.093 –0.219 –0.112 0.051 0.199

181.483 59.102 –24.174 –46.556 –25.362 16.932 34.020

0.253 –0.197 –0.070 –0.034 –0.066 – 0.013

–24.999 –141.297 –259.324 –70.827 –117.539 – 29.494

D1F: First-floor dummy DR1: One-room dummy DRF: Family-type dummy

– – –

– – –

–0.042 0.706 –1.581

–76.386 94.008 –125.536

– – – – –

–0.263 –0.011 0.025 –0.040 0.403

–123.852 –14.917 63.409 –74.509 137.089

Cross-Term Effect by Property Characteristics DR1×FS DR1×WK DR1×BY DR1×ACC DRF×FS

– – – – –

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DRF×WK DRF×BY DRF×ACC

– – –

– – –

0.004 –0.002 –0.035

Ward (city) Dummy

Yes

Yes

Railway/Subway Line Dummy

Yes

Yes

Time Dummy

Yes

Yes

Adjusted R square= Number of observations=

0.608 13,147

0.758 488,348

4.966 –3.705 –46.599

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Condition for Profit Gaps The above office and housing rent function parameters are used to measure theoretical rents for buildings in our analysis. Building data identified through the GIS polygon include use, floor-space ratio, area, number of floors, building shape and geographic coordinates. Including time effects, these data are included to compute theoretical (predicted) office and housing rents for each building in 1996 and 2001. First, we computed theoretical rents, compared theoretical office and housing rents and confirmed the distribution of buildings that should be converted into housing for higher rents. The distribution of buildings for which housing rents would be higher than office rents is given for 1991, 1996 and 2001 (Figures 2, 3 and 4 in main document). In 1991, there are few buildings for which housing rents were higher than office rents, but such buildings proliferated year by year as bubbles burst. Particularly, clear distribution biases were confirmed. Such rent or profit gaps do not lead immediately to building use conversions because these are accompanied by demolition and reconstruction costs. If land-use conversions are expected to improve profit even with these costs taken into account, incentives for conversions may be effective. If land-use conversions are temporarily projected to improve profit at a certain point, however, they may not necessarily be implemented. Because real estate properties are durable investment goods, land-use conversions may not be implemented unless net profit is expected to improve even with costs taken into account for a certain period of time.

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In: Progress in Economics Research. Volume 23 ISBN 978-1-61324-394-7 Editor: Albert Tavidze © 2012 Nova Science Publishers, Inc.

Chapter 8

CONSUMERS’ RESPONSES TO CORPORATE SOCIAL RESPONSIBILITY: INCREASED AWARENESS AND PURCHASE INTENTION Ki-Hoon Lee*

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Griffith Business School, Griffith University, Queensland 4222, Australia

ABSTRACT Competitive business environments in recent years have put pressure on firms to examine their corporate social responsibility (CSR) activities. Importantly, it is observed that a transitional movement has begun from traditional CSR (i.e. giving back to society without any expectation of return) to strategic CSR (socially and economically win-win) in many corporations. A fundamental belief among business academics and practitioners is that CSR pays off for the firm as well as for the firm’s stakeholders and society in general. A failure to find strong empirical support for the relationship between CSR activities and financial performance has, however, been troubling to those advocating CSR. This lack of empirical relationship between CSR activities and financial bottom line is perceived by some businesses as evidence that these activities not relevant for successful business performance. *

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Ki-Hoon Lee

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Past studies have investigated how consumers perceive and respond to various CSR activities including corporate sponsorship, corporate donations, corporate voluntarism, and community involvement. Some important findings are related to attributions developed by consumers about motives of the corporation that conducts CSR activities, and whether these attributions exert a positive or negative influence on consumer attitudes toward the corporation. However, previous studies have not characterized corporate behaviors in terms of their perception by consumers as significant CSR, and researchers have paid little attention to consumers’ understanding of this notion of CSR. The present study explores the relationship between consumer awareness of CSR activities and the consumer’s purchase intentions. To this end, a questionnaire survey involving Korean consumers is employed. For the analysis, measurement scales for CSR activities and consumers’ purchase intention scales are respectively developed. From the results it is found that there is a significant positive relationship between these two parameters. This study finds that, as CSR activities, corporate social contribution and local community contribution affect consumers’ purchase intention while corporate environmental protection and contribution have no effects on purchase intention.

Keywords: Corporate social responsibility; consumer awareness; purchase intention; public relations communication strategy.

1. INTRODUCTION Over the past decade, the stream of research into how corporate social responsibility (hereafter CSR) may help a firm and its products and services to consumers has broadened considerably (Maignan, 2001). Corresponding terms used to express corporate social responsibility include corporate citizenship, corporate sustainability, and corporate responsibility. Since Milton Friedman (1970)’s incendiary argument in New York Times Magazine that “the social responsibility of business is to increase its profits” has been proliferation of definitions and arguments for and against his stance. In business terms, the World Business Council for Sustainable Development (WBCSD, 2004) defined CSR as “the commitment of business to contribute to sustainable economic development, working with employees, their families, the local community and society at large to improve their quality of life.” In management literature, Davis (1973) offered the definition of CSR as “the

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firm’s considerations of, and response to, issues beyond the narrow economic, technical, and legal requirements of the firm to accomplish social [and environmental] benefits along with the traditional economic gains which the firm seeks (p.312).” This research trend has flourished as the marketing potential of corporate responsibility initiatives, including corporate environmentalism, corporate citizenship, and corporate sustainability, has grown (Drumwright, 1994; Menon & Menon, 1997; Lee, 2009). Also, a broad range of CSR activities can be observed within the marketing discipline including cause-related promotion, donations, charity events, corporate sponsorship and employee volunteerism (Webb and Mohr, 1998; Brown and Dacin, 1997; Sen & Bhattacharya, 2001; Dean, 2002; Becker-Olsen et al., 2006). However, previous studies mainly focused on limited aspects of corporate social responsibility, such as community involvement or corporate giving or have considered corporate social responsibility (CSR) in general without inquiring into consumers’ understanding of this notion. This has led to inconsistency in marketing and customer-focused research in relation to CSR activities. As Sen and Bhattacharya (2001) pointed out, our understanding of the effects of CSR activities on consumers is weak despite an increasing emphasis on CSR in the marketplace. Maignan and Ferrell (2004) echoed Sen and Bhattacharya (2001)’s claim, stating that “past findings remain hardly comparable because they focus on specialized facets of CSR (p.17).” In addition, the concept of corporate social responsibility and most empirical works on this topic originated from Anglo-Saxon countries - mainly the U.S. and the U.K (Maignan, 2001; Matten & Moon, 2004). Given the international scope of corporate activities today, it is important for businesses and society to know whether corporate social responsibility is perceived in the same manner for other country contexts. The present paper intends to shed light on the nature of CSR activities as perceived by consumers. Working in the Korean context, this study will contribute to understanding of the boundary conditions on past studies and consequently help establish the external validity of the relationship between consumers’ awareness and purchase intentions. To this end, the paper examines the relationship between consumers’ awareness of CSR activities and their purchase intentions within the Korean context. The remainder of this paper is structured as follows: (i) conceptual background of corporate social responsibility in marketing principle, (ii) development of research tools and methods, (iii) analysis of study findings, and (iv) conclusion.

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Ki-Hoon Lee

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2. CONCEPTUAL BACKGROUND The term corporate social responsibility (CSR) has come into increasingly popular use, but it is only in recent years that the marketing agenda has expanded to include discussion of the concept of CSR or sustainability. In the marketing discipline, Lantos (2001) offered a definition of CSR as “the organization’s obligation to maximize its positive impact and minimize its negative effects in being a contributing member to society, with concern for society’s long-term needs and wants (p.600)”. Peattie (1999) noted that there are several important issues that arise in adopting CSR in the marketing discipline: (i) it is very difficult to define in practice; (ii) it is about social as well as environmental protection; and (iii) it is future oriented. CSR and related issues are not easy to define and implement in business practice, and thus researchers should explore and deliver what constitutes CSR at a business level. Also, social and environmental issues are dominant in CSR, and therefore scholars seek to protect the well-being of people through the delivery of social value and protection of the environment. Notably, the concept of CSR takes into consideration marketing strategy beyond the long-term, taking an open-ended view. Traditionally, corporate and marketing scholars have seen CSR as being incompatible with business objectives (Porter, 1996). Current competitive business environments orientate marketing strategies towards both the external environment and the future, ensuring that they remain competitive and sustainable in the long term. An increasing number of CSR studies have appeared in the marketing literature over the past decade. In particular, studies on consumer responses to CSR initiatives have proliferated (Brown and Dacin, 1997; Sen and Bhattacharya, 2001), along with work on the perceived importance of CSR among marketing practitioners (Singhapakdi et al., 1996) and benefits from corporate CSR actions (Maignan et al., 2001, 2003; Mohr et al., 2001). There is also a substantial body of empirical cases indicating that CSR contributes positively to market value and corporate performance (Brown and Dacin, 1997; Ellen et al., 2000; Sen and Bhattacharya, 2001). In business practice, CSR takes a variety of forms, including philanthropy, donations, cause-related marketing, environmental responsibility, and green marketing, among others. Regardless of their form, CSR intends to portray corporate image and reputation as a response to the needs of society. CSR initiatives offer support for such strategies. In particular, previous research has looked at the relationship between corporate attitudes (Brown and Dacin, 1997) and

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purchase intentions (Murray and Vogel, 1997). Importantly, it is worthwhile to examine whether intended CSR efforts and effects are achieved or not. Specifically, what motivations affect consumers’ attitude to a firm’s CSRrelated behavior? Furthermore, if consumers are aware of a firm’s CSR activities, is there a positive link between CSR awareness and purchasing intentions? From a corporate perspective, it is important to define socially responsible consumer for developing marketing initiatives, activities, and strategies. Webster (1975) offered a comprehensive definition of the socially conscious consumer as “a consumer who takes into account the public consequences of his or her private consumption or who attempts to use his or her purchasing power to bring about social change (p.188).” More recently, Mohr et al. (2001) advanced this definition as “a person basing his or her acquisition, usage, and disposition of products on a desire to minimize or eliminate any harmful effects and maximize the long-run beneficial impact on society (p.47).” They go on to describe key characteristics of a socially responsible consumer as “to avoid buying products from companies that harm society and proactively seek out products from companies that support society”. In this study, we adopt Mohr et al. (2001)’s definition of the socially responsible consumer. As Mohr et al. (2001) noted, consumers’ awareness of CSR activities should be secured before this factor can influence purchasing intentions and behaviors. Lack of awareness is likely to hinder consumer responses to CSR. Interestingly, past studies on consumer response to CSR have not taken the awareness problem into account. Rather, most studies have assumed awareness of CSR, and then measured consumer responses. More importantly, previous studies have paid little attention to consumers’ awareness and understanding of CSR activities and their purchase intentions. One of a few exceptions is the work of Mohr et al. (2001). Due to a lack of previous research on consumers’ awareness of CSR, they took an experimental approach to explore consumers’ attitudes regarding purchase intention. Carrying out forty-eight semi-structured interviews in the US, their study concluded that most interviewees do not regularly use CSR as a purchasing criterion. Similarly, Sen and Bhattacharya (2001) found that, regarding CSR actions and initiatives at a corporate level in certain CSR domains, including labor relations and employee working conditions, awareness can have a direct effect on the consumers’ purchasing intentions, particularly for consumers with certain CSR-related beliefs. Sen and Bhattacharya (2001) adopted the category of CSR – Corporate Social Ratings Monitor developed by KLD (Kinder, Lydenberg, Domini & Co. Inc. 1999) with six domains of

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community, diversity, employee support, environment, non-US operations and product. More recently, Maignan (2001) adopted four dimensions of CSR (economic, legal, ethical, and philanthropic responsibilities) from Carroll (1973)’s work. She argues that U.S. consumers view economic and legal responsibilities as two key CSR categories while French and German consumers rate economic responsibilities as the least important CSR category. However, it is worth noting that in the real world of business practice, consumer awareness of CSR initiatives is fairly low (Bhattachary and Sen, 2004; Sen et al., 2006). Even recent studies (e.g. Bhattachary and Sen, 2004; Maignan, 2004; Sen et al., 2006) suggest that consumers’ awareness of CSR activities is a key obstacle in gaining strategic rewards from such activities. Academics and practitioners in the marketing discipline have also reported multifaceted dimensions of CSR in business practice, such as environmental, economic, philanthropic, and economic dimensions. In addition, consumers’ response to CSR in the market place may not be primarily manifested in product choice. Thus, it is very important for academics and practitioners to investigate ‘why’ and ‘how’ consumer CSR responses differ in CSR categories and activities; more importantly, the relationship between awareness and buying behavior should be explored.

3. RESEARCH METHODS This study was conducted in the period between the 1st October and 31st October, 2008. A randomly selected sample of 250 South Korean consumers participated in this study. A total of 250 questionnaires were distributed and 233 were returned. Eighteen questionnaires were not fully answered and were thus excluded from the analysis. Thus, a total of 215 samples, constituting a 86% returned ratio, were applied in this study. The average age of the respondents in this sample was 39 (Mean=39, Minimum=18, Maximum=64) and 50.7 % of the sample was female (N=109). Among the respondents, 22.3 % graduated high school, 54.9% received college and university education, and 22.8 % were university graduates or above.

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Table I. Respondent Characteristics N=215

%

Male Female

106 109

49.3 50.7

20-29 years 30-39 years 40-49 years ≥ 50 years

90 59 38 28

41.9 27.4 17.7 13.0

High School College (2-year) University (4-year) University Graduate University Postgraduate

48 25 93 39 10

22.3 11.6 43.3 18.1 4.7

Gender

Age

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Education

4. INSTRUMENT DEVELOPMENT For research instrument, we developed measures of (1) consumers’ awareness of corporate social responsibility activities and (2) consumers’ purchase intention, respectively. For the measurement items of consumers’ awareness of CSR activities (M=4.92, S.D.=1.34, α =.91), we adopted the 5 items from Maignan (2001) and added 4 items. A total of 9 items were thus employed with a 7-point Likert scale ranging from 1 (not at all) to 7 (extremely well). The 9 items are local economic development, consumer protection, social welfare, donations, education, environmental protection, culture activities, local community development, and local community involvement. For analysis purposes, we categorized the items of corporate social responsibility activities as follows: (1) corporate social contribution (local economic development, consumer protection, social welfare, donations, and education), corporate environmental contribution (environmental protection), and corporate local community contribution (culture activities, local community development, and local community involvement). For a reliability test, Croanbach’s alpha was applied and the range of the alpha value was from 0.87 to 0.94. For the measurement items of consumers’ purchase

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intentions (M=4.82, S.D.=1.35, α =.94), we adopted the 5 items from Maignan’s work with a 7-point Likert scale ranging from 1 (definitely would not) to 7 (definitely would). The following is an example of one of the developed items: ‘I would purchase products from a socially responsible company.’ Table II. Instrument and Scales Measurement Category

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Consumers’ awareness of CSR activities (M=4.92, S.D.=1.34, α=.91)

Consumers’ purchase intention (M=4.82, S.D.=1.35, α=.94)

Items Local economic development Consumer protection Social welfare Donations Education Environmental protection Cultural activities Local community development Local community involvement I would pay more to buy products from a socially responsible company I consider the ethical reputation of business when I shop I avoid buying products from companies that have engaged in immoral actions I would pay more to buy the products of a company that shows caring for the well-being of our society If the price and quality of two products are the same, I would purchase from the firm that has a socially responsible reputation

Scales

7-point Likert Scales: 1 (not at all) – 7 (extremely well)

7-point Likert Scales: 1 (definitely would not) – 7 (definitely would)

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5. FINDINGS Prior CSR research in the marketing discipline suggests that CSR activities in certain CSR domains (e.g., environmental protection, local community involvement) may have a direct effect on consumers’ purchase intentions, and consumer awareness of these activities may also affect purchase intention. For example, Maignan and Ferrell (2003) found that consumers in the US and Germany were prone to differentiate economic responsibilities from legal and ethical responsibilities. Within a Korean context, the present study found that consumers’ awareness of CSR activities and their purchase intentions are linked positively. The aim of this research is to test the relationship between consumers’ awareness of CSR activities and their purchase intentions. The study analysis revealed that there is a positive relationship between the consumers’ awareness of CSR activities and consumers’ purchase intentions (t=13.61, df=213, p