Macroeconomic Responses to the COVID-19 Pandemic: Policies from Southeast Europe 303075443X, 9783030754433

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Table of contents :
Foreword
Preface
Acknowledgements
Contents
Notes on Contributors
Abbreviations
List of Figures
List of Tables
Part I Macro Economics of COVID-19
1 Current and Long-Run Challenges for the Croatian Economy, in Comparison
1.1 Introduction
1.2 Post-COVID Challenges
1.3 Policy Recommendations
References
2 COVID-19 Contagion Among Countries
2.1 Introduction
2.2 The Model for Introducing Lockdown (Determining the Tipping Point for the Start of Epidemics)
2.3 Explaining COVID Contagion Among Countries
2.4 Correlation Analysis
2.5 Regression Analysis
2.5.1 Structure of Estimated Equations
2.5.2 Equations
2.6 Application for Slovenia and Croatia
2.7 COVID Crisis in 2020 Versus Financial Crisis in 2008
2.8 Conclusion: Major Findings and Policy Suggestions
2.8.1 Findings
For Croatia and Slovenia
In General
Policy Suggestions
Appendix
References
3 Short-Term Impact of COVID-19 in the Clusters of EU Market Economies
3.1 Introduction
3.2 Theoretical Background
3.3 Applied Methodology and Data Sources
3.3.1 Cluster Analysis
3.3.2 Data
3.4 Results
3.4.1 The Result of Clustering
3.4.2 Behaviour of Clusters During the First Wave of the Virus
3.5 Conclusions
References
4 Macro Economic Model of COVID-19 Pandemic Crisis
4.1 Introduction
4.2 Curve of the Pandemic Shock and the Curve of the Economic Crisis
4.3 Macroeconomic Model of COVID-19 Crisis
4.4 COVID-19 Crisis and Circular Flow of the Economy
4.5 Framework of Macroeconomic Response to COVID-19 Crisis
4.6 Conclusion
References
Part II Economics Policies during COVID-19
5 Central Bank’s Balance Sheet Management in Times of Systemic Crises
5.1 Introduction
5.2 Liquidity Trap and the Transformation of Monetary Policy
5.3 Central Bank Balance Sheet: The Most Important Instrument of Contemporary Monetary Policy
5.3.1 The Structure of the Central Bank Balance Sheet
5.3.2 Different Forms of Balance Sheet Policies
5.3.3 Monetary Transmission Mechanisms Based on the Central Bank’s Balance Sheet
5.3.4 Long-Run Changes of CB’s Balance Sheet: Example of Bundesbank
5.4 Comparative Analysis of the Central Banks’ Balance Sheets
5.4.1 Comparison of Major Central Banks: Fed, Eurosystem, BoE, and BoJ
5.4.2 Comparison of the Balance Sheets Euro Area’s Central Banks
5.4.3 Comparison of Non-Eurozone EU Central Banks
5.4.4 Individual Analysis Between Selected CEE Countries in the COVID-19 Health Crisis
Hungary
Czech Republic
Poland
Romania
Croatia
Bulgaria
5.5 Discussion and Policy Implications
5.5.1 Summary of the CBs’ Balance Sheets’ Comparisons
5.5.2 Balance Sheet Policy as Modern “Debt Monetization”
5.5.3 Policy Implications
5.6 Conclusion
References
6 Quantitative Easing, Stock Exchange, Inflation and Monetary Paradigm in the US: Lessons for Emerging Economies
6.1 Introduction
6.2 Quantitative Easing, Inflation, and Asset Prices
6.2.1 Great Recession QE vs Coronavirus Crisis QE
6.3 Rethinking Macroeconomics and Rebirth of MMT
6.4 Quantitative Easing–Stock Market Nexus
6.5 Results: So How Strong Is the Nexus?
6.6 Conclusion
References
7 Monetary Policy in Croatia During Two Recessions
7.1 Introduction
7.2 Monetary Policy Framework in Croatia
7.3 The Great Recession
7.4 The Second Crisis
7.5 Credit Policy During Two Crisis
7.6 The Evolution Process
7.7 Monetary Policy Recommendations
7.8 Conclusion
References
8 Monetary Transmission in Croatia: A View from the Eurozone’s “Waiting Room”
8.1 Introduction
8.2 Literature Review
8.3 A VAR Analysis of Monetary Transmission in Croatia
8.4 A View on the Monetary Transmission in Croatia from the Eurozone’s “Waiting Room”
8.5 Conclusion
References
9 Monetary and Fiscal Policy Response During COVID-19 Crisis in Bosnia and Herzegovina: Constraints and Potentials
9.1 Introduction
9.2 Monetary Policy in Small Open Economies with Reflection on Western Balkan Countries
9.2.1 Inability to Conduct (the Appropriate) Discretionary Monetary Policy in Small Open Economy
9.2.2 Reaction of Western Balkan Central Banks to Crises
9.3 Monetary Policy in BiH and (In)ability of Central Bank of BiH to React in Crisis
9.3.1 Potentials in the BiH’s Banking System
9.4 Fiscal Policy in a Small Open Economy—Literature Review and Comparison of BiH and Western Balkan Countries
9.5 Fiscal Policy in BiH
9.5.1 Constitutional and Institutional Organization of BiH
9.5.2 The Implementation of Fiscal Policy in BiH and the Constraints to React in Crisis
9.5.3 The Potentials of the Fiscal Policy in BiH
9.6 Conclusions and Recommendations
References
Part III Broader Impact of COVID-19
10 Emergency Financial Mismanagement in Croatia During COVID-19 Crises
10.1 Introduction
10.2 From Tactical to the Strategic EFM
10.3 Financial Response to the Pandemic Crisis in Croatia
10.4 Three Major Issues in Policy Response in Croatia
10.5 Structural Roots of the Inefficient EFM in Croatia
10.6 Underdeveloped Emergency Management System
10.7 Deficient Strategic Planning
10.8 Public Administration Politicization
10.9 Conclusion
References
11 Modern Monetary Theory and COVID-19 Crisis
11.1 Introduction
11.2 Post-Keynesian Economics
11.3 Modern Money Theory
11.4 Endogenous Money Theory
11.5 Avoiding Fiat Money
11.6 MMT in Eurozone
11.7 MMT in European Union: The Case of Croatia
11.8 Conclusions
References
12 Impact of COVID-19 on Working from Home in Serbia: Possibilities and Consequences
12.1 Introduction
12.2 Literature Review
12.3 Research Method
12.3.1 Research Results and Discussions
12.4 Method of Researching the Effects on Health
12.4.1 Research Results
12.5 Conclusion
References
Index
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Edited by Neven Vidaković Ivan Lovrinović

Macroeconomic Responses to the COVID-19 Pandemic Policies from Southeast Europe

Macroeconomic Responses to the COVID-19 Pandemic

Neven Vidakovi´c · Ivan Lovrinovi´c Editors

Macroeconomic Responses to the COVID-19 Pandemic Policies from Southeast Europe

Editors Neven Vidakovi´c Loti Trading LLC Zagreb, Croatia

Ivan Lovrinovi´c Faculty of Economics and Business University of Zagreb Zagreb, Croatia

ISBN 978-3-030-75443-3 ISBN 978-3-030-75444-0 (eBook) https://doi.org/10.1007/978-3-030-75444-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword

The COVID-19 pandemic reveals our human-made economic and financial systems as they really are—complex, interconnected, and vulnerable. Doyne Farmer from Oxford describes the “world economy where heterogeneous, global production networks (50 million firms with billions of physical links) interact with household networks (2 billion households, 3.3 billion workers and trillions of links to consumed products), a web of contracts (trillions), and ownership patterns where a few firms and individuals own almost everything”. Macroeconomics attempts to describe analytically the global economy and reduce this complexity to a system of equations. However, the crisis makes it clear that the macroeconomy is inherently intricate and interlinked and offers complex interactions on individual levels, that give rise to emergent properties at the macro level and endogenous shocks. It is not a closed equilibrium system, subject to occasional exogenous shocks, knocked off track but with a combination of monetary, fiscal, and structural policies gets back to a steady state. When considering the economy as a complex adaptive system, new tools and techniques are required to understand the full scope of this system. The OECD established its New Approaches to Economic Challenges (NAEC) Initiative to distil the lessons and roots of the Global Financial Crisis. OECD Member governments agreed to create a space to discuss and critique economic ideas, models, narratives and experiment with new analytical approaches. Paul Krugman once said that OECD is v

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conventional wisdom central, and he meant that as a good thing—we need a place to agree on common approaches and shared understanding of economics and policy. Krugman also described NAEC as “a skunk works for economics and policy”—experimentation and innovation. And probably both are necessary for effective policymaking. NAEC is trying to advance new approaches to macroeconomics. However, all systems have a certain inertia. There has been a great deal of investment in the techniques that have been used for some time and this leads naturally to take very seriously the problem of shifting to new and possibly less tested approaches. The role of NAEC is to put these new approaches and rethinking the framework, on the table. It is not to argue that there should be an automatic switch to any of the new approaches presented, but rather to put them in the picture so that they are taken into account.

What is wrong with macroeconomics? Rick Bookstaber’s book The End of Theory described the “Four Horsemen of the Econopalypse”—the four characteristics of human and systemic behaviour that macro frameworks—Intertemporally optimizing, rational representative agent models cannot capture. These characteristics are not minor aspects of the economic system but fundamental features of them. The Four Horsemen include computational irreducibility, emergent phenomena, non-ergodicity, and radical uncertainty (Bookstaber, 2017). 1. Computationally irreducible systems have outcomes that cannot be summarized by a system of equations. Instead, they must be experienced, or in the case of models, simulated, period by period in order to find out what actually happens. 2. Emergent phenomena are situations where the individuals’ actions contribute to outcomes at the system level that deviate from the agents’ actions, and in some cases, countermand the agents’ actions or even bring harm to them, as with stampedes (see Harper and Lewis, 2012). 3. Economies are non-ergodic systems’—i.e. outcomes depend critically on history and context, every situation is different and can produce outcomes that differ significantly from previous situations. In other words, the future does not always look like the past.

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4. Finally, radical uncertainty (also known as Knightian uncertainty) means that not only are the probabilities of various events and disturbances unknown, but the event space itself is not fully known (Kay and King, 2020).

Fixing Macro or Rebuilding Macro? There are differing perspectives on how to respond to these fundamental problems. Some argue that economics needs significant reform, but it should be done essentially through extending and modifying existing frameworks. Specifically, the idea of the economy as an equilibrium system should be preserved, but more behavioural and institutional realism should be introduced, more allowance for various market failures made, political economy concerns should be revived, and more empirical data utilized. Others believe a more radical reframing of the field is needed. Specifically, the equilibrium framework should be abandoned in favour of complex systems, dynamic, reflexive, and evolutionary approaches, high degrees of behavioural and institutional realism, and adoption of newer analytic methods such as computer simulation, network theory, and big data statistical approaches (Beinhocker and Hanauer, 2014; Cerna and Hynes, 2018). One person who believes in this more radical reframing is Andy Haldane, Chief Economist of the Bank of England. He previously wrote about the similarities between pandemics and financial crisis noting that the structure of our system is conducive to fragility, with short-term individualistic incentives within a framework that is increasingly interconnected and interdependent. As Andy Haldane’s prophetic comparison in 2009 put it: “Both events were manifestations of the behaviour under stress of a complex, adaptive network. Complex because these networks were a cat’scradle of interconnections, financial and non-financial. Adaptive because behaviour in these networks was driven by interactions between optimising, but confused, agents. Seizures in the electricity grid, degradation of ecosystems, the spread of epidemics and the disintegration of the financial system – each is essentially a different branch of the same network family tree.” (Haldane, 2009). https://www.bis.org/review/r090505e.pdf.

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Resilient Economies NAEC has proposed a new approach to the economy and economies. Such a new approach encompasses a new set of goals and measures of economic and social progress (emphasizing well-being, social cohesion, environmental boundaries); new frameworks of economic analysis (acknowledging the historical, cultural, political, and environmental dimensions of economic behaviour); and new kinds of policies (from correcting market failures and managing trade-offs to structural transformation) (OECD, 2020). This approach can tackle interrelated goals such as achieving environmental sustainability, reducing inequalities, raising well-being, and ensuring the socio-ecological system is resilient to future shocks. Resilience has become an important subject during and after the COVID crisis. It has a long tradition in macroeconomics. As Ben Bernanke argued, “the best approach for dealing with this uncertainty is to make sure that the system is fundamentally resilient and that we have as many fail-safes and back-up arrangements as possible”. Yet resilience is a challenging issue for economists who typically place an emphasis on short-term efficiency rather than long-term resilience. Hynes et al. (2020) argue that the emphasis on efficiency in the operation, management, and outcomes of various economic and social systems is not a conscious collective choice, but rather the response of the whole system to the incentives that individual components face. Building resilience does not mean abandoning efficiency, but rather maximizing socio-economic systems’ longterm sustainability in the face of future disruptions. Combining resilience with efficiency is a key policy challenge for macroeconomics but it holds the promise of allowing society to withstand future shocks (Trump et al., 2020).

Responses to the Pandemic NAEC has a strong connection with South-East Europe with Ambassadors Erdem Basci (Turkey) and Irena Sodin (Slovenia) chairing the Friends of NAEC. Their leadership and engagement kept the NAEC initiative striving to pave the way for new avenues of research while also maintaining the crucial link between economic science (developed in academia) and economic engineering (the economics used for policymaking). This volume is in the finest traditions of NAEC. It offers

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lessons from the COVID crisis still unfolding (modelling the contagion and the impact on the economy). It highlights interdisciplinary analysis on how the crisis is changing views of economic policy (especially the interplay between monetary and fiscal policies), and broader issues (financial management, new working arrangements and their impacts) while introducing new concepts that are the subject of debate such as Modern Monetary Theory (MMT) and their implications for debt, inflation and macro policy. Above all this volume-enhancing understanding of our macroeconomic system, applied to the national and regional experiences of South-East Europe. Economics is an essential tool for improving the well-being of citizens. The pendulum has swung between a state-centric or market-centric approach. The pandemic highlights the need for the State to step in when things go wrong. Economies are not as stable as traditional economic framework predict, but neither are they are unstable, as complexity science would suggest. There must be some self-stabilizing dynamics within market-based systems. Looking to the future and with mounting pressures due to climate change, demographics, inequalities, it’s likely that structural reforms (labour market flexibility, competition in product markets, functioning financial markets, promoting diffusion of innovation) to enable markets to self-organize in an efficient way may not be sufficient. If these were the hallmarks of policy in the late twentieth century, then the twenty-first century will have to be about managing the complex human-made systems in which we operate. But of course, this is a debate and this volume helps us to assess how COVID-19 might change our perspective on growth and efficiency and how these objectives may need to be complemented with sustainability and resilience. The book offers practical ways in which these ideas could be put into practice within a specific set of economies shaped by their own cultures, histories and social norms yet interacting with a complex set of systems that extend far beyond their borders through health care, financial markets, and global value chains. COVID has illustrated how deeply interconnected our economies and societies are and success for

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South-East Europe will largely hinge on how it can manage its domestic economy while harnessing the benefits of integration with the global one. William Hynes Senior Advisor to the Secretary-General and Coordinator of New Approaches to Economic Challenges at OECD – OCDE Paris, Europe

References Beinhocker, E., and Hanauer, N. 2014. Capitalism Redefined. Democracy 2014 (31): 30–44. Bernanke, B. 2010. Interview with the International Herald Tribune (IHT), May 17. Bookstaber, R. 2017. The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction. Princeton, NJ: Princeton University Press. Cerna, L. and Hynes, W. 2018. A Pluralist Approach to Public Policy: The Case of the OECD’s New Approaches to Economic Challenges (NAEC) Initiative. International Journal of Pluralism and Economics Education 9 (4): 376–390. Haldane, Andrew G. 2009. Rethinking the Financial Network, BIS Review, 53. https://www.bis.org/review/r090505e.pdf. Harper, D. and Lewis, P. 2012. New perspectives on emergence in economics, Journal of Economic Behaviour & Organisation 82 (2–3): May 2012, 329– 337. Hynes, W., Trump, B., Love, P., and Linkov, I. 2020. Bouncing Forward: a Resilience Approach to Dealing with COVID-19 and Future Systemic Shocks. Environment Systems and Decisions 40: 174–184. https://doi.org/10.1007/ s10669-020-09776-x. Kay, J. and King, M. 2020. Radical Uncertainty: Decision-Making for an Unknowable Future, London: The Bridge Street Press. OECD, 2020. Beyond Growth. Towards a New Economic Approach. 10.1787/a6a 5f2eb-en. Trump, B. D., Linkov, I., Hynes, W. 2020. Combine Resilience and Efficiency in Post-COVID Societies. Nature 588.

Preface

The focus of this introduction is to create a coherent overview of the papers in this monograph and to reconcile constraints that countries of SEE face. COVID pandemic has created a new situation for the region of SEE. Rising fiscal debts and an inept banking system are identified as the main challenges for the future. As such optimal monetary policy mix is proposed. Monetary policy has to focus on the activation of the credit channel of monetary transmission. Fiscal expansion should continue, but with a focus on the control of the term structure of debt. Countries of SEE are inextricably tied to the EU and so policies of EU have to be created with countries of SEE in mind.1 A COVID-19 pandemic is an economic event that will be talked about for decades. Just when the global economies were completely getting over the adverse shock of the Great Recession new crisis hit. Again, both monetary and fiscal policies had to rise to the occasion and help the economy as much as possible. A small contribution to the theoretical analysis of the COVID-19 pandemic on a particular region is this monograph as well. The main objective of this monograph is twofold. The first objective is to create a proposition of the optimal monetary and fiscal policy mix for the post-COVID-19 world from SEE perspective. The vaccination process has started, and the pandemic will be over soon. What comes 1 The Economist, (2021): Some pleasant fiscal arithmetic: Should governments in

emerging economies worry about their debt? London; February 13th, 2021.

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after the pandemic and lockdowns will be a challenging and interesting time. This book aims to make several contributions to what economies policies should look like in order to make the post-COVID-19 economy a better and more stable one. The second objective of this book is to give a contribution to the answer to the question: what kind of a world do we want post-COVID-19 with a particular focus on the SEE region? The first problem can be answered with a proposal for the interaction of the fiscal and monetary policy for the next few years. The second problem will be a work in progress for a long time. The economies of South and Eastern Europe are each separate entity and have their own specific characteristics but are fully integrated into the European and global economy. Whatever happens to the EU and whatever the state of the EU economy is, it will be replicated in the economies of SEE. There is no avoiding the relationship and the effects of policy transfer from EU to SEE region regardless of their current relationship or status with the EU. Because of this, it is impossible to separate any kind of economic analysis of SEE without a full understanding of the future development of the EU. Some countries like Slovenia are fully integrated into the EU, others like Hungary or Croatia are part of the EU, but not of EMU. For instance, Croatia and Bulgaria are on the path to the euro, they entered into ERM2 transitional monetary arrangement, although they have excessive macroeconomic imbalances. On the other side of the spectrum are the Republic of North Macedonia, Albania, Serbian, Montenegro, and Bosnia and Herzegovina have only started their journey into the EU. The process of integration will only increase over time and the more Europe integrates the more will disbalances of any individual country have an effect on the EU as a whole. This is the principal point in logic that for a full understanding of the future of SEE countries and how to design policies for SEE an understanding of policies of EU and fully integrated EU countries is needed. Countries of SEE have had quite different experiences over the last 30 years, but their fates are intertwined with the future of the EU and the overall course of the globalization process. This monograph will provide such policy suggestions. Here we would like to summarize the contributions of the authors in this monograph and we are trying to contribute to the design of the optimal economic policies for the SEE region. The region is inexorable connected with the EU and therefore EU and ECB policies spill over into the economic policies of the SEE countries. This fact decreases the

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maneuvering room of the SEE countries, but it also provides opportunities to adjust their policies to make the best of the EU. Any economic policy design has to be based on the fact countries of SEE are small open economies where any economic shock is greatly amplified. This book is organized as follows: The first part of the monograph is focused on the macroeconomic overview of the pandemic and the countries affected by the pandemic. The main emphasis is on the relative comparisons between the countries. Kolozs et al. (2021) point out that economies in the EU have had very different structures and starting points once the COVID-19 began. This analysis also makes any uniform economic policies hard. Different economies will need different specific policies, but the overall framework can be similar for all SEE economies. Kolozs et al. find that initial starting points have largely determined the effects and responses of the crisis. On the other hand, Holzer (2021) focuses on Croatia and what are the main characteristics/deficiencies of the Croatian economy. He concludes the focus on just one economic sector (tourism) has severely diminished other potentials of the Croatian economy. A useful starting point for the longer term analysis of the COVID ˇ pandemic and how it will develop over time is provided by Cavrak (2021) who points out the pandemic has four stages: (1) supply shock; (2) demand shock; (3) falling expectations and rising uncertainty; and (4) the shock of rapid bad measures. We are now in the third and fourth stage. As the vaccines are rolling out more and more people are increasingly concerned about what will happen to the economies once they open and the enormous fiscal and monetary stimulus which has kept the economy afloat during the lockdown starts to wane. The economic effects of lockdowns and the question of human vs. economic costs were addressed in a paper by Šiblar (2021). The issue of the cost of economic policies has always been at the forefront of the economic policy design. The successful policies are the ones that have the most impact on jobs creation and real economic growth, two variables EU policies are not able to jolt equally across the EU. We are seeing that uniform policies regardless of are they related to the handling of the COVID pandemic or a particular sector of the economy are not appropriate for the countries of the SEE. This brings us to monetary and fiscal policy in the region of SEE which is analyzed in the second part of the monograph. Again, it is useful to take a broad overview as the starting point. A particularly detrimental analysis

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of the QE has been presented by Sinkovi´c and Škare (2021). The effects of the QE have largely been on the value of the stock market with limited real effects. The monetary expansion as a policy was studied also in Lovrinovi´c et al. (2021) while developed countries have embraced monetary policy expansion as QE and increase in the size of the balance sheet, smaller countries have not done so. Lovrinovi´c et al. also question the sustainability of such policies in the long run. Vidakovi´c (2021) analyses monetary policy in Croatia and confirms the slow adoption of new monetary policy tools. At the same time, Vidakovi´c looks at the change in the credit policy of Croatian banks. Although they have large liquidity banks in Croatia mostly lend to the government and not to corporations. Benazi´c and Uˇckar (2021) also, analyze monetary policy in Croatia and use VAR model to determine the impact of the interest rates on banking policies. Kreso, Lazovi´c-Pita, and Durakovi´c (2021) look at a particular case of monetary and fiscal policy in Bosnia and Herzegovina. The paper clearly identifies the limitations of monetary and fiscal policy in the existing political arrangement of BiH. The second part of the monograph has a common theme: there is a disconnect between the monetary policy actions and the real economy needs. The banks have high liquidity, and the monetary policy is accommodative, but the real economy is not getting enough funds to boost investments and economic growth. The theoretical effects of a decrease in the interest rates are not being transferred into long-term investments and economic growth. The third part of the monograph addresses topics that have also taken a prominent place during the COVID pandemic. Bari´c (2021) investigates the issues of financial crisis management. Recent business cycles have been more focused on the financial sector not on the real economy, precisely because of that emergency financial management has come into prominence. The paper in-depth analyses how to create an appropriate policy response and what were the deficient points of financial crisis management in Croatia. Domazet (2021) analysis of the modern monetary theory in general, in Eurozone and in Croatia in particular. MMT has travelled from being an obscure theory to becoming a forefront of policy response in the economies. The paper looks at how MMT can be used to exit the current economic crisis. Without acknowledging it, The Economist (2021)

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recently published an article that is implicitly accepting MMT as mainstream. But they put all the accent on the interest rate in relation to the GDP growth rate (what they call the “growth corrected interest rate”). And they say things like: “Economists have long worried that public borrowing can crowd out private investment (or hurt the trade balance). That is less of a concern if the government spends on investment. It is also less of a worry if the economy is operating below capacity: public spending can then “crowd in” additional investment by improving incomes and profit prospects.” The COVID pandemic has had an effect on all elements of the economy. Radovi´c-Markovi´c and Jovanovi´c (2021) look at the effects of work from home in Serbia and conclude the increase in work from home has led to negative effects. The third part of the monograph shows how the COVID pandemic has had an effect on all elements of economic science and was of life. The policy recommendations of Bari´c (2021), Domazet (2021) and Radovi´cMarkovi´c and Jovanovi´c (2021) clearly show that economics is finding ways to improve the economy in all segments of economic activity. The economic policy and state of the economy of the EU and European Monetary Union are exceptionally important for the countries of SEE since they are connected with the EU and Eurozone. The countries of the SEE region share the same problems with the EU, regardless of how much they are integrated into the EU. Throughout the monograph, it has been emphasized that the economic policies of the EU and ECB will significantly affect the SEE countries. There is no escaping the relationship. Except there is an important caveat, the countries of the SEE region are “small open economies” that are highly susceptible to volatile capital flows. This fact amplifies any economic disturbances and this is precisely why economic prudent and caution is advised when designing new policies. We can split potential policy responses into two separate parts: monetary policy and fiscal policy. But, the most important is appropriate “policy mix”, to achieve optimal results. More complex analysis of the new monetary policy strategies in EU and EU periphery economies (SEE countries) is beyond the scope of this book. But, it is our conclusion that monetary policy has to focus on how to increase banks’ lending to private enterprises in order to stimulate investments and consequently employment. Small open economies can hope to attract foreign investments, but should realize they have to focus on their own monetary arrangements. Stimulating lending of the real

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economy sector through unconventional monetary policy strategies (QE) is desirable. Exchange rate policies should also be implemented if the central bank has sufficient mechanisms to control the exchange rate passthrough effects. The optimal policy would be to stimulate commercial banks lending, enabling efficient transmission mechanism functioning. The European Union fiscal rules (Maastricht criteria) have been suspended as a consequence of COVID-19 crisis, but they will have to be modified, if only because of the high levels of debt (see, Blanchard et al., 2021).2 Fiscal policy should do “whatever it takes” to stimulate the economy and work together with the unconventional monetary policy in order to stimulate growth, but the short and medium-term focus has to be on maintaining control of the term structure of debt. We would like to emphasize that here is an important issue of overall debt stability. In the EC document “Debt sustainability monitor” (2021),3 the debt problem is clearly recognized at the EU level. But, it is also clearly recognized that COVID-19 pandemic is changing EU economic governance, as well (Guttenberg et al., 2021):4 “The pandemic will completely shake up the EU‘s economic governance in five ways: EU debt is possible and will become a reality; the EU and the Eurozone get a fiscal capacity; the European Semester will be history; the crisis management architecture is politically questioned; and the Eurozone loses its relevance for EU decisionmaking. Taken together, these five lessons from the pandemic will render the old pre-pandemic Eurozone reform agenda obsolete. EU institutions should use the coming 18 months to prepare a new reform agenda for EU economic governance that can deliver tangible results before the next EU long-term budget will be negotiated”. The past year has thought us to raise fundamental questions and they require a systematic rethink of the reform agenda, that will significantly affect SEE economies in the near future.

2 Blanchard Olivier, Leandro Alvaro and Zettelmeyer Jeromin, (2021): Redesigning EU Fiscal Rules: From Rules to Standards; Petereson Institute for International Economics (PIIE); PIIE Working paper 21-1; Washington DC, February 2021. 3 Debt Sustainability Monitor 2021. Institutional paper 143, European Commission Directorate-General for Economic and Financial Affairs https://ec.europa.eu/info/sites/ info/files/economy-finance/ip143_en.pdf. 4 Guttenberg Lucas, Hemker Johannes and Tordoir Sander, (2021): Everything will be

different: How the pandemic is changing EU economic governance; Hertie School, Jacques Delors Centre; Policy Brief, Berlin; 11 February, 2021.

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Many COVID measures should be designed to prop up the real economy in SEE countries and macroeconomic policy responses should be focused on increasing public investments in “Green Economy” and economic infrastructure projects with high fiscal multipliers. It is about designing optimal “fiscal – monetary mix”, that is crucial, because of the complex nature of the COVID-19 crisis. In 2021 the most important risk in economic policy design and implementation is uncertainty. We hope that this monograph will present some general outlines for decision-makers in SEE economies and multilateral financial institutions and contribute to academic discussions in SEE countries. Zagreb, Croatia February, 2021

Neven Vidakovi´c Ivan Lovrinovi´c

Acknowledgements

By November 2020 economic situation in Croatia was getting worse by the minute. The economic plan implemented by the government was very simple: lock down the economy, introduce new social transfers in order to preserve jobs even for a short period of time, and hope that the money from EU funds will provide a long-awaited economic respite. This bleak situation was even more exasperated on the side of the economic profession where very little research about the impact of COVID-19 on the economy was done. Most academic economic institutions in Croatia have provided little or no answer to the burning economic problems: pandemic and earthquakes. Apart from solving day-to-day problems, there was no long-run economic plan on what to do after the COVID-19 is over? In November a small group of macroeconomists answered a call from Dubravko Radoševi´c, former economic adviser to the President of the Republic of Croatia, to meet and discuss academic projects on COVID19 crisis in Croatia and SEE region. At the first meeting the present ˇ were Dubravko Radoševi´c, Ivan Lovrinovi´c, Vladimir Cavrak, Martina Soleniˇcki, Karlo Vujeva, and Neven Vidakovi´c. The centre of our discussion was to answer a simple question: what can be done? Of course, from an academic point of view. Very quickly we came to a simple proposal, we are going to organize a conference and then we are going to publish research papers in an international monograph. The idea from the onset was to have an international group of economists from the region who can share their research. We did not want

xix

xx

ACKNOWLEDGEMENTS

just to have economic research about the state of the economies in the region, we wanted what we have dubbed: real-time research. Economic papers which reflected the current situation with as recent data as possible and economic papers that at the same time provided an opportunity to create outlines of policy proposals in order to improve the economy. Having an international team meant that we also have to move our narrow research from Croatia to the region of South and Eastern Europe and the European Union. At the initial meeting, we created a shortlist of people from the region we wanted to include in the research project and all of them have immediately said yes to our invitation. We were glad to realize other economists were also looking for an outlet for their research and were eager to participate in a constructive way to solve problems. The international scientific conference “Macroeconomic Policy during COVID-19 Crisis” was organized in honour of the centenary of the Faculty of Economics and Business from the University of Zagreb and it was held on the 10th of December 2020 when participants were able to present their views on COVID-19 crisis and policy options. All credits for the successful organization of the conference goes to the management of the Faculty of Economics and Business Zagreb, Department of Finance and Professor Ivan Lovrinovic and his team. In your hands, you are holding the works of more than 20 economists who have answered the call to do something, to think about the current situation (lockdowns, deep recession, unemployment, rising uncertainty, etc.). As editors, we realized we cannot cover every topic we want, but at the same time knowing the authors in this monograph we knew we are going to have an outstanding body of research. We have decided to split the monograph into three main parts. The first part is focused on the macroeconomics of the region and COVID. The second part is focused on monetary and fiscal policies during the COVID-19 crisis. In the third part, we faced a challenge how to incorporate other economic and borderline economic problems we want to address like the labour market developments and issues of national security and crisis management. Apart from the aforementioned Dubravko Radoševi´c, authors would like to thank William Hynes, Senior Adviser to the Secretary General of the OECD and the Head of the New Approaches to Economic Challenges (NAEC); Stjepan Zduni´c, Senior Research Fellow from the Institute of Economics Zagreb and former Minister in the Government of Croatia;

ACKNOWLEDGEMENTS

xxi

Joachim Becker, Deputy Director, Institute for Foreign Trade and Development, Department of Economics, and Professor at WU Vienna University of Economics and Business, who supported us from the beginning, Joze Mencinger, Senior Research Fellow from the Institute of Economics Ljubljana and former Minister of Economy in the Government of Slovenia for his valuable comments on the draft version of the book and Lavanya Devgun and other editors from Palgrave Macmillan for their contribution to this project and Ian Anderson for his creative support. Neven Vidakovi´c Ivan Lovrinovi´c

Contents

Part I Macro Economics of COVID-19 1

Current and Long-Run Challenges for the Croatian Economy, in Comparison Mario Holzner

2

COVID-19 Contagion Among Countries Franjo Štiblar

3

Short-Term Impact of COVID-19 in the Clusters of EU Market Economies Vivien Czeczeli, Pál Péter Kolozsi, Gábor Kutasi, and Ádám Marton

4

Macro Economic Model of COVID-19 Pandemic Crisis ˇ Vladimir Cavrak

3 17

53

85

Part II Economics Policies during COVID-19 5

Central Bank’s Balance Sheet Management in Times of Systemic Crises Ivan Lovrinovi´c, Martina Soleniˇcki, and Karlo Vujeva

111

xxiii

xxiv

6

CONTENTS

Quantitative Easing, Stock Exchange, Inflation and Monetary Paradigm in the US: Lessons for Emerging Economies Marinko Škare and Dean Sinkovi´c

7

Monetary Policy in Croatia During Two Recessions Neven Vidakovi´c

8

Monetary Transmission in Croatia: A View from the Eurozone’s “Waiting Room” Manuel Benazi´c and Dean Uˇckar

9

Monetary and Fiscal Policy Response During COVID-19 Crisis in Bosnia and Herzegovina: Constraints and Potentials Sead Kreso, Lejla Lazovi´c-Pita, and Selena Durakovi´c

Part III 10

187

209

233

Broader Impact of COVID-19

Emergency Financial Mismanagement in Croatia During COVID-19 Crises Robert Bari´c

11

Modern Monetary Theory and COVID-19 Crisis Tihomir Domazet

12

Impact of COVID-19 on Working from Home in Serbia: Possibilities and Consequences Mirjana Radovi´c-Markovi´c and Jovica Jovanovi´c

Index

157

265 291

319

345

Notes on Contributors

Robert Bari´c Political Scientist, Ph.D. is an Assistant Professor in the Department of International Relations and Security Studies at the Faculty of Political Sciences at the University of Zagreb in Zagreb, Croatia. He holds an M.Sc. degree in international security (Faculty of Political Science, Zagreb University), and Ph.D. degree in international security/international relations (Faculty of Political Science, Zagreb University). Prior to an academic career, he was a member of the Croatian Armed Forces (1993–2019), involved in key programs connected with Croatian accession to NATO and development of Croatian defense relations with the EU. He served also as a Assistant Adviser for the National Defense at the Office of the President of the Republic of Croatia and he was a member of the Diplomatic Mission of the Republic of Croatia at NATO in Bruxelles (Belgium). Manuel Benazi´c Economist, Ph.D. is a full professor of Economics at the University of Pula (Croatia), Faculty of Economics. He has work experience in banking and public administration. He is a team member and researcher in scientific and professional projects, reviewer for several scientific journals and conference proceedings. He has published a large number of scientific papers on the subject of monetary economics, banking and finance. ˇ Vladimir Cavrak Economist, Ph.D., is tenured Professor of Economics at the Department of Macroeconomics and Economic Development, xxv

xxvi

NOTES ON CONTRIBUTORS

University of Zagreb, Faculty of Economics & Business in Zagreb, Croatia. His research interests include macroeconomics, Croatian economy, and macroeconomics for entrepreneurs. He served as the ViceDean of the Faculty of Economics and Business in Zagreb, Croatia. He is the author of more than 70 scientific articles and books and author or co-author of several university textbooks and textbooks for high schools. Vivien Czeczeli Economist, Ph.D., student, Junior Researcher at the Economy and Competitiveness Research Institute of the University of Public Service, Associate Lecturer at the University of Public Service, Budapest, Hungary. Her main research areas are international economics and monetary economics. Tihomir Domazet Economist, Ph.D., was Assistant Minister of Finance in the Ministry of Finance, the Government of the Republic of Croatia; also he was a member of the Council of Economic Advisers in the Government of Croatia. He was a visiting professor of economics to the universities abroad. He attended several courses in the United Kingdom, USA, and China. He was also Head of the Institute for Finance and Development in Zagreb, Author of many books of economics and finance, as well of many studies and expertise in the field of macroeconomics, fiscal policy and finance. Selena Durakovi´c Economist, Ph.D., is an Assistant Professor at the School of Economics and Business, University of Sarajevo, Bosnia and Herzegovina and a CERGE-EI Foundation Teaching Fellow. She holds a Ph.D. from Staffordshire University, United Kingdom. Mario Holzner Economist, Ph.D., is Executive Director at the Vienna Institute for International Economic Studies (Vienna, Austria). He is also coordinating economic policy development and communication with a focus on European economic policy. Mario Holzner is a lecturer in applied econometrics at the University of Vienna, Department of Economics. In November 2020 he was appointed as a member of the Council of Economic Advisers of the President of the Republic of Croatia. Jovica Jovanovi´c, M.D., D.M.Sc. is Full Professor at the Department of Occupational Medicine, Faculty of Medicine, and a part-time Professor at the Faculty of Occupational Safety University of Niš, Serbia. He is Deputy Director for Medical Affairs in the Institute of Occupational

NOTES ON CONTRIBUTORS

xxvii

Health Medicine in Niš. He was the Director of the temporary “COVID19 Hospital” in Niš. He has authored three monographs, four university books, and numerous journals and conference articles. Pál Péter Kolozsi Economist, Ph.D., Director of the Magyar Nemzeti Bank (Central Bank of Hungary), Researcher at the Economy and Competitiveness Research Institute of the University of Public Service, Associate Professor at the Corvinus University of Budapest, Hungary. He earned his doctoral degree at the Institute of Political Science in Paris. He specialized in macro finances, liquidity management and monetary policy, has significant teaching and research experience in finance, international finance and public finance. He is the author of several scientific publications and book chapters on the above topics. He has been working at the Magyar Nemzeti Bank, before which he worked as Adviser to the President of the State Audit Office. Sead Kreso Economist, Ph.D., tenured Professor of Economics and Finance at the School of Economics and Business, University of Sarajevo (Sarajevo, Bosnia and Herzegovina) and former Dean at faculty. He is a Chair of the Department of Finance and has been engaged in numerous projects and published extensively in the fields of monetary and fiscal policy. He was a member of the Council at National Bank of Bosnia and Herzegovina, Minister of Finance in the Government of the Republic of Bosnia and Herzegovina; currently, he is a member of the Audit Committee at the Central Bank of Bosnia and Herzegovina (CBBiH). Gábor Kutasi Economist, Ph.D., Associate Professor and Head of the Research Institute of Competitiveness and Economy in the University of Public Service, Budapest, Hungary; external researcher of the Institute of the Hungarian Foreign Affairs and Trade, guest lecturer of Prague University of Economics and Corvinus University of Budapest, former scholar of DAAD Osteuropaprogramm and the Hungarian Academy of Science Bolyai Scholarship, former researcher of National Bank of Hungary and Zeppelin University. Lejla Lazovi´c-Pita Economist, Ph.D., is an Associate Professor at the School of Economics and Business, University of Sarajevo, Bosnia and Herzegovina and a CERGE-EI Foundation Teaching Fellow. She holds a Ph.D. from the University of Bamberg, Germany.

xxviii

NOTES ON CONTRIBUTORS

Ivan Lovrinovi´c Economist, Ph.D., tenured professor at the Department of Finance, Faculty of Economics and Business, University of Zagreb, Croatia. He is the main lecturer in courses Monetary Policy and International Financial Management. He has published dozens of scientific and professional papers and five scientific books. He was Dean of the Faculty of Economics and Business at the University of Zagreb, while from 2016 until 2020 he served as MP in the Croatian Parliament (Hrvatski sabor) and as a member of its Finance and Budget Committee. Ádám Marton Economist, Ph.D., student, Junior Researcher at the Economy and Competitiveness Research Institute of the University of Public Service, Budapest, Hungary; Associate Lecturer at the University of Public Service. His research areas include applied macroeconomics with a particular focus on fiscal policy, public debt and indebtedness and ageing society. Mirjana Radovi´c-Markovi´c Economist, Ph.D., Senior Research Fellow at the Institute of Economic Sciences in Belgrade (Serbia); she is also a University Professor of Economics at the University of Belgrade. She has served as a professor at a number of international universities, foundations, and research institutes. She has written several books and more than two hundred peers’ journal articles. Her publications are published by top publishing companies as Routledge, Francis Taylor, Springer, Palgrave McMillan and others. Dean Sinkovi´c Economist, Ph.D., is an Associate Professor of Economics, Vice Dean for International Affairs & Business Relations and Managing Editor for the Journal Economic Research. He served as a Vice Dean for Research and International Relations at the University of Pula. He currently works as a visiting professor at the University of Applied Science, Fachhochshule Burgenland (Austria) and International Burch University in Sarajevo (Bosnia and Herzegovina). He authored and coauthored many research papers and published chapters in several books. Marinko Škare Economist, Ph.D., is tenured Professor of Economics at the Faculty Economics and Tourism University of Pula (Pula, Croatia). His previous positions included Dean of Economics Faculty in Pula, and Vice-Rector of University of Pula. He authored and coauthored many research papers and published chapters in several books. He was elected

NOTES ON CONTRIBUTORS

xxix

as a new Rector of the University of Pula, starting his term from 1st of September 2021. Martina Soleniˇcki Economist, Ph.D., Assistant Professor at the Department of Finance, Faculty of Economics and Business, University of Zagreb, Croatia. Currently, she teaches the following courses: Monetary Policy, International Financial Management, Investment Banking. She has published several scientific papers in the field of finance and monetary policy. Franjo Štiblar Economist, Ph.D., got a B.A. in law and economics from the University of Ljubljana, Slovenia, M.A. from the institute of Economics Sciences in Beograd Yugoslavia. He also got his Ph.D. from the University of Pennsylvania (L.R.Klein, R. Shiller). He is a tenured professor of economics at the School of law at University of Ljubljana, Head of Center for Legal and Economic Studies, Faculty of Law University of Ljubljana (Slovenia). His other previous posts included being Dean of Law School, Chief Economist for largest commercial bank in Slovenia—Nova Ljubljanska Banka, Visiting professor at John Hopkins University, consultant to the World Bank. Currently, he is also a member of the Supervisory Board, in private savings bank—Delavska hranilnica, Ljubljana. Dean Uˇckar Economist, Ph.D., is a full professor at the Faculty of Economics of the University of Pula (Croatia). He is the Head of the Department of Finance and the holder of several courses in the field of finance at the undergraduate, graduate and postgraduate (doctoral) level of studies. His primary areas of interest are corporate finance, financial markets, investment analysis, and monetary economics, about which he has written numerous scientific papers. Neven Vidakovi´c Economist, Ph.D., Research Associate, he got his B.A. in economics and financial math from the University of Michigan in Ann Arbour, USA, his masters in economics from the University of Ljubljana (Slovenia) and Ph.D. from the University of Maribor (Slovenia). During his career, he worked as a specialist for Risk Management (Asset Liability Management) in largest commercial bank PBZ in Zagreb, a subsidiary of Italian INTESA Group and several years in INTESA in Milan (Italy). He is an Adjunct Professor of Economics at several private business schools and faculties in Croatia and Slovenia. His academic research is focused on the field of Monetary Economics. He is the author of five books and over

xxx

NOTES ON CONTRIBUTORS

20 research papers. He is also working as a macroeconomic and financial market analyst. Karlo Vujeva Economist, M.A., teaching assistant and a Ph.D. candidate at the Department of Finance, Faculty of Economics and Business, University of Zagreb, Croatia. In 2018, he obtained his second master’s degree at the Universidad Carlos III de Madrid, Spain.

Abbreviations

EMU EU GDP SEE WHO

European Monetary Union European Union Gross Domestic Product South and Eastern Europe World Health Organization

xxxi

List of Figures

Fig. 1.1 Fig. 1.2

Fig. 1.3

Fig. 1.4

Fig. 1.5

Fig. 1.6 Fig. 1.7

Real GDP per capita at PPS, EU27 = 100 (Note 2020 data is forecasted. Source Eurostat) Real GDP decline in 2Q 2020, in % year-on-year (Note Horizontal line represents the euro area average. Source wiiw) Tourism and trade in % of GDP (Note Travel and tourism only represents the direct contribution to GDP. Source TCdata360, WDI) Grants—EU recovery and resilience facility (2021–2023), in % of GDP (Source European Commission, author’s calculations) Average credit rating; 1 (prime) to 7 (substantial risks), Autumn 2020 (Sources Moody’s, Fitch, S&P. Average of available ratings) UN population projections, % change between 2015 and 2045 (Source UN, Medium fertility variant) Employment rate (LFS), female, 15 +, 2018 (Note Horizontal line reflects EU27 average; Belarus age 15–74, Kosovo age 15–64. Source Eurostat, wiiw & World Bank’s SEE Jobs Gateway Database)

4

5

6

7

7 8

9

xxxiii

xxxiv

LIST OF FIGURES

Fig. 1.8

Fig. 1.9

Fig. 1.10

Fig. 1.11

Fig. 1.12

Fig. 3.1

Fig. 3.2

Fig. 3.3

Relative functional specialisation of greenfield FDI projects in Serbia, 2003–2015 (Notes A relative functional specialisation of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019]) Relative functional specialisation of greenfield FDI projects in Germany, 2003–2015 (Notes A relative functional specialization of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019]) Relative functional specialization of greenfield FDI projects in Croatia, 2003–2015 (Notes A relative functional specialization of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019]) Estimated number of robots per 10,000 persons employed in the manufacturing industry, 2019 (Note Horizontal line represents the World average. Source International Federation of Robotics) The Network Readiness Index 2020 (Note The index is an aggregate of the sub-indices covering issues of technology, people, governance and impact. Source Portulans Institute) Dendogram of the results of the cluster analysis (25 Member States) (Source Own figure using the SPSS program) Average change in public debt (horizontal axis) and in balance of the budget (vertical axis) (Source Own figure based on Eurostat data) Travel and tourism average, total contribution to GDP (vertical axis), and changes in export share (horizontal axis) (Source Own figure based on World Bank data)

10

11

12

13

14

62

65

66

LIST OF FIGURES

Fig. 3.4

Fig. 3.5

Fig. 3.6

Fig. 3.7

Fig. 3.8

Average development of social expenditure (horizontal axis) and the GINI indicator (vertical axis) (Source Own figure based on Eurostat data) Group behaviour of cluster-forming variables, rate of variable (vertical axis), cluster number (horizontal axis) a. Balance of the budget, as a percentage of GDP. b. Public debt, as a percentage of GDP. c. GINI indicator. d. Social expenditures, as a percentage of GDP. e. Tourism, as a percentage of GDP. f. Export share, as a percentage of GDP (Source Own edited) Group behaviour of variables indicating a crisis, rate of variable (vertical axis), cluster number (horizontal axis) a. Development of industrial production in the four months before the crisis (November 2019–February 2020) and during the crisis (March–June 2020) b. Development of unemployment rate in the four months before the crisis (November 2019–February 2020) and during the crisis (March–June 2020) c. Workforce mobility in the period before the crisis (15–29 February 2020) and during the crisis (March-June 2020) d. Government bond yields in the period before the crisis (2 January 2020) and during the crisis (7 May 2020) (Source Own edited based on data from Eurostat, Google Community Mobility, Bloomberg Note Horizontal axis: 1. not exposed to tourism, 2. debt-free, 3. decreasing export exposure, 4. socially sensitive, 5. tourism-dependent, 6. debt-reducing, 7. deficit-increasing) Co-movements in the time series of clusters in terms of mobility (horizontal axis) and changes in industrial production (vertical axis) (March-June 2020) a. Not exposed to tourism (Cluster 1) b. Debt-free (Cluster 2) c. Decreasing export exposure (Cluster 3) d. Socially sensitive (Cluster 4) e. Tourism-dependent (Cluster 5) f. Deficit-increasing (Cluster 7) h. Debt-reducing (Cluster 6) (Source Own edited Note The captions for the dots include two letters as a country code, while the second two numbers represent the month of the year 2020. For example, IT04 represents the April 2020 data of Italy) Connections between changes in government bond spreads (2 January–5 May 2020, horizontal axis) and mobility (vertical axis) (Source Own edited data based on data from Bloomberg, Google)

xxxv

67

68

71

75

77

xxxvi Fig. 4.1

Fig. 4.2 Fig. 4.3 Fig. 5.1 Fig. 5.2

Fig. 5.3

Fig. 5.4

Fig. 5.5

Fig. 5.6

Fig. 5.7

Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4 Fig. 6.5 Fig. 6.6 Fig. 6.7 Fig. 6.8

LIST OF FIGURES

Theoretical COVID-19 pandemic and recession curve ˇ (Source Author: V. Cavrak, based on Ed. Baldwin and Weder di Mauro [2020]) ˇ AS-AD model of corona shock (Source Author: V. Cavrak) Macroeconomic model of COVID-19 crisis removal ˇ (Source Author: V. Cavrak) Stylized QE transmission mechanism (Source Joyce et al. 2011) Growth of major central banks’ balance sheets (normalized so that 2007 = 1) (Source Central banks’ statistics; WDI; authors’ work) Central bank balance sheet to nominal GDP (2007/2019/2020) (Source WDI; central banks’ statistics; author’s calculation) Securities as a percentage of total assets (2007/2019/2020) (Source Central banks’ statistics; authors’ work) Percentage growth in the size of euro area central bank balance sheets (2007/2019) (Source Central banks’ statistics; author’s work) Selected balance sheets’ sizes in the euro area versus GDP (2007/2019) (Source Central banks’ statistics; WDI; author’s work) Central balance sheets of selected non-eurozone central banks (2007/2019) as a percentage of GDP (Source National CB statistics; WDI; authors’ work) S&P/Case-Shiller US National Home Price Index (Source FRED) S&P 500 index 2009–2020 (Source www.macrotrends. net/2324/sp-500-historical-chart-data) Cash assets to total assets of the large US commercial banks (Source FRED) Treasury and agency securities to total assets of the large US commercial banks (Source FRED) Monetary expansion and money velocity (Source FRED) Federal debt, household debt, and debt of nonfinancial corporations in USA (Source FRED) S&P 500 dividends and stock buybacks (quarterly data) (Source S&P Dow Jones Indices 2020) S&P 500 stock price index vs earnings (Source http:// www.econ.yale.edu/~shiller/data.htm)

90 93 98 119

122

123

124

130

130

134 160 160 161 161 164 171 172 174

LIST OF FIGURES

Fig. 6.9 Fig. 6.10 Fig. 6.11 Fig. 6.12

Fig. 6.13

Fig. 7.1 Fig. Fig. Fig. Fig. Fig. Fig.

7.2 7.3 7.4 7.5 7.6 8.1

Fig. 8.2

Fig. 8.3

Fig. 8.4 Fig. 8.5

Fig. 8.6

Stock markets and real economy decoupling in the USA 1870–2020 (Source Authors calculation) Cross-spectral analysis of quantitative easing and US stock market 1870–2020 (Source Authors’ calculation) Cross-spectral analysis of US stock market and inflation 1870–2020 (Source Authors’ calculation) Breitung and Candelon (2006) frequency domain Granger causality test from QE to stock market conditional on 10-year treasury yield (Source Authors’ calculation) Shows graphs of transition probabilities between regime 1 (actual QE) and regime 2 (No QE) (Source Authors’ calculation) Decrease in the quantity of domestic money (Source Vidakovi´c 2016) Sterilization operation (Source author) M0 vs. M1 during Great Recession (Source CNB) M0 vs. M1 during COVID (Source CNB) Structure of loans 2008–2019 (Source CNB) Structure of loans 2020 (Source CNB) Real gross domestic product, prices, money, interest rate and real effective exchange rate (Source The Croatian National Bank [2020a] and authors’ calculations) VAR impulse responses to Cholesky one S.D. (d.f. adjusted) innovations ± 2 S.E. confidence interval (Note “L” indicates logarithm of the variable. Source Research results) Velocity of M1 money stock (V1), velocity of M4 money stock (V4) and the M1 money stock/GDP ratio (in %) (Source The Croatian National Bank [2020a, b] and authors’ calculations) Liquidity surplus (in billion EUR) and overnight interest rate (in %) (Source The Croatian National Bank [2020c]) Distribution of other monetary financial institutions’ deposits (left) and loans by original maturity (right) (in million EUR) (Source The Croatian National Bank [2020a]) Confidence indicators (standardized values, seasonally adjusted index) (Source The Croatian National Bank [2020b])

xxxvii

175 177 178

181

182 192 198 199 200 201 202

216

221

222 223

224

225

xxxviii Fig. 8.7

Fig. 8.8

Fig. 9.1 Fig. 9.2

Fig. 9.3

Fig. 9.4 Fig. 9.5 Fig. 9.6 Fig. 9.7

Fig. 9.8 Fig. 9.9 Fig. 9.10

Fig. 9.11

LIST OF FIGURES

Change in demand of enterprises for loans and/or credit lines over the past three months (left) and expected changes over the next three months (right) (Note In net percentage, positive value = increased demand, negative value = decreased demand. Source The Croatian National Bank [2021b]) Change in demand for loans to households over the past three months (left) and expected changes over the next three months (right) (Note In net percentage, positive value = increased demand, negative value = decreased demand. Source The Croatian National Bank [2021b]) Central banks’ interest rates (Source Bank for International Settlement 2021, own interpretation) Reserve requirement and average reserves held by commercial banks in CBBiH (Source CBBiH [2021], own interpretation) Growth rates in loans to enterprises and households (selected items from the consolidated balance sheet of commercial banks in BiH) (Source CBBiH [2021], own interpretation) Commercial banks’ foreign assets and excess reserves (Source CBBiH [2021], own interpretation) Cash in commercial banks’ vaults (Source CBBiH [2021], own interpretation) Suggestion for the use of existing potentials in financial system (Source Kreso 2019) Constitutional organization of BiH (Note N.B. As of 2014, total number of local communities in RS is increased to 63 when Stanari obtained a status of municipality. Source Kreso 2005) Fiscal structure of BiH (Source Lazovi´c-Pita 2015, p. 174) Organization of fiscal institutions in BiH (Source Lazovi´c-Pita and Stambuk 2016, p. 2109) Total revenues: taxes and SSC in BiH, 2005–2019 (Source International Monetary Fund GFS-revenues [2020], own interpretation) Selected categories of expenditures in FBiH, share to total expenditures and GDP (Source Federal Ministry of Finance [2020], own interpretation)

226

226 239

241

242 243 243 245

248 249 249

250

251

LIST OF FIGURES

Fig. 9.12

Fig. 12.1 Fig. 12.2 Fig. 12.3 Fig. 12.4 Fig. 12.5 Fig. 12.6 Fig. 12.7

Selected categories of expenditures in RS, share to total expenditures and GDP (Source Ministry of Finance of RS [2020], own interpretation) Structure of respondents by gender (Source Radovi´c-Markovi´c et al. 2021a) Structure of respondents who work from home by level of education (Source Radovi´c-Markovi´c et al. 2021a) Influence of COVID-19 on the volume of operating activities in organizations of different sizes Work from home by activities in Serbia (Source Radovi´c-Markovi´c et al. 2021a) Work from home by level of education and type of activity (Source Radovi´c-Markovi´c et al. 2021a) Advantages of working from home (Source Radovi´c-Markovi´c et al. 2021a) Disadvantages of working from home (Source Radovi´c-Markovi´c et al. 2021a)

xxxix

252 322 323 324 325 325 327 328

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7

Correlogram: Relations of COVID with environment Regression equations Estimated (Ye) and actual (Ya) values of COVID indicators Estimated (Ye) and actual (Ya) values of COVID indicators Summary table of variables included in the analysis extended with descriptive statistics The clusters created Standard deviation of indicators characterising the crisis period by cluster Correlations and R 2 values for the whole set of countries Simplified presentation of the central bank balance sheet Assets’ structure of the major central banks (2007/2019/2020) Assets’ structure of the major central banks, as a percentage of the total amount (2007/2019/2020) Lending to EA credit institutions by Eurosystem (2007/2020), in millions of EUR Structure of liabilities of the largest central banks (2007/2019/2020) Eurozone central banks asset structure (2007/2019), in millions of EUR Structure of euro area central banks’ liabilities (2007/2019), in millions of EUR

24 34 41 43 61 63 70 73 116 125 126 127 129 132 135

xli

xlii

LIST OF TABLES

Table 5.8 Table 5.9 Table Table Table Table Table Table

7.1 8.1 8.2 8.3 8.4 9.1

Table 12.1 Table 12.2 Table 12.3

Asset structure of balance sheets of central banks of EU member states that have not adopted the euro Structure of liabilities of balance sheets of central banks of EU member states that have not adopted the euro Quantity of money during great recession Unit root tests VAR diagnostic tests VAR Granger causality/block exogeneity tests VAR variance decomposition (in %) Public expenditures and public debt to GDP, in WB countries (including Croatia), in percentage Assessment of gender differences in terms of work satisfaction from home Analysis of subjective difficulties of employees who work from home and at the employer’s premises Analysis of occupational risks in the workplaces of employees working from home and at the employer’s premises

137 139 196 217 218 218 220 246 327 333

334

PART I

Macro Economics of COVID-19

CHAPTER 1

Current and Long-Run Challenges for the Croatian Economy, in Comparison Mario Holzner

1.1

Introduction

The COVID-19 pandemic is hitting the economy of Croatia fiercely, an economy that had little developed over the past three or four decades. Eurostat data on the real GDP per capita at Purchasing Power Standards (PPS) in percent of the EU27 average in 1990 and 2020 presents a devastating picture (Fig. 1.1). Compared to other countries in Central, East, and Southeast Europe (CESEE), Croatia was among the leading group in terms of real income, at around 60% of the EU27 average initially. Since then most other economies from the region have substantially improved their relative position. Croatia’s relative income per capita level remained almost flat. Over the same period, the country lost about 15% of its population. Other peers were able to keep the number of inhabitants fairly stable. What are the reasons for such a bad performance over the long run, knowing that already the 1980s were a difficult period for the Croatian

M. Holzner (B) The Vienna Institute for International Economic Studies (wiiw), Vienna, Austria e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_1

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100 90 80 70 60 50 40 30 20 10 0 XK AL BA MK RS ME

BG HR RO 1990

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Fig. 1.1 Real GDP per capita at PPS, EU27 = 100 (Note 2020 data is forecasted. Source Eurostat)

economy? Technically, Croatia suffered a number of recessions, which lasted much longer than in comparable countries. Here, the stubborn adherence to a fixed exchange rate regime was not helpful and the real exchange rate was overvalued for a prolonged period (Gligorov and Vidovic 2001a, b, 2004, 2006; Kraft and Stucka 2002). Certainly, the war in the first half of the 1990s and the subsequent postponement of the process of European integration was a grave setback. While others entered the European Union and NATO and thus were the target of large-scale FDI, Croatia was holding back in development and deprived of highly productive and technology-intensive manufacturing FDI. The plan to establish a national capitalist class that could substitute foreign capital and related transfer of know-how had failed. At the same time, the economy had to restructure and compensate for the loss of the large Yugoslav market. Moreover, in that market, before the break-up of the federation, Croatia had the status of a core state if analyzed in the framework of the World-systems theory (Wallerstein 1974). Together with Slovenia, it was economically more diversified and wealthy, and compared to the other, more peripheral republics it was relatively more industrialized and produced manufactured goods rather than raw materials for

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export. Today, Croatia is within the European economy a sort of a semiperipheral state, desperate to catch up to the core and at the same time not to backslide into the periphery proper. This is reflected in the geoeconomic structure of the Croatian economy itself, with a backward, agricultural East, a West, and South that is almost completely dependent on tourism and a Northern part of the country that has a more diversified economic structure with a few promising start-ups (e.g., in the e-mobility sector). Strong overall reliance on tourism was detrimental for Croatia’s economy, when the COVID-19 pandemic hit Europe in early 2020. The service sector in general and tourism specifically were affected by the curfews, lockdowns, and border closings. Nevertheless, most CESEE economies still have a rather small services sector and thus the initial growth collapse was smaller as compared to e.g., the euro area average of almost 15% in the first quarter of 2020 (Fig. 1.2). However, Croatia’s (and for that matter also Montenegro’s) second-quarter growth declined above the euro area average, due to the mentioned focus on tourism. It is interesting to note that Croatia’s neighbors Slovenia and Hungary also suffered a relatively high slump compared to other CESEE countries. They are among the region’s economies with the highest overall trade ME HR HU SI MK SK UA CZ RO AL TR XK BA LV BG RU PL EE RS KZ LT BY 0

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Fig. 1.2 Real GDP decline in 2Q 2020, in % year-on-year (Note Horizontal line represents the euro area average. Source wiiw)

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share (Fig. 1.3), which made them also vulnerable via the COVID-19 trade interruption channel. On a positive note, Croatia’s EU accession in 2013 makes it eligible for the massive financial support from the EU’s Recovery and Resilience Facility over the period 2021–2023. The cumulative transfers will make at least 8% of GDP (fixed amount for 2021–2022), but more likely around 11% (including the variable amount depending on the GDP performance in 2020–2021). This is a substantial boost to the economy in the assumed economic recovery period. No other EU member state can expect more support from the block (Fig. 1.4), in relative terms. These funds will increase public and private investment and thus help to heal the scars of the recession and in addition help the country in its much-needed transition to a green economy. Another silver lining is Croatia’s soon expected accession to the euro area. After decades of real depreciation via prolonged recessions, and an endemic euroization of the economy, Croatia can expect to gain from a euro area accession in several ways. Particularly, this has the potential to improve its credit rating, which, at the moment, is rather unfavorable, somewhere between the ratings of Russia and North Macedonia (Fig. 1.5). An improved credit rating

Travel and Tourism in % of GDP

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Fig. 1.5 Average credit rating; 1 (prime) to 7 (substantial risks), Autumn 2020 (Sources Moody’s, Fitch, S&P. Average of available ratings)

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goes along with lower interest rates and thus higher public and private investment.

1.2

Post-COVID Challenges

What will be the major challenges for Croatia beyond the current COVID-19 crisis? Probably the most important one is the forecasted further demographic decline. UN population projections foresee for Croatia another population drop of about 15% over the next couple of decades. This is at the upper bound of the projected decline in the CESEE countries (Fig. 1.6). Things appear even bleaker if one looks at the working-age population, as the demographic decline goes hand in hand with the massive aging of the society. This is the result of decades of emigration of young families. While, technically, a smaller population can help to increase the GDP per capita, population shrinkage comes at high costs for the society, both in economic as well as political terms. More balanced development is certainly to be aimed for. As targeted immigration—at least currently—is not a policy option in Croatia (or most of CESEE for that matter), other policy choices have to 30 20 10 0 -10 -20 -30 BG LV UA HR LT MD RO RS HU PL EE BA BY RU SK AL MK SI ME CZ TR KZ

Fig. 1.6 UN population projections, % change between 2015 and 2045 (Source UN, Medium fertility variant)

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be evaluated. One of them is to increase the share of female employment in order to compensate for the loss of the labor force. And indeed, there is still room for improvement in Croatia, where this share is still quite below the EU average and even further below some of the former Soviet republics (Fig. 1.7). Another long-run challenge is the aforementioned semi-peripheral position of Croatia in the European economy and its value chains. CESEE economies have typically a functional specialization in international value chains in the segments that are of low value-added, i.e., in production proper. Serbia is a case in point with a strong functional specialization in production and hardly any greenfield FDI investment in higher valueadded segments such as headquarters and R&D functions or logistics and support services, compared with the world average (Fig. 1.8). This pattern is perfectly complementary with the functional specialization of core economies such as the German one (Fig. 1.9), where specialization in higher value-added headquarters and support services can be detected. Croatia is an interesting case and somewhat different to most other CESEE economies, as there the specialization in production proper is 70 60 50 40 30 20 10 0 BY KZ EE LT RU UA LV CZ SI SK BG HU PL AL RO HR ME RS MD MK TR BA XK

Fig. 1.7 Employment rate (LFS), female, 15 +, 2018 (Note Horizontal line reflects EU27 average; Belarus age 15–74, Kosovo age 15–64. Source Eurostat, wiiw & World Bank’s SEE Jobs Gateway Database)

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2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 HQ

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Fig. 1.8 Relative functional specialisation of greenfield FDI projects in Serbia, 2003–2015 (Notes A relative functional specialisation of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019])

just at the world average, while higher value-added segments of the value chain in post-production logistics and support services show a specialization pattern that is above the world average (Fig. 1.10). This shows on the one hand that Croatia did not receive a comparable share of manufacturing FDI as its CESEE peers but that it was able to specialize in certain higher value-added segments of the global value chains. However, there are no greenfield FDI with headquarters functions recorded and only very little R&D over the past years. Both are worrying. This is even more so, as large parts of the value chain might face headwinds from the ongoing automation and robotization process, which on the one hand could help to weather the demographic decline but on the other hand has the potential for further centralization of value creation in the core economies. Certainly, it is better to be part of that process than just a bystander. However, while neighboring Slovenia is among the top-20 economies, in terms of the estimated number of robots per 10,000 persons employed

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1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 HQ

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Fig. 1.9 Relative functional specialisation of greenfield FDI projects in Germany, 2003–2015 (Notes A relative functional specialization of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019])

in the manufacturing industry, Croatia is nowhere on the map (Fig. 1.11). Similarly, Croatia’s position in terms of preparedness for digitalization is at best mediocre, when comparing its Network Readiness Index with the peers (Fig. 1.12). Thus, the question must be posed, whether the new digital economy is an opportunity for Croatia to catch up or further fall behind. A lot will depend on the right policy mix to be chosen in the years to come (during and) after the pandemic.

1.3

Policy Recommendations

In order to overcome the COVID-19 crisis, the demographic decline, the functional specialization trap, the digital and automation lag, the investment must be stepped up significantly. Following the economic historian Alexander Gerschenkron (1952), a more rapid growth spur has the potential to make a country break free of economic backwardness.

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1.4 1.2 1 0.8 0.6 0.4 0.2 0 HQ

R&D

ProducƟon

LogisƟcs

Support services

Fig. 1.10 Relative functional specialization of greenfield FDI projects in Croatia, 2003–2015 (Notes A relative functional specialization of above 1 in any value chain function indicates that that particular country is more often used as the location for that value chain function than the world average. Source FDI markets database, wiiw calculations based on the methodology of Stoellinger [2019])

Where neither entrepreneurs nor banks were able to make a difference, the state had to step in and make the spur more likely to be successful. A broad range of supportive policies can be envisaged. Given that monetary (i.e., exchange rate) policy is not available for Croatia, alternative methods of real depreciation can be tried in order to make the economy more competitive. This includes for instance the introduction of a more centralized wage bargaining system that keeps average wage levels on a longer-term productivity (cum inflation) growth path. Here the role models of the Austrian or the Irish social partnership could be studied. An easier to implement option would be the use of fiscal devaluations via e.g., an increase in consumption taxation and an equivalent reduction of employer’s social security contributions, in order to simulate an exchange rate depreciation (Vuksic and Holzner 2016; Holzner et al. 2018, 2019; Tkalec et al. 2019).

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1000 900 800 700 600 500 400 300 200 100 0 SG KR JP DE SE DK HK TW US BE IT NL ES AT CN FR SK CA CH SI FI

Fig. 1.11 Estimated number of robots per 10,000 persons employed in the manufacturing industry, 2019 (Note Horizontal line represents the World average. Source International Federation of Robotics)

Other policy recommendations (Holzner and Vidovic 2018) include an improvement of the (administrative) absorption capacities of EU funds in order to increase public and private investment; support Croatian tourism by joining the Euro and Schengen area as quickly as possible; back the quick EU accession of neighboring Serbia, Bosnia and Herzegovina as well as Montenegro in order to increase aggregate demand along Croatia’s long Southeast border; or, alternatively, help the Western Balkan economies to at least have a partial accession to the Union’s single market and selected treaties with high economic impact (Bertelsmann Stiftung and wiiw 2020); make the agricultural system more productive and exploit potentials for a more cooperative structure of the agricultural sector based on the Austrian and German cooperative Raiffeisen model; broaden the industrial base on Northern Croatia by connecting more to the nearby Styrian automotive cluster. Moreover, establish fiscal space by taxing those parts of the income distribution with the highest income elasticity of demand for imports (i.e., the rich and wealthy) and spend on a few imports as possible, in order to improve future crisis resilience. Invest much more in vocational

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Fig. 1.12 The Network Readiness Index 2020 (Note The index is an aggregate of the sub-indices covering issues of technology, people, governance and impact. Source Portulans Institute)

training and related facilities, the public health care sector, cultural and sports centers. This has the potential to support local production, to improve human capital and job creation and most of all to allow for a better life for young families in order to revert the negative demographic trends and the related brain drain. In a similar vein, large-scale municipality housing projects could help to solve the affordable housing shortage for the young and employ low-skilled, while reducing the overall price level. And a related increase in the supply of green public transport could offer jobs to the less skilled and substitutes widespread individual car imports, while at the same time also reducing the overall price level and facilitating the transition to a green economy. All of these measures should have the potential to directly or indirectly generate public and private, domestic and foreign investment in order to overcome the challenges of the COVID-19 crisis, the demographic decline, the functional specialization trap, and the digital and automation lag of Croatia.

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References Bertelsmann Stiftung and wiiw. 2020. Pushing on a String? An Evaluation of Regional Economic Cooperation in the Western Balkans. Report by Bertelsmann Stiftung and the Vienna Institute for International Economic Studies (wiiw). Gerschenkron, Alexander. 1952. Economic Backwardness in Historical Perspective. In The Progress of Underdeveloped Areas, ed. Bert F. Hoselitz, 3–29. Chicago, MA: University of Chicago Press. Gligorov, Vladimir, and Hermine Vidovic. 2001a. The Croatian Economy: Overview and Recent Developments. 1st Quarterly Report for the President of the Republic of Croatia, The Vienna Institute for International Economic Studies (wiiw). Gligorov, Vladimir, and Hermine Vidovic. 2001b. Croatia: Enduring Problems. 2nd Quarterly Report for the President of the Republic of Croatia, The Vienna Institute for International Economic Studies (wiiw). Gligorov, Vladimir, and Hermine Vidovic. 2004. Croatia’s Delayed Transition: Competitiveness and Economic Policy Challenges. wiiw Research Report, No. 304. Gligorov, Vladimir, and Hermine Vidovic. 2006. Croatia: Growth Slowdown and Policy Alternatives. wiiw Research Report, No. 324. Holzner, Mario, and Hermine Vidovic. 2018. Wirtschaftliche Perspektiven für Kroatien: Eine Analyse der kroatischen Wirtschaft und abgeleitete Politikempfehlungen. wiiw Forschungsbericht, No. 9. Holzner, Mario, Marina Tkalec, Maruska Vizek, and Goran Vuksic. 2018. Fiscal Devaluations: Evidence Using Bilateral Trade Balance Data. Review of World Economics 154 (2): 247–275. Holzner, Mario, Marina Tkalec, and Goran Vuksic. 2019. Composition of Trade Flows and the Effectiveness of Fiscal Devaluation. The World Economy 42 (2): 453–477. Kraft, Evan, and Tihomir Stucka. 2002. Fiscal Consolidation, External Competitiveness and Monetary Policy: A Reply to the WIIW . Croatian National Bank Surveys, No. 8. Stoellinger, Roman. 2019. Functional Specialisation in Global Value Chains and the Middle-Income Trap. Wiiw Research Report, No. 441. Tkalec, Marina, Maruska Vizek, and Goran Vuksic. 2019. Fiscal Devaluation and Real Exchange Rates in the Euro Area: Some Econometric Insights. Review of International Economics 27 (2): 694–710. Vuksic, Goran, and Mario Holzner. 2016. Trade and Fiscal Imbalances in Southeastern Europe: Can Fiscal Devaluation Help? Economic Systems 40 (4): 568–581. Wallerstein, Immanuel. 1974. The Modern World-System: Capitalist Agriculture and the Origins of the European World-Economy in the Sixteenth Century. New York, NY and London: Academic Press.

CHAPTER 2

COVID-19 Contagion Among Countries

Franjo Štiblar

2.1

Introduction

This is a macro empirical study of COVID-19 contagion (COVID) in the world’s 41 largest economies (according to criteria of The Economist ) and in Slovenia and Croatia. The COVID crisis is accompanied by uncertainty, by what Nasim Taleb has called the “black swan.” This is much worse than the usual risks related to other events that have been well researched in the past. The COVID crisis is in its second wave of contagion, and the fact that it has been present for only 9 months limits possibilities for analyzing it. In terms of consequences of the COVID crisis, in the short run there is human suffering with cases of contagion and COVID-related deaths, on one side, and economic downturn on the other (more in Štiblar 2020). High hopes have been put into early vaccination, but precaution is needed with regard to potential obstacles in procedures of execution once new vaccines have been officially approved. The race among pharmaceutical companies is well underway, but it is not always a fair and ethical one.

F. Štiblar (B) University of Ljubljana, Ljubljana, Slovenia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_2

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Each company is aiming to be better than the others—by achieving a 90% or greater success rate—but their aim remains to maximize profit. In 2021, vaccination could stop further spread of COVID and economies could be out of the recession. Recession in the technical sense (decline in GDP in two consecutive quarters) will probably not occur, although the revival of growth will start from a much lower level. Regarding anti-COVID packages of measures, they seem to be well equilibrated tackling both problems of people directly and not through a trickle-down process and helping enterprises. It could happen that the financial sector, mostly banks, will be the last to suffer from the crisis, namely, once protection measures for the real sector (enterprises) and for the population (households) have ceased to exist. For banking, (Štiblar 2018b) it is critically important that nonbank penetration of the banking market be finally well regulated, as they do not offer the required guarantees in the capital (solvency) and money (liquidity) for keeping finances stable of the country. The story of unregulated cryptocurrencies is a similar one. Regulation of both does not mean resistance to technological progress but merely preserving financial stability. The complexity of the pandemic, due to the breadth of its effects, requires action in several areas of social life—first, in the economic sphere (where strong fiscal and monetary stimulus would be needed), then in the geostrategic position of the country, its demographic structure and political system (UN Report 2020). I am in favor of a nuclear option in the economic field, that is, a budgetary and monetary stimulus to the degree that is needed to resolve the crisis. The old austerity story is dead for the majority of the world’s decision-makers, as its implementation caused unnecessary suffering of people in the 2008 global financial crisis. In contrast to micro studies, this paper empirically analyzes the global macro situation in times of COVID, whereby the unavailability of data for the phenomenon of the crisis—present for only three quarters of 2020—is a strong obstacle. With COVID, the situation changes almost daily, while economic and other country data (demographic, geographic, political…) are regularly available except that they are late. The 2019 data are the latest available. Despite this deficiency, it seems worthwhile making a first assessment of the macro determinants of the COVID contagion, while being aware of the problem of the short observation period and data limitations. Still, it is better to have some preliminary evaluation than to wait for years for more reliable statistical data to become available.

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In this light, the present paper discusses several aspects of the spread of the COVID crisis among countries. Data for the 41 most important economies have been collected (as measured by the size of the absolute value of GDP, according to The Economist tables) and two countries of our special interest have been added: Slovenia and Croatia. Together, these countries count for over 90% of the world economy. Firstly, a proposal is made here about how to quantify the decision process for introducing lockdown in this crisis. Secondly, the impact of the economic and social environment (demographic, geographic, and political) on the spread of COVID is analyzed by means of correlation and regression analysis. And thirdly, a summarized comparison of the previous 2008 financial crisis with the present COVID crisis is made, emphasizing the difference in the policy response to both crises, which hopefully will make the consequences of the present COVID crisis less catastrophic than the consequences of the 2008 global financial crisis were. The article ends with a conclusion which summarizes major findings and proposes specific anti-COVID policy measures.

2.2 The Model for Introducing Lockdown (Determining the Tipping Point for the Start of Epidemics) The COVID crisis has caused two major types of damage to countries: harm from the number of those falling ill or dying, and losses in the economy1 due to falling activity. The decision-makers have to find an optimal compromise between both so that total damage for the country is minimized. This decision-making process is always present, whether they are aware of it or not. With a lot of simplifications, the process could be made formal. The starting assumption is that the longer the lockdown, the smaller the harm of losing human lives, and the larger the losses in economic activity. The tipping point for starting lockdown is the moment when the daily damages from lives lost are larger than losses from closing economic activity. The formal model for an introduction of lockdown would have the following form:

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economic losses in day

losses in human life in day

(GDP /number of yearly working days) : (cost of human life * number of deceased) (GDP/ working day) ≥ < (value of human fife * daily number of dead) equation 1

At the tipping point, expected human losses surpass expected economic losses (equation 1). We start with a day of no lockdown, when economic losses are minimal, while human losses are enormous. If a lockdown is introduced, economic losses start increasing with each day of lockdown, while human losses decline because, due to quarantine, fewer people die. Increasing daily economic loss after a certain number of days surpasses daily human losses and that day is the tipping point for abolishing lockdown. A simple example for Slovenia: e50 billion/250 working days in year ≥ e10 million2 * daily number of deceased Human loss surpasses economic loss for Slovenia at number 20 of deceased per day.3 The above equation has four variables, which can of course vary and thus could be adjusted: • not all GDP can be lost during the lockdown, and the economic loss due to lockdown differs depending on the structure of the economy and the intensity of lockdown, • the 250 working day number in a year of 364 days can differ among countries, • value of human life (a controversial number) differs among countries, a person’s ability…, • the number of deceased due solely to COVID is difficult to establish with precision. Countries with no lockdown obviously do not value human life. The Swedish response (i.e., doing without lockdown) entails that a calculation should be made for the whole period of the COVID crisis until the spread of contagion stops among the entire population and deaths from COVID disappear. If lives are valued less, the number of lockdown days is smaller. Given the number of days in lockdown for a country, one can ascertain the country’s value of human life. For Sweden, with no lockdown, the

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calculated value of human life is only e330 thousand. Alternatively, in Equation 1 COVID-related deaths could be replaced by the number of COVID cases and costs incurred by each case.

2.3 Explaining COVID Contagion Among Countries The subjects of analysis are the 43 largest economies in the world (the list is provided in the Appendix), for which the following 32 statistical indicators have been calculated. Data are from the end of November 2020. It is assumed that each country in the analysis COVID is related to a country-specific environment (and by the inclusive term “environment” we mean the several factors that contribute to the COVID crises—not merely economic factors):

COVID (COVID tests, cases and deaths) ← →

economic factors E demographic factors D geographic factors G political factors P

List of variables: 1. Age = median number of years in a country’s population, Worldometer, D. 2. Area = thousand square kilometers, Worldometer, G. 3. BOGf = budget deficit in 2020, % of GDP, forecast, Nov. 21, 2020, The Economist, E. 4. BONDl = interest rate on 10 year government bonds, latest, The Economist, E. 5. BOPf = current account, % of GDP, 2020 forecast, The Economist, Nov. 21, 2020, E. 6. Castest = COVID cases/COVID tests, Nov. 22, 2020 Worldometer, C. 7. Ccase = COVID cases, in thousands, Worldometer, Nov. 22, 2020, C. 8. Ccasepop = COVID cases in thousands per one million, Worldometer, Nov. 22, 2020 C.

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9. Cdeat = COVID deaths, in thousands, Worldometer, Nov. 22, 2020, C. 10. Cdeatcas = COVID deaths/COVID cases, Worldometer, Nov. 22, 2020, C. 11. Cdeatpop = COVID deaths, in thousands per one million, Worldometer, Nov. 22, 2020, C. 12. Ctest = COVID tests, in thousands, Worldometer, Nov. 22, 2020, C. 13. Ctestpop = COVID tests, in thousands per one million, Worldometer, Nov. 22, 2020, C. 14. Democr = index based on 60 indicators, 10 = max, 1 = min, EIU, Nov. 25, 2020, P. 15. Dens = number of people per square km, Worldometer, D. 16. GDP = GDP, billion USD in 2017, nominal, Worldometer, E. 17. GDPpc = GDP, USD per capita, 2017, nominal Worldometer, E. 18. Geolat = geographic latitude of country, in degrees, absolute value, G. 19. gGDPf = GDP growth rate in %, forecast for 2020, The Economist, Nov. 21, 2020, E. 20. gGDPl = GDP latest quarterly growth rate of GDP, y/y, The Economist, Nov. 23, 2020, E. 21. Gini = Gini coefficient of inequality, 0 lowest, 100 highest, CIA, Nov. 23, 2020, E. 22. gLoan = latest growth rate of loans to the private sector, Trading Economics, 2020, E. 23. HealGDP = the share of expenditures for health in % of GDP, WHO, 2018, E. 24. Healpc = expenditures for health per person in USD, 2018, E. 25. Migr = net migration, in thousands, Worldometer, 2019, D. 26. Migrpop = net migration per one million, in %, Worldometer, 2019, D. 27. NSdummy = dummy variable: latitude North = 1, latitude South = 0, G. 28. Pop = population, in millions, 2020, D. 29. serGDP = % share of services in GDP, world economic indicators, World Bank, 2019. 30. TourGDP = % share of income from tourism in GDP, World Tourist Organization, 2019. 31. Unempl = unemployment rate in %, latest, The Economist, D.

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32. Urban = % share of population living in urban area, Worldometer, latest, D. Groups of unobservable factors, concepts: C = COVID variables (8 indicators) D = demographic variables (7 indicators) E = economic variables (13 indicators) G = geographic variables (3 indicators) P = political variable (1 indicator).

2.4

Correlation Analysis

Matrix of correlation coefficients Comment on Table 2.1 (correlation among COVID C and environment En variables): When there is a lack of available data due to short time series, calculation of correlation becomes additionally important, compared to regression analysis. Economic factors are predominant in the COVID cross-section analysis for 43 countries, but other factors of environment (En) are also included: demographic, geographic, and political (En = E, D, G in P). There is reciprocal (mutual) causality between COVID-19 contagion and a country’s environment for evaluation of which correlation analysis is appropriate C →←En. Due to the fact that there are only 9 months’ experience and data for COVID-19, specification of regression equations start with variables of the environment as determinants (causes) impacting expansion of COVID-19 tests, cases and related deaths in each country (consequences). In most cases, only the impact of the environment can be calculated (C ← En). In cases of forecasted values of the environment, the reverse causality is already possible to calculate (C → En). Correlation matrix is calculated for 8 dependent variables presenting the COVID situation by November 22, 2020, in relation to the 24 variables of the environment. The entire data matrix has the following form:

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Table 2.1 Correlogram: Relations of COVID with environment CORREL

Castest

Ccase

Ccasepop

Age Area BOGf BONDl BOPf Castest Ccase Ccasepop Cdeat Cdeatcas Cdeatpop Ctest Ctestpop Democr Dens GDP GDPpc Geolat gGDPf gGDPl GINI gLoan HealGDP Healpc Migr Migrpop NSdummy Pop serGDP TourGDP Unempl Urban

−0.34 −0.08 −0.13 0.31 −0.30 1.0 0.14 0.38 0.34 0.50 0.53 −0.18 −0.32 0.04 −0.17 −0.20 −0.32 −0.20 −0.27 −0.40 0.31 0.07 0.29 −0.26 −0.04 −0.22 −0.22 −0.11 −0.05 0.08 0.29 −0.02

−0.17 0.41 −0.34 0.06 −0.20 0.14 1.0 0.27 0.94 0.00 0.27 0.73 0.09 0.30 −0.08 0.63 0.01 −0.10 −13 −0.18 0.30 −0.13 0.27 0.19 0.29 −0.09 −0.07 0.44 0.26 −0.15 0.08 −0.07

0.34 −0.07 −0.33 −0.39 −0.11 0.38 0.27 1.0 0.31 −0.08 0.84 0.04 0.34 0.31 −0.09 0.08 0.31 0.33 −0.47 −0.28 −0.24 −0.00 0.18 0.36 0.29 0.20 0.03 −0.24 0.48 −0.11 0.11 0.27

Cdeat Cdeatcas −0.20 0.42 0.40 0.06 −0.23 0.34 0.94 0.31 1.0 0.23 0.42 0.64 0.07 0.03 −0.10 0.60 −0.01 −0.15 −0.18 −0.16 −0.40 −0.10 0.45 0.17 0.35 −0.11 −0.15 0.33 0.30 −0.10 0.11 0.05

−0.34 0.21 −0.05 0.29 −0.30 0.51 0.01 −0.08 0.23 1.0 0.33 0.12 −0.23 −0.23 −0.25 0.12 −0.26 −0.09 0.04 0.01 0.19 0.04 0.28 −0.19 −0.11 −0.17 −0.17 0.20 −0.11 0.05 0.06 −0.03

Cdeatpop

Ctest

Ctestpop

0.13 −0.02 −0.38 −0.22 −0.24 0.53 0.27 0.84 0.42 0.33 1.0 0.03 0.22 0.26 −0.18 0.07 0.14 0.17 −0.57 −0.31 0.02 0.07 0.28 0.21 0.27 0.13 −0.11 −0.20 0.43 −0.11 0.23 0.35

−0.07 0.60 −0.13 −0.07 −0.12 −0.19 0.74 0.04 0.64 0.12 0.03 1.0 0.13 −0.23 −0.06 0.85 −0.01 0.04 0.11 0.08 0.17 −0.05 0.03 0.14 0.12 −0.10 −0.10 0.78 −0.07 −0.12 −0.09 −0.15

0.42 0.10 −0.19 −0.45 0.35 −0.32 −0.09 0.35 0.07 −0.23 0.22 0.13 1.0 0.32 0.30 0.12 0.65 0.42 −0.18 0.03 −0.24 −0.10 0.06 0.54 0.31 0.44 0.16 −0.19 0.61 −0.15 −0.15 0.46

Note For 43 units of observation (countries), correlation coefficient is significantly different from 0, if /r/ ≥ 0.25, and shows slight presence of correlation, if /r/ ≥ 0.19 Source Author’s calculation

2

Indicator

COVID-19 CONTAGION AMONG COUNTRIES

Castests Ccases Cdeaths

25

……. etc. (8 C variables, 24 En variables)

Country USA China Germany . . etc. (43 countries)

(a) Correlation among COVID variables C: The assumption is those correlations among C tests, cases, and deaths from COVID are strong. COVID cases and deaths are strongly positively correlated among themselves, while COVID tests depend on decisions made by authorities and are therefore less related to the other two COVID variables. The results in Table 2.1 confirm this hypothesis: there is a significant positive correlation among variables of cases and deaths, but a weaker correlation with tests, which in some cases are even negative. As expected, the absolute number of tests, cases and deaths are all highly positively correlated. Detailed presentation of Table 2.1: • Column 1: the share of cases to tests executed Castest is positively correlated with the share of cases in the population Ccasepop, number of deaths by COVID Cdeat, the share of deaths in cases of Cdeatcas, the share of deaths in the population Cdeatpop, while being negatively correlated with number of tests in a country Ctest and negatively correlated with the number of tests per one million Ctestpop; • Column 2: number of cases in a country Ccase is positively correlated with cases in the population, number of deaths, share of deaths in cases in the population, and number of tests; • Column 3: number of cases per one million Ccasepop is positively related to the share of cases in tests, number of cases, number of deaths, the share of deaths in the population, and share of tests in the population.

26

F. ŠTIBLAR

• Column 4: number of deaths in country Cdeat is positively related to the share of cases in tests, number of cases, share of tests in the population, the share of deaths in the population and number of tests, while it is weakly related to the share of deaths in cases. • Column 5: share of deaths in cases Cdeatcas is strongly positively related to the share of cases in tests share of deaths in the population and weakly related to the number of deaths from COVID, while it is weakly negatively related to the number of tests in the population. • Column 6: number of deaths in the population Cdeatpop is strongly positively related to all other COVID variables except the share of deaths in the population and number of tests, while it is weakly positively related to share of tests in the population. • Column 7: number of tests Ctest is the weakest link with other COVID variables. It is positively related to the number of cases and the number of deaths, while it is weakly negatively related to the share of cases in tests. • Column 8: share of tests in the population Ctestpop is positively related to the number of cases in the population and number of deaths in the population, while it is negatively related to the number of cases in tests and the number of deaths in cases. (b) Correlation of 8 COVID variables with 24 variables of environment En:C ←→ En The sign of some correlation coefficients differs from expectations, which can be the result of reverse causality between variables C → En or of the fact that the general level of development of a country prevails as an explanatory environment variable. The overall level of development of a country, which could prevail and thus explain some unexpected correlations in the study, includes several dimensions: economic GDPpc, political democracy, a geographical position that is farther away from the equator, more urbanization, and higher density of population, etc. The hypotheses are that better economic performance indicates less COVID contagion, that demographic characteristics indicate an ability for spreading COVID, and that geographical variables indicate the role of a country’s global position in spreading COVID. Higher political democracy could be relevant for COVID spread.

2

COVID-19 CONTAGION AMONG COUNTRIES

27

The results indicated in the table show that not all economic variables are significantly related to COVID (financial variables among them), but many demographic variables are surprisingly strong; some geographic and political variables, meanwhile, sometimes show an unexpected relation. *Economic variables With regard to economic policy variables, a higher budget deficit (as a fiscal policy variable) improves the COVID situation, while the growth of loans to the private sector remains (as a monetary policy variable) insignificant. Higher budget deficit indicates more public money to finance health care service, but monetary expansion through modern monetary policy does not occur per se in 2020, because it started already in 2015. There is enough liquidity in the global economy; the only problem is that it does not reach regular businesses and people because it is wrongly directed toward the richest companies and people. A higher standard (GDP per capita) has a less significant positive correlation to protection against COVID, as the variable indicates two opposite tendencies at the same time: higher health service, but also a higher degree of communication with other people both within a country and abroad. Higher inequality among the population (GINI higher) indicates fewer COVID tests, more COVID cases, but fewer COVID deaths in the country. Among variables representing the internal openness of the country, the strongest positive correlation to COVID is seen in the share of services in GDP, as more services indicate more contacts among people and thus the higher possibility of spreading COVID. A similar explanatory variable— namely, the share of tourism income in GDP (assumption: more tourism means more mingling among people)—is not significantly related to the spread of COVID. A current account deficit indicates a weakness in a country and is therefore correlated with a higher level of contagion in that country. A higher share of health expenditure in GDP is positively related to a higher share of COVID tests among the population, but, surprisingly, it is also related to higher cases and COVID deaths. One variable that could encompass the concept of overall country development could probably explain some of the unexpected correlations. Elements pertaining to overall country development could be the average age of the population, the higher share of services in GDP, higher openness of a country to

28

F. ŠTIBLAR

other countries, higher latitude, and a higher democracy index—leading to the idea that COVID is an illness of rich countries and of rich people. The few available economic variables presenting the economic situation in a country in mid-2020 already indicate the negative impact of COVID contagion on its economy—for instance, the larger fall of quarterly GDP, decreased forecasts for GDP and budget the deficit for the whole of 2020 (albeit predicted in mid-2020), and increased unemployment. *Demography The median age of the population as an indicator of the aging population shows some expected correlation: countries with an older population perform more COVID tests and they have more cases in tests, but they have a lower share of deaths to cases of COVID. The density of habitation is less significantly related, while a higher degree of urbanization causes a higher spread of COVID, as expected. A higher share of net immigration in a country’s population is positively correlated to more COVID tests, but not to a higher share of COVID cases in tests. It is also positively related to higher COVID deaths in the population. As expected, countries with a larger population have fewer COVID cases and fewer deaths per one million of the population, if they are all absolute numbers (e.g., the USA). *Geography Correlation results are to a certain degree unexpected but also revealing. The farther away from the equator in latitude a country is situated, the more COVID tests it conducts per one million, the fewer cases it has. Countries from the Northern Hemisphere do not differ significantly from countries from the Southern Hemisphere, except that they find fewer cases in COVID tests. As expected, countries covering a larger area have more COVID tests, cases, and deaths, as they usually also have a larger population. They have a higher share of COVID deaths among COVID cases. *Political explanatory variable The only political variable introduced in the analysis is the country democracy index as measured by The Economist EIU and constructed from 60 different factors. Regarding democracy, countries are rated from highest 10 (first is Norway with 9.87) to 1 (lowest is North Korea with close to 1). A higher level of democracy is negatively correlated with a share of deaths among cases. The higher level of democracy is positively correlated with the number of cases in the population, the number of

2

COVID-19 CONTAGION AMONG COUNTRIES

29

deaths in a population, and the number of tests in the population. One explanation could be that a higher degree of democracy is connected with more opposition to the rules of individual control that are required in COVID prevention. Detailed presentation of Table 2.1 by variables of environment: *Row 1: medium age of country’s population Age is: • negatively related to Castest: an older population has fewer cases in tests, • positively related to cases/population: a country with an older population has made more tests, • negatively related to death/cases: due to better quality of hospitals, • positively related to test/population: countries with on older population have more tests in the population. *Row 2: area (the size) of country in square kilometers is: • • • •

positively positively positively positively

related related related related

to to to to

number of cases, number of deaths, number of tests, share of deaths in cases.

*Row 3: budget balance BOGf, forecasted for 2020, is related: • • • • •

negatively to share of cases in tests, negatively to share of cases in the population (reverse causality?), positively to number of deaths (reverse causality), negatively to percentage of deaths in the population, negatively to share of tests in the population.

*Row 4: Interest on government bonds, latest, BONDl, is related: • • • •

positively to share of cases in tests, negatively to share of cases in the population, positively to share of deaths in cases, negatively to share of tests in the population.

30

F. ŠTIBLAR

*Row 5: current account forecast for 2020 BOPf, is related: • negatively to cases/tests, • negatively to death/cases, • positively to tests/population. *Row 14: Index of Democracy Democr, is related: • positively to deaths/cases. *Row 15: Density of population Dens, is related: • negatively to deaths/cases, • positively to test/population. *Row 16: GDP, is related: • positively to cases of COVID, • positively to number of deaths from COVID, • positively to tests for COVID. *Row 17: GDP per capita GDPpc, is related: • • • •

negatively to cases/tests, positively to cases/population, negatively to deaths/cases, positively to tests/population.

*Row 18: Geographical latitude in absolute degrees, Geolat, is related: • negatively (weak) to cases/tests, • positively to cases/population, • positively to tests/population. *Row 19: GDP growth rate in 2020, forecast, is related: • negatively to cases/tests,

2

COVID-19 CONTAGION AMONG COUNTRIES

31

• negatively to cases per one million, • positively to death per one million. *Row 20: growth of GDP, latest quarter of 2020, is related: • negatively to cases/tests, • negatively to cases/population, • negatively to death/population. *Row 21: higher Gini coefficient indicating higher inequality, GINI, is related: • • • • •

positively to cases/tests, positively to number of cases, negatively to cases/population, negatively to number of deaths, negatively to tests per one million.

*Row 22: growth of loans to private sector gLoans is not related to COVID variables. *Row 23: share of health expenditures in GDP HealGDP, is related: • • • • •

positively positively positively positively positively

to to to to to

cases/tests, number of cases, number of deaths, deaths/cases, deaths per one million.

*Row 24: Individual USD expenditures for health, is related: • • • • • •

negatively to cases/tests, positively to number of cases, positively to cases/population, negatively to deaths/cases, positively to deaths per one million people, positively to tests per one million.

*Row 25: Net migration to country, 2019, is related:

32

F. ŠTIBLAR

• • • • •

positively positively positively positively positively

to to to to to

number of cases, cases per one million, number of deaths, deaths per one million, tests per one million.

*Row 26: share of net migration to population, 2019, is related: • negatively to cases/tests, • positively to cases per one million, • positively to tests per one million. *Row 27: NS dummy (1 for North, 0 for South hemisphere) is: • negatively related to cases/tests. *Row 28: Population Pop, is related: • positively to number of cases, • positively to number of deaths, • positively to number of tests. *Row 29: share of services in GDP, is related: • • • • •

positively positively positively positively positively

to to to to to

number of cases, cases per one million, number of deaths, deaths per one million, tests per one million.

*Row 30: share of tourism in GDP tour/GDP, 2018, is not related to COVID variables. *Row 31: Unemployment rate, latest, Unempl, is related: • positively to cases/tests, • positively to deaths per one million.

2

COVID-19 CONTAGION AMONG COUNTRIES

33

*Row 32: share of urban population in country, Urba, related: • positively to cases per one million, • positively to deaths per one million, • positively to tests per one million.

2.5

Regression Analysis

The following equations in Table 2.2 show the impact of country-specific environment on its COVID contagion. Statistical significance of estimated 12 regression equations in Table 2.2: Collinearity does not exist among explanatory variables in ten equations: the first two equations have only one correlation /r/ = 0.5, second, third and fourth group of two equations the highest correlation below /r/ < 0.3 and the last group /r/ = 0.62. Statistical significance (F-statistics) of estimated equations is unusually high for cross-section analysis with the data for the 43 countries. Durbin–Watson statistics are not relevant for cross-section (panel) analysis, the values of coefficient of determination R2 are relatively high, between 0.27 and 0.54, which is good. 2.5.1

Structure of Estimated Equations

At the time of estimation COVID contagion was only 9 months old. At the moment (i.e., at the end of November 2020) good 2020 data for explanatory variables for economic, demographic, geographic, and political developments in the country are not yet available. The dependent variables are the selected relative indicators of COVID presence and not the absolute ones. In particular, it does not make sense to research thoroughly the absolute size of the number of COVID tests, morbidity, and deaths, because they obviously depend on the size of the population, the size of the territory of the country, etc. The relative numbers of COVID tests per one million, disease per million, and deaths per one million are more suitable, as this establishes the same criteria for all countries, regardless of their absolute size.

b1.X1 (tb1) 6.13 (1.98) Urban 7.14 (2.54) Urban 0.16 (1.31) Urban 0.16 (1.41) Urban 5.4e-7 (0.73) Area −0.0012 (−0.77) Democr 0.0094 (2.67) BONDl 0.0103 (3.10) BONDl

A (ta)

−638.6 (−1.81)

−404.2 (−1.98)

2.88 (0.14)

−19.41 (−2.03)

0.025 (2.27)

0.028 (2.83)

−0.0085 (−0.24)

−0.025 (−1.00)

1. Cdeatpop

2. Cdeatpop

3. Ccasepop

4. Ccasepop

5. Cdeatcas

6. Cdeatcas

7. Castest

8. Castest

Regression equations

Y

Table 2.2

3.92 (0.59) serGDP −48.6 (−3.67) gGDPf −1.45 (−2.52) gGDPf −1.40 (−2.45) gGDPf −0.0007 (−0.45) Democr −2.09e-7 (−1.47) GDPpc −0.004 (−0.67) Geolat −0.0048 (−3.25) gGDPl

b2.X2 (tb2) −42.70 (−3.0) gGDPf −18.8 (−1.91) BOPf 0.30 (2.29) Geolat 0.245 (2.32) Geolat −2.24e-7 (−1.54) GDPpc 0.0011 (2.48) HealGDP −0.0047 (−3.168) gGDPl 0.0065 (3.39) HealGDP

b3.X3 (tb3)

0.0065 (3.38) HealGDP

−1.08 (−1.27) BONDl −0.88 (−1.71) BOGf 0.0010 (2.25) HealGDP

−9.64 (−0.70) BOGf

b4.X4 (tb4)

−0.79 (−1.53) BOGf

−17.7 (−1.72) BOPf

b5.X5 (tb5)

−0.55 (−1.15) age

b6.X6 (tb6)

0.415 9.00

0.422 6.77

0.207 3.31

0.218 2.59

0.385 5.95

0.415 4.22

0.446 10.46

0.466 6.46

R2 F

34 F. ŠTIBLAR

1.680 (0.83) Urban 2.647 (1.39) Urban 0.0435 (6.97) Ctest 0.0199 (17.9) Ccase

−487.26 (−1.77)

−755.5 (−3.42)

322.2 (1.16)

4.39 (1.49)

9. Ctestpop

10. Ctestpop

11. Ccase

12. Cdeat

5.267 (0.99) serGDP 9.708 (2.37) serGDP

b2.X2 (tb2) 3.024 (1.37) Geolat 4.401 (2.32) Geolat

b3.X3 (tb3) 0.0034 (1.60) GDPpc 0.056 (2.29) (Dens)

b4.X4 (tb4)

Note For 43 observations: regression coefficients are significantly different from 0 (significant) if /t-value/is above 1.6, and slightly significant if /t-value/is over 1.28 Source Author’s calculation

b1.X1 (tb1)

A (ta)

Y 0.042 (1.63) Dens

b5.X5 (tb5) −6.458 (−0.72) BOGf

b6.X6 (tb6)

0.887 322.0

0.542 48.5

0.508 9.82

0.543 7.09

R2 F

2 COVID-19 CONTAGION AMONG COUNTRIES

35

36

F. ŠTIBLAR

Years must pass before we can obtain the final reliable information about the COVID impact on the environment. Geography and to a large extent demography will not change in the future; economic variables will. All calculations indicate the thesis that COVID is an illness of rich people from rich countries, where travel and communication is more frequent or better: these countries are more developed in a number of dimensions. People have more interpersonal relations. According to the estimated 12 equations, economic variables show sometimes less explanatory power on average than other variables of the environment. Some economic variables could already be impacted by the COVID crisis, namely, the prediction of future values of GDP, budget deficit, current account, etc. For each of the 5 COVID-dependent variables, two estimations have been made—the first emphasizing the explanatory substance of chosen variables and the second taking more into account also statistical significance. 2.5.2

Equations

In the process of estimation, three COVID variables given in absolute terms are, for obvious reasons, not estimated. The number of COVID tests, cases, and deaths depend directly on the size of the country, population, and some other factors in absolute terms. Among the remaining five dependent COVID variables, measured in relative terms, the three with tests, cases, and deaths measured per one million people showed statistically and substantively better results than the remaining two dependent variables Cdeat/case and Ccase/test—in construction of which one COVID indicator is compared with another. They are intended to explain why there is a difference among analyzed countries in the share of COVID deaths in a number of cases and why the number of cases found in tests varies among countries. *Equations 1 and 2 explain the share of COVID-related deaths per one million: Cdeatpop. This indicator shows COVID morbidity in a country. It is under the positive impact of higher urbanization, a larger share of services in GDP, lower forecasted growth of GDP in 2020 (reverse causality?), higher budget deficit (higher fiscal stimulus), and higher current account deficit (more imports of anti-COVID devices than exports as an indication of the higher the openness of country).

2

COVID-19 CONTAGION AMONG COUNTRIES

37

Equation 2 deals with the same explanatory variables as equation 1, except that statistically less significant variables services/GDP and budget deficit are left out. The positive impact of the degree of urbanization and the share of services indicating more inter-human communication is less clear. The higher budget deficit and the larger current account deficit explains that the number of COVID-related deaths is higher (in relative terms, that is, per one million) because: • of the fact that, due to the larger number of COVID deaths per one million residents, the government is dedicating more money to solving the problem, which increases their budget deficit; • of the fact that, due to the increased COVID deaths, the government is importing more anti-COVID devices and thus increasing the current account deficit. It is evident from these two examples that COVID contagion in 2020 has already impacted the predictions of The Economist for two deficits in the individual countries for the whole of 2020. It is thus a matter of causality: COVID → Economy. For the other explanatory variables in the study, data are still lacking for 2020, which means that we cannot estimate the effect of COVID on them. The same reverse causality C → economy holds for the latest data about forecasted negative GDP growth in 2020. Negative forecasts of all three variables could be the results of a pessimistic atmosphere in a country on the basis of a high COVID death ratio, which would mean a reverse causality: a bad COVID situation influences the negative economic forecast for the analyzed country. *Equations 3 and 4 explain the number of COVID cases per million in a country: Ccasepop. This is the most important indicator of the spread of COVID among a country’s population. It is positively impacted by degree of urbanization (more people live in cities, where they are closer and communicate more with each other, hence the faster and larger spread of COVID), forecasted GDP growth for 2020 (the more COVID cases relative to population, the lower the country’s GDP, as predicted by The Economist ), higher geographical latitude (countries farther from the equator have more COVID cases in the

38

F. ŠTIBLAR

population); less financially credible countries have fewer COVID cases, a higher budget deficit means more cases (reverse causality), and countries with an older population have fewer COVID cases. According to equation 4, the degree of COVID contagion per one million in a country is positively impacted by higher urbanization, lower forecasted GDP growth, being farther away from the equator, and the higher budget deficit (more stimulus, reverse causality). For a higher number of COVID cases per one million, higher urbanization, lower forecasted GDP for 2020 are expected; surprising, however, is the negative impact of a country’s distance from the equator, higher financial instability, the higher median age of population and higher forecasted budget deficit. Again, reverse causality could be at work: a higher number of COVID cases per one million indicates a pessimistic climate in a country, which leads to a negative forecast of its future economic performance. *Equations 5 and 6 explain the share of deaths to COVID cases: cdeatcas. The indicator shows the ability of a health system (hospitals) in a country to prevent COVID illness ending in death. The ratio death/cases is higher in countries with a larger surface area, with more democracy, and a higher share of health expenditures in GDP and in countries with lower GDPpc. In equation 6, the explanatory variable area was eliminated from the equation due to low significance. Of all 10 dependent COVID variables in estimated equations 5 and 6 have the smallest level of explanation (lowest coefficient of determination). Some other factors are apparently also relevant for explaining why the ratio of COVID deaths in cases differs among analyzed countries. Lower GDP per capita is an expected explanation for a higher ratio of COVID death/cases, but higher democracy makes for surprising correlations (less willing to give into surveillance and loss of freedom?), as does a higher share of health expenditures in GDP (cause or consequence of COVID penetration?). *Equations 7 and 8 determine the ratio of cases to tests made in a country: Castest. The ratio indicates the level of a country’s success in finding COVID patients through COVID testing. A larger share of COVID cases in tests in a country are related to the lower credibility of a country (higher interest on country bonds), smaller

2

COVID-19 CONTAGION AMONG COUNTRIES

39

distance to the equator, a larger fall in GDP in mid-2020 compared to the same quarter of 2019, and a higher share of expenditure for health in GDP. Equation 8 has the same specification, except that geographic latitude is eliminated from explanatory variables. The variation of case/test ratio among countries is not satisfactorily explained. There must be some additional explanatory forces at work. *Equations 9 and 10 explain the number of tests per one million in a country: Ctestpop. This indicator measures the ability of health authorities to perform COVID tests and thus prevent COVID illness from spreading in the country. The share is higher in more urbanized countries, with a higher share of services in GDP, greater distance from the equator, higher GDP per capita, higher density in a country and higher budget deficit (higher fiscal stimulus). In equation 10, the variables GDP per capita and budget deficit are left out from equation 9. Explanatory variables make estimated equations 9 and 10 highly acceptable. They are the best equations in the analysis by criteria of statistical significance and substantive common sense. Higher country development leads to higher testing among its population. In addition, we discerned that the positive impact of tests on cases (equation 11) and positive impact of cases on deaths from COVID (equation 12). Equations 11 and 12 are just confirming the positive impact of the higher number of COVID tests on the higher the number of COVID cases and that the higher number of COVID deaths is related to higher the number of COVID cases.

2.6

Application for Slovenia and Croatia

We use the estimated regressions in 32.2 and apply actual values of the explanatory variable for Slovenia and for Croatia to obtain the estimated value of COVID indicator Ye. Estimated regression equations present a general rule of COVID incidence induced from data of 43 most relevant countries in the world. It is compared with the actual value of COVID indicator Ya to find out where and how much-observed country COVID differs from the general rule as embodied in the estimated equation. We try to identify reasons for that difference.

40

F. ŠTIBLAR

SLOVENIA: When, Ya ≥ Ye, the reported actual COVID indicator for Slovenia is higher than what general rule for 43 countries would indicate. Some additional domestic factors could explain the difference, for instance, more COVID tests are performed than what would be expected from the general rule in the equation. When Ya < Ye, the value of the reported actual COVID indicator for Slovenia is smaller than what is expected from the general rule as observed by an estimated equation. The reasons for that should be identified for undertaking policy action. In Slovenia (Table 2.3) the actual number of COVID deaths in million people is much higher (double), than what the equation would predict (equations 1 and 2). Some, not yet identified specific factors, increased death number in the second wave to put Slovenia at the top of the global country list. Among explanatory variables, specified in equations, the strongest impact comes from the high level of urbanization, the lower forecast for GDP in 2020 and a higher share of services in GDP. Regarding the number of COVID cases per 1 million people (equations 3 and 4) actual number is much higher than predicted, again indicating for Slovenia influence of additional explanatory factors, which are not included in the equation. But, the difference between the higher actual and lower estimated number of COVID cases is smaller than in the case of the number of COVID deaths in the population as a dependent variable. The strongest single explanatory variable in equations 3 and 4 is geographic higher latitude, which is Slovenia’s farther distance from the equator. Forecasted negative BDP growth and a higher degree of urbanization also play a significant role. Number of COVID death relative to the number of COVID cases (equations 5 and 6) is in Slovenia actually smaller than predicted on basis of the general rule observed from equations. Reasons can be better medical service for COVID patients or a milder form of COVID disease. The higher share of health expenditures in GDP also plays an important role. The number of COVID cases compared to the number of tests made for COVID presence (equations 7 and 8) are in practice higher than what can be expected from the equation rule. Slovenia discovered more COVID patients in tests made than what is the rule. Some COVID patents were not discovered through testing. Important explanatory variables with a positive impact for case/test variables are the higher share

337 urba 393 urba 8.8 urba 8.8 urba 0.00015 area 0.00075 democr −0.00094 bondl −0.00103 bondl 92.4 urba 145.6 urba

−639 A −404 A 2.88 A

−19.41 A 0.018 A

0.019 A −0.0085 A −0.025 A

−487.26 A −755.5 A 139.1 Geolat 202.4 Geolat

0.00834 Healgdp 0.0611 Ggdpl 0.0493 Healgdp

−0.00056 Gdppc −0.0184 Geolat 0.0624 Ggdpl 347.1 Sergdp 639.8 Sergdp

11.2 Geolat −0.0009 Gdppc

286 ggdpf −115 Bopf 13.8 Geolat

9.4 Ggdpf 0.00075 Democr

258 Sergdp 326 Ggdpf 9.7 Ggdpf

79.0 gdppc 5.88 (dens)

0.0493 healgdp

4.41 dens

−8.7 bogf

0.11 bondl 9.9 bogf 0.0076 healgdp

−108 bopf

108 bogf

Estimated (Ye) and actual (Ya) values of COVID indicators

72.33 bogf

−24.8 age

247.9 Yest 238.2 Yest

0.027 Yest 0.0844 Yest 0.0857 Yest

19.9 Yest 0.026 Yest

Yest 242 199 Yest 23.21 Yest

Ya−Ye −22.4 Ya−Ye −12.7

Ya−Ye −0.011 Ya−Ye 0.0512 Ya−Ye 0.05

Ya−Ye 10.7 Ya−Ye −0.010

Ya−Ye 246 Ya−Ye 289 Ya−Ye 7.37

Note Ya = Yact = Yactual, Ye = Yest = Yestimated Numbers in table are product: regression coefficient x value of explanatory variable for Slovenia Source Author’s calculation

1. cdeatpop Yact = 488 2. cdeatpop Ya = 488 3. ccasepop Ya = 30.57 4. ccasepop Ya = 30.57 5. cdeatcas Ya = 0.016 6. cdeatcas Ya = 0.016 7. castest Ya = 0.1356 8. castest Ya = 0.1356 9. ctestpop Ya = 225.5 10. ctestpop Ya = 225.5

Table 2.3

2 COVID-19 CONTAGION AMONG COUNTRIES

41

42

F. ŠTIBLAR

of health expenditure in GDP and the country’s higher quarterly GDP growth during 2020. The relative number of COVID tests in the population (equations 9 and 10) is in fact in Slovenia lower than what would come out as a rule from estimated equations. Testing can be treated as an already antiCOVID measure. It means that not enough tests were made and cases of COVID appear regardless of testing. The strongest positive stimulus for testing COVID in Slovenia appears to be a high share of services in GDP. People employed in the service sector are more exposed to COVID transmission due to more frequent contacts they have with other people, including COVID patients. CROATIA: When Ya ≥ Ye, the reported actual COVID indicator for Croatia is higher than what the general rule for 43 countries, embodied in estimated regression equations, would indicate. Some additional domestic factors can explain the difference, for instance, more COVID tests were performed than what would be expected from the general rule in the equation. When Ya < Ye, the reported actual COVID indicator for Croatia is smaller than what is expected from the general rule as observed by an estimated equation. Again, reasons for difference should be identified and appropriate policy measures proposed to reduce the difference and diminish COVID contagion in Croatia (Table 2.4). Implications for from regression analysis somewhat differ from results for Slovenia. Croatia has in fact a much lower number of COVID deaths in one million people than what would be predicted from estimated equations 1 and 2, while Slovenia higher. Among relevant determinants of COVID deaths are for Croatia high degree of urbanization and lower forecasted GDP growth for 2020. The spread of COVID cases among the population is for Croatia in fact higher than what comes from the rule obtained by estimated equations 3 and 4. Factors that contribute to a higher share of COVID cases in the population are the country’s higher geographical latitude, forecasted GDP growth for 2020, and higher urbanization. The higher median age of the Croatian population causes a smaller number of COVID cases. On explanation could be relatively higher overall development compared to some other countries in the sample.

355.4 urba 414.1 urba 9.28 urba 9.28 urba 0.0004 area 0.00066 Democr 0.0084 Bondl 0.00923 Bondl 97.44 Urba 153.5 Urba

−638.6 A −404.2 A 2.88 A

−19.41 A 0.018 A

0.019 A −0.0085 A −0.025 A

−487.26 A −755.5 A 136.1 Geolat 198.1 Geolat

0.00698 Healgdp 0.0709 Ggdpl 0.0413 Healgdp

−0.00003 Gdppc −0.018 Geolat 0.0725 Ggdpl 331.3 Sergdp 610.6 Sergdp

11.83 Geolat −0.00024 Gdppc

224.8 Ggdpf 75.2 Bopf 13.50 Geolat

12.74 Ggdpf 0.00065 Democr

246.6 Sergdp 442.3 Ggdpf 13.20 Ggdpf

44.9 gdppc 4.1 (dens)

0.0413 healgdp

3.07 dens

7.9 bogf

−0.922 bondl 8.84 bogf 0.00635 healgdp

70.8 bopf

96.4 bogf

Estimated (Ye) and actual (Ya) values of COVID indicators

64.5 bogf

−24.2 age

190.1 Yest 210.5 Yest

0.0263 Yest 0.094 Yest 0.098 Yest

23.28 Yest 0.0247 Yest

Yest 355.4 527.4 Yest 21.59 Yest

Note Ya = Yact = Yactual, Ye = Yest Yestimated, −numbers in table are product: regression coefficient x value of variable for Croatia Source Author’s calculation

1. cdeatpop Ya = 318.0 2. cdeatpop Ya = 318.0 3. ccasepop Ya = 24.48 4. ccasepop Ya = 24.48 5. cdeatcas Ya = 0.013 6. cdeatcas Ya = 0.013 7. castest Ya = 0.150 8. castest Ya = 0.150 9. ctestpop Ya = 162.9 10. ctestpop Ya = 162.9

Table 2.4

Ya−Ye −27.2 Ya−Ye −47.6

Ya−Ye −0.0133 Ya−Ye 0.056 Ya−Ye 0.052

Ya−Ye 1.20 Ya−Ye −0.0117

Ya−Ye −37.4 Ya−Ye −209.3 Ya−Ye 2.89 2 COVID-19 CONTAGION AMONG COUNTRIES

43

44

F. ŠTIBLAR

The estimated ratio of COVID deaths to the number of COVID cases (equations 5 and 6) is higher than actual. There must be something Croatia does better to reduce the number of COVID-related deaths below the number expected as a rule from equations. An important determinant of deaths/cases for Croatia appears to be the level of democracy, in the sense that more democracy leads to higher deaths in COVID cases (liberal approach). The location of the country farther away from the equator also adds to the number of deaths in COVID patients. The share of COVID cases in a number of COVID tests (equations 7 and 8) is higher in actual life in Croatia than what is estimated by the equation. Some people become COVID patients without being tested for COVID. The important explanatory variables for estimated ratio cases/tests for Croatia are the credibility of the country (interest rates on 10-year government bonds), the share of health expenditures in GDP (better health service) and the latest 2020 lower quarterly GDP growth rate. The estimated number of COVID tests in one million people (equations 9 and 10) is, again, higher than actual. Less COVID tests were made in Croatia than what they should be according to the rule embodied in estimated equations. More COVID tests should be performed. Positive impact on COVID tests have the higher share of services in GDP, the higher degree of urbanization, the higher geographic latitude of Croatia, and higher density of population.

2.7 COVID Crisis in 2020 Versus Financial Crisis in 2008 There are similarities and differences between both crises. The global financial crisis is already widely analyzed (for instance, Shiller 2009; Blyth 2015; Rodrik 2012; Štiblar 2009). (a) The financial crisis was a human-made catastrophe (Rogoff and Reinhart 2009). while the COVID crisis is a nature-made catastrophe, albeit partly due to additional “help” of human inappropriate penetration into nature. (b) The line of causality goes in opposite directions in both crises: Financial crisis: financials → policy measures → households, enterprises, and banks

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45

COVID crisis: financials ← households, enterprises ← policy measures ← COVID. (c) The social extent of the COVID crisis is much greater, including economic and non-economic dimensions, while the financial crisis was predominantly based on economic and financial sector. (d) The policy solutions in the 2008 financial crisis were based on onesided orthodox austerity measures for most countries, especially in the EU and especially in Slovenia (criticized by Blyth 2015; Blanchard and Leigh 2011; Corsetti et al. 2012; Guajardo et al. 2011; Krugman 2013). In a study, I made in 2015 (published in Slovenian language, Štiblar 2015a, b) and later published in English in 2018 (Štiblar 2018a)—that is 7 years (or 10 years) from the start of the financial crisis—I found that such policy measures of an orthodox ordo-liberal and neo-liberal approach caused great losses in GDP growth as well as much human suffering. The believers in austerity lost one decade before the economy returned to the level of GDP per capita before the crisis (special case: Slovenia). This mistake is described in the following model (Štiblar 2018a). Macroeconomic policies in 42 leading world countries between 2008 and 2014:

Y=

a+

b1 x X1 +

b2 x X2

(ta)

(tb1)

(tb2)

KBDP =

1.21 + 0.0038 x DKRED - 0.027 x DBOG

KNEZAP =

1.41 - 0.413 x KKRED

(24.1) (2.044)

R2

F

0.19

4.70 eq1

(-2.12) 0.068 2.95 eq2

(5.11) (-1.72) DINFL =

-3.42 - 0.633 x DBOG + 5.13 x KKRED (-0.91) (-2.23)

0.16

3.73 eq3

(1.59)

where during the period 2008–2014: • faster credit growth (DKRED) and the larger budget deficit (DBOG) led to faster growth (KBDP),

46

F. ŠTIBLAR

• faster credit growth (DKRED) led to lower unemployment (KNEZAP), and • higher budget deficit (DBOG) and faster credit growth (KKRED) led to higher inflation (in the fact there was deflation). The idea of austerity, especially in the form of expansionary contraction policy measures (proposed by Alesina 2010), proved to be wrong in theory, as well as in the practical application in several countries and in its unsuccessful attempts in getting EU countries out of the great recession (Blyth 2015). The empirical analysis in this study shows that when applied as a way out of the 2008 crisis, austerity-based monetary and fiscal restrictions led to a GDP slump, an increase in unemployment, and the threat of deflation. The social consequences of such a dangerous policy are well recognized: millions of people in the world and especially in the EU were pushed into poverty and suffering, being punished for the sins of others, namely, financial and economic, political elites engaged in subprime lending. Policy measures in the 2020 COVID crisis, only 9 months old and in full expansion with a second wave of contagion at the time of analysis, rightfully abandoned fiscal austerity and monetary restrictions, so that once COVID is under control with vaccination, economic and social recovery could be faster, and the slump could be smaller, although we will come to a new normal in everyday life. The econometric analysis in this paper indicates the ways to go forward with policy measures both in economic and non-economic fields to recuperate faster and with a smaller loss of GDP. However, to be successful it is necessary that the undertaken measures last long enough and take the form of three nuclear options: to print as much money as is needed, to make as large a budget deficit as is needed, and to introduce lockdown measures that are as strong as possible, but for a shorter period. This is what we have learned from policy mistakes made during the 2008 financial crisis.

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47

2.8 Conclusion: Major Findings and Policy Suggestions This is a work in progress. Over the course of time, more data will be available for a longer period, meaning that the evaluation of COVID contagion’s impact on a country’s economic performance and social changes will be possible. That will add to understanding the role of COVID in the world, both as a cause and as a consequence of events in society. 2.8.1

Findings

For Croatia and Slovenia Differences between actual and estimated values of COVID indicators, as calculated for Slovenia and Croatia, give the way for some policy suggestions to improve their COVID situation. Variables of geographical type are impossible to change in foreseeable future, the same holds true for most demographic variables. But economic variables are easier to change in the desired direction with appropriate measures of economic policy. In fact, some signs of relations indicate the reverse causality: economic variables were already changed due to the occurrence of COVID, as in the case of forecasting lower GDP growth, higher budget deficit, higher current account deficit, etc. In both countries estimated values of COVID indicators exceeds actual numbers. (Ye ≥ Ya) for the number of tests in population and for the number of deaths relative to the number of cases. In difference to Slovenia the same holds for Croatia for the number of deaths in the population. For the other two indicators, the number of cases in population and number of cases to the number of tests, the actual number exceeds the estimated (Ya ≥ Ye) in both countries and should decline. In General The proposed model for introducing lockdown is given in its most simplified form with the intention of contributing to the systematization of everyday decision-making by authorities in each country. In fact, the model shows ex-post how decisions about lockdown are made. All four basic variables in the model could be refined (properly adjusted to specific

48

F. ŠTIBLAR

circumstances in each country): the share of GDP lost during the lockdown, number of working days in a country, value of human life and who exactly are those who lost their life due to COVID contagion. The correlation analysis indicates negative relation between tests and COVID contagion variables, positive relations of variables indicating a country generally development with COVID contagion, the insignificance of credit expansion variable, age being relevant for COVID contagion, vicinity of equator, and degree of political democracy having both negative relations with COVID contagion. The regression analysis tried to find determinants of COVID contagion in the most relevant 43 countries in the world, i.e., those producing over 90% of the global GDP. Some results are surprising, some explanatory variables are not optimally specified, some of the data used are not fully reliable, and some determinants are missing. Importantly, the regime of measures against COVID matters a lot (and differs from country to country), but consistent macro data on it is not available for each country. We introduce several variables defining the structure of society that are potentially relevant for explaining the spread of COVID. Many of them are not policy variables that can be changed as anti-COVID measures. They are included for an explanation of COVID contagion as relevant economic, demographic, geographic and political determinants in a country and as such are more or less fixed. The political democracy index was less significant and sometimes yielded surprising results in the analysis. Higher democracy according to the Economist EIU index does not guarantee lower COVID contagion as higher democracy can mean less order and supervision—both of which are needed in the war against COVID. Geographical variables are fixed and cannot be changed—that is, the geostrategic position of a country and its geographical size. However, results show that countries farther away from the equator suffered more from COVID, due to their higher general level of development which includes also more communication among (rich) people. Some demographical variables are good explicators of COVID contagion in-country, relation with others are surprisingly against common sense or not significant. The higher degree of urbanization, density, and a higher share of services in BDP increase the spread of COVID in a country, as expected. However, net migration, the unemployment ratio (ILO 2020), and the size of the population in a country did not have strong explanatory power in the analysis.

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49

The major emphasis was given to economic variables (IMF WEO 2020). Among policy variables, budget (fiscal policy) performed well, while the growth of private loans (monetary policy) and interest rates on country bonds (financial credibility of the country) were not significant explicators of COVID. It is regrettable that while fiscal stimulus has an observable variable (share of the budget deficit in GDP in 2020) which performs according to fiscal stimulus rules, the monetary variables (a latest increase of loans to the private sector, interest on government bonds) remain insignificant in most regression equations. Two reasons for that are: firstly, statistical data that comes from less reliable sources is of course not fully reliable, and secondly, additional monetary stimulus is no longer needed in 2020, as it was put in place around the world already circa 2015, based on modern monetary theory (zero interest rates, the supply of liquidity through quantitative easing). The problem is that direction of overly strong monetary expansion is wrong. Its stimulus flows directly toward financially fit customers who are able to repay loans. These are rich people in leading global companies, while channels from central banks and commercial banks to the general public and the regular enterprise sector are corked. Central bank money is going through banks in the wrong direction: instead of helping increase regular enterprise activity and/or increasing disposable income of households, which would lead to increasing demand, it is flowing to the rich and used by them for financing purchases of stocks, real estate, and cryptocurrencies. There are voices in the research community calling for a central bank direct line of supply of loans to both the public and enterprises while avoiding banks as intermediaries. With prices in both the stock exchange and real estate markets growing, such policy enables the rich to get richer. For these reasons, stock exchange indexes are achieving new record highs, real estate prices and values of cryptocurrencies are growing, despite the overall significant decline of economic activity due to the COVID crisis. An increase in GDP per capita does not diminish the spread of COVID in a country, thus supporting the idea that COVID is a disease of rich people in rich countries, who communicate more than others. And, decreasing inequality (Stiglitz 2012; Piketty 2015) would decrease the spread of COVID. Policy Suggestions Nothing can be done regarding fixed geographic determinants and it is difficult to change the political system in the foreseeable future. Among

50

F. ŠTIBLAR

demographic determinants of COVID, short-term policy actions cannot decrease the average age in a country’s population, their number, and their density. Maybe something can be done in the middle term to decrease unemployment and decrease the urbanization level. Nuclear fiscal and nuclear monetary options (stimulating the economy as much as needed) are appropriate short-term economic policy measures when complemented with other anti-COVID measures such as short-term full lockdown of the country. Moreover, reducing inequality (Piketty 2015; Stiglitz 2012) and providing more money for hospitals, centers for the elderly, and kindergartens would be desirable would also help to improve COVID situation.

Notes 1. Normally, losses to the entire environment in a country includes also demographic, geographic, political and some other elements. For the sake of simplicity, these are not included here. 2. The number e10 million is taken from personal insurance tables, while calculated daily economic loss is e200 million (50 billion/250 working days). 3. At the end of November 2020 this number is 40 on average for Slovenia— that is, twice the calculated number in the model, which means that lockdown is justified.

Appendix List of analyzed countries (Source The Economist ) 1. USA 2. China 3. Japan 4. UK 5. Canada 6. Austria 7. Belgium 8. France 9. Germany 10. Greece 11. Italy 12. Netherlands

23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34.

Turkey Australia India Indonesia Malaysia Pakistan Philippines Singapore South Korea Taiwan Thailand Argentina (continued)

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51

(continued) 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

Spain Slovenia Croatia Czechia Denmark Norway Poland Russia Sweden Switzerland

35. 36. 37. 38. 39. 40. 41. 42. 43.

Brazil Chile Colombia Mexico Peru Egypt Israel Saudi Arabia South Africa

References Alesina, A. 2010. Fiscal Adjustment: Lesson from History. Ecofin, Madrid, April. Blanchard, O., and D. Leigh. 2011. Four Hard Truths. IMF Direct, December. Blyth, M. 2015. Austerity: Oxford UP, UK, December 2012, revised version. Corsetti, G. et al. 2012. Sovereign Risk, Fiscal Policy and Macroeconomic Stability. IMF Working Paper 33. Guajardo, J., D. Leigh, and A. Pescatori. 2011. Expansionary Austerity: New International Evidence. IMF Working Paper 11/158, July. ILO Interim Report. 2020. Geneva, September. IMF. 2020. World Economic Outlook, Washington DC, October. Krugman, P. 2013. The ECB and the Austerity Trap, Opinion Pages, NYT, 3.31.2013. Piketty, T. 2015. The Economics of Inequality, Harvard UP. Rodrik, D. 2012. The Globalization Paradox, US, 2012. Rogoff, K. S., and C. Reinhart. 2009. This Time Is Different: Eight Centuries of Financial Folly, Nahal Maryland House. Shiller, R. 2009. Irrational Exuberance, Broadway Books. Štiblar, F. 2009. The Impact of the Global Crisis on Montenegro and the Western Balkans, CBCG, Podgorica, June. Štiblar, F. 2015a. Introduction of Euro in Slovenia. In Financialization in South East Europe, ed. D. Radoševi´c and K. Vidoševi´c. Germany: Peter Lang. Štiblar, F. 2015b. Škodljivost zategovanja pasu, GG, EIPF, Ljubljana. Štiblar, F. 2018a. Damaging Austerity Policies. In Global Economic Modeling, A Volume in Honor of L. R. Klein, ed. Peter Pauly, 314–332. Toronto: World Scientific. Štiblar, F. 2018b. Kako do dobre banke, GV Založba, Ljubljana, May. Štiblar, F. 2020. Zunanji pogoji gospodarjenja, ZBS, Ljubljana, October.

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Stiglitz, J. 2012. The Price of Inequality, Norton, USA, 3/2012. UN. 2020. Sustainable Development Goals, Report 2020, Financial Times, The Economist, different issues.

Data Sources ILO, SURS, EIPF, BS, UMAR, Eurostat, EBRD, IMF, OECD, The World Bank Data, Worldometer Trading Economics, EIU. The Economics of Inequality, Harvard UP, 2015

CHAPTER 3

Short-Term Impact of COVID-19 in the Clusters of EU Market Economies Vivien Czeczeli, Pál Péter Kolozsi, Gábor Kutasi, and Ádám Marton

3.1

Introduction

The pandemic caused by the COVID-19 virus and the public health have fundamentally determined the economic policy measures taken in response in 2020. A decline in economic activity and the fear of declining

An earlier and more detailed version of this paper has appeared in Public Finance Quarterly (Czeczeli et al. 2020b). V. Czeczeli · P. P. Kolozsi (B) · G. Kutasi · Á. Marton University of Public Service, Research Institute of Competitiveness and Economy, Budapest, Hungary e-mail: [email protected] V. Czeczeli e-mail: [email protected] G. Kutasi e-mail: [email protected]

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_3

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jobs and income security have been common in all affected countries, but its extent, process and structure have shown certain variations. The 2008 global economic crisis gives rise to the assumption that the condition and economic preparedness of individual countries are decisive factors for the process of a crisis. The experience of preceding economic and financial crises was that initial macroeconomic conditions were deterministic in the impact of a crisis on a market economy. Berkmen et al. (2012) concluded that more leveraged domestic financial systems, stronger credit growth, and more short-term debt tended the countries to suffer a larger effect on economic activity in a financial crisis. In the analysis prevailed by Frankel and Saravelos (2012), the central bank reserves and past movements in the real exchange rate were the two leading indicators in the crisis performance. Feldkircher (2014) found empirical evidence that precrisis credit growth shaped the economic response in 2008. Cecchetti et al. (2011) spotlighted the twofold aspect of determinants. They found that both vulnerability and luck can determine the crisis impact. They concluded that less crisis damage occurred in countries with a bettercapitalized banking sector, lower loan-to-deposit ratios, a current account surplus, high foreign exchange reserves, and low levels and growth rates of private sector credit-to-GDP, but these economies also featured a low level of financial openness and less exposure to US creditors, suggesting that good luck played role in their 2008–2009 performance. Cuaresma and Feldkircher (2012) strengthen the particularity of pre-crisis macroeconomic determinants, their results demonstrated that „economic growth above potential before the crisis coupled with external disequilibria as well as financial openness were particularly important mechanisms that increased” the output loss in the crisis. The following analysis wants to answer this question: Can the economic differences associated with the coronavirus be related to the socio-economic situation of a country at the outbreak of the crisis, and can deviations be detected in the short-term output variables of the economic crisis based on such vulnerabilities? In Europe, the economic crisis has been managed with a mix of basically similar economic policies (Czeczeli et al. 2020a), so we aim to explore phenomena that can be related to the grouping of countries.

Á. Marton e-mail: [email protected]

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SHORT-TERM IMPACT OF COVID-19 IN THE CLUSTERS …

55

Our study focuses on 25 European countries and is based on multidimensional clustering, in which the basis of group formation is the state of public finances (public debt and deficit), income distribution within society (social expenditures in the state budget and GINI indicator), external economic processes (export share), as well as exposure to tourism as a sector requiring mobility. The behaviour of the clusters thus created is analysed using four short-term trend indicators: labour mobility, unemployment, industrial production and risk spread data. In the last step of the analysis, it is examined to what extent the clusters moved in parallel in the short-term period before the crisis, and then to what extent they moved apart from one another, or possibly experienced similar trends, during the crisis. The position in terms of each variable is evaluated in the months before and during the crisis by means of standard deviation and correlation calculation. Subsequently, the co-movement of crisis indicators and the resulting trends during the crisis period are analysed. Our initial assumption is that there is a correlation between economic behaviour during the crisis and the state of public finances, income distribution and external vulnerabilities prior to the outbreak of the crisis. The current study is to be the initial element of a complex analysis project that aims to understand the dynamics, correlations and interactions of the coronavirus pandemic. It is essentially relevant for our analysis that, in many cases, the data and time series necessary for drawing durable conclusions in-depth are not yet available, thus, our results can be considered as a first estimate. In the context of certain impacts, further research is needed, but the correlations explored in this study may also help to define the direction of future research activities.

3.2

Theoretical Background

Over the past decade, there has been a lively theoretical debate about the role of economic policy in connection with the 2008 global financial crisis, from which the Austrian school (von Hayek 1995) and the Keynesian theory (Keynes 1936) emerged victorious with their intervention and stimulation approaches (Szepesi 2013; Lentner and Kolozsi 2019; Móczár 2010; Csaba 2009). This became a cornerstone for crisis management and the rethinking of models, while the non-Keynesian fiscal policy based on Friedman’s monetarist approach (Friedman 1977), stimulating consumption through austerity (Feldstein 1982; Alesina and Perotti 1995; Perotti et al. 1998; Schucknecht and Tanzi 2005; Benczes 2008), has been pushed out of the forefront of economic policy.

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One of the characteristic features of the treatment of the 2020 coronavirus pandemic have been that, in contrast to 2008, as a result of the above, the theoretical search for appropriate methods did not delay interventions this time, the activist perception of the state has clearly remained dominant in the economic approaches. Still, fiscal policy and economic theory have faced new challenges. The restrictions introduced due to the coronavirus are clearly to be interpreted as a drop in demand and thus as a negative demand shock. How is a demand shock classically manifested in economic thinking? As a typical interpretation, consumption is lower at the same price level, and aggregate demand is lower at the same interest rate level. In such cases, the usual fiscal step is to replace lost private demand (household consumption, private investment) with higher government consumption, from reserves or from credit. Various budgetary multiplicator calculations also provide a hint regarding the appropriate level of expenditure increase and tax reduction in such situations. However, in the case of the coronavirus, the process of the exogenous demand shock is different: Households would be very happy to consume and companies would be ready to invest, but restrictions by the state and caution impose a physical barrier to accessing services and products. Thus, price and interest rate sensitivity do not change, only the consumed quantity is maximised, like in the case of the classic quantitative quota, only that demand is limited, rather than supply. Fiscal policy is also not supposed to simply make up for lost demand, as it is in fact suppressed demand in this case. On the one hand, in the short term, the problem of time inconsistency must be managed, meaning that capacities or, from another perspective, sources of income must be, actually kept alive in order that demand can prevail again after the cancellation of lockdown. On the other hand, in the long term, the state also has to contribute to the restructuring of the economy in order to avoid, to some extent, a repeated break-in demand. If we accept that in the event of an epidemic, the demand shock works in the special way already described, then the Lucas critique of the ineffectiveness of economic policy (Lucas 1976) can also be ignored as the economy is not in a natural, long-term constant (stationary) the equilibrium state of supply, but in a lower production level. In this situation, it would not be able to return to this level on its own on a market basis until the pandemic comes to an end. As the bankruptcy of companies, the loss of jobs and, ultimately, capacity drops and recoveries are not regulated by movements in supply and demand

3

SHORT-TERM IMPACT OF COVID-19 IN THE CLUSTERS …

57

but by an exogenous factor, therefore, if the government leaves capacity owners alone, the economy may not be able to return to the original level of long-term equilibrium supply. That is why fiscal activism cannot be considered ineffective, even at a theoretical level. At the same time, the COVID-19 crisis cannot be interpreted narrowly, merely from the aspect of a demand shock. The crisis describes an unusual combination of supply and demand shocks. In the modern monetary system, this has been the first economic shock simultaneously reducing both supply and demand (Baqaee-Farhi 2020; Shastri 2020; Bekaert et al. 2020). Therefore, negative demand-side impacts may be amplified by supply-side weaknesses. A sudden stop in manufacturing activities, along with the specificities of global value chains, deserve special attention in the current situation. Failing that, the absence of inputs may lead to a series of factory closures, which could also have spill-over effects in areas less affected by the virus. Production processes may collapse in countries that are more exposed to infected regions. Apart from production, the supply side is also affected by the reduction in labour supply (UNIDO 2020). According to Bekaert et al. (2020), the distinction between supply and demand shocks is also important because the crisis management of negative demand and supply shocks requires very different forms on the fiscal and monetary sides. Aggregate demand shocks are defined as ones that guide inflation and real activity in opposite directions. In contrast, demand shocks guide inflation and real activity in the same direction. The extent and nature of the shocks will be determined by developments in the coronavirus pandemic. In the event of rapid decay, the supply shock will disappear quickly and production will recover soon. The creation of the clusters presented in this study is justified by the fact that market economies and fiscal policies do not operate in exactly the same form, with identical institutions and processes (Hall and Soskice 2001; Farkas 2017). The approach separating European social models has already started to recognise this, which can also be regarded as a kind of classification of fiscal models as it classifies the quality of public taxes and expenditures and the level of the balance of the budget as distinguishing features (Boeri 2002; Boeri and Baldi 2005; Sapir 2005; Schubert and Martens 2005). The following cluster analysis is based on a similar approach, aiming to make a distinction between economic models relevant to the crisis in the context of European market economies.

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3.3

Applied Methodology and Data Sources

Studies based on the cluster analysis procedure aim to establish an initial framework. This group formation maps out the economic and social conditions at the end of 2019 in certain Member States of the European Union.1 It presents the economic situation that was characteristic of each country when the SARS-CoV-2 (COVID-19) virus, and the resulting economic impacts, reached a given country, as well as the resulting economic effects. Cluster analysis forms the basis of the analyses performed. 3.3.1

Cluster Analysis

From among the grouping procedures, one of the most popular econometric methods is cluster analysis, which results in homogeneous groups based on various variables. The 27 European Union Member States2 under review can be considered a small sample, which led us to use hierarchical clustering on the database created. Grouping was based on 6 variables. Two of the variables represent fiscal policy conditions, two represent the exposure of each economy to tourism and exports, and two represent the social situation. Each variable involved in the analysis can be measured on a metric measurement scale. Accordingly, the Ward procedure was used for clustering. Similarities between individual elements can be mapped out based on distance in the Ward procedure (Simon 2006, Sajtos and Mitev 2007). According to the survey conducted, Malta and Lithuania can be regarded as countries with outliers, so, for methodological reasons, these Member States may not be included in the database providing a basis for the cluster analysis.3 A weak correlation can be detected between the variables involved in the analysis based on Pearson’s correlation coefficient, and, because these are macroeconomic variables, from a methodological perspective, cluster analysis can be performed on those variables. Accordingly, in addition to the parameters described, the distance matrix of countries can be established, and individual clusters can be delimited. After the clusters have been created, the economic indicators measured during the pandemic will be analysed in order to reveal differences and similarities between the groups of countries. During the analysis process, using data from the period between March–June 2020 for each cluster, a standard deviation and, for the co-movement of individual indicators,

3

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59

a correlation are calculated, and R 2 is also determined as an indicator for the strength of correlation. When revealing short-term impacts, the analysis approaches from four aspects. The pandemic and the restrictions were channelled into economic activity by changes in mobility, so this is the starting point. The result is a change in industrial production, as a measure of the degree of contraction in economic activity. This will be followed by developments in unemployment and changes in risk spread, reflecting financial risks. 3.3.2

Data

The cluster analysis was aimed to map out, as clearly as possible, the situation at the end of 2019 (in order to be able to study the short-term effects of the COVID-19 pandemic in a complex manner, both between and within clusters). Nevertheless, the data and analysis projected for that period would not reflect the relevant macroeconomic relations and situation. Accordingly, trends in the processes of recent years were mapped out using various simple statistical methods for each variable. During the analyses, 2016 was used as a baseline year, while in the case of data for the year under review, a bottleneck was created by the availability of data in international databases. (In the case of indicators reflecting the social and societal situation, the latest data set available for the whole sample is represented by the values at the end of 2018.) The exact description of the variables may be as follows: • average change in the balance of general government deficit (−) and surplus (+) over the period 2016–2019—percentage; • in the case of general government gross debt, the difference between 2016 and 2019—percentage points; • the difference of exports of goods and services, % of GDP between 2016 and 2019—percentage points; • Travel and tourism total contribution to GDP, average of year-end data between 2016 and 2018—percentage; • Share of COFOG—GF10—Social protection expenditures, threeyear average of year-end data between 2016 and 2018—percentage; • GINI indicator, three-year average of year-end data between 2016 and 2018—percentage.

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The analysis of clusters formed on the basis of historical data was continued using four indicators suitable for the identification of shortterm impacts: • industrial production,4 volume index of production, index 2015 = 100, change was included in the calculations—percentage, • worker mobility, average of daily data (based on Google COVID-19 community mobility reports), as a percentage of the baseline value, • unemployment rate—seasonally adjusted data, not calendar adjusted data, relative to the working age population—percentage, • government bond spreads—percentage point. Industrial production data on a monthly basis were identified using the relevant Eurostat indicator, which includes the fields of mining, quarrying, processing industry, electricity, gas, steam supply and air conditioning. The data series of industrial production is also a proxy indicator of developments in GDP, which allows monthly comparison with other data, as opposed to GDP change estimated by statistical offices over quarterly periods. The change in mobility was quantified with the help of the Google Community Mobility database. The data available here show to what extent people’s ‘movement’ deviates from the typical baseline value. The unemployment rate shows the ratio of the unemployed to the working-age population as a percentage, based on the Eurostat database. Government bond spreads come from the Bloomberg database and show the values of the premiums of five-year bonds relative to German benchmark data. In the second part of the empirical analysis, these indicators are used to identify the effects representing the developments of the months most severely affected since the beginning of the pandemic. Our aim is to examine, based on the country groups created, whether any pattern can be identified in the outcome variables of the crisis caused by the pandemic based on the clusters arranged according to the economic, fiscal and social state before the crisis. In addition to providing a detailed picture of immediate economic responses that have been given in each country, the research identifies whether there is a correlation between the initial economic situation and the economic developments resulting from the shock caused by the pandemic. Detailed descriptive statistical data for each variable are included in Table 3.1.

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Table 3.1 Summary table of variables included in the analysis extended with descriptive statistics Variable

Average

Standard deviation

Fiscal variables Average change of −0.71 1.4 balance of the budget (as a percentage of GDP) −6.58 4.48 Change in gross consolidated public debt ratio Variables representing economic exposure Change in export 1.79 3.15 share Travel and tourism 11.19 5.52 average, total contribution to GDP Indicators of societal and social situation 17.4 3.67 Average change in the rate of social expenditures (COFOG—GF10, as a percentage of GDP) Average of the 29.79 3.92 GINI indicator Variables describing short-term effects Industrial 100.66 14.5 production −35.97 13.65 Mobility of people to work Unemployment rate Government bond

6.24 1.75

3.07 2.53

Minimum

−3.16

−15

−4.88 4.52

Maximum

Data source

1.44

Eurostat

0.1

Eurostat

7.12

World Bank

25

World Bank

12.1

24.7

Eurostat

22.8

39.17

Eurostat

59.4 −68.6 2 0.01

132.7

Eurostat

−13.67

Google Community Mobility Eurostat Bloomberg

16.2 13.17

In the context of spreads, these descriptive statistics were based on the values of 2 January and 7 May 2020

Due to differences in scale size, the variables included in the cluster were standardised at z value z = x−μ σ . The variables developed in the above manner provide a picture of economic and social relations in recent years in each country, and, furthermore, they reflect the state before the economic downturn caused by the lockdown due to the crisis.

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3.4 3.4.1

Results

The Result of Clustering

The number of clusters can be established in different ways: based on the relative size of clusters, the elbow criterion and the distances (Sajtos and Mitev 2007). The individual clusters were delimited taking all these considerations into account, and in an endeavour to form as homogeneous country groups as possible. The results of the studies are illustrated in the dendogram in Fig. 3.1.

Fig. 3.1 Dendogram of the results of the cluster analysis (25 Member States) (Source Own figure using the SPSS program)

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Based on the dendogram, it is possible to form several clusters with different numbers and numbers of items. In order to form the appropriate groups, it is necessary to examine the standard deviation of each group of countries to be formed in relation to the total standard deviation, i.e. the homogeneous nature of each cluster created. Based on the analyses, the version including seven clusters can be considered the most homogeneous, based on which we created seven groups. The assignment of the countries to the clusters is shown in Table 3.2. As far as item numbers are concerned, groups of almost identical size, including 3, 4 and in one case 5 countries, were created. The clusters created are clearly separated from one another and reflect the macroeconomic and social situation in recent years. • Examining the differences between the individual clusters, it can be concluded that a surplus regarding the average balance of the budget was accumulated only by socially sensitive countries and ones with a decreasing export exposure. The largest deficit was achieved by the countries of the debt-reducing and the relatively significant deficitincreasing cluster. • This trend can also be observed in the development of public debt, because debt-reducing countries have the lowest debt reduction in the period under review. Fiscal discipline and the existence of structural imbalances may also play a significant role in this respect in the Table 3.2 The clusters created

Cluster 1: Not exposed to tourism

Belgium, Netherlands, Ireland, Poland

Cluster 2: Debt-free Cluster 3: Decreasing export exposure Cluster 4: Socially sensitive

Bulgaria, Estonia, Latvia Czech Republic, Hungary, Slovakia Denmark, Finland, Germany, Sweden Cyprus, Greece, Croatia United Kingdom, France, Italy, Romania, Spain Austria, Portugal, Slovenia

Cluster 5: Tourism-dependent Cluster 6: Debt-reducing Cluster 7: Deficit-increasing

Source Own calculation Note The designations are to be understood as relative to other groups in each case

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given group of countries. In contrast, compared to debt-reducing countries, average debt reduction in the group not exposed to tourism increased nearly tenfold, while in the initial deficit-increasing cluster it increased nearly 11-fold between 2016 and 2019. In the case of the indicator reflecting the change in export share, no significant differences can be identified; nevertheless, debt-free countries and ones with a decreasing export exposure, which also produced the highest per capita GDP growth, recorded a drop in export growth. However, this requires a detailed examination in order to be able to identify possible temporary changes and longterm trends. (This is done when identifying, characterising trends within each cluster). A review of the indicator reflecting the contribution of the travel and tourism sector to GDP also clearly reveals that the highest exposure is characteristic of countries depending on tourism. The weight of the tourism industry is not negligible either in the case of Italy, Spain, the United Kingdom and France from Cluster 6 and countries of Cluster 7, i.e. Austria, Portugal and Slovenia. In terms of social expenditure, there is no significant difference between the groups of countries. The countries of the debt-free group deviate significantly from the overall sample, in a negative direction. Similarly, there is no significant difference in the GINI indicators. Two additional variables were also included in the analysis, which will also be examined during the short-term cluster analysis. Based on year-end 2019 data, it can be concluded that unemployment rates are moderate (around 5% or lower) for most clusters, but the tourism-dependent and debt-reducing clusters are significantly different. For both clusters, cluster averages are considerably increased by indicators from southern European countries with structural problems and high youth unemployment like Greece (17.3%), Italy (10%) or Spain (14.1%). An analysis of per capita GDP growth shows that newly acceded Member States have higher growth rates (debt-free and with a decreasing export exposure) than the socially sensitive group with countries that are long-established members of the EU. If individual clusters are examined by groups of variables, then the differences within each cluster can also be identified.

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When forming the groups, fiscal variables can be considered key indicators in three clusters (Fig. 3.2). These three clusters are the following: tourism-dependent, debt-reducing and deficit-increasing. The examination of all Member States makes it clear that the public debt ratio decreased everywhere between 2016 and 2019, except for two countries. In France, it increased by 0.1 percentage point, while in Italy it remained unchanged. However, taking the average development of budget balances into consideration, a more heterogeneous pattern emerges. In the period under review, partly as a positive consequence of economic trends, the average balance of the budget exceeded the Maastricht threshold of 3% only in Italy and Spain. Furthermore, 8 member states experienced a surplus. This category includes the socially sensitive group, with the exception of Finland, which is characterised by the effects of fiscal discipline and regulations.5 When forming the groups, the indicators describing external exposure became key group-forming criteria for 3 groups of countries: debt-free, tourism-dependent, and deficit-increasing (see Fig. 3.3). From among the indicators describing external exposure, compared to the baseline year of 2016, a slight reduction in the change in export share is shown by the group of debt-free countries and those with a decreasing export exposure, as well as Romania. In the case of Estonia, the Czech Republic 2 IT

FR -4

-3 RO

0 UK

-2

0

1

EE-2

ES

%

-1

FI

SK

-4

DK

-6

BE

debt-reducing

LA

PL

HR CY

-8

HU -10

SI PT

percentage point

-14 IE

CZ SE BG

DE

dependent on tourism

AT -12

deficitincreasing

2

EL

NL

-16

Fig. 3.2 Average change in public debt (horizontal axis) and in balance of the budget (vertical axis) (Source Own figure based on Eurostat data)

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V. CZECZELI ET AL. 30

25

dependent on tourism

HR CY

decreasing export exposure %

EE

20

EL PT

15

ES

AT IT

10

BG LA

CZHU

DE

SI UK

SE

FR DK

SK RO 5

BE

NL

deficitincreasing

FI IE

PL

0 -6

-4

-2

0

2

4

6

8

percentage point

Fig. 3.3 Travel and tourism average, total contribution to GDP (vertical axis), and changes in export share (horizontal axis) (Source Own figure based on World Bank data)

and Hungary, which show the largest reduction, this change describes a typical trend for the last few years. In these countries, an ever lower share of the national income is generated by export activities. In many cases (e.g. Hungary), the share of export activities is still significant, but there is a gradual fall in the previously significant trade balance surplus. In other affected countries, including Romania, the development of export share shows a relatively stable picture, with minor fluctuations. Looking at the countries of the debt-reducing group, the increase in export share is also moderate. In these countries, the contribution of exports to the GDP is approximately 30%, which is quite low, meaning that dependence on foreign markets (foreign demand) is more moderate. In contrast, the group not exposed to tourism typically has a high export share, so their sales revenues show a higher dependence on the economic situation of other countries. The tourism sector represents a major source of employment, government revenues and foreign currency revenues for a number of developed and developing countries. Since the virus virtually stopped all tourismrelated activities, many countries have experienced a significant decline in GDP as well as a large increase in the unemployment rate. The group of countries most sensitive to revenues from tourism are tourism-dependent,

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67

debt-free and deficit-increasing countries. However, the countries not exposed to tourism and those with a decreasing export exposure are much less exposed to revenues from travel and tourism. The GINI indicator, expressing income inequality, is the largest in the debt-free countries, meaning that inequality is the highest here (see Fig. 3.4). The least favourable value was recorded in Bulgaria. As another characteristic of the country group, the share of social expenditures is the lowest here. As a result, the group of debt-free countries includes those with the highest inequality, as opposed to the lowest share of social expenditures. Inequality is the lowest in countries with a decreasing export exposure. An important contribution to this fact is that Slovakia and the Czech Republic have the most favourable values among the countries reviewed. Socially sensitive countries, the majority of which follow the model of the welfare state, as well as Germany, which can be described as a social market economy, and France, spend the largest amounts on social expenditures. The former has a ratio of 12%, while in the case of latter, the value of the indicator is more than 20%. This means that the public care system 40 BG

debt-free

38 36 LA

34 32

RO

ES UK

EE CY

% 30

HR PL

28

ITEL

PT

DE

IE

FR

HU NL

SE

26

DK

AT

BE CZ

24

FI

SI SK

22 20 10

12

14

16

18

20

22

24

26

%

Fig. 3.4 Average development of social expenditure (horizontal axis) and the GINI indicator (vertical axis) (Source Own figure based on Eurostat data)

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and the social safety net are characterised by very different sizes in the individual countries. Based on the average, minimum and maximum values of the clusterforming variables illustrated in the group of Fig. 3.5 (balance of a. Balance of the budget, as a percentage of GDP

b. Public debt, as a percentage of GDP

c. GINI indicator 40

3 2 1 0 -1 -2 -3 -4 -5

200 35

150 30

100 25

50 0

max

min

max

average

d. Social expenditures, as a percentage of GDP

20

1. 2. 3. 4. 5. 6. 7.

1. 2. 3. 4. 5. 6. 7.

min

1. 2. 3. 4. 5. 6. 7.

max

average

e. Tourism, as a percentage of GDP

26

30

24

25

min

average

f. Export share, as a percentage of GDP 140 120

22 20

100

15

80

20 18

60

16

10 40

14 5

12 10

20 0

0 1. 2. 3. 4. 5. 6. 7.

max

min

average

1. 2. 3. 4. 5. 6. 7. max

min

average

1. 2. 3. 4. 5. 6. 7. max

min

átlag

Fig. 3.5 Group behaviour of cluster-forming variables, rate of variable (vertical axis), cluster number (horizontal axis) a. Balance of the budget, as a percentage of GDP. b. Public debt, as a percentage of GDP. c. GINI indicator. d. Social expenditures, as a percentage of GDP. e. Tourism, as a percentage of GDP. f. Export share, as a percentage of GDP (Source Own edited)

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69

the budget, public debt, GINI indicator, social expenditures, share of tourism, export share), the following conclusions can be drawn. • As far as the balance of the budget is concerned, it is Cluster 6 (debtreducing countries) that differs the most with its higher deficit. From the point of view of budget balance averages, it is difficult to distinguish between the other six clusters. In terms of homogeneity, it is debt-reducing, debt-free (Cluster 2) and deficit-increasing (Cluster 7) countries that have a very strong internal coherence, and the three groups also take positions that can be easily distinguished from one another. • Regarding public debt, countries with a decreasing export exposure (group 3) and socially sensitive ones (group 4) take almost identical positions with respect to both cluster average and low standard deviation (i.e. homogeneous composition). A similar observation can be made when comparing the averages of the debt-reducing and deficit-increasing groups, while the extreme values show a heterogeneous composition. Cluster 2, made up of homogeneous debt-free countries, is markedly different from the others with its low debt ratio. • In the case of the GINI indicator, describing social exposure, the non-tourism-dependent Cluster 1, the socially sensitive and the deficit-increasing countries produce similar averages, a distinction can only be made between them based on the group extremes. The other clusters are different from each other in terms of average, but it is only the non-tourism-dependent cluster and the tourismdependent cluster (Cluster 5) that can be considered relatively homogeneous. There are marked differences in terms of average social expenditure. Only the non-tourism-dependent cluster and the tourism-dependent countries have similar averages. However, the clusters are characterised by very strong internal heterogeneity. Only the debt-free countries are homogeneous, and only the deficitincreasing ones have a relatively small difference between their extreme values. • As far as exposure to tourism is concerned, most clusters are homogeneous or show a relatively small difference between extreme values (except debt-reducers), and their averages can be distinguished from one another. There is little overlap between the clusters in terms of average export share as well; it is only countries not exposed

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to tourism and those with a decreasing export exposure that have nearly identical averages. As regards homogeneity, the average is a good indicator of debt-free, tourism-dependent and socially sensitive countries, as well as debt-reducing ones. 3.4.2

Behaviour of Clusters During the First Wave of the Virus

Based on the variation data detailed in Table 3.3, the clusters cannot be described as nearly homogeneous in terms of the time series characterising the four crisis periods. In some months and for some indicators, however, certain clusters are well characterised by the cluster average. Examples include the change in industrial production for Cluster 1 in April, Clusters

March April May June March April Unemployment May

Change in government bond spread

Cluster 7: Deficitincreasing

Cluster 6: Debtreducing

Cluster 5: Tourismdependent

Cluster 4: Socially sensitive

Cluster 3: Decreasing export exposure

7.05 4.02 8.80 8.71 1.33 1.29 1.33

6.90 7.18 11.16 8.71 1.74 2.16 2.60

6.77 5.26 3.48 0.67 1.86 2.10 2.06

10.81 16.81 12.85 9.11 1.53 1.85 1.93

5.52 9.32 12.07 1.34 4.47 4.18 4.35

10.39 6.69 1.97 3.27 4.23 4.58 4.48

9.75 10.38 14.03 16.55 1.00 0.85 0.64

June March April May June

1.14 5.35 11.02 11.88 10.54

4.03 4.48 2.89 1.39 4.65

2.83 1.71 4.48 6.68 6.79

2.13 5.87 6.39 3.26 7.13

0.71 4.86 1.25 1.71 4.67

4.45 10.76 7.52 9.74 9.68

1.11 1.24 5.49 6.98 5.65

2 January - 5 May 2020

0.38

0.11

0.69

0.07

0.55

0.44

0.29

Change in industrial production

Mobility

Cluster 2: Debt-free

Cluster 1: Not exposed to tourism

Table 3.3 Standard deviation of indicators characterising the crisis period by cluster

Note relatively low standard deviation is coloured Source own calculation

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3 and 6 in May, or, in addition to these two, Cluster 5 in June. In the case of unemployment, there are clusters in March and April, whose countries hold together within the group, with the exception of Clusters 5 and 6. In terms of mobility, however, only the April data of Clusters 2 and 5 can be regarded as nearly homogeneous, while in the case of the government bond spread, Clusters 2 and 4 behave like clusters. Based on the analysis of the changes illustrated by the group of Fig. 3.6, from the point of view of examining industrial production in the period before the crisis, individual cluster averages varied from 105 a. Development of industrial production in the four months before the crisis (November 2019 - February 2020) and during the crisis (March-June 2020) 145

b. Development of unemployment rate in the four months before the crisis (November 2019 - February 2020) and during the crisis (March-June 2020) 18.0

135

16.0

125 115

14.0

105

12.0

95

10.0

85

8.0

75

6.0

65

4.0

Max (%)

Min (%)

average (%)

2.0 0.0 1. (before) 1. (during) 2. (before) 2. (during) 3. (before) 3. (during) 4. (before) 4. (during) 5. (before) 5. (during) 6. (before) 6. (during) 7. (before) 7. (during)

1. (before) 1. (during) 2. (before) 2. (during) 3. (before) 3. (during) 4. (before) 4. (during) 5. (before) 5. (during) 6. (before) 6. (during) 7. (before) 7. (during)

55

Max (%)

Min (%)

average (%)

Fig. 3.6 Group behaviour of variables indicating a crisis, rate of variable (vertical axis), cluster number (horizontal axis) a. Development of industrial production in the four months before the crisis (November 2019–February 2020) and during the crisis (March–June 2020) b. Development of unemployment rate in the four months before the crisis (November 2019–February 2020) and during the crisis (March–June 2020) c. Workforce mobility in the period before the crisis (15–29 February 2020) and during the crisis (March-June 2020) d. Government bond yields in the period before the crisis (2 January 2020) and during the crisis (7 May 2020) (Source Own edited based on data from Eurostat, Google Community Mobility, Bloomberg Note Horizontal axis: 1. not exposed to tourism, 2. debt-free, 3. decreasing export exposure, 4. socially sensitive, 5. tourism-dependent, 6. debt-reducing, 7. deficit-increasing)

V. CZECZELI ET AL.

c. Workforce mobility in the period before the crisis (15-29 February 2020) and during the crisis (March-June 2020)

d. Government bond yields in the period before the crisis (2 January 2020) and during the crisis (7 May 2020) 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

60 40 20 0 -20 -40 -60 -80 1. (before) 1. (during) 2. (before) 2. (during) 3. (before) 3. (during) 4. (before) 4. (during) 5. (before) 5. (during) 6. (before) 6. (during) 7. (before) 7. (during)

-100

Max (%)

Min (%)

average (%)

1. (before) 1. (during) 2. (before) 2. (during) 3. (before) 3. (during) 4. (before) 4. (during) 5. (before) 5. (during) 6. (before) 6. (during) 7. (before) 7. (during)

72

Max (%)

Min (%)

average (%)

Fig. 3.6 (continued)

to 115%, which assumes a relatively homogeneous state. Within the clusters, the debt-free and debt-reducing countries, as well as those with a decreasing export exposure can be considered homogeneous, while the non-tourism-dependent and tourism-dependent groups are characterised by greater fluctuations. During the period of the crisis, however, countries show larger variations within a group. In all clusters, industrial production decreased to a different extent. As for the averages, the reduction of the indicator was smaller in the group of non-tourism-dependent, debt-free, socially sensitive and tourism-dependent countries, and it is especially the debt-free and socially sensitive groups where the change in the minimum value lowered the average. In the case of the other clusters created, the degree of decline was higher. As far as the unemployment indicator is concerned, a more heterogeneous pattern emerged between the individual clusters even in the pre-crisis period. The tourism-dependent and debt-reducing countries had considerably higher average unemployment rates than the other country groups, but this can be attributed to the exceptionally high outlier values. The crisis did not result in higher-than-average unemployment in most of the countries; however, the maximum values shifted, especially in the group of debt-free countries. Furthermore, in the tourism-dependent countries, the maximum value even shows a drop. In addition, the difference in extreme values did not change significantly.

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Workforce mobility shows the most heterogeneous picture before and after the crisis. Cluster averages show similar reductions from similar levels. As another common phenomenon, the difference between the extreme values of the clusters has increased sharply. Regarding the risk spread on government bond yields, there has been a general increase, but the degree thereof showed significant differences. While the risk premium remained stable in the countries not exposed to tourism, average interest rate premiums in debt-free, tourism-dependent and deficit-increasing countries rose relatively sharply. For the latter two clusters, homogeneity also fell significantly, as shown by the difference in extreme values. Correlation data (see Table 3.4) suggest that there is no relevant statistical correlation between unemployment and change in industrial production (compared to the same period of the previous year). Based on correlation data and the minimum value of R2 describing the closeness of the relationship, unemployment is not closely related to the decline in mobility, either. Therefore, it is not relevant to examine the co-movement of these indicators. However, it is justified to examine the relationship between industrial production and mobility, as the correlation indicator between the two is 0.545, and R2 , describing the strength of fit of the linear trend function, explains the relationship between the two with a two-digit figure (28.6%). Therefore, the relationship between these two values will be analysed below by cluster. In the case of the risk spread of government bonds, the difference between 2 January and 5 May 2020 was taken into account, so correlation with the April data, before 5 May, was calculated for the other data. No co-movement can be detected with unemployment. There is Table 3.4 Correlations and R 2 values for the whole set of countries

R2 correlation

Change in industrial production and unemployment (March–June)

Change in industrial production and mobility (March–June)

Unemployment and mobility (March–June)

Change in industrial production and spread in Aprila

Change in mobility and spread in Aprila

0.001565 −0.03956

0.286013 0.534802

0.037504 −0.19366

0.005501 0.074167

0.086472 −0.29406

Source Own calculation Note a change in government bond spread (2 January–5 May 2020)

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a minimum correlation with industrial production, while R2 has almost zero explanatory power. It is only the reverse co-movement compared to the drop in mobility that deserves special attention (correlation: –0.294; R 2 : 0.0865). The group of Fig. 3.7 shows a set of graphs describing industrial production and mobility: in all clusters, the drop in mobility occurred in parallel with the slowdown in industrial production. Assuming that mobility is a kind of proxy for public health measures, co-movement is intuitive, as more substantial public health constraints result in a drop in industrial production (of course, due to the international nature of the industry, it may be justified to examine industrial trends in the light of the data of trading partners, but the integration of these aspects is beyond the scope of this study). It is visible that mobility fell dramatically in April, with a considerable correction in most countries by May, and the debt-free group, as well as the Czech Republic and Hungary from the cluster with a decreasing export exposure, and the majority of countries belonging to the group not exposed to tourism returned to the March level by June (mobility data is missing from Slovakia). Clusterlevel peculiarities can again be detected. Cluster 2 can be described as one experiencing a minimum loss of mobility and a return to the positive domain. Cluster 3 shows fully co-movement for both variables, but industrial production did not even reach the previous year’s level by June (The Polish economy ‘stands out’ from the group with a decreasing export exposure as—although the Polish curve has a similar shape—the change in industrial production returned to an exceptionally high level of growth in June.). In several countries, depending on the date of announcement of the pandemic, March data still show increasing industrial production and production is increasing again in June, i.e. it does not merely indicate a decreasing level of reduction (compared to the same month of 2019). In Finland and Denmark, production did not even fall into the negative domain. However, the other half of Cluster 4 shows a less homogeneous movement. Sweden failed to converge to the starting point in March in terms of mobility and production. Germany was successful in this respect, but its industrial production was still significantly lower than a year before. (In the case of Greece and Slovenia, industrial production decreased only to a minimum extent in April, and from May its change returned to the positive domain again on an annual basis. At the same time, the

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SHORT-TERM IMPACT OF COVID-19 IN THE CLUSTERS …

a. Not exposed to tourism (Cluster 1)

b. Debt-free (Cluster 2)

20.0

20

PL0315.0 PL06

IE03

LA05

LA03 LA06

15

10.0 B IE04

-80.0

BE03 BE06 PL05 NL03

IE06

-60.0

-40.0 BE04

NL04 PL04

10

5.0

EE03 EE06 BG03

LA04

5

0.0

-20.0 NL06

-5.0

0.0

EE04 -40

-50

N

-30

EE05

-15

c. Decreasing export exposure (Cluster 3)

d. Socially sensitive (Cluster 4)

10

-40

5

FI04

CZ060 CZ03 HU06 -20 -10 -5 0

-30

HU05

CZ05

-10 -15

-50

CZ04

FI03

FI05

FI06

SE03

DK03 DK06 DK05 SE06 -30 -20 -10 SE05 SE04 DE03 DE06

DK04 -40

-20 -25

HU04

0

-10

-15.0

-50

-5

BG05

BG04

-10.0

0 BG06 -10

-20

IE05

HU03

75

DE05

-30 DE04

-35 -40

e. Tourism-dependent (Cluster 5)

20 15 10 5 0 -5 0 -10 -15 -20 -25 -30 -35

f. Deficit-increasing (Cluster 7) 20

20 15 EL03

-60

EL04 HR04-40

10

5 HR03 EL05 HR06E 0 -20 0 -5 HR05 -10

SI05 AT03 -80

-40 AT05

-60 SI04

-25

PT06 PT05

PT04

SI0610 5

AT06 -20

PT03 AT04

-15 -20

15

SI03

0 -5 0 -10 -15 -20 -25 -30

Fig. 3.7 Co-movements in the time series of clusters in terms of mobility (horizontal axis) and changes in industrial production (vertical axis) (MarchJune 2020) a. Not exposed to tourism (Cluster 1) b. Debt-free (Cluster 2) c. Decreasing export exposure (Cluster 3) d. Socially sensitive (Cluster 4) e. Tourism-dependent (Cluster 5) f. Deficit-increasing (Cluster 7) h. Debt-reducing (Cluster 6) (Source Own edited Note The captions for the dots include two letters as a country code, while the second two numbers represent the month of the year 2020. For example, IT04 represents the April 2020 data of Italy)

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h. Debt-reducing (Cluster 6)

Fig. 3.7 (continued)

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Dutch, Portuguese and Swedish economies failed to return to the positive domain by June.) As a peculiarity of the tourism-dependent countries of Cluster 5, mobility compared to the starting point was in the positive domain throughout the period, and industrial production fell sharply only in April on an annual basis, and all three countries were able to return to growing production. As a peculiarity of Cluster 6, all countries belonging to the debtreducing group show very wide variations, compared to the others, both in terms of job travel fluctuation (mobility) and declining industrial production. The former is in the range of (–20; –70), while the latter is in the range of 25–30 percentage points over the four months reviewed. Cluster 5 shows a mixed picture with respect to industrial production, but there are a lot of similarities in the development of mobility, not only within the group, but also with debt-free countries and ones with a decreasing export exposure. Cluster 1 is really heterogeneous, and it would be difficult to make a general statement here in the context of production and mobility. The correlation illustrated in Fig. 3.8 suggests that no far-reaching conclusions can be drawn from the relationship between changes in the risk spread of government bonds and the fall in mobility, but in some cases, it is possible to recognise the clusters identified from pre-crisis data. The socially sensitive cluster is clearly described by the characteristics of low risk spread and a 30–45% drop in mobility. The Netherlands is also close to this group based on these two criteria. The members of the debt-free group are also close to one another (Bulgaria and Latvia— no data for Estonia, as it has very little debt, and no 5-year debt at all). The Croatian and Greek members of the tourism-dependent group

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Fig. 3.8 Connections between changes in government bond spreads (2 January–5 May 2020, horizontal axis) and mobility (vertical axis) (Source Own edited data based on data from Bloomberg, Google)

suffered a similar degree of mobility drop (−52% and −54%, respectively), but they show a significant difference in interest spread, presumably due to their crisis-independent public finance situation (see Fig. 2). Countries in the debt-reducing cluster also show the same mobility drop with minimum standard deviation, with the exception of Romania, but similarly to Ireland, which is, however, in another cluster. However, their interest spreads appear to be basically determined by the debt trajectory, rather than the 2020 crisis. For the other clusters, it is not possible to identify such a markedly different position compared to the others in the context of risk spread and mobility. Based on the monthly change in unemployment, there is a significant standard variation within the clusters in terms of both the degree of change and its development over time, so the clusters based on preparedness data before the crisis cannot be distinguished with respect to labour market impact. This is not surprising since many of the countries reviewed distorted market processes through job retention measures (see Czeczeli et al. 2020) and, furthermore, unemployment statistics are necessarily based on administrative rules. However, it can be generally concluded that the closure already increased unemployment in April at the latest.

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3.5

Conclusions

During the analysis, our starting point was a modified theory, which adapted the New Keynesian theory of economic policy to the peculiarities of the global economic crisis caused by the pandemic. This gave rise to the conclusion that, due to the inevitable drop in mobility, it is not enough to merely replace household consumption with public expenditure, but it is also necessary to focus on maintaining capacity. The methodology of the study was based on Ward clustering and a coherent analysis of short-term variables. Using the method of clustering, seven groups, each containing 3–5 countries, were defined based on six economic indicators that measure the vulnerability and exposure of the countries with respect to public finances, external economy and income distribution (i.e. social aspects) before the economic crisis. The groups of countries thus formed showed some similarities, as expected, but surprises were also found compared to the traditional versions of capitalism and the classic literature of European social models. When examining clusterforming variables, it was concluded that the clusters are clearly separable in the pair of social indicators. As for the other four indicators describing the initial situation before the crisis, the separation of the seven clusters is not so marked. As far as the budget deficit is concerned, Cluster 6 stood out and deviated significantly in the direction of a deficit, while Cluster 5 was unique due to a significant deviation of extreme values. With respect to public debt, the clusters can be divided into two types: Clusters 2–4 typically entered the pandemic with lower levels of debt, Clusters 5–7 with a higher level, while Cluster 1 swayed between the two. The examination of export share also resulted in a similar division: it was high in groups 1– 3 and considerably lower in groups 4–7. In terms of exposure to tourism, only Cluster 5 and Cluster 1 are different from the other five, more or less homogenous groups of countries with a higher and lower share of GDP, respectively. The defined clusters were analysed for the first four months of the pandemic, March–June 2020, based on four indicators that characterise a short period and that can be quickly realised statistically: 1. monthly change in industrial production compared to the same period of the previous year, 2. change in worker mobility, 3. change in unemployment, and

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4. change in the interest spreads of government bonds. Based on the evaluation of standard deviation, correlation and fit, it seemed justified to examine changes in mobility and industrial production, as well as mobility and risk spread in pairs. Our analysis gave rise to the conclusion that the four crisis indicators suggested a trend of homogeneity between clusters. All clusters showed a decline in industrial production compared to the short-term pre-crisis reference period. It is also true, with the exception of Cluster 1, that heterogeneity within the clusters increased with the development of the indicator. The average of each cluster increased slightly in terms of unemployment, while heterogeneity within the cluster did not increase. In the case of workforce mobility, cluster averages essentially moved in parallel, starting from roughly the same level and reaching approximately the same level in the direction of declining mobility. Larger deviations during the shift towards increasing yields can be detected in connection with the risk spread on five-year government bonds. The combination of annual indicators, providing a basis for the clusters, and variables describing their behaviours during the crisis does not make it possible to lay down general rules. This suggests that the short-term decline caused by the first wave of the coronavirus was not fundamentally rooted in different exposures in terms of public finances, social aspects and external economy. This is consistent with the initial theoretical basis of our analysis, stating that a crisis caused by an exogenous shock does not exert the same effect as a shock based on economic reasons. Debt-reducing countries starting with high budget deficits and high levels of public debt (Cluster 6) experienced an above-average decline in industrial production. Also, they suffered a significantly higher increase in risk spread than Cluster 1, similarly consisting of well-developed countries not exposed to tourism, or the socially sensitive Cluster 4. Even without Romania, the average increase in interest spreads among debt-reducing countries between the periods before and after the crisis is almost three times higher than in the socially sensitive countries and more than eleven times higher compared to countries not exposed to tourism. The increase in risk spreads was also higher than in other clusters among tourism-dependent (Cluster 5) and deficit-increasing countries (Cluster 7), which also started out with high levels of public debt, in contrast to, for instance, countries with a decreasing export exposure

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(Cluster 3), which include semi-developed countries, but had a lower initial debt level. However, this trivial causal relationship (i.e. the connection between the level of public debt and the degree of risk spread) is contradicted by the significant risk spread increase in the countries of the debt-free Cluster 2. Nevertheless, a decisive factor here may be that there is no data on five-year bonds for Estonia as the maturity of its minimum debt is so short. As a result, it was not included in the calculation, which distorts the result. Therefore, the contradictory behaviour does not seem to be confirmed. It seems to be confirmed, though, for each cluster that the drop in mobility occurred in parallel with the slowdown in industrial production, which is an intuitive correlation given that more substantial public health constraints lead to a higher drop in industrial production. When examining changes in industrial production together with developments in workforce mobility, it was found that, in the short term, most clusters showed a V-shaped movement, meaning that the degree of recession and immobility was already more moderate in the fourth month. There appears to be a close co-movement in debt-reducing countries (Cluster 6) in terms of both production and mobility. The same conclusion can be drawn with respect to the cluster with a decreasing export exposure (Cluster 3), which is, however, considerably different from the fluctuation of debt-reducing countries. Debt-free (Cluster 2) and deficit-increasing (Cluster 7) countries show a homogeneous shift in terms of mobility, while they suffered different degrees of damage in industrial production. The behaviour of countries not exposed to tourism (Cluster 1) and socially sensitive ones (Cluster 4) within the cluster makes it clear that it is a good idea to examine further structural and institutional factors in order to explore the decisive factors of the crisis path. The relationship between changes in the risk spread of government bonds and the drop in mobility does not give rise to far-reaching conclusions. It can be observed that the big drop in mobility did not result in a sharp increase in unemployment, but correlates strongly with the decline of industrial production. It seems, that the economic policies were effective to protect the jobs and partly the income security, too. Moreover, it means that the economic policies had room for manoeuvre which was not experienced in the crisis happened a decade earlier. It was a special mix of tolerance of the financial markets and the accumulation of policy reserves that made it possible to raise the deficit enormously or finance the government bond markets with monetary actions right on

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time. Since the external shock of COVID-19 has originated in sanitarian factors and the application of the heterodox modern monetary theory has become reasonable since the global financial and European debt crisis in 2008–2010, the short-term public budget constraint turned to be softer. However, the policy actions in 2020 tightened the fiscal room by allowing tax credit and financing jobs and industries. Nevertheless, the pandemic crisis is facing a solution. Thus, the tolerance towards the expansionary economic policy declines, and the importance of macroeconomic vulnerability becomes more acute. The liquidity remained available during the first wave of pandemia because the crisis was not a financial collapse. Nevertheless, the next wave(s) can have the economic focus to return to the solvency challenge which reraises the importance of the state of reserves, the balance of public finances, sustainability of public debt. It would be dangerous and irresponsible to extend the first wave experience of soft fiscal constraints as a base to long-term crisis management. In general, it can be concluded for most countries that crisis indicators passed the low point of the first wave of the pandemic and experienced a correction by June, more or less to their original growth path. This confirms the initial assumption that economic policy had to manage an inevitable drop in mobility, rather than decreasing demand.

Notes 1. The following country codes are used in the study: AT—Austria, BE - Belgium, BG—Bulgaria, DE—Germany, CY—Cyprus, CZ—Czech Republic, DK—Denmark, EE—Estonia, EL—Greece, ES—Spain, FI— Finland, FR—France, HR - Croatia, HU - Hungary, IE—Ireland, LA— Latvia, NL—Netherlands, PL—Poland, PT—Portugal, RO—Romania, SE—Sweden, SI—Slovenia, SK—Slovakia, UK—United Kingdom. 2. Luxembourg was not included in the initial database created. 3. In the case of Malta, the indicator travel and tourism total contribution to GDP can be considered an outlier over the relevant period, while in the case of Lithuania the change in export share is an outlier value. 4. Volume index of mining, quarrying, processing industry, electricity, gas, steam supply and air conditioning. 5. For a detailed explanation of developments in these balances, see Marton (2018).

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Farkas, Beáta. 2017. Piacgazdaságok az Európai Unióban (Market Economies in the European Union). Akadémiai Kiadó, Budapest, http://dx.doi.org/10. 18414/Ksz.2017.7-8.872. Feldstein, Martin. 1982. Government Deficits and Aggregate Demand. Journal of Monetary Economics 9 (1): 1–20. https://doi.org/10.1016/0304-393 2(82)90047-2. Feldkircher, Martin. 2014. The Determinants of Vulnerability to the Global Financial Crisis 2008 to 2009: Credit Growth and Other Sources of Risk. Journal of International Money and Finance 43: 19–49. Frankel, Jeffrey, and George Saravelos. 2012. Can Leading Indicators Assess Country Vulnerability? Evidence from the 2008–09 Global Financial Crisis. Journal of International Economics 87: 216–231. Friedman, Milton. 1977. Nobel Lecture: Inflation and Unemployment. Journal of Political Economy 85 (3): 451–472. https://doi.org/10.1086/260579. Hall, Peter A., and Soskice David. 2001. Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford University Press. https://doi. org/10.5465/amr.2003.10196861. von Hayek, Friedrich A. 1995. Piac és szabadság (Market and Freedom). Budapest: KJK. Keynes, John Maynard. 1936. General Theory of Employment, Interest and Money. London: Macmillan. Lentner, Csaba, and Pál Péter Kolozsi. 2019. Old Problems in a New context— Excerpts from the New Ways of Thinking in Economics After the Global Financial Crisis. Economics & Working Capital 1–2: 53–62. Lucas, Robert 1976. Econometric Policy Evaluation: A Critique. In K. Brunner and A. Meltzer (eds.), The Phillips Curve and Labor Markets. CarnegieRochester Conference Series on Public Policy. (Vol. 1, pp. 1–18). New York: American Elsevier. Marton, Ádám. 2018. The Relationship Between Fiscal Consolidation and Sovereign Debt. Does Fiscal Correction Decrease or Increase Debt Rate? Public Finance Quarterly 1 (2018): 24–38. Móczár, József. 2010. Crisis of Economics: Neo-Classic vs. Keynesian Economics. Magyar Tudomány (Hungarian Science) 171 (3): 318–330. Perotti, Robert, Rolf Strauch, and Jürgen von Hagen. 1998. Sustainability of Public Finances. ZEI: University of Bonn. Sajtos, László, and Ariel Mitev. 2007. SPSS kutatási és adatelemzési kézikönyv. (The Handbook of SPSS Research and Data Analysis). Budapest: Alinea Kiadó. Sapir, André. 2005. Globalisation and the Reform of European Social Models. Background document for the presentation at ECOFIN Informal Meeting in Manchester. Bruegel Institute, September 9. Schubert, Carlos Buhigas, and Hans Martens. 2005. The Nordic Model: A Recipe for European Success? EPC Working Paper, No. 20.

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Schuknecht, Ludger, and Vito Tanzi. 2005. Reforming Public Expenditures in Industrialised Countries. Are There Trade-Offs? European Central Bank Working Paper, No. 435, February, ECB. Shastri, Rajiv. (2020). Policy Dilemma: Is the Covid-19 Pandemic a Demand or Supply Shock? Business Standard. https://www.business-standard.com/art icle/opinion/policy-dilemma-is-the-covid-19-pandemic-a-demand-or-supplyshock-120042300627_1.html. Accessed on 15 August 2020. Simon, Judit. 2006. A klaszterelemzés alkalmazási lehet˝ oségei a marketingkutatásban (Applications of Cluster Analysis in Marketing Research). Statistical Review 84 (7): 627–651. Szepesi, György. 2013. Géniuszok párharca. Milton Friedman és J. M. Keynes vitája Tim Congdon és Robert Skidelsky el˝ oadásában (War of the Geniuses. The Debate between Milton Friedman and J. M. Keynes as Presented by Tim Congdon and Robert Skidelsky). Economic Review, Vol. LX, June 2013, 633–649. UNIDO. (2020). The Economic Impact of Covid-19 Pandemic. http://www. unido.or.jp/en/news/6801/. Accessed on 15 August 2020.

CHAPTER 4

Macro Economic Model of COVID-19 Pandemic Crisis ˇ Vladimir Cavrak

4.1

Introduction

The health crisis due to the COVID-19 coronavirus in an enormously short time affected the whole world and caused a historically unique and unexperienced impact on all spheres of human life, including economic relations that fell into a crisis of unimaginable proportions with unknown duration. No economic crisis to date (the Great Depression 1929–1930, the Great Recession 2008–2009) has occurred so rapidly with a deep decline in economic activity and has not affected the whole world at the same time. In order to discuss mitigation measures and exit from the current economic crisis of COVID-19, it is necessary to (a) understand well its character, mechanisms of impact on the economy, and the main consequences (three or four simultaneous shocks) and (b) more precisely define the initial economic position with which the Republic of Croatia “welcomed” the crisis (secular stagnation).

ˇ V. Cavrak (B) Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_4

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Due to the unique way of origin, mechanisms, and deep consequences, this crisis will be a great challenge for economic science and profession. Economists are, unfortunately, known as the greatest dogmatists and captives of old ideas who are reluctant and difficult to abandon even when empiricism clearly and unequivocally denies them. The last world financial crisis empirically refuted many postulates of classical (and neoliberal) economy, but many economists still firmly adhere to these teachings, although it is clear that due to the specifics of this crisis, new, innovative solutions should be sought. Economic science, if it wants to justify its existence, must be able to provide quick and dynamic responses to sudden situations because the future does not, as a rule, happen according to historically known patterns. Numerous world universities and think tanks, driven by the negative experiences of the Great Recession 2008–2009 and the “euro crisis”, have in recent years developed an activity to redefine important postulates of economics, which has already led to changes in economic textbooks, especially macroeconomics. Some of these changes are also important for understanding this crisis. In the case of the current COVID-19 pandemic crisis, the state (in the form of the Civil Protection Headquarters of the Republic of Croatia) suspended the functioning of the market because a decision was made to “prohibit leaving the place of residence and permanent residence” (March 23, 2020). Services and the labor market, which greatly affected the functioning of the money and foreign exchange markets. The decision is justified by the public choice to give priority to preserving health. Given such a major decision, unprecedented, rapid, and appropriate intervention is expected to eliminate the risk of “further spread of the disease” and bring the market back to “normal” condition. To create optimal measures and end the crisis and create a better life after the COVID crisis, it is necessary to define our starting position. The definition of the starting position is because Croatia differs from other countries and because symmetrical health shock will have asymmetric consequences for different countries and different regions in Croatia. This regional perspective is also important.1 This is also important in the context of membership in the European Union. EU has clearly demonstrated its slowness, inefficiency, and lack of solidarity in the last financial crisis. The voices coming from the EU in the first days of this crisis showed that the situation has not changed significantly since the last elections. Disagreements over “how, how much, and

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to whom we need to help,” have intensified again, so EU is still at risk of a new systemic crisis. In the four weeks since the pandemic was declared, EU leaders have failed to overcome divisions between South and North countries on a “brave response to the COVID-19 epidemic” with “the most comprehensive and ambitious package ever prepared.” This means that no agreement was reached by the beginning of April on loans and a request for an investment fund to be financed from a joint debt with a Eurobond (Caizzi 2020).2 The only idea that has been approved is the idea of relaxing rigid fiscal rules with the aim that “national governments can invest as much money as they need in their economy.” (Valero, 2020.) If this is taken at face value, the EU is not able to respond quickly to the challenges of the pandemic together and leaves it to national governments to do what they think they should and within their own means and capabilities. On the positive side, however, this decision to relax fiscal rules by the European Commission provides room for fiscal intervention by national governments, as restrictions on the fiscal deficit and public debt have been relaxed. As for the European Central Bank (ECB), it reacted somewhat faster than the European Commission and on 27 March 2020 published recommendations on the distribution of dividends during the COVID-19 pandemic with the aim of preserving and strengthening the capital of credit institutions so that they could fulfill their role in financing households, SMEs, and corporations during the coronavirus shock. Supporting the real economy and absorbing losses at this point must take precedence over the discretionary distribution of dividends (ECB 2020, March 27). At the initiative of the ECB, the CNB also issued a similar recommendation on dividend payments to banks. However, it has so far limited its interventions to the foreign exchange market in order to maintain the exchange rate and liquidity of the financial system.3 Croatia had the slowest recovery from the last financial crisis, which lasted a full six years. This situation has exhausted the resources of households and businesses. It has also limited the fiscal capacity for current intervention. In addition to these unfavorable elements in this situation, there is one favorable one that many European countries do not have. And that is the national currency: kuna! However, in terms of the advantages of the currency sovereignty of the kuna, there are almost insurmountable differences. The government and the CNB firmly believe in the benefits of a quick replacement of the kuna by the euro and are trying, even in this never-before-seen crisis, to preserve the plan for

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the accelerated introduction of the euro. In the first days of the eruption of the COVID crisis, the advantage of currency sovereignty was not officially recognized, but it was pointed out as a “disadvantage.” In contrast, many countries around the world have already taken advantage of currency sovereignty or announced extensive recovery packages based on the sovereignty of their currency. Since there is no consensus on the initial positions regarding the crisis (characteristics, mechanisms, scope, duration, etc.) or on the current state of the Croatian economy, I am still prompted to offer some possible ways of thinking and a general framework for a macroeconomic strategy to combat the COVID-19 crises.

4.2 Curve of the Pandemic Shock and the Curve of the Economic Crisis The current economic crisis has been initiated by epidemiological shock, which has its regularities and exact structural distribution of emergence and disappearance. The pandemic medical shock curve usually comprises six phases that alternate with each other but during which the pandemic has different dynamics and different duration of time for each phase. The recognition of the current stage is extremely important for recognizing the right moment of action in the right way. The six phases are (1) examination of the first cases; (2) identifying the potential for continuous transmission; (3) start of the pandemic wave; (4) pandemic wave acceleration; (5) pandemic wave deceleration; and (6) preparations for future pandemic waves.4 The first two phases form a pre-pandemic interval in which there is a great responsibility on the medical profession to spot, recognize, alert, and take health care measures in time. The other four phases cover the pandemic interval. The first death in China was recorded on January 9, 2020, and outside of China on January 13 (Thailand). By the end of January 2020, many countries already had the first cases and as early as March 11, a pandemic was declared. By the end of March 2020 (data as of March 28, 2020), 172 countries (and 29 territories) had confirmed cases of the disease (a total of 621,090 patients), which confirms a global problem. In Croatia, the first case of the disease was publicly confirmed on February 25, 2020, almost two months later than the onset of the disease in China. In March 2020, the pandemic curve in Croatia had an

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ascending shape, with the estimate that growth would not be exponential but linear (657 people became ill, five died, and 49 were cured). Due to health protection and taking the necessary health care measures, the Civil Protection Headquarters was activated on time, which actively monitors the development of the situation and takes measures within its area of responsibility. At its 214th session held on March 17, 2020, the Government of the Republic of Croatia adopted 63 measures to help the economy (of which 31 measures are various payment deferrals, 15 define loans and loan facilitation and bank guarantees, the rest are mostly anecdotal). The content and structure of the measures, despite probably good intentions, soon caused dissatisfaction among employers and unions and further increased uncertainty. The timing of the adoption of the measures was good because the Government reacted in the phase of initiating the pandemic wave (one week after the declaration of the pandemic and three weeks after the announcement of the first patient) but the content of the measures was relatively unconvincing and inadequate. All economics participants using China and other countries as an example of future pandemic developments could clearly predict that Croatia was entering an uncertain phase of acceleration of the pandemic wave. The economic participants had justifiably higher expectations since the economic damage would be incalculable. The foregoing considerations are important for at least two reasons, both concerning the time profile and the strength of the impact of the health shock on the economy. First, the time dynamics of the health shock precedes the economic shocks, and second, the profile of the economic shock is inverse in relation to the intensity of the health shock or health care measures (see Fig. 4.1). Higher intensity of health care measures (upper curve with a dashed line) to align the pandemic curve puts more strain on the health system sharply increasing its costs) and generates a greater negative amplitude of economic shocks and a deeper economic crisis (lower curve with a dashed line). The introduction of quarantine (stopping the production and movement of people, stopping the flow of goods and finances, closing shops, crafts, public institutions and services, closing schools, kindergartens, colleges, etc.) means completely stopping some activities or reducing them to a minimum. The sudden stop or “lockdown” in almost all parts of the world is what makes a significant difference between this economic crisis and those recorded in economic history.

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Fig. 4.1 Theoretical COVID-19 pandemic and recession curve (Source Author: ˇ V. Cavrak, based on Ed. Baldwin and Weder di Mauro [2020])

The curves of the pandemic and recession, shown in Fig. 4.1, have a theoretical character. Empirical data and available estimates suggest that the phases of acceleration and deceleration of the pandemic in the case of the Republic of Croatia could last 30–90 days with the potential danger of one or more subsequent waves. As for the economic crisis that follows, according to initial estimates, it could last 6–12 months with prolonged action, perhaps until the end of 2021. The depth of the economic crisis, measured by the fall in the gross domestic product (GDP) could be around −10% (2020). OECD estimates for G20 plus Spain indicate an even larger decline in GDP (OECD 2020). For each month of an economic lockdown, about 2% of annual GDP growth will be lost. Rough estimates for the Republic of Croatia confirm a similar scenario.5

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The depth and duration of this crisis will initially depend on the public health response and success of its policies. In the case of a successful public health response that involves controlling the spread of the virus within two to three months, the prospects for economic recovery could be more positive.6 In some parts of the world, recovery was expected as early as the third quarter of 2020, while the Eurozone could recover during the first quarter of 2021. In the event of smaller public health response, and especially if it fails to prevent more waves of pandemics, the economic recovery period in the Eurozone could be extended until the third quarter of 2023 (Oliver 2020). Estimates for the Republic of Croatia are still unreliable and range widely. Unfortunately, there is no service in Croatia that collects and publicly publishes all the necessary up-to-date data for these calculations, so we have to rely on approximations. Domestic data are published with a large time lag compared to actual events, often for more than six months, which makes them unusable in this situation. If we rely on foreign data then they point us to drastic facts about a drop in production in most sectors by 35–90% in just two weeks in March 2020. The situation will be particularly difficult in countries where the structure of the economy is dominated by the tourism, entertainment, and tertiary services sectors. The (too) high dependence of the Croatian economy on tourism (the so-called “Dutch disease”) has been the subject of warnings by numerous economists, experts, and institutions like the German IFO Institute (Falck and Schonherr 2016). Structural reforms and structural changes have been lacking, despite these warnings. The reason for the lack of change is due to the favorable effects of tourism on the balance of payments and the growth of foreign exchange reserves. However, now all the vulnerability of such an unfavorable structure of the national economy has been shown. There are very few sectors that have increased production. This applies mainly to the sectors that produce medical equipment and materials needed in the fight against infection, the food, telecommunications, medicines, and some energy and services sectors. In conclusion, in the case of Croatia, the absolute priority of health measures has been defined since the beginning of the crisis, which, on the other hand, implies the deepest recession amplitude, which could be assumed in mid-March 2020, even before the first government measures to help the economy.

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4.3

Macroeconomic Model of COVID-19 Crisis

As for the mechanism of the impact of health shock on the economy, I will use one of the more understandable and obvious representations in the standard framework of the AS–AD model known to economists and with little effort understandable to a wider audience not educated in economics. This model has been modified in relation to standard textbooks because instead of the price level (P) we have inflation (π) on the ordinate. This brings the model closer to reality because central banks target inflation rather than a certain price level. A broader explanation of this modification goes beyond the scope of this text. Unlike all known economic crises so far, this latest one contains as many as four shocks: (1) supply shock; (2) demand shock; (3) falling expectations and rising uncertainty; and (4) the shock of rapid bad measures. After the first onset, the shocks recursively support each other and generate a negative spiral (stagdeflation spiral). The first three shocks are quite certain and the fourth one is a potential shock (poor assessment of the situation, ignorance of the future, deficient measures, distrust of the government and economic policymakers, etc.). Given the difficulties in the initial work of crisis management in terms of rapid protection of the economy and citizens, this shock seems certain. Noting that the fourth shock will have a potentially longest duration because any wrong measure taken at any point in the duration of the crisis can further increase the effects of the shock on the economy. The main difficulties of crisis management arise from the cognitive gap and the time gap of decision making and implementation. There have already been widespread debates about the so-called “totalitarian” and “democratic” responses to the COVID-19 crisis, which reflect differences in the timing and response to the crisis in different countries around the world. A simplified economic model of the economic crisis during the COVID-19 pandemic is shown in Fig. 4.2. The initial shock is a health shock that initiates a supply shock because local and global production and supply chains are disrupted due to health protection measures. Inventories are being used up, but the investors are by definition a limited quantity, so there is a breakdown of supply after the inventories are exhausted. Due to a large number of deaths, fear, panic, and uncertainty appear, which lead to a decrease in consumption and the

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ˇ Fig. 4.2 AS-AD model of corona shock (Source Author: V. Cavrak)

decrease in investments. A drop in demand causes a drop in a company’s cash flow leading to fear of bankruptcy. Initially, companies are protected from potential bankruptcy by laying off employees, which leads to rising unemployment. This leads to a decline in the income of households with unemployed people and increases the amount of “bad loans” and the inability to repay loans. The decrease in employment and households’ income, on the one hand, jeopardizes the financial system, which is exposed to greater risk and reduces the purchasing power of households, leading to a further decline in demand. Reduction in credit in turn further increases uncertainty and fear, so we enter a new deeper negative circle of the loop: an additional decline in consumption, a decline in production and employment, a decline in corporate and household income, and so the negative loop multiplies.7 In natural disasters and wars, the Government generally immediately increases public spending and thus restores the aggregate demand even above previous levels for the purpose of reallocating production or rebuilding efforts. Because production in these situations recovers more slowly than demand, inflationary pressures can occur. In the case of the COVID-19 crisis, this will probably not be the case in the first phase, but we will initially have a problem with a deep fall in GDP and deflation (as

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shown in Fig. 4.2) and only in the second phase when economies begin to recover there is a possibility of slight inflationary pressures (because supply recovery may have a different time profile than supply recovery). Due to the need for a rapid and comprehensive fiscal response to the crisis, it is quite certain that public debt and budget deficits will rise significantly above normal levels and set limits without initial inflationary pressures but the debt that will be created will remain causing permanently higher levels of debt. All of the above points to the expectation of the worst possible and hitherto unseen combination, a crisis characterized by stagdeflation and high public debt.

4.4

COVID-19 Crisis and Circular Flow of the Economy

Currently, no one dares to give the precise quantifications of the final effects of the crisis because, as has been said, there are many unknowns. But what is already known and what can be estimated with great certainty is that the GDP in the Republic of Croatia in 2020 (and partly in 2021) will fall by about 10%. In any case, for the costs of the health crisis and the elimination of the economic crisis, an amount equivalent to the potential loss of GDP must be secured and invested in advance, which in a less favorable scenario is an amount that can easily approach 50–60 billion kuna. Many industrial companies and crafts have stopped production or their production has decreased by more than 60% in the first two weeks of March 2020 due to the lockdown restrictions. The services sector is almost entirely “frozen” with a few exceptions. The success and results of the tourist season in both 2020 and 2021 are being questioned. Exports and imports of goods are reduced to a minimum of functioning for the needs of the health system and nutrition. All this will be reflected in a sharp rise in the unemployment rate. Government measures to support the minimum are insufficient to maintain employment levels to a greater extent because entrepreneurs are afraid of a longer-term decline in income. Due to fear and uncertainty and due to low trust in domestic institutions, all these events will further encourage the decline in consumption, which has already been reduced to basic survival items. Expenditures on long-term consumption goods will be delayed for a longer period of time as well as investments. The only exception may

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be some investments in the health system, possibly in the restructuring of food and medicine production. According to the usual time distribution of macroeconomic variables, the investment will recover the slowest because we are facing a large shock of supply and demand, which means that even after the end of the health crisis, companies will operate at a low capacity. The recovery of investment spending in “standard” crises occurs approximately six–eight months after the recovery of personal consumption. All of the above indicates the certainty of a large decline in budget revenues (tax and non-tax). The decline of revenue will be inversely proportional with the measures taken to support the firms and households, especially if measures are late to implement. All of the above will have a major impact on the financial markets, the securities market (bonds and stocks) as well as the foreign exchange market. It is quite certain that the consequences of the health crisis in the economy will be great and the effects of the crisis are occurring in a complex way. The effects of the crisis are spread out over the entire economic system. The best summary of the effects of the COVID-19 health crisis on the economy was given by R. Baldwin using the circular economic flow model (Baldwin 2020). The national economy functions if the cash flow is caused by the processes of production, exchange, and consumption function. That is why it is most important to preserve cash flows because their interruption causes the stagnation of the entire economic “machine.” Households that lose income (salaries, annuities, pensions, social benefits) experience financial problems and bankruptcy (inability to repay loans, inability to pay utility bills, etc.). The situation of households in Croatia is particularly difficult due to the current situation, which was preceded by a long recession and financial exhaustion. Many are therefore exposed to relatively high debts, so they do not have the reserves to bridge the situation in which they find themselves without their own will or decision. The livelihood of many households depends almost exclusively on current income. The decline in household income reduces spending on goods and services and thus the inflow of money to businesses and the state. Falling demand reduces domestic demand but also imports. As the crisis occurs simultaneously almost all over the world there is a disruption of exports and imports as global chains of production and supply are disrupted. This

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reduces international cash flows. The reduction of cash flows has a particularly strong impact on small open national economies such as Croatia. Large economies such as the USA, China, Germany, Great Britain, etc., have a lower degree of openness and larger internal markets, so they can more easily absorb the shock of falling foreign demand. The fall in exports will have a greater negative impact on the Croatian economy than some other European economies that are less open and more self-sufficient because they have built a more competitive economic structure. Falling demand and negative supply shocks lead to a number of disruptions in domestic and international production and supply chains whose reconstruction, rebuilding, and restructuring will take a long time after the end of the health crisis. This will be the biggest and long-term problem as a sharp drop in production will be difficult to return to normal, not only because of disruptions in production and supply chains, but also because of potential future decisions by some countries to increase self-sufficiency in the food, energy, and medicines sectors. This implies fewer orders and less export demand. No matter that economics as a science considers such decisions bad, their popularity is not fading. The former will have a particularly strong effect on reducing production and slowing down the pace of its renewal. This slowdown will be accentuated by rational consumer decisions that will delay the purchase of everything that is not immediately needed or considered a durable good. Due to that, the entire Quaternary and Tertiary sectors of services and especially the production of durable goods (furniture, equipment for houses, apartments, cars, etc.) will suffer. All of the above will lead to enormous losses for entrepreneurs and an increased risk of bankruptcy. Companies in Croatia have previously faced a prolonged six-year crisis and credit crunch, which has long limited investment growth and technological recovery, so the economy has faced this crisis with significant technological backlogs, and this crisis will significantly deepen these problems. In addition, the Croatian economy has several major structural problems. One is an unfavorable structure dominated by small and micro enterprises that were once claimed to have the advantage of being flexible. This advantage will now prove to be a disadvantage because most SMEs do not have the financial capacity to withstand a long period of such a large drop in production and turnover and the advantage of flexibility will typically be used to lay off labor and drastically reduce wages. The closure of companies, the cessation of their

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work, brings into question the business of those who may have a better financial shape. The problems households and businesses will face will spill over into defaults on their obligations to banks and the government. If everything was just left to market reaction, the collapse of all economic participants would follow: households, companies, banks, the state. Therefore, everything should be done to help maintain the economic functions of households and businesses must be large and generous, and fast. The medical shock will be over at some point and if appropriate measures are not taken the economic scars could be large and long-lasting. Two things are very important: time and proper intervention strategy (good policy mix). The packages of measures must be comprehensive because that is the only way to achieve the credibility of the government, trust in public institutions, and social cohesion. Otherwise, in addition to the deep economic crisis, we may soon be threatened by a social and political crisis. Right now it is the moment of doing “whatever it takes,” the instructions of Jason Furman (President Obama’s chief economist) are instructive. He lists six good tips: (1) better to do too much than too little; (2) use existing mechanisms wherever possible; (3) invent new programs wherever necessary; (4) diversify and not be afraid of duplication or the possibility of unintentional creation of “winners”; (5) engage the private sector as much as possible; and (6) ensure that the response is dynamic and lasting (Ed. Baldwin and Weder di Mauro 2020a, p. 15). The basic idea of good strategy and tactics relies on the need to develop a unified intervention strategy that aims to formulate and implement a good policy mix that must include at least the following: • • • • • •

Fiscal policy; Monetary policy; Financial regulation policy; Social security policy; Industrial policy; Trade policy.

The above policies (Ed. Baldwin and Weder di Mauro 2020, p. 15) must not function partially and inconsistently. A high degree of coordination is

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required given the type and scope of interventions and the time dynamics. In this way, the success of the intervention can be achieved and the credibility and trust of the public can be achieved, and then the removal of negative expectations, which are an extremely important and resilient variable in such situations.

4.5

Framework of Macroeconomic Response to COVID-19 Crisis

We can now proceed to an overview of the macroeconomic model of mitigating and eliminating the economic crisis caused by health shock. Again, we will use a simple AS–AD model (Fig. 4.3). Here we theoretically start from the lowest point of the recession but we take into account that in this case, we do not really want to reach that point. This means that all the measures that are theoretically and analytically presented and explained in this paper are taken before the onset of the deep recession and at the same time and not sequentially. Here the order of the set of measures is numbered 1–3 but it is understood that in reality these measures must

Fig. 4.3 Macroeconomic model of COVID-19 crisis removal (Source Author: ˇ V. Cavrak)

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be taken as soon as possible in their full scope and they have to be as simultaneous as much as possible. This is very important to minimize the effects of negative expectations and uncertainty. Macroeconomists know that negative expectations and uncertainty in real situations can “take” well-designed strategies and measures in a completely undesirable direction. Thus, in this analysis, we start from the point of the deepest recession and equilibrium with a significant decrease in GDP and a small deflation. The first set of measures concerns the maintenance and recovery of demand using expansionary fiscal and monetary policies. This is shown in Fig. 4.3 by shifting the AD curve from D3 to D4 (arrow 1). This time consumption should be leading because supply is growing at a slower pace and there is no reason to increase production as long as consumption is declining. That is why it is important to stimulate demand in time, which should “pull” supply. Figure 4.3 shows a small risk of mild inflation, which is not a problem in this case because, in the next step, the renewal and increase in supply will again exert deflationary pressure, so the net result will still be mild deflation. It all depends on the pace of supply renewal and the magnitude of fiscal and monetary expansion in the previous step, which can be controlled by monetary policy measures through the so-called fine-tuning. The second step or positive supply shock, shifting the AS curve from AS1 to AS2 (arrow 2) is actually the most complex and has the longest duration. It lasts from the onset of the crisis to several months (or quarters) after the end of the health crisis. The third shift of the AD curve from D4 to D5 (arrow 3) illustrates the possible effect of favorable expectations, removal of fear, panic, and uncertainty, and achieving credibility and trust in economic policymakers (Government, Parliament, CNB). These factors have a strong effect during all phases of the crisis and their adverse impact is initially trusted by the health system and confidence in the first government measures (the health system segment has successfully carried this phase). With the end of the health crisis, these factors will be very important for the speed of recovery of supply and demand. As far as exact fiscal and monetary policy measures are concerned, it is possible to use a whole range of instruments but the policymakers should focus their attention on measures that are simple and quick, without unnecessary administration and bureaucratic obstacles (the second government package was better than first).

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The first and foremost goal must be to provide households and businesses with sufficient liquidity for all payments in order to preserve and maintain cash flows. The first three issues that need to be focused on and solutions determined for them are: debts (businesses and citizens), payments (again by citizens and businesses), and salaries. For all employees and the self-employed, without exception, during the health crisis (two or three months?) due to which the state’s decision was made to stop the movement of people and goods, the payment of salaries should be ensured at the expense of the fiscal structure as much as possible to the private and public sectors. In this way, the maintenance of all financial flows in all systems is achieved, which includes all entities: citizens, companies, the state, banks import–export. Partial and superficial solutions, especially those that reduce or interrupt financial flows, lead us into a deep and long-lasting depression and crisis and impose (unjustified and unnecessary) economic damage and economic pain for many citizens. The various attempts to use the COVID-19 crisis argument to implement structural and other reforms are not good and do not contribute to solving them, but deepen the problems even further. At the beginning of a pandemic crisis, it is very important to maintain supply and demand and reduce all forces that can disrupt the social and political cohesion of society. It is extremely important that the necessary structural reforms are carried out exclusively on the basis of a tripartite agreement between the social partners (state–trade unions–employers). This is always important but in this crisis it is crucial! Unilaterally imposing restrictive measures in public finances, especially cutting wages and pensions in these circumstances, would act to further deepen the recession, reduce social cohesion, and take us away from the principle of solidarity. It is completely clear that the so-called “Internal devaluation policies ” further deepened the decline in demand in pandemic conditions. Policies of internal devaluation also increase the certainty of economic depression for several reasons: first, that any reduction in public expenditure by definition reduces aggregate demand, second, that it would bring an additional dose of fear for the future and thus through negative expectations further reduced demand. And there is a third reason, the policy of internal devaluation, and especially if implemented unilaterally, for these two previous reasons leads us to the danger that private investment will not be able to recover in the long run. This is because if the equilibrium of supply and demand is reached at a low level of supply, there will be no reason for the growth of

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private investment in the long run and this certainly leads us to the L—a form of depression that will last for many years. Numerous structural reforms in the second (post-health) phase of the crisis will occur automatically as a result of market pressure and the need for the Croatian economy and companies to adapt to completely new opportunities and environments because the COVID-19 crisis will challenge and change many things. This will primarily be endogenously stimulated by processes that at this stage make sense to be further stimulated by strategies of smart specialization, development of new technologies, and the like. The public sector will certainly be exposed to this.8 Therefore, it is crucial to maintain all financial flows, to maximize demand and social cohesion, and to gain valuable time to develop all other measures on the side of reconstruction and restructuring of production and exports. The issue of government borrowing and the growth of the fiscal deficit in these circumstances should not primary policy focus. Public spending is now the only macroeconomic component that can and must maintain the level of activity in the short term and further stimulate economic activity. This refers to total public spending, especially social transfers, wages, and purchases by the state (especially goods and services from domestic businesses because import chains have been disrupted until further notice). This also applies to public investments, which in these circumstances gain additional importance. It is necessary to continue all started investments and urgently start a new investment cycle of public investments focused on health and health, the digital transformation of public administration and development of new technologies, and investments in projects that will reduce costs and increase competitiveness. Such a strategic commitment is supported by the conclusions of many studies on the relatively high fiscal multiplier at a time of economic downturn. Multipliers of public spending and transfers to the population at the time of economic downturn are significantly higher than tax multipliers and are many times higher than multipliers during the business cycle and at the time of flight (Blanchard and Leigh 2013; Gechert and Rannenberg 2014). In other words, in this situation, the effects of increased public spending are much greater than manipulating taxes. Fiscal expansion, especially in the form of public investment in this situation would have a favorable anti-recessionary effect.

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For employees who will lose their jobs and households without employed members, the self-employed, and similar categories, it is necessary to provide direct transfers from the government so that they can also pay their loans and other obligations. It is possible to consider the measure of redemption of debts and obligations of citizens and companies. In this case, it is not a problem that the state thus temporarily becomes the partial owner of certain companies. Exemption or deferral of payment is a weaker option because it introduces bureaucratization, subjectivism, voluntarism which increases mistrust and in the long run reduces revenues to companies and forces them to operate at a lower equilibrium level of production or even bankruptcy and closure. Special attention should be paid to micro, small and medium enterprises and family farms that form the backbone of the modern Croatian economy. Companies need to be reimbursed for paid salaries (average of the last three months and not the minimum wage) and provided with cheap sources of liquidity loans. This ensures the functioning of cash flows and does not jeopardize the financial system, i.e., it avoids the occurrence of the financial crisis and the bankruptcy of banks. These measures will have a significant impact on the fiscal system and an increase in government debt and deficits. However, if it manages to maintain the functioning of the economy and provide all the prerequisites for faster recovery after the end of the health crisis, it will mean less loss of GDP and does not have to greatly disrupt the public debt-to-GDP ratio. Such policies would be less painful for households and businesses. As for fiscal restrictions due to EU membership, they are now relaxed because the relaxation of restrictions was also needed by developed EU countries (Germany, France, etc.) which did not respect these restrictions even before in relatively normal circumstances when they needed a fiscal injection. In any case, the government has open room for fiscal stimulus. So far, different aid packages have been used for citizens and businesses in different countries. In general, economists agree that the volume must match the estimated decline in GDP. So for example, the UK is taking a package worth as much as 15% of their GDP. These are large amounts, so the logical question is how to finance it? In the case of Croatia, there are several possibilities and sources of funding. The budget needs to be restructured in a shorter period of time because the cost structure has changed due to the pandemic and the lockout. But one should not shy away from fiscal expansion. At the time of the low-interest rates, it is possible for the government to borrow

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abroad, but also on the domestic market. In such situations, a part of economists believe, in accordance with modern monetary theory, holds that direct financing of the budget by central banks is justified. If ever there was an opportunity to use monetary sovereignty then it is today! This is a significant advantage of Croatia that EMU countries do not have. In these times, it is unreasonable to stick to the surviving taboos about the “danger of inflation”, the danger of “excessive debt” and the like. Because otherwise the economic damage and pain of businesses and citizens will be too great.9 So far, the CNB has intervened only to protect the exchange rate and liquidity of banks, while more direct monetary interventions against the real sector have been absent. Although the European Central Bank has also made a recommendation in this regard favoring more direct monetary interventions. Bank liquidity was high even before the onset of the COVID-19 crisis, suggesting that regular channels of monetary impact on the real sector are poorly functioning. Therefore, it is important to ensure faster and more transparent channels of liquidity inflow to citizens and companies, and this is possible in the short term only through fiscal incentives that will be financed by the CNB. Problems with the budget deficit, the growth of the debt-to-GDP ratio, and the like should be addressed later.10 EU, IMF, World Bank, and similar international institutions are also available as potential sources of funds. However, as almost all countries are under pressure from the crisis, the demand for these funds will exceed the capacity of these institutions. This again means we have to go back to our own capabilities and resources.

4.6

Conclusion

The economic crisis initiated by the health shock of the COVID-19 virus infection is unique in its economic history. The most important features are its rapid emergence and spread around the world, which gives it the character of a deep global crisis. The main cause, unlike previous recessions and depressions, does not come from the financial and economic system but is an exogenous shock due to the pandemic. Defining public choices in terms of prioritizing the protection of the health of the population and urgently taking a number of health care measures has led to a sudden stop and lockdown of economic and financial flows at the local and global level. This, unlike previous recessions and depressions, has

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caused as many as four negative shocks: (1) supply shock; (2) demand shock; (3) shock of negative expectations and uncertainties; and (4) potential shock of untimely and inadequate macroeconomic policy reactions. Such a combination can lead to long-term depression with signs of a deep decline in GDP and deflation (“stagdeflation”). In order to prevent a large drop in GDP and an L-shaped depression, it is necessary to take a comprehensive policy mix of macroeconomic policies, especially monetary and fiscal policy, very quickly. But due to the complexity, depth, and specific temporal distribution of the depression, it is necessary to combine the macroeconomic set of measures simultaneously with measures in the areas of financial regulation, social security, industrial policy, and trade policy.

Notes 1. It is perfectly clear that there are significant differences between the abilities and capacities of the health care sector which has to absorb the shock of the pandemic. There are also considerable differences between the levels of economic and social development. Capacity for absorption and dealing with economic and social problems are not the same in the developed EU countries and the countries at the bottom of the development hierarchy. There are also differences considering the membership of the eurozone. And there are especially large differences between countries which are members of the EU and Croatia’s neighboring countries. 2. There is more and more confirmation of irreconcilable differences within the EU. To this contributes the news of the resignation of Mauro Ferrari, chairman of European Council for research (Associated Press, 8th of April 2020). He explained his resignation with three reasons: the lack of coordination between heal policies within the EU countries, objections of some countries to initiatives for common financial support, and increasing one-sided decisions to close the borders. https://www.vecernji.hr/vijesti/dao-ostavku-i-nabrojio-pro puste-eu-u-borbi-protiv-koronavirusa-1392679—www.vecernji.hr. 3. During the five FX interventions during the March 2020 CNB sold to commercial banks 2.2 billion euros. In spite of the monetary operations, the depreciation pressured increased, so March 2020 had the largest depreciation of HRK vs. euro since December of 2008. 4. More: https://www.cdc.gov/flu/pandemic-resources/national-strategy/ intervals-framework.html. 5. Based on the initial data (Mari´c 2020) so far 500,000 employees have requested a payroll subsidy. For March and the following months, they

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will receive reduced pay. If we add to this the increased number of unemployed who will receive only unemployment benefits, it will macroeconomically mean about 2 billion Kuna less personal consumption. Due to reduced salaries, public revenues will be about 1.2 billion Kuna less per month. If investments make up approximately 20% of GDP and if they have fallen by 60% and maybe even more, the loss of aggregate investments is around HRK 3.8 billion per month. This gives a total of about seven billion kunas. This accounts for about 1.9% of GDP without including the dynamics of falling imports and exports. Therefore, an estimate for the Republic of Croatia of the potential monthly decline in GDP at the time of shutting down the economy of approximately 2% can be used. If we assume that the lockdown will last for three months and that in the optimistic scenario the recovery and revival of economic activity will then take another three months, then this gives a significant decrease in GDP of about 10% (35–40 billion kuna). It is quite reasonable to expect the possibility of another and perhaps more lockdowns that will further stop the economic activity. New lockdowns would prolong the recession for six months and make recovery much slower than the previous optimistic scenario. In such a scenario, the fall in GDP could be twice as large. In that case, the fall in GDP could be 50–60 billion kuna. The length of the recovery phase will be strongly influenced by expectations and the speed of recovery in the countries that are Croatia’s main foreign trade partners (Italy, Germany, and BiH) and which belong to the countries with the most serious consequences of the pandemic. 6. The Economist for the G7 forecasts a quarterly decline in GDP for the first quarter of 2020 ranging from 0.3 to 5%. In the second quarter of 2020, a significantly larger decline is expected from −0.4% for Japan to − 10% for more countries (Italy, Germany, France) (The Economist 2020). In the group of countries with an estimate of the largest decline in GDP are Germany and Italy, our largest foreign trade partners. 7. An interesting approach to macroeconomic analysis was offered by Fornaro and Wolf (2020) using the standard framework of the neoKeynesian model with employment on the horizontal axis and changing productivity on the vertical axis. The analysis boils down to the primary effect of the supply shock which is due to the decline in production and leads to a decline in productivity and demand. They see the main problem in the crisis resolution phase in the limitations of the conventional monetary policy due to the proximity of the liquidity trap. That is why they place more hope in fiscal policy, but with too much emphasis on the power of initiating public investments. To solve this crisis, this will be important, but still insufficient and somewhat inappropriate because

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the effect of investments (even public ones) is relatively slow. Particularly informative and noteworthy is the analysis of Surico and Galeotti (2020). 8. These processes are perhaps best illustrated by the example of the education and research system, which almost “overnight” transformed regular work into “online mode.” On some other occasions, such a transformation would take several years. The same applies to examples of rapid digital transformation of some public administration systems. 9. Unicredit (Ed. Silvestre 2020) predicts a decline in GDP in 2020 in the Eurozone by 13% and in the largest EU economies (Germany, France, Italy, Spain, Greece) from 13 to 18.6%. In doing so, they do not predict inflation but slight deflation (which is in line with the model explained in this text). Given a strong fiscal response, they also predict the growth of the fiscal deficit in 2020, which could amount to 11–13%. In terms of the ratio of public debt to GDP, the ratio is projected to increase in all EMU countries by as much as 25–42 percentage points. If these estimates were roughly applied to the macroeconomic crisis program in the Republic of Croatia and assumed a medium scenario of increasing the general government debt to GDP ratio by about 30%, it would mean that we have the “capacity” to increase the debt by about 60 billion kunas. This assessment also coincides with the assessment presented in the first part of this paper. 10. The strategy is as simple as in any war. The most important thing is to stay alive and get out of the war with as little damage possible, because that way you can recover easier and faster. In addition, see Keynes (1940, p. 62) as well as Blanchard and Pisani-Ferry (2020).

References Baldwin, R. 2020. Keeping the Lights on: Economic Medicine for a Medical Shock. Dohva´ceno iz VOX CEPR Policy Portal, ožujak 13. https://voxeu.org/art icle/how-should-we-think-about-containing-covid-19-economic-crisis. Blanchard, O., and D. Leigh. 2013. Growth Forecast Errors and Fiscal Multipliers. IMF Working Paper, WP/13/1. IMF, International Monetary Fund. Blanchard, O., and J. Pisani-Ferry. 2020. Monetisation: Do Not Panic. VOX, CEPR Policy Portal, April 10. https://voxeu.org/article/monetisation-donot-panic. Caizzi, I. 2020. Coronavirus, all’Eurogruppo niente intesa su Mes e eurobond. Salta la conferenza stampa. Corriere della sere, L’Economia, April 8. https://www.corriere.it/economia/finanza/20_aprile_08/coronavirus-alleurogruppo-niente-intesa-mes-eurobond-salta-conferenza-stampa-8548c3c47962-11ea-afb4-c5f49a569528.shtml?refresh_ce-cp.

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Correia, S., S. Luck, and E. Verner. 2020. Pandemics Depress the Economy, Public Health Interventions Do Not: Evidence from the 1918 Flu. Preprint research paper, March 30. https://ssrn.com/abstract=3561560. ECB. 2020. Recommendation of the European Central Bank. European Central Bank, March 27. https://www.ecb.europa.eu/ecb/legal/pdf/ecb_ 2020_19_f_sign.pdf. Economist, T. 2020. Q2 Global Forecast 2020: Coronavirus Sinks Global Growth Forecasts for 2020. Dohva´ceno iz The Economist Intelligence Unit 2020. https://www.eiu.com/default.aspx. Ed. Baldwin, R., and B. Weder di Mauro. 2020a. Dohva´ceno iz Mitigating the COVID Economic Crisis: Act Fast and Do Whatever It Takes. CEPR Press. https://voxeu.org/content/mitigating-covid-economic-crisisact-fast-and-do-whatever-it-takes. Ed. Baldwin, R., and B. Weder di Mauro. 2020b. Economics in the Time of Covid-19. CEPR Press: Economics in the Time of COVID-19. Ed. Silvestre, C. 2020. The UniCredit Economics Chartbook, Quarterly, the Mother of All Recession Has Arrived. Milan: UniCredit, Macro Research. Falck, O., and S. Schonherr. 2016. An Economic Reform Agenda for Croatia. IFO Institute, January 2016. https://www.ifo.de/DocDL/ifo_Forschungsbe richte_70_2016_Falck_Schoenherr_Croatia.pdf. Fornaro, L., & M. Wolf. 2020. Coronavirus and Macroeconomic Policy. VOX CEPR Policy Portal, March 10. https://voxeu.org/article/coronavirus-andmacroeconomic-policy. Gechert, S., and A. Rannenberg. 2014. Are Fiscal Multipliers Regime-Dependent? A Meta Regression Analysis. Dusseldorf: IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute. Keynes, J.M. 1940. How to Pay for the War. London: Macmillan and Co., Ltd. Mari´c, J. (2020). Na burzu stiglo 10 tisu´ca novih nezaposlenih, na “Vladinoj pla´ci” u Hrvatskoj cˇ ak pola milijuna ljudi. Novi list, 7. travanj 2020. OECD. 2020. OECD Updates G20 Summit on Outlook for Global Economy. Dohva´ceno iz OECD, March 27. https://www.oecd.org/newsroom/oecdupdates-g20-summit-on-outlook-for-global-economy.htm. Oliver, L. 2020. It Could Take Three Years for the US Economy to Recover From COVID-19, March 30. Retrieved From World Economic Forum. https:// www.weforum.org/agenda/2020/03/economic-impact-covid-9/?utm_sou rce=sfmc&utm_medium=email&utm_campaign=2715687_Agenda_weekly3April2020-Campaign&utm_term=&emailType=Newsletter. Surico, P., and A. Galeotti. 2020. The Economics of a Pandemic: The Case of Covid-19. Dohva´ceno iz London Business School, March 23. https://icsb. org/wp-content/uploads/2020/03/LBS_Covid19_final.pdf.pdf.pdf.pdf-1. pdf.pdf.

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Valero, J. 2020. Commission Proposes Unprecedented Suspension of EU’s Fiscal Rules. Euractiv, March 20. https://www.euractiv.com/section/eco nomy-jobs/news/commission-proposes-unprecedented-suspension-of-eus-fis cal-rules/.

PART II

Economics Policies during COVID-19

CHAPTER 5

Central Bank’s Balance Sheet Management in Times of Systemic Crises Ivan Lovrinovi´c, Martina Soleniˇcki, and Karlo Vujeva

5.1

Introduction

In normal economic conditions, the monetary policy of central banks is reduced to the use of the interest rate as the main instrument. Put differently, if the business cycle is behaving as expected, the central bank is serving its dual role as (a) the monetary authority over inflation rate and (b) the lender of last resort (LOLR) toward the banking sector. In such a situation, the central bank’s balance sheet serves only for various adjustments aimed at ensuring price stability as a key objective of the

I. Lovrinovi´c (B) · M. Soleniˇcki · K. Vujeva Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia e-mail: [email protected] M. Soleniˇcki e-mail: [email protected] K. Vujeva e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_5

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monetary policy for most countries in the world. However, with the emergence of two systemic crises—The Great Financial Crisis (GFC) and the COVID-19 health crisis—normal conditions cannot be assumed anymore. With a conventional monetary policy, central banks have generally been successful in maintaining stable inflation and thus fulfilling their mandate. By manipulating the reference interest rate, they gave signals to the market and made efficient conduct of monetary policy, especially after the introduction of the Taylor rule. However, in the period up to 2007, conditions were created for the emergence of market distortions and bubbles of which the US housing market became the culprit. Then, as is well known, GFC happened. Consequently, maintaining an inflation rate of up to 2% was no longer an overarching immediate goal for central banks; financial stability became imperative in the short term due to the significance of the financial crash. However, the short term became a decade for most central banks, and now, the COVID-19 health crisis prolonged this “new normal” indefinitely. To be more precise, with the onset of the GFC, central banks resorted to new instruments to compensate for the constraints of monetary policy. Firstly, it was the introduction of macroprudential regulation, which achieved its most important changes in redefining the protective layers of capital, primarily banks. This is evident in the innovated Basel standards. But, in addition to this, central banks of most developed countries—as a response to the sluggish growth in the conditions of the liquidity trap and “secular stagnation” (Summers 2014)—started to conduct unconventional monetary policy on a grand scale. In other words, they started to conduct what is now known as “quantitative easing” (QE). As a direct consequence, the sizes and structures of their balance sheets have dramatically changed. Thus, throughout the years, the central banks’ balance sheet has become the main instrument of monetary policy in the aftermath of the GFC and COVID-19 recession. At the same time, a major asset in central banks’ balance sheets has become (public) debt. This could prove to be a major problem once when the counter-cyclical policy would demand higher interest rates. In the conditions of low inflation with a debt burden higher than before, this could potentially lead to an inability to conduct symmetrical (restrictive) monetary policy and/or enhance the probability of a prolonged crisis, for which the existing institutional framework has no apparent solution beyond the rise of inflation. In this paper, we analyze this change and discuss its structural characteristics and possible consequences. In doing so, we compare the sizes

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and structures of central banks’ balance sheets among various groups of countries, noting the most important differences between them. These groups are (a) USA, Japan, the Euro area and the UK, (b) EU member states that have adopted the euro, and (c) EU member states that have retained their currency. In the last group mentioned, special attention is paid to the central banks of Central and Eastern Europe (CEE). The structure of the paper is as follows. After the introduction, Chapter 2 gives a contemporary macroeconomic context of the liquidity trap and discusses the changing role of monetary policy after 2008. Chapter 3 summarizes stylized facts and trends in size, structure, and role of central banks’ balance sheets. In Chapter 4, we analyze CB’s balance sheets of various countries in detail. Finally, before the conclusion, in Chapter 5, we discuss findings, make some future considerations and provide policy implications.

5.2

Liquidity Trap and the Transformation of Monetary Policy

With the onset of the GFC in 2008 and the COVID-19 health crisis in 2020, there has been a rapid spread of the crisis through various channels. However, one structural characteristic of advanced economies that is especially distinguished after 2008 is the prevalence of low (and negative) interest rates. They came to be mostly due to the monetary policy reaction in the zenith of GFC. But, due to slow and sluggish growth in the postGFC years, they came to stay, effectively locking advanced economies in the situation of a liquidity trap. Of course, the environment of liquidity trap made further conventional interest rate policy ineffective: after the initial interest rate reduction, further expansionary monetary policy through interest rate channel was not possible due to zero lower bound (ZLB). In other words, with the onset of the GFC, central banks tried to restore the internal balance and stabilize financial markets by (a) lowering interest rates toward zero and (b) proving liquidity in the LOLR capacity. However, the desired effects were achieved only in part: while they did eventually stabilize financial markets, they did not stimulate aggregate demand and credit activity on the desired level. One plausible explanation is a well-known fact: commercial banks naturally behave pro-cyclically, thus, a traditional transmission mechanism would not be enough.

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When central banks realized that the traditional transmission mechanism has deteriorated, they turned to a novel monetary policy instrument—their balance sheet—which proved to be a powerful (albeit controversial) instrument of unconventional monetary policy. Specifically, central banks have taken over certain functions and activities that until then were used exclusively by commercial banks and market makers in financial markets, such as buying various debt and equity securities, directly granting loans to certain and especially important non-financial entities, which was earlier unthinkable. In a different perspective, central banks in the most developed countries were no longer acting as a “Lender of last resort” (LOLR) only for banks, but for the entire financial market and significant private sector companies that belong to the somewhat elusive shadow banking sector. Hence, unconventional has become the new norm, as central banks took on the role of maintaining the stability of financial markets and control over the yield curves. Lender of last resort is generally regarded as a traditional anti-cyclical role of central banks. LOLR doctrine is alternatively known as the “Bagehot’s rule”—which states that the monetary authority should, in the face of panic, lend often and freely, against good and trustworthy collateral. This lending assistance should be done with the aim to aid illiquid but solvent banks, while the loan itself should include a penalty interest rate (Bordo 1990). In modern times, the doctrine is best represented through ELA (Emergency Liquidity Assistance) facility. The main purpose of the LOLR doctrine is to help the financial system in distress, with these stylized operational goals in mind: (1) protect the aggregate money stock (not individual institutions), (2) allow insolvent banks to fail, (3) accommodate solid but temporarily illiquid institutions, (4) charge penalty rates, (5) grant loans only against good collateral, (6) announce these rules before the event of the crisis to minimize uncertainty (Humphrey 1989). If done right, these steps should secure the stability of the financial system and contain the financial panics and bank run to a minimum. While not devoid of controversy, before 2008, LOLR was regarded as the expected stance toward monetary intervention. However, after the GFC, the LOLR role was not just heavily activated, more so, it has been subsequently transformed into the unconventional and much more controversial role.

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This new role of central banks would be more appropriate to name as the explicit debt monetizers. Central banks around the world, in less than one decade, went from conservative bankers to liquidity providers and market makers, and then finally to the main outright purchasers of longterm public and private debt in historically high amounts. Direct evidence of this shift is evident in the record sizes and transformed structures of central banks’ balance sheets. Hence, the balance sheet policy (BSP) could be regarded as the key novel instrument of major central banks. As it will be shown in the following chapters, the COVID-19 recession only continued, albeit more aggressively, already existing trends. But now not only do central banks of advanced economies conduct outright bond purchases, this also applies to a growing number of emerging market economies.

5.3 Central Bank Balance Sheet: The Most Important Instrument of Contemporary Monetary Policy In this part of the paper, we provide a general structure of the modern central bank’s balance sheet, with the focus on the sources of base money creation in the economy. After that, on the example of Bundesbank, we pinpoint that the long-run changes of the balance sheets’s size and structure are to be expected. However, two systemic crises of 2008 and 2020 are not part of these “normal” expectations and they present the divergence from the trend. 5.3.1

The Structure of the Central Bank Balance Sheet

Much can be seen and concluded from the balance sheets of central banks. Its structure does not change on a daily basis, but it is the result and indicator of the concept of monetary policy and its direction of action. Above all, it allows the discovery of base money creation channels and the level of monetary policy sovereignty.1 In Table 5.1, we provide a stylized presentation of the central bank balance sheet. On the assets side, we distinguish three major sources of base money creation; on the liabilities side, we see the distribution of base money and other liabilities of the central bank. The assets and liabilities of the central bank are divided into domestic and foreign. Assets, in

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Table 5.1 Simplified presentation of the central bank balance sheet

Central bank’s balance sheet Assets

Liabilities

Foreign assets (FX reserves)

Currency in circulation Deposits of credit institutions Deposits of the government

Claims on domestic credit institutions Claims on central government Source Authors’ work

abbreviated form, include loans to banks, government loans, and foreign exchange reserves. Liabilities include base money (including currency in circulation and bank deposits), government deposits, and other liabilities. Balance sheet policy can be implemented in three ways: (a) increase the balance sheet without changing its structure (quantitative easing), (b) increase the balance sheet and change its structure, and (c) do not increase the balance sheet but change its structure (qualitative easing). The term “change of structure” refers to the practice when the central bank buys assets that it did not previously hold in its balance sheet, so such assets are called “unconventional” and include a wider range of securities from government to corporate with lower liquidity and higher risk.2 The structure of the central bank’s assets shows whether the central bank is: (a) foreign exchange holder, (b) treasuries holder, or (c) private sector holder. From the structure of liabilities it can be concluded whether the central bank is: (a) note issuer, (b) bankers’ banker, or (c) government’s banker (Pattipeilohy 2016). 5.3.2

Different Forms of Balance Sheet Policies

As it was briefly explained in the previous chapter, balance sheet policy (BSP) has become a key contemporary instrument of monetary policy. Differently, it is a key pillar of transmission within the framework of unconventional monetary policy, enabling central banks to become active direct participants (market makers) in operations with non-banking entities. Even so, the term “unconventional monetary policy” cannot be reduced only to an increase in the balance sheet and a change in its

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structure, because it also includes the deviations from previous “normal” practices. Some examples of these “normal” practices are: (a) CB’s mostly conduct short-term operations,3 (b) CB’s usually trade/accept government securities in refinancing operations as collateral, (c) CB’s usually “do business” only with the banking sector, (d) CBs are the last resort for banks only, (e) CB’s normally pay interest to banks on deposits with CB’s, (f) CB’s traditionally do not announce future measures of the monetary policy. Borio and Disyatat (2009) distinguish four forms of balance sheet policies (BSP): (a) quasi-debt management policy, (b) credit policy, (c) bank reserves policy, and d) foreign exchange interventions as operations expanding the balance sheet of a central bank. These are often undifferentiated and labeled as quantitative easing (QE), but differ in many countries due to the country-specific issues. Also, even though these forms can have various targets, they all share the same objective: to lower yields and reduce credit risks by removing riskier assets from the private sector and thus, shrinking the debt overhang. From the government perspective, the main purpose of quasi-debt management policy is to flatten the yield curve through purchases of sovereign debt, and therefore easing the refinancing costs of the governments. Behrendt (2013) distinguishes the monetization of debt from the monetization of quasi-debt, where quasi-debt means the redemption of public debt on the secondary market. Thus, there is no difference between these two categories except in the method of redemption. The policy of using a central bank balance sheet is significantly different between countries, especially when it comes to asset structure. Central banks that have more precise shaped transmission channels to individual segments of the financial market or banking have more quickly stabilized the negative impacts of both the financial and COVID-19 crises. The dominant term for the BSP in the last decade is “quantitative easing” or QE. It was first seen in Japan even before 2008. In a broader sense, QE represents a whole spectrum of transactions between the central bank and the (public) debt markets. As such, it is an explicit monetary tool by which the balance sheets expand. However, QE does not need to involve only public debt; when it involves private securities with the aim to improve credit conditions for the private sector, it is often named “credit easing” (Bernanke 2009). In the early days of GFC, “credit easing” was widely used by central banks (for example, by the Fed through purchases of mortgage-backed securities (MBS), by the ECB through its Securities

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Market Program (SMP), and by the Bank of England through its Asset Purchase Facility (APF). The third form of BSP (bank reserves policies) aims to affect directly the quantity of reserves that private banks hold at the central bank. Obviously, this is done with the aim of expanding the money supply via increased reserves and, by doing so, stabilizing the national interbank market (Behrendt 2013). Finally, the fourth form involves foreign exchange interventions. The purchase of foreign exchange by the central bank is a way to increase the balance sheet, and it is a very common practice in smaller and open economies. 5.3.3

Monetary Transmission Mechanisms Based on the Central Bank’s Balance Sheet

Two main channels through which the monetary policy based on the balance sheet as the main instrument mainly works are the portfolio balance channel and the signaling channel. Other channels through which balance sheet policies may impact the financial markets and the economy include market liquidity channel, confidence channel, and bank lending channel (Joyce et al. 2011). Figure 5.1. shows stylized QE transmission mechanism. The portfolio balance channel is an extremely important channel in the policy of quantitative easing and the way it works is basically simple. It boils down to the fact that there are different asset classes that are not perfect substitutes in portfolios formed by investors. The central bank can buy large quantities of certain assets and thus influence its price and yield. This further affects spreads on other types of assets based on arbitrage transactions. If large purchases of assets by the central bank lead to rising prices and falling yields, this can further have positive consequences for the economy. Falling interest rates make investments cheaper and easier to refinance expensive debts. In this case, business investments and consumption of citizens (purchase of houses, cars) are encouraged, which increases consumption as the main engine of GDP growth. The increase in consumption and GDP also increases profits, and the rise in securities’ prices encourages more and more investors from the real economy to invest in financial markets, which further increases prices, especially stocks. This can lead to the creation of price bubbles and create new problems.

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CB's securities purchases

Confidence

Policy signaling

Portfolio rebalancing

Market liquidity

Asset prices and the exchange rate

Money

Bank lending

Cost of borrowing

Total wealth

Spending and income

Inflation target

Fig. 5.1 Stylized QE transmission mechanism (Source Joyce et al. 2011)

The portfolio balance channel’s effectiveness depends on the subjects whom they are bought from as well as on the type of the assets bought. Monetary policy through portfolio balance channel is more effective if central banks buy assets, which are held by other institutions rather than banks since most of the banks use acquired liquidity to improve their balance sheets, so the liquidity doesn’t reach the real economy. Furthermore, the effects of monetary policy through portfolio balance channel depend on the type of assets central bank purchases through QE. For example, if the central bank purchases longer maturity securities, this will reduce the long-term interest rates and result in flattening the yield curve. Other example includes purchases of specific securities, like mortgage-backed securities (MBS), which provide liquidity to the specific segment of the financial market especially distressed in the wake of the crisis, lower MBS yields and consequently mortgage interest rates. Central banks (Fed, ECB, and BoE) used various measures and instruments of targeted action on individual segments of the financial market

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in order to establish balance and maintain it. Purchases of illiquid assets result in higher market liquidity, lower liquidity premium and encourage trading in these markets—market liquidity channel. The signaling channel includes all the information that market participants can draw about future monetary policy stance based on the central bank’s balance sheet policies. The central bank purchases of different securities send signals to the market participants and overall public about the central banks being determined in fostering economic recovery that can result in higher confidence in specific parts of financial markets, as well as the overall economy. So it is evident that the signaling channel and confidence channel are tightly connected. Both depend on market expectations and effectiveness of the both is conditioned by the central bank’s credibility. The Bank lending channel implies that higher banks’ reserves as a result of central bank balance sheet policies will be transferred to the economy by lending to households and companies which will result in higher consumption, investment, and GDP. The bank lending channel is relatively weak in times of crisis since banks absorb liquidity to improve their own balance sheets weaken as a result of losses in the value of their assets and rising non-performing loans. 5.3.4

Long-Run Changes of CB’s Balance Sheet: Example of Bundesbank

The structure and size of central banks’ balance sheets have evolved through time in accordance with overall changes in the economy. We can briefly examine this long-run structural change on the historical example of the Bundesbank. The structure of the Bundesbank’s balance sheet has changed considerably through the years. In 1970, its balance sheet was 77.3 million DEM. It should be noted that these are volatile times for monetary policy, as the Nixon shock happened only one year after.4 Due to uncertainty, 20% of Bundesbank’s assets were gold, which is relatively significant. However, by 1980, gold’s share is much lower at around 7%. The largest share in both years mentioned is the “balance with foreign banks and money market investment abroad.” In essence, this represents foreign assets. In 1970, foreign assets had a 37% share in total. In 1980, this share was 23%. In addition to this, we emphasize the significance of the “domestic bill of exchange” which accounted for 18% of total assets in 1970 and 21% in 1980. Bills of exchange had an important role as a bridge between the real and monetary economy because the production

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of various goods was backed by the creation of base money. Its role was to provide liquidity to the real economy and to send signals to the central bank about the possible weaknesses in the economy. Of course, Bundesbank was in charge of setting refinancing conditions versus the banking sector (Bundesbank 1970). On the liabilities side of the Bundesbank’s balance sheet, in both years, item “Banknotes in circulation” dominated (47% in 1970, 45% in 1980). The second most important item was “Deposits of banks” (34% in 1970, 29% in 1980). In addition to this, in 1970 there was an item called “Anticyclical reserves” (7% of total liabilities) that served for the intervention against the undesirable parts of the business cycle. Fast forward to 2019, the balance sheet of the Bundesbank looks considerably different, due to the fact that Germany accepted the euro and is part of the Eurosystem. On the assets side, two items became very significant: (a) Securities of euro area resident in euro (for monetary purposes) and (b) Intra-Eurosystem claims (which mostly reflect Target2 imbalances). In 2019, the former contributed 32% of assets and the latter to 51%.

5.4 Comparative Analysis of the Central Banks’ Balance Sheets While we have seen that the changing size and structure can be expected long-run phenomenon, this is not what we have witnessed in the last decade. Due to the severity of the GFC and COVID-19 crisis, central banks’ balance sheets grew several times, on an unprecedented level. For example, Fig. 5.2 shows that, compared to the levels in 2007, Fed’s balance sheet in 2020 is more than eight times higher, BoE’s is more than 11 times higher, BoJ’s is more than six times higher and Eurosystem’s is more than four times higher. Due to the effects of the two crises, it would be easy to conclude that it is a cyclical trend. However, these were not normal business cycle recessions. Even before the COVID-19 influenced groundbreaking monetary expansion, balance sheets were already at historically record levels. And, as we will show, this was the case even in 2019, more than ten years after the start of GFC. That alone pinpoints the structural characteristics and/or paradigm shift in the conduct of monetary policy. COVID-19 interventions only exacerbated this structural trend (Fig. 5.2).

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14

12

10

8

6

4

2

0 United States

United Kingdom 2007

Japan 2019

Eurozone

2020

Fig. 5.2 Growth of major central banks’ balance sheets (normalized so that 2007 = 1) (Source Central banks’ statistics; WDI; authors’ work)

Based on a comparative analysis of the balance sheets, it can be concluded which money issuance channel it uses the most, to what extent it is sovereign in domestic money issuance, and to what extent it responds effectively to the economic shock. It is also evident to what extent central banks monetize government, financial and non-financial sector debt, and thus the degree of their impact on financial markets.5 ,6 Consequently, this part of the paper takes a closer look at the structure and size of the balance sheets of three groups of countries: (a) USA, EA, UK and Japan, (b) the eurozone member states and (c) members of EU outside of the eurozone. 5.4.1

Comparison of Major Central Banks: Fed, Eurosystem, BoE, and BoJ

Major central banks are naturally the trend-setters. What they do historically becomes the norm and distinguishes one monetary era from the other. All of these banks—with the odd exception of the Bank of Japan (BoJ)—were more or less traditional, conservative central banks before 2008. Then, when the US housing market went down, Fed—led by Ben Bernanke—acted very aggressively in a Keynesian way with a number of

5

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novel monetary tools. Other banks followed, albeit some with considerable and costly delays (such as ECB). As a consequence, both sizes and structures of their balance sheets’ have experienced considerable changes. Because of this, we take the last year before the GFC as our starting point of analysis and compare it with 2019 and 2020. The crucial year for the analysis is not so much 2020—which expectedly shows record growth due to COVID-19 induced interventions—but 2019, because it implies that the growth and transformation are secular. Figure 5.3 shows the change in sizes of major central balance sheets in comparison to its country GDP. What is immediately evident is the unprecedented growth of BoJ’s balance sheet. It went from 21% of nominal GDP in 2007 to over 100% in 2019 already. COVID-19 health crisis drove it even further over the size of Japan’s GDP. Other examples are more conservative, but still significant. For example, Eurosystem’s combined balance sheet is now over 50% of euro area GDP, while the Fed’s balance sheet rose from 6 to 32% of GDP in the analyzed timespan. Not only did the size of these balance sheets change, their structure also went through a considerable transformation. By a large margin, this is due to the unconventional monetary policy of quantitative easing (QE) that became the norm in the aftermath of the GFC. Figure 5.4 shows the 1.4 125%

1.2 103%

1

0.8

56%

0.6

0.4

27% 21%

19%

0.2 6%

39%

35%

32%

17%

5%

0

United States

United Kingdom

CB Balance Sheet / GDP (2007)

Japan

CB Balance Sheet / GDP (2019)

Eurozone CB Balance Sheet / GDP (2020)

Fig. 5.3 Central bank balance sheet to nominal GDP (2007/2019/2020) (Source WDI; central banks’ statistics; author’s calculation)

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1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Fed

BoE Securities 2007

Eurosystem Securities 2019

BoJ

Securities 2020

Fig. 5.4 Securities as a percentage of total assets (2007/2019/2020) (Source Central banks’ statistics; authors’ work)

securities as a percentage of total assets in major banks’ balance sheets in 2007, 2019, and 2020. Generally, we can distinguish three contemporary periods regarding the central banks of the most developed countries. First, in the years leading up to the crisis, diversity in the balance sheet structure increased. However, during the global financial crisis in 2007–2009, this trend was reversed and the structure of central bank balance sheets became more homogeneous. The supply of money to the banking sector increased by increasing the central bank’s lending to banks. However, from 2009 onwards, the trend of heterogeneity in the structure of balance sheets of the Eurosystem members has been intensifying again (Pattipeilohy 2016). Table 5.2 shows the detailed asset structure of the world’s most important central banks, analyzing in parallel the structure in pre-crisis 2007 and “pre-crisis” 2019—which captures structural trends after the GFC and the global liquidity trap—and finally, 2020 that is characterized by the COVID-19 interventions. As it can be seen, Fed’s balance sheet grew from $890 billion in 2007 to $4.16 trillion in 2019 already and then finally to $7.36 trillion in 2020. Similarly, the BoE’s balance sheet experienced growth from £39 billion in 2007 to over $950 billion in 2020. The BoJ’s balance sheet size rose from 113 trillion JPY in 2007 to 690

754.612 7.053 96.044 67.390

3.751.189 461.368 2.847.102 491.689

6.730.731 759.116 3.900.861 539.560

47.045 31.552 637.175 37.982

234.982 136.222 624.232 54.328

57.701 130.515 1.792.839 104.895

2020

2007

2019

Lending to credit institutions 2020

2007

2019

Securities

22.640 – 177.106 5.227

2007

FX assets

20.571 12.106 371.730 25.966

2019

Assets’ structure of the major central banks (2007/2019/2020)

22.429 8.976 381.278 8.652

2020

890.662 39.363 1.507.981 113.426

2007

Total 2020 4.165.591 7.363.351 601.583 959.000 4.671.425 7.014.661 604.484 690.026

2019

Notes Data is given in LCU (EUR, GBP and USD in millions, JPY in billions); Methodology differs among central banks, because of that some discrepancies are possible in the structure of the claims/liabilities between various central banks Source Central banks’ statistics; authors’ work

Fed BoE Eurosystem BoJ

Table 5.2

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trillion JPY in 2020. Finally, the Eurosystem’s balance sheet grew from e1.5 trillion in 2007 to over 7 trillion euros in 2020. In all of these central banks’ balance sheets, we can see the following: (a) overall balance sheet’s size grew at a historical level already between 2007 and 2019, (b) 2020 has significantly accelerated already existing trends, (c) major component of the balance sheet’s growth are the securities. Having this in mind, the relationship between contemporary fiscal and monetary policy becomes clearer, as central banks’ swap bonds (mostly government bonds) for base money, inflating their own balance sheets in return. Consequently, the most fundamental change is visible in the strong growth and dominance of bonds on the asset side of all listed central banks here (Table 5.3). Each of these central banks had a net increase in the relative share of securities in its balance sheet portfolio in the observed period. At the end of 2020, government securities had a 91% share of total Fed’s assets; for the BoJ it was 78, 79% for BoE7 and 56% in the case of the Eurosystem. And according to the survey done by BIS (2019), almost 73% of all securities purchased between 2008 and 2018 were government securities. This is a major change versus 2007 pre-crisis levels, especially in the case of the BoE and the Eurosystem. In 2007, securities made less than 18% of all assets in the BoE’s balance sheet and only 6.4% in the case of the Eurosystem. In the case of the Euro area, in addition to bonds, bank lending has remained significant due to the bank-centric nature of the European financial system. This is especially evident in 2020 when lending to euro Table 5.3 Assets’ structure of the major central banks, as a percentage of the total amount (2007/2019/2020) Securities

Fed BoE Eurosystem BoJ

Lending to credit institutions

FX assets

2007 (%)

2019 (%)

2020 (%)

2007 (%)

2019 (%)

2020 (%)

2007 (%)

2019 (%)

2020 (%)

84.7 17.9 6.4 59.4

85.7 76.7 60.9 81.3

91.4 79.2 55.6 78.2

5.3 80.2 42.3 33.5

5.6 22.6 13.4 9.0

0.8 13.6 25.6 15.2

2.5 0.0 11.7 4.6

0.5 2.0 8.0 4.3

0.3 0.9 5.4 1.3

Source Central banks’ statistics; authors’ work

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area credit institutions rose from e624 billion in 2019 to e1.79 trillion in 2020. However, the vast majority of this increase is not made up of traditional LOLR short-term financing measures but longer-term refinancing operations. Table 5.4 showcases a stark contrast between 2007 and 2020. In 2007, the majority of lending was done through “Main refinancing operations,” representing short-term liquidity provisions. In 2020, almost all of the lending is longer term. When it comes to countries like the US, Japan, Euro area, and the UK, it should be emphasized that their currencies are also “world money,” so they do not need much foreign exchange reserves in central bank balance sheets compared to less developed countries whose currencies do not play such a role. The Fed, BoJ, and BoE had about 1% of foreign currency in their assets in the observed period. Eurosystem had 5.4% of assets in 2020 consisting of foreign reserves. While the rest of the world increased the quantity of foreign exchange reserves in order to preserve international liquidity, countries whose currencies are “world money” increased the amount of gold as a basis for liquidity. Although gold has long been officially demonetized, it still plays an important role in maintaining confidence in these currencies. Gold has once again proved to be a more important pillar of security, confidence, and international liquidity in these countries in times of fundamental uncertainty. Having said this, Eurosystem had a relatively larger share of foreign assets before the financial crisis than the other major central banks. As noted by Nagel (2012), this was a relict of the past (before the launch Table 5.4 Lending to EA credit institutions by Eurosystem (2007/2020), in millions of EUR Lending to EA credit institutions in EUR 2007 1. Main refinancing operations 2. Longer-term refinancing operations 3. Fine-tuning reverse operations 4. Structural reverse operations 5. Marginal lending facility 6. Credits related to margin calls Total Source ECB; author’s work

2020 368.607 268.476 0 0 22 2 637.107

234 1.792.574 0 0 0 0 1.792.808

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of the monetary union) when many national central banks managed the exchange rate and, in that capacity had accumulated large amounts of foreign exchange reserves. On the liabilities side (Table 5.5), “Liabilities to credit institutions” are growing the most, namely, the excess reserves as a direct consequence of large-scale QE policies after the GFC and the European debt crisis (and most recently, due to the COVID-19 recession). To highlight the structural trend once again, we can take a closer look at the US first. In the Fed’s balance sheet, liabilities to credit institutions have been rising from $52 billion in 2007 to $2 trillion in 2019 and $3.54 trillion in 2020. Such a high level in 2019 persisted even though Fed actually tried to deflate its balance sheet in the years past. Then 2020 happened, and with it continued balance sheet growth. In the case of other central banks, liabilities to credit institutions also account for the largest part of growth. In the UK they rose from £20 billion in 2007 to £767.8 billion in 2020, in Japan from 26 trillion JPY in 2007 to 518 trillion JPY in 2020, and in the Euro area from e379 billion in 2007 to e3.57 trillion in 2020. 5.4.2

Comparison of the Balance Sheets Euro Area’s Central Banks

Euro area’s (EA) central banks greatly vary in size and importance for the overall conduct of the Eurosystem’s monetary policy. Logically, their structure can also be heterogeneous. However, the growth trend is apparent in all of the eurozone’s central banks between 2007 and 2019, as can be seen in Fig. 5.5. The largest central bank’s balance sheet growth was in Finland, followed by Latvia, Portugal, and Spain. Though, the most interesting cases are those of Germany on one side and Italy and Spain on the other side. Firstly, due to their sizes and importance. Secondly, due to the growing Target 2 imbalances between them specifically (ECB 2021). Growth of euro area balance sheets’ is perhaps better represented in terms of GDP. Figure 5.6 shows this in the selected countries of the euro area. Again, the most interesting cases are those of Germany on one side and the south periphery on the other side (Greece, Italy, Portugal, Spain). As it is now well accepted, ECB did not intervene in the GFC with the same resolve as did for example Fed. Initially, ECB was focused on minimizing the credit and counterparty risk that was threatening interbank

2019

2020

2007

2019

2020

Liabilities to credit institutions 2007

2019

2020

Liabilities to other residents

791.801 1.754.066 2.037.973 52.371 2.014.136 3.547.616 4.529 351.934 1.613.514 38.449 74.171 85.394 20.778 495.406 767.807 12.602 86.721 – 676.678 1.292.742 1.443.564 379.307 1.823.246 3.570.863 48.673 319.703 621.330 76.461 109.616 113.572 26.335 471.292 518.429 3.505 12.633 47.158

2007

Banknotes in circulation

Structure of liabilities of the largest central banks (2007/2019/2020)

2019

2020 890.662 4.165.591 7.363.351 39.363 601.583 959.000 1.507.981 4.671.425 7.014.661 113.426 604.484 690.026

2007

Total

Notes Data is given in LCU (EUR, GBP and USD in millions, JPY in billions); Methodology differs among central banks, because of that some discrepancies are possible in the structure of the claims/liabilities between various central banks Source Central banks’ statistics; authors’ work

Fed BoE Eurosystem BoJ

Table 5.5

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5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

Fig. 5.5 Percentage growth in the size of euro area central bank balance sheets (2007/2019) (Source Central banks’ statistics; author’s work) 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

CB Balance Sheet / GDP 2007

CB Balance Sheet / GDP 2019

Fig. 5.6 Selected balance sheets’ sizes in the euro area versus GDP (2007/2019) (Source Central banks’ statistics; WDI; author’s work)

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markets and with it the monetary transmission mechanism of the eurozone. Of course, the structure of external financing for the non-banking sector was significantly different. Bank financing accounted for around 70% of total external financing in the euro area. In the US, around 80% of total external financing was accounted for by market-based sources (such as bond issuance), making the early QE policies much more natural and potentially more efficient in the US (Dell’Ariccia et al. 2018). Now let’s turn to the detailed structure of the eurozone. The assets of the balance sheets of the central banks of the Eurosystem members consist of domestic and foreign assets. The most important items on the assets side are “Securities of euro area residents denominated in euro,” “Lending to EA credit institutions,” and “Intra-Eurosystem claims.” The key items on the liabilities side are “Banknotes in circulation,” “Liabilities to EA credit institutions,” and “Intra-Eurosystem liabilities.” Table 5.5 shows the detailed assets’ structure of the EA central banks’ balance sheets between 2007 and 2019. What is immediately apparent is the vast growth of balance sheets’ sizes between these years. It is very important to notice that this growth does not account for COVID-19 induced growth in 2020, pointing to the structural trend of growth due to the aftermath of GFC and the European debt crisis. Furthermore, there are noticeable differences in structure between compared years. In 2007, “Lending to EA credit institutions” is the most significant item on the assets side, as it has the highest share in most countries. This is to be expected in “normal times” as the central bank acts as the lender of last resort in times of distress. However, in 2019, the contrast is more than evident: “Securities of EA residents” are by far the most dominating item, reflecting the paradigm shift in the conduct of monetary policy toward the unconventional, longer-term outright purchases of securities. On the liabilities side, 2007 balance sheets are again structured as expected (Table 5.6). “Banknotes in circulation” is growing expectedly with the higher economic activity through the years. On the other hand, “Liabilities to EA credit institutions” have been rising much more, as a direct consequence of base money creation through the QE policies in the years in between, especially from 2015 onwards. Except for the record growth of balance sheets’ sizes and the transformed nature of the base money creation, one more item drew much attention around the time of the European debt crisis in the case of EA central banks: “Intra-Eurosystem liabilities.” Specifically, the main

4.633 5.109 *= *= 6.863 14.511** 0 10.518 9.883 0 *= *= 2.085 *= 8.611 14.932*’ *= 2.103 29.341

67.706 119.704 6.131 5.661 47.789 589.552 568.254 75.075 64.542 452.029 8.721 11.283 7.406 1.349 120.165 62.665 22.406 11.355 359.886

1361.4% 2243.0% *= *= 596.3% 3962.5% N/A 613.8% 553.1% N/A *= *= 255.2% *= 1295.5% 319.7% *= 439.9% 1126.6%

12.694 56.311 *= *= 230 71.055 267.955 8.727 39.449 28.07 *= *= 32.914 *= 45.961 2.464*** *= 156 71.373

17.369 19.279 9 23 4.648 95.274 75.681 7.651 2.032 220.141 12 48 4.724 40 26.791 17.325 533 995 130.515

2019

2007

07–19 (%)

2007

2019

Lending to EA credit institutions

Securities of EA residents in EUR

36.8% −65.8% *= *= −98.0% 34.1% −71.8% −12.3% −94.8% 684.3% *= *= −85.6% *= −41.7% 603.1% *= 537.8% 82.9%

07–19 (%) 19.964 25.502 *= *= 7.465 76.766 83.951 1.443 568 43.743 *= *= 18.399 *= 13.759 13.405 *= 2.576 4.786

2007 36.175 7.939 10.767 2.242 62.604 129.972 908.356 9.978 36.315 52.149 5277 2957 192.150 5.62 109.038 49.193 10.157 3.748 147.962

2019 81.2% −68.9% *= *= 738.6% 69.3% 982.0% 591.5% 6293.48% 19.2% *= *= 944.4% *= 692.5% 267.0% *= 45.5% 2991.6%

07–19 (%)

Intra-Eurosystem claims

Eurozone central banks asset structure (2007/2019), in millions of EUR

61.946 112.356 6.265 2.336 22.809 360.707 483.674 42.660 53.528 244.376 4.226 5.325 59.009 2.883 102.107 38.670 13.782 8.360 175.228

2007

Total

154.849 181.789 18.418 9.336 126.250 1.141.544 1.779.846 109.154 116.376 960.383 18.745 19.700 207.256 9.288 301.087 159.785 52.283 18.814 716.220

2019

150.0% 61.8% 193.9% 299.6% 453.5% 216.5% 267.9% 155.9% 117.4% 293.0% 343.6% 270.0% 251.2% 222.2% 194.9% 313.2% 279.4% 125.0% 308.7%

07–19 (%)

*Claims on the Federal Government; **Euro-denominated fixed-income securities; ***Monetary policy operations; *’ Foreign reserve assets (net); * = Countries weren’t part of Eurozone in 2007, thus methodology differs to such extent that direct comparison in this table is not viable Source Central banks’ statistics; authors’ work

Austria Belgium Cyprus Estonia Finland France Germany Greece Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Portugal Slovakia Slovenia Spain

Table 5.6

132 ´ ET AL. I. LOVRINOVIC

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tensions in this item are connected to Target2 imbalances, with creditor countries on one side and debtor countries on the other. The largest surplus in the Target2 payment system has Germany (ECB 2021). IntraEurosystem claims represent Germany’s position of creditor versus euro peripheries, such as Italy or Spain. In other words, these are consolidated claims of Bundesbank versus ECB and other central banks of the Eurosystem (Sinn and Wollmershäuser 2012). Because these are the claims versus other countries of the Eurozone, it essentially represents foreign assets (even though it is a single currency area). It could be argued that this item of Intra-Eurosystem claims reflects incompleteness of the EU as a state project, as significant imbalances prevail to this day in the Target2 system. An alternative perspective on the Target2 system is given by Lavoie (2015) who considers the Target2 payment system as the eurozone’s contemporary variation of Keynes’ idea for the international clearing union. The essence of this idea is the “recycling” of the surplus countries toward the deficit or debtor countries, keeping balance in check. Admittedly, this puts Bundesbank in a precarious position if the euro project ends abruptly. 5.4.3

Comparison of Non-Eurozone EU Central Banks

This section analyzes the balance sheets of central banks that are part of the European System of Central Banks (ESCB), specifically the central banks of EU member states that have retained their national currencies (Bulgaria, Croatia, Czech Republic, Denmark, Hungary, Poland, Romania, and Sweden). First, we will address the general structure of financing of the ESCB central banks. All of these countries are predominantly relied on banks and have significantly lower public debt relative to GDP compared to euro area member states. Before the GFC, many of these countries were in a period of transition, namely the CEE countries. In that time, their central banks’ assets were largely under the influence of state interventionism and sleeve lending to strategic sectors of the economy and target enterprises. After the transition to a market economy, the item loans to the state disappeared and all of them constantly increased the quantity of foreign assets, which came to heavily dominate. Fast forward to the post-GFC economic outlook, non-eurozone countries did not experience rapid growth on such an unprecedented level as did the CB’s balance sheets in the most advanced countries. However, it

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was still apparent in a number of countries. Figure 5.7 compares the size of the balance sheet as a percentage of GDP in 2007 versus 2019 with the data available. The largest increase in the central bank’s balance sheet in terms of GDP was recorded in the Czech Republic; CNB’s balance sheet rose from around 20 to 60% of GDP between 2007 and 2019. Other countries experienced much less dramatic growth. Table 5.7 provides the balance sheet structure in detail. From this table, it can be seen that the most important asset class in the balance sheet of the analyzed central banks is the “Foreign exchange (FX) assets,” ranging from 85 to 99% of total assets, with the exception of Sweden. Riksbank experiences a significant decline in the share of this item to 51% between 2007 and 2019. Accordingly, all central banks (except Sweden) can be classified in the “FX holder” group. Such a dominant share of foreign assets is a consequence of the choice of monetary strategy of these countries, which in this way want to manage the stability of the exchange rate, and through it the key goal—the stability of inflation. In that sense, the volume of base money creation is determined by the given indirect goal (exchange rate). 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Czech Republic

CroaƟa

Hungary

CB Balance Sheet / GDP 2007

Poland

Sweden

CB Balance Sheet / GDP 2019

Fig. 5.7 Central balance sheets of selected non-eurozone central banks (2007/2019) as a percentage of GDP (Source National CB statistics; WDI; authors’ work)

18.052 22.129 *= *= 11.148 128.852 183.781 16.269 7.957 112.213 *= *= 1.414 *= 34.871 15.346 *= 2.899 67.612

2007

34.723 43.190 2.566 3.361 21.712 242.693 313.774 29.539 20.082 201.628 4.666 6.935 3.878 1.247 69.941 27.962 13.670 5.739 142.460

2019 92.3% 95.2% *= *= 94.8% 88.4% 70.7% 81.6% 152.4% 79.7% *= *= 174.3% *= 100.6% 82.2% *= 98.0% 110.7%

07–19 (%)

Banknotes in circulation

6.548 17.789 *= *= 5.910 73.698 109.513 7.107 21.839 42.622 *= *= 10.779 *= 21.528 9.265 *= 356 52.320

2007 40.768 45.443 12.429 4.901 90.403 518.291 560.231 9.108 36.672 101.775 5.660 7.214 100.531 5.433 139.756 19.213 3.012 4.347 108.162

2019 522.6% 155.5% *= *= 1429.7% 603.3% 411.6% 28.16% 67.9% 138.8% *= *= 832.7% *= 549.2% 107.4% *= 1121.07% 106.7%

07–19 (%)

Liabilities to EA credit institutions

25.402 61.659 *= *= 0 12.035 99.498 13.195 12.896 16.244 *= *= 44.786 *= 21.949 6.206 *= 3.490 21.141

2007 46.463 63.974 36 0 0 754 435.764 25.658 18.868 437.846 3.833 861 95.291 300 0 76.976 918 2.815 391.747

2019 82.9% 3.8% *= *= 0.0% −93.7% 338.0% 94.5% 46.3% 2595.4% *= *= 112.8% *= −100.0% 1140.3% *= −19.3% 1753.0%

07–19 (%)

Intra-Eurosystem liabilites

61.946 112.356 6.265 2.336 22.809 360.707 483.674 42.660 53.528 244.376 4.226 5.325 59.009 2.883 102.107 38.670 13.782 8.360 175.228

2007**

Total

Structure of euro area central banks’ liabilities (2007/2019), in millions of EUR

154.849 181.789 18.418 9.336 126.250 1.141.544 1.779.846 109.154 116.376 960.383 18.745 19.700 207.256 9.288 301.087 159.785 52.283 18.814 716.220

2019

150.0% 61.8% 193.9% 299.6% 453.5% 216.5% 267.9% 155.9% 117.4% 293.0% 343.6% 270.0% 251.2% 222.2% 194.9% 313.2% 279.4% 125.0% 308.7%

07–19 (%)

* = Countries weren’t part of Eurozone in 2007, thus methodology differs to such extent that direct comparison in this table is not viable; **Balance sheets’ total was calculated in EUR by using exchange rates from local currency on 31 December 2007 for those countries that was not yet part of the Eurozone Source Central banks’ statistics; authors’ work

Austria Belgium Cyprus Estonia Finland France Germany Greece Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Portugal Slovakia Slovenia Spain

Table 5.7

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Thus, foreign assets are the most important channel for creating base money, and for these countries, we can say that their issue of domestic money is exogenously determined by the size of foreign assets. It is a specific form of the gold standard or currency board. With no currency pegged to gold in our time, instead of gold, the currency of primary countries has become the currency of several countries, whose domestic money also plays the role of world money. Central banks generate a minimum amount of base money ex nihilo, without foreign influence. Their domestic money must have coverage in foreign currency, foreign money which itself has no cover and which these countries create by granting loans to banks or buying government bonds. This is where the degree of sovereignty in the issuance of base money is manifested, which is generally low in most of analyzed non-eurozone countries. Due to the chosen monetary strategy—price stability—which they achieve through the exchange rate, the mentioned central banks are not able to be “government bankers” or “private sector bankers.” It is interesting for all such countries that their public debt is significantly below the average of EU members, while external debt has grown continuously and strongly in relation to their GDP. With the onset of the financial crisis in 2008 and especially the health crises COVID-19 economic policies of the mentioned countries relied primarily on fiscal policy and commercial banks rather than their central banks. Those due to the monetary strategy based on the exchange rate, could not play the role of providers of last resort even remotely compared to the central banks of sovereign central banks and states. That is why the term “exchange office” is increasingly used for central banks whose assets are dominated by foreign assets. Table 5.8 shows the growth of the item “claims on credit institutions” only in Hungary, which is drastic, while in Denmark and Sweden it is significantly reduced. Foreign assets increased in all central banks, mostly in the Czech Republic, Hungary, and Poland. Of particular interest is the “claims on central government” item, which shows that no central bank that is a member of the EU and has retained its own currency has been a “government banker.” Only in Sweden was there a strong increase in this item just before the COVID-19 crisis. This shows that monetary sovereignty is more formal and little used, and the real and key channel for creating base money was foreign assets, i.e., fiat money from other countries. It is obvious that in these countries, the function of lending to the state was taken over by domestic and foreign commercial banks

– 1.883 0 37** 1.749.826 10 0 0

2019 23.255*’ 68.177 719.681 161.722 4.436.866 153.208 101.408 172.556

2007

FX assets

47.094 142.605 3.356.214 404.089 10.082.066 439.924 192.361 460.610

2019 – – 27.833*** 171.313 0 21 –

1

2007

0



2019

– 32.099 39.178 0 0 375.534*

Claims on central government

26.513 75.981 756.510 424.539 4.704.096 170.439 103.803 211.926

2007

Total

50.881 152.406 3.449.848 480.936 12.347.868 489.100 194.556 899.965

2019

Methodology differs among central banks, because of that some discrepancies are possible in the structure of the claims/liabilities between various central banks; all figures are represented in millions LCU. *Includes securities of residents in Sweden denominated in Swedish kronor; **Includes claims re banks’ and mortgage credit institutions’ TARGET accounts; ***Includes domestic bonds; *’Includes cash and deposits in foreign currencies, and financial assets at fair value through profit or loss; Data for Bulgaria is for 2008 and 2019, respectively Source Central banks’ statistics; authors’ work

– 4.178 9 216.794 303 1.552 0 9.129

2007

Claims on credit institutions

Asset structure of balance sheets of central banks of EU member states that have not adopted the euro

Bulgaria Croatia Czech Republic Denmark Hungary Poland Romania Sweden

Table 5.8

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with significantly higher interest rates, while at the same time the world’s largest central banks financed their countries in huge amounts by buying government securities. “Money in circulation” from 2007 to 2019 increased in all of the listed central banks except Sweden (Table 5.9). It grew the most in Hungary, the Czech Republic, and Poland. “Liabilities to banks and other financial institutions” increased in all of these central banks, except Romania. The highest growth was recorded in the Czech Republic, Sweden, and Poland. “Government liabilities” increased at all of these central banks, with the exception of Denmark. 5.4.4

Individual Analysis Between Selected CEE Countries in the COVID-19 Health Crisis

After acknowledging the mild structural trends between 2007 and 2019, what follows now is an individual brief analysis of the measures of selected individual central banks, monetary and fiscal policy of EU member states that have not adopted the euro, in the fight against the COVID-19 crisis. Countries analyzed here are Hungary, Czech Republic, Poland, Romania, Croatia, and Bulgaria. Hungary The balance sheet of the Hungarian central bank “Magyar Nemzeti Bank” (BNK) in 1998 was 5.672 billion forints (HUF), at the end of 2007 4.632 and in 2020 20.393 billion. From the above data, it can be concluded that the balance sheet of the MNB by the end of 2007 decreased, but from then until the end of 2020 increased 4.4-fold. There was a significant change in the structure of MNB assets in 2013 when there was an increase in bank loans to about 700 billion HUF, in 2015 twice as much and at the end of 2020, this item reached HUF 4.462 billion. In 2018 there was a stronger increase in the item “securities” which amounted to HUF 441 billion at the end of the year, and at the end of 2020. 2.382 billion HUF. The item “foreign assets” in 1998 accounted for 37% of total assets, at the end of 2007 over 90% and retains such a share until 2015. At the end of 2020, it fell to 63%. In the same period, the item “loans to residents” accounted for 22% and securities for 12% of total assets. The largest and fastest growth of the MNB balance sheet occurred in 2020 due to the COVID-19 crisis, when it rose from HUF 12.815

19.104 30.976 644.367 70.551 6.530.351 238.777 86.235 64.488

2019 5.006 46.888 279.197 209.862**’ 1.689.562 33.158 64.682 143

2007 14.462 74.624 2.408.337 230.556*** 2.296.997 130.395* 43.057 117.666

2019

Liabilities to banks and fin. institutions

7.487 216 152.359 89.898 254.946 19.160 8.499 –

2007 8.853 6.712 291.684 3.100 1.342.567 9.326 23.101 314.944**

2019

Government liabilities

26.513 75.981 756.510 424.539 4.704.096 170.439 103.803 211.926

2007

Total

50.881 152.406 3.449.848 480.936 12.347.868 489.100 194.556 899.965

2019

Notes Methodology differs among central banks, because of that some discrepancies are possible in the structure of the claims/liabilities between various central banks; all figures are represented in millions LCU; *Includes Liabilities to other domestic monetary financial institutions related to monetary policy operations and liabilities due to issued securities denominated in domestic currency; **Includes debt certificated issued; ***Includes net current accounts and settlement accounts, and certificates of deposit; **’Includes net current accounts and certificates of deposit; Data for Bulgaria is for 2008 and 2019, respectively Source Central banks’ statistics; authors’ work

9.179 16.007 353.703 61.551 2.188.951 85.994 25.455 114.324

2007

Money in circulation

Structure of liabilities of balance sheets of central banks of EU member states that have not adopted the

Bulgaria Croatia Czech Republic Denmark Hungary Poland Romania Sweden

Table 5.9 euro

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billion in March to HUF 20.392 billion at the end of the same year. So, in those eight months, the balance sheet grew by about 60%, as Hungary announced a large anti-crisis package worth 13.6% of GDP (60% of it was liquidity support and 40% was direct fiscal support). MNB started with the QE policy in May 2020 (Benecki et al. 2020). Hence, COVID-19 crisis led to a strong and rapid increase in MNB’s assets in 2020, especially loans to banks in domestic currency. Liabilities show a strong increase in the items “money in circulation” and “residents’ deposits,” with the latter item being slightly higher, with bank deposits accounting for 63%. Residents’ deposits are at the end of 2020 accounted for 39% of liabilities. In 2020, the Hungarian central bank has started to use government bonds more intensively. Also, it started to use the signal channel with clear announcements of the measures it will take, as evidenced by the following quote: • The MNB’s Government Securities Program Involves Hungarian FixedRate Forint Government Securities. the MNB Will not Restrict the Scope of Maturities of Government Securities to Be Purchased, Nevertheless, Purchases Will Focus on Securities with at Least 3 Years to Maturity. to Prevent the MNB from Becoming a Dominant Market Participant Regarding a Given Government Securities Series, the Amount to Be Purchased of Any Securities Series in the Secondary Market May not Exceed 33 Percent of Stocks Outstanding, in Line with the European Central Bank’s (ECB) Practices…the MNB Seeks to Involve Key Participants in Terms of Market Activity in the Program (Banks and Investments Funds)…the MNB Will Carry Out Purchases Under the Government Securities and the Mortgage Bonds Programs as Long as Economic and Financial Developments Arising from the Coronavirus Pandemic Corroborates It… the Monetary Council Did not Set a Total Amount of Purchases for Either Program. the MNB Will Perform a Technical Revision When Stock Increases Reach HUF 1,000 Billion in Government Securities and HUF 300 Billion in Mortgage Bonds. (MNB 2020)

But, during the COVID-19 crisis, the Hungarian central bank used mostly the bank loan channel in its assets side—which is understandable—since the financing of its economy is heavily dependent on bank loans, while the financial market is poorly developed. There was no significant increase in inflation or liquidity of the real sector. The increase in the amount of domestic currency fits into the policy of the Hungarian

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central bank, which continuously pursues a policy of depreciation of the forint and thus contributes to boosting the competitiveness of domestic production. Czech Republic The balance sheet of the Czech central bank has increased 4.4 times from 2007 until 2021, but its structure has not changed significantly. The main item in the assets was other foreign assets, i.e. foreign exchange reserves, which at the end of 2019 amounted to 90% and at the end of 2020 as much as 98%. In the liabilities of 2007, the most important item was “money in circulation” which accounted for 51%, and “bank deposits ” for 39%. At the end of 2020, the share of money in circulation in liabilities decreased significantly to 19%, but the item “bank deposits” rose sharply to as much as 77%. At the beginning of the COVID-19 crisis, the Czech Republic announced the large anti-crisis program in the range of 12.3% of GDP. Public guarantees constituted 70% of it. However, the program was not supported by the central bank through QE policy, as the Czech central bank (CNB), remains conservative in rejecting the QE and employing it only as the last resort option (Benecki et al. 2020). Poland In contrast to the Czech Republic, Poland did involve its central bank in the anti-crisis program against the COVID-19 recession. Announced measures were in the region of 11.3% of GDP, with very expansionary fiscal policy. But, as Benecki et al. (2020) pinpoint, such bold redistributive measures probably couldn’t be deployed without the central bank’s support. They estimate that the Polish central bank’s support could reach over 10% of GDP and should then be the highest in the region. In the meantime, such an expansion so far did not have a major influence on the exchange rate. On one hand, the central bank did announce asset purchases on a grand scale. On another hand, Poland has a specific monetary sector where strict liquidity control is possible. Specifically, most of the new liquidity is provided through a state-owned bank BGK so the bets against PLN are discouraged. In addition to this, the central bank cut interest rates and frontloaded outright purchases of government securities, which effectively lowered the yield (Benecki et al. 2020).

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Romania Romania’s anti-crisis program has been relatively small at 3.2% of GDP. The majority of that is public guarantees, but the direct support is minor due to pro-cyclical policy in the past. However, the COVID-19 crisis also triggered a change in the monetary policy, as the central bank of Romania started its first QE program in April 2020. Understandably, its scale has been limited due to the exchange rate worries. In addition to the QE, Romania’s central bank cuts its interest rates further (Benecki et al. 2020). The balance sheet of the Central Bank of Romania from the end of 2008 by the end of 2020 increased by 57%, which is significantly less than in Hungary, Poland, and the Czech Republic. The assets of its balance sheet are dominated by the foreign exchange reserves which in 2008 accounted for 97% and in 2020 96% of total assets. The liabilities in 2008 dominated by the bank deposits which accounted for 61%, and money in circulation 24%. At the end of 2019, there was a turnaround, so money in circulation accounted for 44%, bank deposits for 22%, and the government deposits for 11% of total liabilities. The Central Bank of Romania, as can be seen, pursues a very similar policy structure of the assets of its balance sheet, which is almost exclusively based on foreign exchange reserves, so we can also classify it in the group of countries “FX holder.” Croatia The Croatian Central Bank (HNB) has increased its balance sheet since 2007 by mid-2020 2.2 times. The most important item in the assets of the HNB’s balance sheet from 1995 has been “Foreign assets,” which until the middle of 2020 amounted to about 98% of total assets. Such a share of foreign assets has been ever-present since 1995. In the middle of 2020 due to the COVID-19 systemic crisis, the share of foreign assets decreased to 85% and the item of claims on the state increased to 12% of total assets, which had been zero for many years before that. This happened because HNB started outright purchases of the government debt on the secondary market. Therefore, the GFC did not change the structure of the HNB’s balance sheet assets, i.e., the channels for creating base money, but the COVID-19 crisis led to a change when the HNB bought HRK 17.5 billion in government bonds and approved about HRK 4 billion in loans to banks. During the COVID-19 crisis, the banking system remains hyper-liquid, however, the real sector of the economy is struggling with the problem

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of illiquidity. In its monetary strategy, the HNB does not use the interest rate as the initial impulse and main channel of the transmission mechanism but the nominal anchor of the exchange rate and these two variables are excluded. The hyper-liquidity of the banking system is evidenced by the fact that in 2020 the bank accounts with the HNB daily averaged over 40 billion, which is about 30% of the money supply and about 40% of base money. Such a high degree of immobilization of money in bank accounts by HNB speaks of their aversion to risk in times of systemic crisis that can only be reduced by the central bank. This also speaks to the inefficiency of the existing monetary transmission channel. Because the monetary strategy strictly adheres to the stability of the kuna exchange rate against the euro, the HNB cannot use the interest rate. However, HNB can buy securities, which it did for the first time in many years, thus maintaining their prices and lowering yields. In early March 2020 HNB has launched three measures to increase liquidity. The first measure referred to the purchase of government bonds from investment funds, insurance companies, and pension funds, which by a special decision enabled direct participation in the purchase/sale of government securities. From mid-March to the end of June 2020 HNB purchased HRK 17.5 billion in bonds from the aforementioned financial institutions as part of fine-tuning operations. The second measure taken by the HNB in early March 2020 was the granting of loans to banks through structural operations in the amount of HRK 3.8 billion for a period of five years and HRK 750 million through regular operations for a week. The third measure aimed at alleviating the crisis—increasing liquidity in euros—referred to the conclusion of a currency swap agreement with the European Central Bank in the amount of two billion euros. By selling bonds, pension funds and insurance companies transformed their long-term assets into short-term deposits, which further increased already a large amount of excess reserves, i.e., free funds in bank accounts with the HNB. Banks have minimally increased retail lending, while corporate lending has been declining for several years due to uncertainty and risk aversion. The purchase of government bonds of HRK 17.5 billion (10% of the HNB’s assets) was performed with insurance companies, pension and investment funds, and, to a lesser extent, with banks. But this money generated by the monetization of public debt has not entered the channels to improve the liquidity of the real economy.

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Finally, the structure of HNB liabilities in 2007 was dominated by “Base money” and “Limited bank deposits,” which accounted for about 90% of total liabilities. Capital and reserves of banks participated with around 9%. In 2020 there were changes so that base money and limited bank deposits accounted for 66% of total liabilities, but there was an increase in government deposits to 13% of liabilities and liabilities to foreign banks to 7%, while capital and reserves accounted for 11% of total liabilities. Bulgaria Bulgaria’s central bank’s balance sheet increased from BGN 26.5 billion in 2008 to BGN 50.7 billion at the end of 2019. The structure of assets is again constantly dominated by foreign assets, which mostly consist of foreign exchange reserves and foreign securities. Foreign assets in 2008 accounted for about 98% of total assets, and such a structure was maintained at the end of 2019. In the structure of liabilities in 2008 the item “money in circulation” dominated, followed by bank deposits and government deposits. Almost the same structure of liabilities was maintained at the end of 2019. The Bulgarian central bank has officially adopted the currency board regime, so it is clear that it maintains such a large share of foreign assets in the central bank’s asset structure. Of all the former socialist countries, Bulgaria was the only one to formally report its monetary regime to the IMF as a “currency board.” Hungary, Poland, the Czech Republic, Croatia, and Romania have not declared their monetary regimes as currency boards, although they function as ones to a large extent, so it can be said that they have “quasi currency boards” monetary regimes. At the beginning of the COVID-19 crisis, Bulgaria declared a state emergency and enacted economy-wide anti-crisis program involving bank moratoriums, interest-free bank loans, and provisions by the development bank, among others (KPMG 2020). Bulgaria’s central bank strengthened its capital and liquidity base of commercial banks with the amount up to BGN 9.3 billion, however, large-scale QE policies have been missing.

5.5

Discussion and Policy Implications

After we provided a detailed analysis of the central banks’ balance sheet policies, what follows in this chapter are brief summaries of most important trends, differences between groups of countries and finally, a broader

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macroeconomic outlook of the analyzed monetary transformation. In this context, we will provide a stylized set of possible policy implications with the aim of minimizing negative spillovers of such drastic changes. 5.5.1

Summary of the CBs’ Balance Sheets’ Comparisons

We have differentiated between three distinctive groups of central banks. The first one is made of major central banks in the global perspective (Fed, BoE, Eurosystem, and BoJ). Starting with the GFC, these banks were pioneers in the transformation of their balance sheets from short-term loans in times of distress toward long-term debt purchases. The earlier exemption is Bank of Japan, which acted with its own sort of unconventional QE policy even before 2008, as Japan was already dealing with the liquidity trap. Following BoJ, Fed was the most aggressive debt purchaser in the GFC. BoE also followed this pattern and in the post-2008 years, largescale long-term outright purchases have become more common. In the case of the ECB/Eurosystem, things happened more gradually as ECB did act as a lender of last resort to the euro area financial sector; however, the political economy of the eurozone at the time was “hands-off” in regard to guaranteeing the national sovereign debt of its members. Greece was the prime example. Others would follow, if not for the famous Draghi’s ultimatum of “whatever it takes” in 2012 (Draghi 2012). After that, ECB did partake in this transformation, especially from 2015 and beyond with its major asset purchasing programs. More than 70% of all purchase securities have been government-made. Thus, all mentioned central banks can be now called “government’s banker” because they have a significant share of government securities in their assets (albeit, this was not the case for the ECB/Eurosystem in the GFC crisis, only much later). Their foreign assets are small, which is understandable, because their domestic currencies are at the same time the most important world currencies. These are central banks that, in the full sense of the word, pursue a sovereign monetary policy that is reflected in the historically unprecedented volume of monetization of government debt. The second group of central banks are those central banks that are part of the Eurosystem and whose countries constitute the eurozone. There is a need to distinguish them additionally because the Eurosystem is obviously different than BoE or BoJ. And while it is more similar to

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the Fed in organization and functioning, the eurozone is much less of an optimal currency area than the US is. By examining the Eurosystem’s central banks in detail, it is possible to see divergent trends in structure between some of the member states. This is especially evident in the items of Intra-Eurosystem claims and Intra-Eurosystem liabilities, where major imbalances persist between creditor countries and debtor countries inside the Euro area. The third group of central banks consists of EU countries that have still not introduced the euro as their currency. Among these countries, additional focus was given to CEE countries. These central banks have enlarged their balance sheets on average since GFC, but at a much slower pace compared to the most advanced economies. Until COVID-19, inflation of their balance sheet was minor and was not a consequence of an unconventional monetary policy. In fact, most of these central banks could be classified as FX holders, due to the foreign assets serving as the main source of the base money creation. Notable exemption to this is Sweden, which made the considerable transformation toward securities purchases even before COVID-19. COVID-19 health crisis partially changed these trends, as now several central banks that could be regarded as FX holders announced and/or started their QE policy, i.e., asset purchasing programs. Nonetheless, the scale of their asset purchases has been limited in most cases. 5.5.2

Balance Sheet Policy as Modern “Debt Monetization”

Changes discussed in previous chapters raise several questions about sustainability and possibility of negative spillovers of such radical shifts in the conduct of monetary policy. While the monetary policy did change considerably in the last two crises that truly have systemic importance, the institutional framework did not and fragility—exhibited by the GFC already in 2008—still remain. Before 2008, central banks did not previously do business directly with non-financial entities and their operations with the government were strictly limited (and most often prevented due to the principle of independence). However, in the aftermath of the financial crisis in 2008, central banks have become among largest and most important securities market makers due to the fact that they have unlimited liquidity compared to anyone else—simply because they can make money ex nihilo.

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That allowed central banks to use their balance sheets, the most important of which was to identify channels for creating base money that would correspond to the vulnerable segment of the financial market or the real economy. The form of action of unconventional monetary policy is essentially determined by the way in which a certain economy is financed, which can be predominantly financed by bank loans or the issue of securities. This fragmentation of base money generation channels in balance sheet assets depends on the degree of development of the financial market when it comes to acting toward financial markets. Actions toward nonfinancial entities were reduced to the purchase of debt securities and shares. In the current era of financial capitalism, it is the financial sector in highly developed countries that is playing an increasingly important role in the structure of GDP, representing the financialization of the economic activity (Lovrinovi´c 2019). However, the dichotomy between the financial and the real economy is increasingly visible. Particularly an important role in the development of financialization was played by banks for which King (2016) says: “Banks today are very different from banks in Bagehot’s time or during most of the twentieth century. They are much bigger, their assets are more complex and difficult to value, they hold far fewer liquid assets, they finance themselves with far less equity capital, and they wield greater political power. As a result, the maxim ‘lend freely against good collateral at a penalty rate’ is outdated.” As we have seen, central banks used a balance sheet policy on an unprecedented level. But due to the nature of central bank transactions—involving exchanges of collaterals for loans or dealing with collaterals explicitly through outright purchases—balance sheet policy can be regarded as a modern debt monetization. Debt monetization, both public and private, has become a key pattern in the alchemy of central banks, which has replaced one form of debt (government bonds) with another form of debt (base money). It is, of course, not an invention of our days, but since 2008 it takes place on such a vast scale that we can call it the modern alchemy of money because one form of debt is redeemed by another form of debt. Both forms of debt are originally managed by the state. Sovereign issues its debt in the form of bonds but also lends to the central bank its legitimacy to generate base money ex nihilo. This debt swap creates the illusion of a real impetus for economic recovery, although it does not address the real roots of the crisis. The essential difference between a

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bond as a debt financial instrument and the central bank’s base money is that the base money, once it enters into circulation, plays the role of both turnover and payments in all transactions, and the government bond can only play the role of turnover, just as a monetary surrogate. Since the state has the power to change all business conditions, it can also declare a bond as an instrument of payment for certain transactions, e.g., tax payments. In the process of monetization, one form of debt is replaced by another: a government bond is replaced by another form of debt—base money (also government money on whose behalf the central bank acts). The key question is whether base money is used primarily to finance and stimulate the real economy or to maintain asset prices in financial markets. Thus, the key difference between the 2008 financial crisis and the health crisis from the beginning of 2020 is not so much in the speed of expansion as in the inability of the labor market and production capacities to function in the latter case. This inability is not caused by market disturbances, but by force majeure, a virus that could not be suppressed in the short term. There were cracks in the economic processes and links between production, transport, and trade that ultimately resulted in a decline in production, accelerated growth in unemployment, and the need for huge subsidies to workers and entrepreneurs. On the other hand, financial markets have not collapsed in 2020 as in the case of 2008 for two reasons: (a) the unconventional monetary policy measures already taken have stabilized prices and yields, (b) a positive psychological effect has been achieved that the central bank will continue to act decisively in supporting liquidity and rescuing the economy. In that sense, central banks further expanded their role of lender of last resort. All this speaks to the power and key role played by the central banks, which have expanded their role as the “lender of last resort” for banks to “the lender of last resort” for the entire economy. In that way, they took on a huge responsibility and risk. Even so, it is clear to financial market participants that the key issues that led to the 2008 crisis have not been resolved. In different words, central banks have become primarily “government securities’ holders.” Through outright purchases of government debt by ex nihilo creation of base money, central banks have in essence monetized existing debt. But, is it always safe debt, and does it stay safe faced with the economic downturn? An example of Greece and the whole European debt crisis showed it is not always the case.

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Policy Implications

Unconventional monetary policy using the central bank’s balance sheet has become the most important form of selective monetary policy and monetization of public debt today, which until recently was attributed only to the former socialist countries. Such large monetary interventions by the central bank led to a change in the understanding of the term “central bank independence.” Central bank balance sheet management has become the most important instrument of short-term stabilization and long-term potential destabilization of the economy at the national and global levels, as well as a place of coordination of monetary and fiscal policy. The question of great moral hazard is also open. Because the structural issues persist even after the balance sheet policy management on such a scale, the main challenge for central banks in the medium term will be to find a way to deflate their balance sheets without hurting the economic recovery. The end goal would be to return toward the conventional rule-based monetary policy, with the focus on the normal functioning of the interest rate. But this is easier said than done. One way to do this is to induce inflation and/or expectations of higher inflation targeting. Without it, the debt burden could prove to be too high for many countries, leaving monetary authorities with their hands tied. But inducing inflation is challenging with the suboptimal functioning of the transmission mechanism. The ever greater part of the base money creation is allocated to the financial markets, and very little is transferred toward the real economy and higher credit activity. In this sense, historical levels of both public and private debt found their way onto the central banks’ balance sheets. Many of these securities will be held until maturity. Thus, central banks’ balance sheets have become the “exit strategy” for many collaterals, including those not considered safe assets. The concept of monetary interventionism by the central banks, which was launched in times of financial and health crises, is a conscious action aimed at establishing a balance. This confirms the previous practice of central banks acting as providers of last resort. However, now we are talking about huge rescue interventions not only of banks but also of other financial institutions, the state, and private companies. The concept of LOLR has been significantly expanded, and its essence is the monetization of debts in countries that pursue a sovereign monetary policy.

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The consequences of such massive asset purchases are yet to be realized from a macroeconomic perspective. These could include, but not be limited to (1) the transmission mechanism of monetary policy, (2) the price/yield ratio of the whole spectrum of bonds, (3) the safe asset shortage, (4) portfolio restructuring of private investors, (5) moral hazard of providing a “backstop” to both governments and private investors, (6) risk transfers between banking and non-banking sectors, (7) time consistency of monetary policy. Potential spillovers could be even more reaching. Therefore, monetary authorities should learn from these experiences and study them closely (Joyce et al. 2012), as many of the policies done have been novel and experimentations in their first form. In any case, the central bank must have as many instruments as it has set targets under the Tinbergen rule. The example of the Fed clearly shows how many instruments they created and activated. If the vast majority of central banks have so far targeted an inflation rate of up to 2%, the question arises as to what they can target in the segment of the financial market, so that asset price bubbles no longer dominate in the low growth and low inflation environment. The current institutional framework does not seem suited for the issues it is facing. These issues are not arising from the balance sheet policies per se, but they themselves are not geared toward solving them. These structural problems can arise from a number of sources: maturity mismatch of banks’ assets and liabilities, repeal of the Glass-Steagall Act, the possibility of issuing money “ex nihilo” by commercial banks, the huge volume of offshore operations, and rising inequality and regressive redistribution with negative effects on the aggregate demand, among others. Balance sheet policies can hardly represent a sustainable solution or even a step in the right direction of the paradigm that will stabilize the national and world economy, harmonizing the real with the financial economy. Though, it is a part of the new paradigm, of aggressive discretionary monetary policy that serves as a market maker for the financial system as a whole. However, central bank balance sheets have become too large and no one can really anticipate how will the return to “normal” economic conditions go. As it is, the balance sheet policy is not constraining financial markets and moral hazards associated with securitization and shadow banking. On contrary, it is serving as an incentive.

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An example of Bundesbank from several decades before our time serves as a historical reminder of radical transformation of economic activity, as well as of central banks’ role. Then, major assets in Bundesbank’s balance sheet were bills of exchange, which have a direct connection with the real economic activity. Nowadays, financialization dominates to such an extent that central banks’ balance sheets have a much larger relationship with the financial markets. In the US, this could be regarded as a direct consequence of the repeal of Glass-Steagall Act. In the Euro area, the obvious problem is the one monetary policy, but many fiscal authorities and consequently, lack of single (safe) European collateral. This leaves member countries and their central banks inherently vulnerable. In addition to this, lack of real optimal currency area is also reflected through Intra-Eurosystem imbalances, which pinpoint toward the hidden divergences and structural problems of the Euro area. The COVID-19 reaction could prove to be a step in the right direction, as for a moment, financial solidarity did prevail in degree not seen after the GFC. For the non-euro and developing countries of the CEE, most of their central banks increased their balance sheets from 50 to 230% between the two systemic crises, which is significantly less than the expansion in larger and more developed countries. Although they kept their currencies, foreign exchange reserves were and remain the most important item and channel for creating base money in the assets of their central banks. This speaks to the underutilization of monetary sovereignty due to the fact that their currencies are not global money, that they have significant external debt, and largely conduct their monetary policy through the exchange rate stability of their currencies. Their monetary systems are largely euroized and the countries mentioned have significant foreign exchange reserves. In situations of external shock, monetary sovereign countries have greater possibilities to intervene. For these reasons, it was expected that the non-eurozone central banks largely pursued a conventional monetary policy until COVID-19. Afterward, some of them have taken the first step toward unconventional monetary policy. But, under the existing institutional framework, it remains unclear will their transformation from pure FX holders result in a positive outcome (more sovereign and active monetary policy), or in a negative outcome (incentivizing the debt burdens in the economy). Unconventional monetary policy is unconventional for a reason and when it solves something, it is important that it does not leave these countries alone in dealing with possible negative consequences.

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Finally, the main question remains: how and within what period of time could the balance sheets of central banks be reduced, how to get out of the situation of liquidity traps, how to return the functioning of the financial market to normal? Until the onset of the COVID-19 crisis, some major central banks (especially in the case of the Fed) had taken a strategy of gradually reducing their balance sheets, as any sharp decline could produce major disruptions. In addition, it takes some time for the balance sheet reduction to be aligned and replaced with the reactivation of interest rates as the main instrument of conventional monetary policy. Debt write-offs could be part of the solution, as current record levels of debt are irreconcilable with secular stagnation of major economies. Such a solution is especially advocated by proponents of the modern monetary theory. In any case, unconventional monetary policy has become the mainstay in the era of financialization and over-reliance on central bank financing in the aftermath of two systemic crises. The use of the central bank balance sheet as a monetary policy instrument has temporarily stabilized the deepening gap between the real and financial economies. However, prolonged maintenance of such a system could prove to be a miscalculated antidote with unforeseen negative spillovers.

5.6

Conclusion

Central banks’ balance sheets have grown several times since the start of the Great financial crisis. This alone merits an answer: is it a cyclical or a secular trend? However, not only have the sizes of the balance sheet been changed, the structure of the assets side, i.e., sources of base money creation have been changed dramatically for a number of central banks. In this paper, we analyzed the balance sheets of various central banks in detail, aiming to put these transformations into a context of contemporary macroeconomic outlook. While doing so, we compared three distinct groups of central banks: (a) USA, Japan, the Euro area and the UK, (b) EU member states that have adopted the euro, and (c) EU member states that have retained their currency. Key differences between them are (a) magnitude of the transformation and (b) timing of the transformation. Major central banks, led by Fed, experienced more pronounced changes and acted as the innovator in the conduct of the balance sheet policy as the new unconventional monetary policy tool. Smaller central banks—especially those of non-eurozone

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EU countries—mostly acted as rigid FX holders all the way until the COVID-19 health crisis. However, contrary to the popular belief that the catalyst for the changes in size and structure was the external shock of COVID-19, we examine that this is only partially true: in the case of non-eurozone EU countries, among them several CEE countries, COVID-19 recession kickstarted some changes in the structure of the assets side of the balance sheet. For the most advanced economies, this cannot be said. In different words, the transformation of balance sheets’ sizes and structures among major central banks seem to be structural and part of the greater secular trends of economic policy transformation in the environment of sluggish growth, low-interest rates, and under-shooting inflation. This transformation—due to the unconventional character and historical levels of change in the conduct of monetary policy—raises the question of sustainability and possible negative spillovers of such policies. Most of the assets purchased by central banks are debt securities. Moreover, most of them are public debt securities, which can incentivize non-optimal fiscal expansion outside of the desired policy framework. Consequent debt overhang could subsequently prove to be a major obstacle in the conduct of anti-cyclical monetary policy. Beyond this, the expected transmission mechanism toward rising credit activity has been disappointing, as the majority of ex nihilo created base money is not transferred toward the real economy. Finally, in the conditions of a liquidity trap, rising public debt to GDP ratios and oversized balance sheet sizes, monetary authorities could be severely constrained in the next business cycle. On the other side, financial markets have become dependent on the base money creation through long-term purchases of debt by the central bank. The direct consequence of this “unconventionality” is the rising asset price inflation. When the next crisis happens, central banks will be in a precarious position to act on a scale they did in the GFC and the COVID-19 crisis. The existing institutional framework does not seem suited to resolve these growing structural issues.

Notes 1. It should be emphasized that the dominant way of financing the domestic economy plays a very important role; in a stylized way, it can be more reliant on bank loans or financing by issuing securities.

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2. The use of such measure is effective primarily in countries with developed financial markets or differently, where the banking sector is not too dominant. Countries in which economic entities are financed predominantly through bank loans almost exclusively use the bank loan channel through which the central bank “feeds” banks in the hope that they will continue the transmission to businesses and citizens. For example, the Fed and the BoE were focused on the purchase of unconventional assets, while the ECB was focused on lending to banks in the response to the GFC. 3. The change in the maturity of central bank transactions could be adequately represented by the example of ECB. Traditionally, ECB used the “Main refinancing operation” monetary tool with a maturity of one week. However, after the GFC the most important financing operation has become the “Long term refinancing operation” whose maturity was originally three months and later extended to a year, two, three and four years now. With this, the ECB sends an important message to the banks; that it will give them as much liquidity support as needed. 4. In this period, Bundesbank was giving strong support to the European monetary cooperation fund which was formally founded in 1973, due to constant rise of the Germany’s economy. 5. Some central banks have unusual assets in their balance sheets. Thus, for example, the Norwegian central bank holds in its assets the Government Pension fund of Norway, which contains the accumulated funds generated by the sale of oil. GPFN accounts for 94% of the Norwegian central bank’s asset structure, with assets recorded as fund value and liabilities as deposits. 6. Some central banks, such as the BoE, formally maintain their independence by establishing and financing special fund that buys government bonds from the state in huge quantities. With this organizational move, it circumvented the legal restrictions on the direct purchase of securities from the state. 7. The assets of the balance sheet of the BoE are dominated by the item “Loans to asset purchases facilities”, which accounts for the major part of held securities. These BoE loans are directed towards the Fund established by the BoE in 2009 with the aim of buying primarily government bonds (gilts).

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King, Mervyn. 2016. The End of Alchemy—Money, Banking and the Future of the Global Economy. New York and London: W.W Norton Company, p. 203. KPMG. 2020. Bulgaria—Government and Institution Measures in Response to COVID-19. Last modified May 14. https://home.kpmg/xx/en/home/ins ights/2020/04/bulgaria-government-and-institution-measures-in-responseto-covid.html. Accessed 19 Jan 2021. Lavoie, Mark. 2015. The Eurozone: Similarities to and Differences from Keynes’s Plan. International Journal of Political Economy 44 (1): 3–17. Lovrinovi´c, Ivan. 2019. Financijalizacija svjetske ekonomije. In Svjetski financijski vrtlog - 30 godina poslije: zbornik radova Znanstveni skup povodom 10. godišnjice smrti akademika Ive Perišina održanog 5. prosinca 2018. u Zagrebu, ed. Gordan Druži´c, Ivan Lovrinovi´c, Martina Basarac Serti´c, and Martina Naki´c, 79–92. Zagreb: Hrvatska akademija znanosti i umjetnosti i Ekonomski fakultet Sveuˇcilišta u Zagrebu. MNB. 2020. The MNB to Launch Its Government Securities and Mortgage Bonds Purchase Programmes on 4 May. Last modified April 28. https:// www.mnb.hu/en/pressroom/press-releases/press-releases-2020/the-mnbto-launch-its-government-securities-and-mortgage-bonds-purchase-progra mmes-on-4-may. Accessed 19 Jan 2021. Nagel, Joachim. 2012. Understanding Central Bank Balance Sheets. International Economy. http://www.international-economy.com/TIE_Su12_Nagel. pdf. Accessed 16 Jan 2021. Pattipeilohy, Christiaan. 2016. A Comparative Analysis of Developments in Central Bank Balance Sheet Composition. BIS Working Papers, 559. https:// www.bis.org/publ/work559.pdf Accessed 15 Dec 2020. Sinn, Hans-Werner, and Timo Wollmershäuser. 2012. Target Loans, Current Account Balances and Capital Flows: the ECB’s Rescue Facility. International Tax and Public Finance 19: 468–508. https://www.ifo.de/DocDL/sinn-itax2012-target.pdf. Accessed 15 Dec 2020. Summers, Lawrence H. 2014. US Economic Prospects: Secular Stagnation, Hysteresis, and the Zero Lower Bound. Business Economics 49 (2): 65–73.

CHAPTER 6

Quantitative Easing, Stock Exchange, Inflation and Monetary Paradigm in the US: Lessons for Emerging Economies

Marinko Škare and Dean Sinkovi´c

6.1

Introduction

Introduction of quantitative easing (QE) during the Great Recession was supposed to be a temporary one-time policy tool to achieve needed financial stability. However, this nonconventional policy has become a permanent tool for each major central bank around the globe. Going into the 2008 crisis, US and UK banks were extremely leveraged, with very low bank reserves so the bailout was done via QE and various forms of government relief programs. Due to historical lessons of money printing, many economists were expecting the spike in

M. Škare (B) · D. Sinkovi´c Faculty of Economics and Tourism “Dr. Mijo Mirkovic”, Juraj Dobrila University of Pula, Pula, Croatia e-mail: [email protected] D. Sinkovi´c e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_6

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consumer inflation. Yet it ended up being a top-down, anti-deflationary bank industry bailout and not a bottom-up, pro-inflationary real economy bailout. Several phases of QE only boosted banks’ liquidity and very little of those funds went to the real economy. Monetary inflation or growth of broad money supply via QE didn’t result in more money chasing fewer goods and services, and therefore wasn’t particularly inflationary for every price since the transmission mechanism from QE to the real economy was small. A simple look at the collapse of the velocity of money clearly explains that transmission was aimed toward some other forms of assets. It actually resulted in the inflation of financial assets such as stocks and bonds as well as housing. This paper shows that the nonconventional policy of quantitative easing has a strong and significant impact on the increase of the prices of the financial assets. Furthermore, unlike for the Great Recession, the policy response to the COVID-19 pandemic was somehow different since the massive monetary and fiscal stimulus was directed toward households and corporations, therefore reaching realms of the real economy. Rapid expansions of central banks’ balance sheets (QE) and government deficits were to great extent being utilized through helicopter money tools. This combination of fiscal spending via monetary financing and central banks’ corporate purchase programs could very well be inflationary since the transmission mechanism from QE to the real economy is high. Furthermore, implementation of such policies in the long-run implies a possible monetary paradigm shift since central banks will be able to increase the money supply to almost any extent independently of the private banks. In that sense, monetary inflation and transmission mechanism might not rely on the expansion of credit via the private banking industry. This paper is related to growing literature that investigates the impact of monetary policy on financial markets (see Bernanke 2020 for review). Many researchers have proved the positive effect of interest rate cuts and expansionary monetary policy on stock returns (Bernanke and Kuttner 2005; Cieslak et al. 2019; Brusa et al. 2020). Authors who examined the impact of QE on financial markets mostly focused on the effects on fixed income assets such as Treasury bonds market (Gagnon et al. 2011; Vissing-Jorgensen and Krishnamurthy 2011) or corporate bond market (Guo et al. 2020). Positive effects of Bank of Japan’s large-scale purchase of ETFs on the Japanese stock prices were found in the work of Barbon and Gianinazzi (2019). Similarly to our findings, Putnins (2020) showed

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that Fed actions taken during the COVID-19 crisis had a substantial positive effect on the stock markets. In this paper, we show how the Fed’s unconventional monetary policy via series of QE has a significant positive effect on the stock market performance since its introduction in 2008. Ultimately this confirms that Fed, for some particular reason, front runs the stock recovery and by such manipulation creates another stock market bubble. By rigging the market Fed eliminates the price discovery mechanism and destroys the free market. The notion—do not fight the Fed seems to be a justified strategy for investors. The question is, once when high inflation finally arrives and central banks around the world had to reverse their policies, who will be responsible when the bubble bursts and people losing a large portion of their investments and pensions?

6.2 Quantitative Easing, Inflation, and Asset Prices The Great Recession of 2007–2009 initiated an introduction of unconventional monetary tools such as quantitative easing (hereafter QE) through which central banks purchase long-term securities such as treasury bonds and mortgage-backed securities from the open market in order to increase the money supply and stimulate lending. At first, it was introduced as temporary the one-time monetary phenomenon to achieve financial stability, yet it became a permanent policy tool for more than a decade. While many economics assumed QE, as a form of “money printing,” will immediately spark higher inflation or even hyperinflation, the consumer prices measured by CPI did not even reach the central bank long-term inflation targets around 2%. However, it is now obvious that inflation was realized in the other spectrum, via asset price increase, primarily in the housing sector and stock market. As a result of the Great Recession, the housing market has bottomed during 2012, when US Case-Shiller Home Price Index dipped below 140 level but is currently standing at almost 240 level (see Fig. 6.1). The key stock market index S&P 500 that has bottomed on March 6, 2009, shortly hitting 666 level, has had astonishing performance ever since, reaching higher than 3900 as of February 2021 (see Fig. 6.2). This almost six-fold increase delivered around 18% annualized total return while USA GDP annualized growth was around 2.2%. Our study shows that this apparent separation between stock prices and the economy was mainly driven by monetary policy tools such as QE and ZIRP (zero-interest-rate policy).

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Fig. 6.1 S&P/Case-Shiller US National Home Price Index (Source FRED)

Fig. 6.2 S&P 500 index 2009–2020 (Source www.macrotrends.net/2324/sp500-historical-chart-data)

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Great Recession QE vs Coronavirus Crisis QE

Prior to the Great Recession, banks in the USA, as well as in most Western economies were extremely leveraged having low bank reserves. Major US banks had cash levels around 3% and historically low holdings of Treasuries so they welcomed financial crisis mostly invested in loans and riskier securities (see Figs. 6.3 and 6.4). With such a leverage burden and just 3% of cash reserves, even a small percentage of loss in assets could result in insolvency. The climax was hit in 2008 which coincidences with record-high private debt levels among households (mortgage, credit card, auto loans, etc.) As the housing bubble started to burst and homeowners

Fig. 6.3 Cash assets to total assets of the large US commercial banks (Source FRED)

Fig. 6.4 Treasury and agency securities to total assets of the large US commercial banks (Source FRED)

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began to default on mortgage payments the value of mortgage-back securities, held by the banks, started a rapid decline which ended in huge financial and economic turmoil. Policy response via QE and Troubled Asset Relief Program (TARP) was mostly aimed at bailing out to big to fail banks with QE providing bank liquidity while TARP boosted bank solvency. Yet it was topdown, the anti-deflationary bank industry bailout and not a bottom-up, pro-inflationary bailout for the real economy. In 2010 financial sector regulations got stricter by introducing Dodd-Frank Wall Street Reform and Consumer Protection Act included a set of measures to regulate the activities of the financial sector and protect consumers as well as various sets of macroprudential policies focusing on banks’ capital requirements and risk management. Interestingly both political wings criticized the proposed government actions, the left argued it was too weak and did not punish Wall Street the way it should while the right pointed out that the government took too much control over the financial sector without addressing the real causes of the financial panic. Both were probably right. However, new regulatory reforms required banks to increase reserve and capital requirements which imply that banks have to hold a greater percentage of their assets in cash and other safe assets. To increase the reserve requirement banks have to sell other assets to get cash but if the entire banking industry does the same, then there are not enough buyers of such assets. Therefore, taking the role of the lender and buyer of last resort Federal Reserve (Fed) created fresh reserves out of thin air, gave it to the banks, and in return took some of their Treasuries and MBOs. This mechanism is being conducted via quantitative easing and along with TARP it recapitalized banks so their cash reserves, as a percentage of total assets, increased to 8% by early 2009 (see Fig. 6.3). Although it was supposed to be a temporary one-time policy tool to achieve needed financial stability the same QE mechanism was applied by the Fed in 2010 (QE 2) via buying $600 billion of Treasury securities and again in 2012 (QE 3) when the Fed decided to launch $40 billion monthly bond purchasing program. It was all done in parallel with the zero-interestrate policy which was kept until 2016. Similarly, in 2009 European Central Bank (ECB) introduced QE via covered bond purchases which were expanded in 2015 when ECB initiated e60 billion per month purchase of euro-area bonds from central governments, agencies, and European institutions. In March 2016, the ECB increased monthly bond

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purchases to e80 billion which also included corporate bonds. Other major central banks, such as the Bank of Japan, Bank of England, Swiss National Bank, and Swedish Riksbank used the same mechanism in a slightly different format. As a result, by 2016 major central banks’ balance sheets ballooned to unprecedented levels, quadrupling their size, and fully altered their composition. Interestingly, central banks from emerging market economies responded in a similar manner, by cutting rates and, for the first time in history, implementing QE policies. In previous financial crisis episodes that resulted in massive capital outflows and currency devaluations, monetary authorities from emerging markets responded with monetary tightening. Besides interest rates cuts, relaxing bank reserve requirements, term repo agreements, and using foreign reserves to fight exchange rate volatility, 18 emerging countries implemented similar QE toolkit as central banks from advanced economies (see IMF 2020). The main claim by central bankers to continue, expand and justify various forms of QE programs was to achieve inflation targets of around 2%. As Mario Draghi, ex-President of ECB stated—“we will continue with QE until we see a continued adjustment in the path of inflation.” However, the entire QE programs before the COVID-19 pandemic were not designed to boost inflation because it did not result in more money chasing fewer goods and services since the money mostly remained within the banking system increasing its reserve levels. Overall transmission mechanism from QE to the real economy was small and the broad money supply did not increase rapidly. Banks refused to lend much of the money to the real sector and fiscal programs did not use banking channels much either. In final, bankers got great assistance from central banks and governments but the wider public did not. Besides, during the last decade, there were also other major forces causing deflation in the consumer prices, from aging demographics (less demand for goods/services), technological improvements, commodity oversupply, globalization to high private debt levels which made household, and business financially restrained. Another evidence that massive pre-COVID monetary expansion did not hit the broader public, or at least they were not willing to spend it, is declining money velocity, the speed at which money circulates in the economy (Fig. 6.5). Money velocity has been continuously declining since the 1980s with a steep fall during the Great Recession and has been declining even under a huge monetary expansion programs. Such a scenario can offset the increase in money supply and even lead to deflation

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Fig. 6.5 Monetary expansion and money velocity (Source FRED)

instead of inflation since fewer transactions are being made throughout the economy. Central bankers very rarely mentioned this phenomenon although it has a negative impact on economic growth. As the banks got more capitalized it seemed that credit markets operate smoothly and another banking systemic crisis was not in sight. However, in mid-September 2019 US banking system surprisingly ran out of cash, causing a huge spike in short-term interbank borrowing rates known as the REPO market crisis. The repurchase agreement (REPO) market is an important part of the financial system where on average $2–4 trillion of collateralized short-term debt is traded each day. It allows financial institutions that own lots of securities to borrow cheaply and allows agents with lots of spare cash (e.g., money market mutual funds) to earn a small return on that cash without much risk since they hold Treasuries as collateral. In mid-September 2019, the repo rate spiked as high as 10% and even then financial institutions with spare cash refused to lend to the ones who needed it. This was a shocking moment for the US financial system because repo rates typically trade closely with the federal funds rate, at that time in between 2 and 2.25%. Fed responded to this strange systemic dysfunction by purchasing around $60 billion of shortterm Treasury securities per month, essentially increasing the supply of the reserves in the system. Subsequently, it increased the size of its daily lending to $120 billion and then to an astonishing $1 trillion in the peak of COVID-19 panic during March 2020. Interestingly Fed announced that repo market bailout does not represent another round of QE because it did not require active management of the supply of reserves, therefore

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declaring it as a non-QE policy intervention. No matter what technical term has been used, the repo crisis exposed serious systemic problems within the US banking system. In summary, policy response and QE programs prior to COVID-19 pandemic represented top-down, anti-deflationary bank industry bailout, and not bottom-up, a pro-inflationary bailout for the real economy. It did offset deflationary shock and collapse of the banking system as well as turned the economy back into the reflationary trend but it was not modeled to generate broader consumer price inflation. However, a combination of QE and ZIRP policies was outright inflationary for asset prices, specifically for real estate and stock prices. Yet probably more problematic is that monetary authorities since 2008 have already implemented the entire set of policy tools to fight future recessions. Unfortunately, the next was indeed a big one, caused by COVID-19 pandemic and resulting in huge economic, social, and health damage to the entire world and more specifically to the countries of the West. This time the world welcomed pandemic with the banking system solidly capitalized but with most of the real sector highly leveraged. Indeed, the response to pandemic by imposing lockdowns and different forms of restrictions has caused the most damage to the real economy, specifically to small and mid-size companies, those who operate within a highly competitive environment and tight margin. With millions of businesses collapsing cash flows, the explosion of unemployment, and record lines in front of the food banks it was obvious that it is not enough for the central banks to simply buy Treasuries or MBS from the banks. With the ongoing model of QE, there was no transmission mechanism to the public. So this time fiscal authorities pushed trillions of dollars directly into the real economy, in a form of stimulus checks, extended unemployment benefits, paycheck protection programs (grants), and bailing out hard-hit industries such as airlines, hotels, or entertainment. The world witnessed epic monetary and fiscal bazookas, with the bailout funds flowing even to the institutions such as hedge funds and corporate lobbyists. To finance such huge expenditures government had to issue a lot of Treasury securities. In the initial stage of the COVID-19 pandemic, the Treasury market became illiquid due to relentless selling from foreign investors and hedge funds and not enough buyers insight. So the Fed stepped in and created $1 trillion of fresh bank reserves out of thin air to purchase $1 trillion of Treasuries over a three-week period. It was the

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most rapid asset purchase program in the entire history of the Federal Reserve and it is still ongoing, although at a slower pace. As a result, Fed’s balance sheet increased by $3 trillion in just three months with $2 trillion spent on buying Treasuries while the rest was spent on purchasing MBOs, corporate and municipal bonds. Unlike previous QE programs, this time money flowed from banks to the Treasury Department and then finally to the wider public. Therefore, QE 4 represents a different story because the government sent tons of money directly to people and businesses, that money ended on their bank deposits thus significantly increasing the broad money supply. The transition mechanism behind this QE-financed fiscal stimulus gets money into the hands of the wider public rather than keeping it within the banking system, therefore it is inherently inflationary not just for the asset prices but also for the prices of goods and services. Most commodities and food prices are already increasing at in much faster pace driven by supply shortfalls due to the COVID-19 pandemic, stronger than expected demand due to large fiscal stimuli, and US dollar depreciation due to relentless money printing. If this momentum keeps up for a longer period of time, then monetary authorities could face serious headwinds since they announced the continuation of QE 4 and zero interest rate policy until at least 2023. Perhaps a one-time $3 trillion intervention might be not enough to cause a persistent trend change in inflation because deflationary forces could somehow outweigh it. Yet other rounds of massive fiscal and monetary injections, along with possible supply chain disruptions, could definitely push prices too far.

6.3

Rethinking Macroeconomics and Rebirth of MMT

The current QE 4 model initiated one of the final solutions of the monetary policy—helicopter money, another unconventional tool to inject cash directly into households’ accounts. In addition, Fed launched special purpose vehicles in order to purchase corporate debt in primary and secondary markets, a policy tool that has already been used by ECB and Bank of Japan. The narrative was to backstop corporations and their employees but it was mostly due to saving fallen angels, the companies who lost investment-grade status due to pandemic and were on the verge of collapsing. Such policy tools allowed Fed to buy high-yield junk bonds,

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something that is inherently morally hazardous since lot of these companies are declared zombie companies or have spent most of their income for share buybacks before the pandemic. Obviously, without such interventions, the corporate debt market would probably collapse since the yield on those bonds would significantly rise, meaning that lots of corporations could not easily finance their operations. Interestingly, Fed purchased $1.8 billion worth of ETF’s that owe bonds to car rental company Hertz, which filed for bankruptcy a month later. Furthermore, it also expanded its municipal bond-buying program to prevent local and state governments from collapsing. Basically, Fed decided to directly or indirectly (bond purchase) bailout every single entity in the economy—households, corporations, municipal/national governments and banks, without even considering the quality and behavior of those entities prior to COVID19 pandemic. It will definitely be interesting to analyze central banks’ balance sheet size and composition in the late post-COVID economies. Massive fiscal spending in combination with central banks buying most of the sovereign debt instruments represent the rebirth of the Modern Monetary Theory (MMT) , since it includes a similar policy toolkit that was used during the 1940s to finance the Second World War. The only difference is that Fed, due to legal constraints, buys Treasuries on the secondary market. However, in practice, it is the same as if the Fed buys them directly from Treasury Department since banks now act as a passthrough entity. Banks do not intend to keep Treasuries, they just buy them from the government and instantly sell them to Fed. In sum, the process is being conducted through the back door. Full implementation of such policies in the long run implies a possible monetary paradigm shift because central banks will be able to increase the money supply to almost any extent independently of the private banks. In such an environment, monetary inflation and transmission mechanism might not rely on the expansion of credit via the private banking industry since the merger of government and central bankers can easily create a massive fiscal + QE combo and directly inject money into the economic system. The value of funds spent on stimuli and bailouts via QE 4 in 2020 were larger than for QE 1, 2, 3 combined and the program along with the zero-interest-rate policy is announced to be ongoing for at least the next two years. A stunning 35% of USD in existence has been printed between March 2020 and January 2021 but it might still not be enough to prevent a double-dip recession. Mainstream macroeconomic policies that are ongoing since the 1980s created a debt-fueled economic system

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that requires constant monetary and fiscal interventions regardless of business cycles being in expansionary or recessionary mode. It seems more like a Ponzi scheme than a solid economic model based on rational policies and realistic projections. After 40 years in implementation is obviously fundamentally flawed and morally hazardous since it resulted in sluggish productivity growth, stagnant or declining wages, rising inequality, frequent boom and bust cycles in the stock and housing market and environment that favors short-term gains and speculation in the stock market instead of long-term investment in physical and human capital. Benefits of such a system were mostly ripped by the top 10 percenters who, even during the economic destruction caused by COVID-19, managed to hugely increase their wealth. Each new expansionary cycle started with the higher level of public debt to GDP and the COVID-19 pandemic vastly accelerated that ratio since we had a dramatic rise in public debt and a spectacular fall in GDP during 2020. Suddenly it seems there are no concerns among policymakers in regard to extremely high budget deficits and the record level of public debt when bailouts became a norm and money printing conventional monetary tool. With such a change in narrative, no wonder MMT is now indirectly being propagated by many policymakers. Interestingly not even similar policy advice was given to the Asian or European countries that were affected by the Asian crisis (1997) and European Sovereign Debt Market Crisis (2015). MMT implies that Treasuries are big enough to finance their entire policy wish list for an unlimited time. That way unused labor or capital can be effortlessly directed to whatever production line politicians desire. It also assumes there will be no inflation and wage increase which is very questionable. MMT policies can provide some lost income for people and businesses during sharp economic decline, such as the one causes by the COVID-19 pandemic, but then the concept is almost identical to standard countercyclical Keynesianism. However, under normal circumstances during an expansionary economic cycle with low unemployment and high labor force participation rate, implementing policies of indefinite money creation and distribution could easily spark hyperinflation. Another pitfall of MMT is that it is not implementable in countries that do not have monetary sovereignty which seems to be inherently unfair. It seems a perfect theory for someone who wants to solve a problem of over-indebtedness by flooding the system with more debt. That way

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policymakers can easily establish universal basic income, a governmentguaranteed payment to each citizen because according to MMT a country with the sovereign monetary system can print currencies as much as needed and distribute it directly to its citizens. We are already witnessing series of stimulus checks given to almost every citizen in the USA, so it might easily become a permanent policy via MMT. Rapid technological advancements and innovations in artificial intelligence. machine learning and robotics could create massive job losses so transfer payments via UBI might be one of the solutions for lost income due to rising unemployment. The efficiency of the entire transfer mechanism could be enhanced with the implementation of the central bank digital currency (CBDC) and facilitated through a particular blockchain model. Central banks around the world are already exploring the idea to implement different forms of digital currencies while blockchain technologies are already being utilized for cryptocurrency transactions. The digital currency still implies a fiat monetary system but this way central banks can easily and quickly transfer funds to recipient’s accounts (digital wallets). In such a scenario banking industry might be swept out from the process of money creation.

6.4

Quantitative Easing–Stock Market Nexus

In the last few decades, the world is undergoing rapid processes of financialization that have fully transformed capitalist economies. During that time financial sector has grown dramatically in the term if its size, activity, and efficiency. Neoliberal policies, based on liberalization, deregulation, and privatization were extremely positive for this process to unfold. The scale of financial operations became much bigger, more complex, and interconnected so through time financial engineers and their innovations became even more important that engineers from the real sector. Through time each aspect of economic and social life has been securitized and transformed into investable capital. As a result, financial markets and institutions generated much greater influence over economic policies and economic outcomes on both macro and micro levels. The key impacts of financialization are to increase the significance of the financial sector relative to the real sector, transfer income from the real sector to the financial sector and increase income inequality and contribute to wage stagnation (see Palley 2007). The major international institutions and donor communities expanded this agenda even toward the poorest of the poor through a microfinance model claiming that such policy will

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eradicate poverty and provide economic development. In the end entire system crashed like a house of cards leaving poor families heavily indebted and low-income countries economically and socially destroyed (see Mader 2015; Bateman 2011; Bateman and Chang 2009). Unbelievably, this enigmatic and destructive model is still ongoing in a slightly different format. The same scenario has also unfolded in developed economies after the Great recession which actually represents the crisis of financialization. Although slightly altered with few minor regulations, the game of financialization newer stopped playing. Furthermore, rapid technological development and digitalization created new revolutionary products via fintech. Online start-ups, social media, and other digital platforms are expanding into the financial sector and offer payments and credit. Platforms like Amazon, Facebook, or Alibaba already implemented various types of financial services into their ecosystems. COVID-19 crisis tremendously accelerated this process in which artificial intelligence is used to determine creditworthiness and communication with clients (see Boot Arnoud et al. 2020). It is still not clear how policymakers will respond to this phenomenon having in mind potential operational and cybersecurity risks as well as consumer privacy issues. One thing is certain, very soon both the physical and digital realms will be fully financialized. QE as a key policy tool to fight the Great Recession, repo crisis, and COVID-19 pandemic has become a norm, a conventional policy that is most likely here to stay. One-time policy tool seems to become a permanent solution for each economic downturn no matter what is the primary cause of the crisis. Although it helped to somehow stabilize the financial and economic system it significantly boosted asset prices such as housing and financial assets. This resulted in the stock markets becoming totally disconnected from reality. Upon implementation of QE policy, we have witnessed remarkable rebounds in the stock markets. The most recent performance during the COVID-19 crisis was at the same time astonishing and puzzling. In February 2020 COVID-19 panic caused a severe market crash in which circuit breakers have been utilized almost on a daily basis and stock markets suffered one of the greatest single-day percentage drops. Between February 20th and March 23rd, when the market hit the bottom, S&P 500 lost 33% of its value, and dipped even below the 2200 level. Yet, despite still deterioration economic conditions, S&P 500 rebounded above 3900 levels as of early February 2021, almost 20% higher than the pre-pandemic peak. So what is driving the stock market so high?

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Fig. 6.6 Federal debt, household debt, and debt of nonfinancial corporations in USA (Source FRED)

Firstly, since the time of the Great Recession the level of household debt has been slowly decreasing while federal debt and corporate debt took an upward path (see Fig. 6.6). At the first glance, this seems positive since households were overleveraged before the 2008 crisis and an increase in corporate debt could point out toward more investment and innovations, therefore, bringing down unemployment and increasing economic growth. However, in the last 40 years, the level of private debt (both households and corporate) has been significantly upward slopping and reached extremes in the last 15 years. High private debt makes consumers and businesses financially constraint and risk-averse which is outright deflationary and hurts the economic performance of the country. So why did corporations take so much debt and how did they use it? It was because they could cheaply borrow money due to historically low interest rates and invest it into physical and human capital as well as innovations, the key driving forces to increase a firm’s productivity and competitiveness. Yet, a good part of new debt, along with earned income, was channeled toward corporate buybacks, a well-known tool to distribute cash to shareholders which in return provide large bonuses for the executives. So instead of investing in productive resources to boost competitiveness in the long run, corporate executives chose to manipulate stock prices for short-term benefits. In addition, in December 2017 US administration provided massive fiscal stimulus via the Tax Cut and Job Act by lowering corporate taxes from 35 to 21%. As a result, in 2018 alone, companies listed in the S&P 500 Index did a combined $806 billion in buybacks, around $200 billion more than

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the previous record set in 2007. Instead of job creation and investments, corporate leaders decided to use fiscal injection for stock repurchase. Stock buybacks have been increasing since 2008 with some corporations, such as airlines, using more than 90% of their cash for this purpose, while others even went on the debt market to finance share repurchases. In addition, corporations used buybacks to attain desired leverage or debt as a share of assets. According to the Bank of International Settlement, excessive leverage is a financial stability concern and should be a matter of adequate policy response (see Aramonte 2020). Between 2009 and 2020, US firms distributed more than $6 trillion in buybacks and around $4 trillion in dividends (see Fig. 6.7). This is estimated as highly stock market positive. Secondly, a decade of QE + zero interest rates policy pushed conservative investors to become stock market speculators. In such an economic environment-saving in banks or investing in low-risk securities such as bonds provides small or even negative inflation-adjusted returns for both retail and institutional investors. This is of course stock market positive. When the Fed started balance sheet normalization in mid-2017, via quantitative tightening, and gradually increased interest rates to 2–2.25% level, it caused adverse reactions in the stock and bond market. As trading liquidity started to drawn, in February and December of 2018 the stock market experienced two significant downturns. At some point, it seemed

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Fig. 6.7 S&P 500 dividends and stock buybacks (quarterly data) (Source S&P Dow Jones Indices 2020)

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that the Fed is diligent in pursuing balance sheet reduction claiming the process of monetary tightening is on autopilot. Yet, soon after S&P 500 crashed 20% in December 2018, Fed started backpedaling and stopped normalization policies. During 2019 it even started decreasing interest rates and bailed out the repo market. As a result, S&P 500 boomed around 1000 points in 2019, a stunning and historical 28% gain. The Fed’s excuse, of course, was to meet inflation targets and prepare for possible headwinds due to a trade war with China. For whatever reason, this proved that there is a vicious circle between QE, ZIRP, and the stock market. In other words, the stock market performance is fully addicted to QE and zero rate environment and once it stops and FED reverses its policies, it will most likely end up in severe stock market collapse. In response to the COVID-19 crisis, the Fed nearly doubled the assets on its balance sheet in just two months and announced unlimited QE. This along with the corporate bonds purchasing program boosted the stock market even when little was known about the development of the efficient vaccine. The standard metrics for evaluating stock markets such as cyclically adjusted price-to-earnings ratio (CAPE) and market capitalization to GDP ratio have both exploded higher since the introduction of QE. Indeed, the stock market capitalization to GDP ratio spiked above 190% as of February 2021 indicating that the stock market is significantly overvalued. Stock market prices have completely separated from economic reality and no more represent true reflections of the corporate earnings (see Fig. 6.8). The euphoria fueled by the Fed’s actions resulted in one of the steepest stock market recoveries and the sentiment spilled over into the bond market where the average yield on junk bonds, as of February 2021, has dropped below 4% for the first time in history. Such an environment prevents bankruptcies even for the so-called zombie companies who can now easily refinance or take new debt to maintain their cash-burning addiction. This is also estimated as a stock market positive since large-scale purchasing of fixed income securities is estimated to have a substantial positive spillover effect on the stock markets. It is conceptualized like the Fed is indirectly buying stocks. Corporate bond prices are linked to corporate profits, stability, and creditworthiness and corporate bond facility allow the Fed to establish an implicit price floor in the secondary market by sending a message to investors that higher bond prices would be supported by the Fed. Other central banks, such as the Bank of Japan and the Swiss National Bank, have already established programs for direct

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4500

Real S&P Composite Stock Price Index

4000

Real S&P Composite Earnings

3500

450 400 350

3000

300

2500

250 Price

2000

200

1500

150

1000

100 50

500 0 1870

Earnings 1890

1910

1930

1950

1970

1990

0

2010

Fig. 6.8 S&P 500 stock price index vs earnings (Source http://www.econ.yale. edu/~shiller/data.htm)

stock purchase. At this point Bank of Japan has become the biggest owner of the stocks listed in the Japanese stock market while Swiss National Bank owns more publicly traded shares of Facebook than its owner Mark Zuckerberg. This is of course stock market positive as central banks have unlimited buying firepower via creating currencies out of thin air. Obviously, this rampant speculation has much of the characteristics of the dot-com bubble but this time any small market correction is perceived to be backstopped by the Fed or other central bank actions. At least that was the case since 2008. Figure 6.9 clearly supports our position on the strong nexus between quantitative easing and stock market growth in the USA. To validate the link (correlation in Fig. 6.9) and causality between quantitative easing and stock market growth we use cross-spectral analysis. Data we use for the modelling appears as listed: v1 rgdp

Velocity of Money Stock for USA, Ratio, Annual, FRED. (1870–2020) Real GDP (millions of 2012 dollars) Measuring worth, Samuel H. Williamson, “S&P Index, Yield and Accumulated Index,

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Fig. 6.9 Stock markets and real economy decoupling in the USA 1870–2020 (Source Authors calculation)

cpi

int1

int2

S&P

1871 to Present,” MeasuringWorth, 2021. URL: http:// www.measuringworth.com/datasets/sap/(1870–2020) US Consumer Price Index, Samuel H. Williamson, “The Annual Consumer Price Index for the USA, 1774–Present,” MeasuringWorth, 2021. URL: http://www.measuringworth. (1870–2020) US Short-Term Rate: Ordinary Funds, Contemporary Series, Samuel H. Williamson, “Sources of Interest Rates” Measuringworth, 2021. (1870–2020) US Long-Term Rate: Contemporary Series, Samuel H. Williamson, “Sources of Interest Rates” Measuringworth, 2021. (1870–2020) US Short-Term Rate: Ordinary Funds, Contemporary Series, Samuel H. Williamson, “Sources of Interest Rates” Measuringworth, 2021. (1870–2020)

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S&P1

S&P2

bond

ta

6.5

The Accumulated S&P Index Average for January, The accumulated index assumes that upon receipt of each cash dividend, the investor holding the portfolio of the stocks in the index would reinvest them in the portfolio. It does not take into account fees or taxes. Samuel H. Williamson, “Sources of Interest Rates” Measuringworth, 2021. (1870–2020) S&P Composite stock price index, January measuring worth, Samuel H. Williamson, “S&P Index, Yield and Accumulated Index, 1871 to Present,” Measuring Worth, 2021. URL: http://www.measuringworth.com/datasets/sap/. (1870–2020) and (2003q1–2020q4) Long-term historic 10 Year Treasury Yields, R. Shiller, MIT Press, 1989, and Irrational Exuberance, Princeton 2015 and US treasury. (1870–2020) Assets: Total Assets: Total Assets (Less Eliminations from Consolidation): Wednesday Level, Millions of US Dollars, Quarterly, Not Seasonally Adjusted, Board of Governors of the Federal Reserve System (US), Assets: Total Assets: Total Assets (Less Eliminations from Consolidation): Wednesday Level [WALCL], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/ WALCL, February 12, 2021. (2003q1–2020q4)

Results: So How Strong Is the Nexus?

To study the synchronization between financial and business cycles in the UK from 1270 to 2016, we use bivariate cross-spectral analysis (see Fig. 6.10). As proxy for quantitative easing, instead of using FED assets growth, we use velocity of money stock (ratio, annual FRED, Friedman and Schwartz 2008). We use coherency spectrum (correlation coefficient) of the form (Iacobucci 2005)    ˆ   S12 (k) Cˆ 12 (k)2 + Qˆ 12 (k)2  = (6.1) Kˆ 12 (k) =  Sˆ1 (k) Sˆ2 (k) Sˆ1 (k) Sˆ2 (k)

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Fig. 6.10 Cross-spectral analysis of quantitative easing and US stock market 1870–2020 (Source Authors’ calculation)

Taking the square of the Eq. (6.1) we get the coherence squared representing R2 in time domain notation. From Fig. 6.11 we can see that squared coherence (bottom right) is statistically significant (5% threshold) at all frequencies beyond 0.03 (above the 5% threshold level line). The squared coherence reach peak in three distinct and separate intervals. The first interval is at a frequency of 0.03 (corresponding to 33 years) with a coherency-squared reaching 0.82. That means in at the 33-year interval (frequency 0.03), quantitative easing can explain 82% of the movements in the stock market growth. In the next interval (5 years average, frequency 0.22), R2 again reaches 0.82 with the same notation and explanation as above. At the third interval (years average, frequency 0.35), dynamics in the FED balance sheet (quantitative easing) can explain 79% (R2 = 0.79) of stock market movements. The synchronization between quantitative easing and stock market growth is exceptionally strong in medium (2–3 years) and long run (33 years). In the medium term, when quantitative easing and stock market growth move together (3–5 years

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Fig. 6.11 Cross-spectral analysis of US stock market and inflation 1870–2020 (Source Authors’ calculation)

average), quantitative easing can explain 80% (R2) of the variance in stock market growth. Phase difference spectrum helps us invalidating the results of the coherency squared analysis. The coherence squared reach highest values (around 0.80) at 3-, 5-, and 33-year interval when the phase difference between quantitative easing and stock market growth (top left in Fig. 6.10) is close to zero. Therefore, the quantitative easing and stock market series have the same phase relationship (highest coherence at 3-, 5-, and 33-year intervals). Thereafter, the phase difference between the two series remains constant—close to zero (see the top left panel in Fig. 6.10). We measure the phase difference using the phase spectrum (time-lag) of the form (Iacobucci 2005)   Qˆ 12 (k) (6.2) Φˆ 12 (k) = arctan − Cˆ 12 (k)

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measuring the number of leads (Φˆ 12 (k) > 0) or lags (Φˆ 12 (k) < 0). From Fig. 6.10 we can see quantitative easing the influence of the movements in the stock market. Influence is particularly strong at 3-, 5-, and 33-year intervals. In the medium and long run, we observe significant impact of quantitative easing on the stock market. However, the impact we register at 2-, 4-, and 9-year intervals is statistically significant but half as strong in relation to the at 3-, 5-, and 33-year intervals. The gain (regression coefficient) follows (Iacobucci 2005)   ˆ   S12 (k) ˆ (6.3) G 12 (k) = Sˆ1 (k) showing the impact of the spectrum (quantitative easing u 1 (k)) on the stock market growth spectrum (u 2 (k)). The gain coefficient demonstrates quantitative easing strongly impact stock market growth in the medium and long term (3–33 years). Variance in the stock market growth (see Fig. 6.11 bottom left) is strongly influenced by the variance (change) in the quantitative easing. The co-spectrum shows quantitative easing and stock market growth series covariance is concentrated in the medium and long term (3–33 years average). Quantitative easing and stock market growth moves along over the medium-term spectrum as we can see from the bottom left panel in Fig. 6.11. We can see that the two series are related since we find a non-random distribution in their phase differences. In the short run quantitative easing lead stock markets while in the medium term and long term they move together (phase difference close to zero). The link between US stock market growth and inflation is displayed in Fig. 6.11. From Fig. 6.11 we can observe a strong link between stock market growth and inflation. R2 is averaging from 0.80 to 1.00 for all intervals, from the short to the long run. US stock market is an important inflation determinant as data from 1870 to 2020 shows. The impact is more pronounced in the short and medium run and less in the long run. Inflation may not be the event of today’s US stock market but for sure is lurking and waiting for the right moment. Bottom right panel on Fig. 6.11 is clear proof. To test the robustness of our results and explain the QE impact on the stock market in more details, we use the spectral Granger causality model

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of the form Geweke (1984) xt = c− +

ρ 

α j xt−1 +

i=1

ρ 



ρ+d nx

p+ jn−x

β1 yt− j +

j=1

ak xt−k +

k− p+1

βk yt−k + et

k− p+1

(6.4) where xt yt zt

cause variable effect variable lagged values of additional variables.

Using the test in the form of Breitung and Candelon (2006) xt = c1 +

p  j=1

α j xt− j +

p  j=1

β j yt− j +

p+d max 

αk xt−k +

k=ρ+1

p+σ mx

βk yt−k + et

k= p+1

(6.5) a modified Wald test for frequency domain tests with p d max

lag order the highest order of integration in the system.

To test for the spectral Granger causality, we use STATA Granger causality test (bgcausality) developed by Tastan (2015) (Škare and Porada-Rochon 2019) (Fig. 6.12). The test statistics for Granger non-causality from the velocity of money (QE – lv1) to stock market (lsp2) are significant at 5 and 10% for frequencies ω (0, 1) and (0, 1.2). The null hypothesis that there is no Granger causality for low-frequency components in the range ω (0, 1.2), which correspond to wavelengths of 5–30 years, is rejected at the level of significance of 5% (QE) does Granger cause stock market growth, depending on the 10-year treasury yield. Other variables, like inflation, real GDP, short-term interest rates have no impact in the Granger sense (test results not reported here). To examine the impact of (QE) on US stock market growth, after proving (QE) Granger cause stock market growth (S&P 500 index),

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Fig. 6.12 Breitung and Candelon (2006) frequency domain Granger causality test from QE to stock market conditional on 10-year treasury yield (Source Authors’ calculation)

we apply time-varying transition modeling following Kim and Nelson (1999), Filardo (1994). The model takes the form       yt = μ St + φ1 yt−1 − μ St−1 + φ2 yt−2 − μ St−2 + φ3 yt−3 − μ St−3   + φ4 yt−4 − μ St−4 + εt (6.6) with regime-switching transition probabilities

p11,t p12,t P(St = st |St−1 = st−1 ) = p21,t p22,t

(6.7)

and probability of regime transition P{St+1 = st+1 | St = st , ct }

p11 (ct ) 1 − p11 (ct ) = 1 − p22 (ct ) p22 (ct )

(6.8)

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Applied Markov switching time-varying transition model correctly identifies the start of the (QE) in 2008 (QE 2) in 2009, and pandemic (QE) in 2020 (QE 3) after 2012 is not identified by the model. Two spikes are clearly visible from Fig. 6.13. Top figure showing the probability of entering into (QE) regime and bottom of not entering in the (QE). In the model, we use also S&P 500 stock price index as a predictor for (QE). The estimated parameter for S&P 500 is statistically significant validating the link between (QE) and stock market growth. Both spectral Granger causality and Markov switching time-varying results prove (QE)

Fig. 6.13 Shows graphs of transition probabilities between regime 1 (actual QE) and regime 2 (No QE) (Source Authors’ calculation)

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is a driving factor in US stock market growth. The expected duration for the (QE) regime is about 4 quarters when (QE) starts.

6.6

Conclusion

Quantitative easing as a key policy model in the fight against the Great Recession, repo crisis, and the COVID-19 pandemic has become a conventional monetary tool in advanced economies. Temporary measures are made permanent by the cycles of recessions, no matter what caused the economic crisis. COVID-19 crisis even pushed monetary authorities from emerging market economies to implement the QE toolkit for the first time in history. Therefore, QE became a global phenomenon that is here to stay as long as there are no fears of higher consumer inflation. Issues of skyrocketing public debt and deficit as well as unlimited currency creation for various economic purposes no longer seem to be a problem for policymakers. It leads to complete reshuffling of macroeconomics with Modern Monetary Theory taking the main stage. However, not every QE program is the same and has identical mechanics and impact on inflation. QE programs prior to COVID-19 were inherently not pro-inflationary since there was no transfer of funds to the wider public, yet huge fiscalQE introduced in 2020 could easily lead to much higher consumer prices. Such a scenario would be the end game for the current global monetary agenda. Although QE was somehow beneficial for long-term economic development, it significantly raised asset prices such as housing and financial assets. As a result, markets became widely disconnected from the actual economic situation. Upon implementing the QE policy, we have witnessed remarkable and puzzling stock market rallies. During a peak of COVID-19 panic in February–March 2020 we witnessed widespread use of circuit breakers and a dramatic stock market crash, with stock markets experiencing one of the largest percentage drops in a single day. The S&P 500 lost 33% of its value and dipped below $2200 before reaching a hard bottom. Despite unemployment remaining high, the S&P 500 has now reached a level that is 20% above its pre-pandemic peak. Our study provides explanations on what drives investments in stocks since 2003. This study identifies QE as the main driver of US stock market growth after the year 2000. The link between QE, reflected in money velocity and stock market growth was always robust, since 1870. Sure, technically no QE before 2008 existed but financial deregulation, since 1870 had a

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large impact on money supply, velocity, and stock prices. We run spectral Granger causality modeling to deal with the problem of stationarity and structural breaks (shocks) in the data. Both spectral coherence analysis and Granger causality test results prove the hypothesis that QE in form of financial deregulation prior to 2008 or printing money after 2008 is the main driver of US stock market growth. Using Markov switching timevarying transition model, we prove that both in 2008–2009 and 2020 QE programs conditioned on S&P 500 stock price index, the movement in the actual stock market was the primary target of QE programs. In fact, the expected duration of QE regimes is directly dependent on the US stock market growth. It is the same S&P 500 price index growth to condition on the duration of the QE regime. Future studies should focus on explaining the exact mechanism and channels behind the QE and stock market growth we identify and provide empirical results for its existence for the US and other international stock markets.

References Aramonte, Sirio. 2020. Mind the Buybacks, Beware of the Leverage. Bank of International Settlements Quarterly Review. Barbon, Andrea, and Virginia Gianinazzi. 2019. Quantitative Easing and Equity Prices: Evidence from the ETF Program of the Bank of Japan. Review of Asset Pricing Studies 9: 210–255. Bateman, Milford (ed.). 2011. Confronting Microfinance: Undermining Sustainable Development. Sterling, VA: Kumarian Press. Bateman, Milford, and Ha-Joon Chang. 2009. The Microfinance Illusion. Available at SSRN: https://ssrn.com/abstract=2385174 or http://dx.doi.org/10. 2139/ssrn.2385174. Bernanke, Ben S. 2020. The New Tools of Monetary Policy. American Economic Review 110: 943–983. Bernanke, Ben S., and Kennet N. Kuttner. 2005. What Explains the Stock Market’s Reaction to Federal Reserve Policy? Journal of Finance 60: 1221– 1257. Board of Governors of the Federal Reserve System (US). 2021. Assets: Total Assets: Total Assets (Less Eliminations from Consolidation): Wednesday Level [WALCL]. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/WALCL, February 12, 2021 (2003q1 to 2020q4). Board of Governors of the Federal Reserve System (US). 2021. Cash Assets, Large Domestically Chartered Commercial Banks [CASLCBW027SBOG].

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Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stl ouisfed.org/series/CASLCBW027SBOG. February 4, 2021. Board of Governors of the Federal Reserve System (US). 2021. Treasury and Agency Securities, Large Domestically Chartered Commercial Banks [TASLCBW027SBOG]. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/TASLCBW027SBOG. February 4, 2021. Boot Arnoud, W.A., Peter Hoffmann, Luc Laeven, and Lev Ratnovski. 2020. Financial Intermediation and Technology: What’s Old, What’s New? IMF Working Paper No. 20/161. Breitung, Jorg, and Bertrand Candelon. 2006. Testing for Short- and LongRun Causality: A Frequency-Domain Approach. Journal of Econometrics 132: 363–378. Brusa, Francesca, Pavel Savor, and Mungo Wilson. 2020. One Central Bank to Rule Them All. Review of Finance 24: 263–304. Cieslak, Anna, Adair Morse, and Annette Vissing-Jorgensen. 2019. Stock Returns over the FOMC Cycle. Journal of Finance 74: 2201–2248. Federal Reserve Bank of St. Louis. 2021. Velocity of M2 Money Stock [M2V]. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stloui sfed.org/series/M2V. February 7, 2021. Filardo, Andrew J. 1994. Business Cycle Phases and Their Transitional Dynamics. Journal of Business and Economic Statistics 12: 299–308. Friedman, Milton, and Anna Jacobson Schwartz. 2008. A Monetary History of the United States, 1867–1960. Princeton: Princeton University Press. Gagnon, Joseph, Matthew Raskin, Julie Remache, and Brian Sack. 2011. The Financial Market Effects of the Federal Reserve’s Large-Scale Asset Purchases. International Journal of Central Banking 7: 3–43. Geweke, John F. 1984. Measures of Conditional Linear Dependence and Feedback Between Time Series. Journal of the American Statistical Association 79: 907–915. Guo, Haifeng, Alexandros Kontonikas, and Paulo F. Maio. 2020. Monetary Policy and Corporate Bond Returns. Review of Asset Pricing Studies (forthcoming). Available at SSRN: https://ssrn.com/abstract=3547931. Iacobucci, Alessandra. 2005. Spectral Analysis for Economic Time Series. In Lecture Notes in Economics and Mathematical Systems (203–219). SpringerVerlag. https://doi.org/10.1007/3-540-28444-3_12. International Monetary Fund. 2020. Global Financial Stability Report (October). https://www.imf.org/en/Publications/GFSR/Issues/2020/10/ 13/global-financial-stability-report-october-2020#Chapter2. Kim, Chang-Jin, and Charles R. Nelson. 1999. State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications, vol. 2. Cambridge: MIT Press.

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Mader, Philip. 2015. The Political Economy of Microfinance: Financializing poverty. Basingstoke, UK: Palgrave Macmillan. Palley, Thomas I. 2007. Financialization: What It Is and Why It Matters. Working Paper wp153. Political Economy Research Institute. University of Massachusetts at Amherst. Putnins, Tallis J. 2020. From Free Markets to Fed Markets: How Unconventional Monetary Policy Impacts Equity Markets. Available at SSRN: https://ssrn. com/abstract=3621460 or http://dx.doi.org/10.2139/ssrn.3621460. Shiller, Robert. 1989. Market Volatility. Cambridge, MA: MIT Press. Shiller, Robert. 2005. Irrational Exuberance, 2nd ed. Princeton; Oxford: Princeton University Press. https://doi.org/10.2307/j.ctt7st4s. S&P Dow Jones Indices. 2020. S&P 500 Q1 2020 Buybacks and Related Data. June 2020. Retrieved February 2021. S&P Dow Jones Indices LLC, S&P/Case-Shiller U.S. National Home Price Index [CSUSHPINSA]. 2021. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/CSUSHPINSA. February 16, 2021. S&P 500 Index—90 Year Historical Chart. 2021. Macrotrends. URL: www.mac rotrends.net/2324/sp-500-historical-chart-data. February 3, 2021. Škare, Marinko, and Malgorzata Porada-Rochon. ´ 2019. Multi-channel SingularSpectrum Analysis (MSSA) of Financial Cycles in Ten Developed Economies 1970–2018. Journal of Business Research 112: 567–575. Stock Market Data Used in “Irrational Exuberance”, Princeton University Press. 2000–2015 (updated). http://www.econ.yale.edu/~shiller/data.htm. Retrieved February 2021. Tastan, Huseyin. 2015. Testing for Spectral Granger Causality. Stata Journal 15: 1157–1166. U.S. Office of Management and Budget and Federal Reserve Bank of St. Louis. 2021. Federal Debt: Total Public Debt as Percent of Gross Domestic Product [GFDEGDQ188S]. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/GFDEGDQ188S. February 10, 2021. Vissing-Jorgensen, Annette, and Arvind Krishnamurthy. 2011. The Effects of Quantitative Easing on Interest Rates: Channels and Implications for Policy. Brookings Papers on Economic Activity 42: 215–265. Williamson, Samuel H. 2021. The Annual Consumer Price Index for the United States, 1774–Present. MeasuringWorth. https://www.measuringworth.com/ datasets/uscpi/. Williamson, Samuel H. 2021. S&P Index, Yield and Accumulated Index, 1871 to Present, MeasuringWorth. http://www.measuringworth.com/datasets/sap/. Williamson, Samuel H. 2021. Sources of Interest Rates Measuringworth. https://www.measuringworth.com/datasets/interestrates/.

CHAPTER 7

Monetary Policy in Croatia During Two Recessions Neven Vidakovi´c

7.1

Introduction

This paper investigates the Croatian National Bank’s conduct of the monetary policy during two crises. The first Crisis is the 2009–2012 crisis and the second one is the most recent COVID-19 crisis. From the onset, it should be stated that both crises have vastly different initial starting points. The first crisis was a financial crisis, much like the 1930s great depression, while the second crisis was a medical crisis with severe economic effects. However, the effects of both crises on the economy have been strikingly similar. Both crises have created significant disturbances in the Croatian economy. The first crisis resulted in a cumulative decrease of GDP of −11.6% in terms of real GDP in the time period from 2009 to 2014 with six years of consecutive negative economic growth. Such a long period of economic growth can only be described as an economic disaster. The effect of the COVID crisis so far can only be seen in a quarterly decrease of GDP of −15.4% in the second quarter of 2020

N. Vidakovi´c (B) Loti Trading LLC, Zagreb, Croatia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_7

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and −10% in the third quarter with a loss of 37,000 jobs.1 The full extent of the crisis will not be known for years. During both crises, monetary policy has been at the forefront of economic policy. During the last decade, global monetary policy has been in an undiscovered country. Interest rates were first pushed to zero and then negative rates were introduced. From traditional purchases of the short-term government securities, central banks have significantly expanded their list of asset purchases: long-term government bonds, mortgage bonds, corporate bonds, even mutual funds. During the crisis of 2020, both ECB and Fed have started to give out direct loans to corporations bypassing the banking sector. Also, new transactions were introduced like long-term repos to guarantee the banks’ liquidity. New monetary policy tools were also introduced like forward guidance. Communication of central bank with the general public has also changed. From strict information on interest rates and quantity of money like we had in the Volcker-Greenspan era, central bank governors have started to communicate frequently, more openly, and have adopted a policy that monetary policy is much more than just managing inflation. The increase in communication can be seen in regular press conferences and the publication of explicit forward guidance. The increase in the communication of the central bank with the overall public has reached its peak in the FED monetary policy review. The new monetary policy tools have been in detail described in Bernanke (2020). Central bankers have also exhibited firm stands on certain issues and unprecedented ability to change, evolve, and react to new situations. The first is best exemplified in Mario Draghi’s famous “whatever it takes2 ” sentence while the second is best exemplified in a FED’s comprehensive monetary policy review undertaken partly during the COVID crisis and resulting in de facto abandonment of inflation targeting with Chairman Powell’s pointing out that economies cannot allow themselves the fate of Japan, a country with prolonged deflation. FED for decades wanted low and stable inflation formally adopting inflation targeting. Realizing the negative effects of prolonged low inflation, FED changed and explicitly stated that preventive interest rate hikes are off the table until the economy fully reflates. While FED fought low inflation and has tried to achieve its dual mandate of full employment and price stability, ECB has had a particularly hard time over the period of the last ten years because it has had to fight on two major fronts. The first was the economic crisis that spilled

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over from the USA to the rest of the world and the second crisis was the stability and continuing existence of the euro. The second crisis has not been fully resolved and after Brexit, it is a distinct possibility. During the most innovative period in the monetary policy, Croatian National Bank has largely been passive and has participated extraordinarily little in both creation of new theory and implementation of best practices adopted by other central banks. The governor of central bank Boris Vujˇci´c even went as far as to admit his own ignorance of monetary policy publicly calling for someone to explain the monetary policy and monetary innovations of ECB to him3 and how can they be applied to Croatia. CNB has mostly been closed and with limited innovation in terms of monetary policy. Before the COVID crisis, the most innovative policy tool introduced was long-term repo operation. The rest of the policies introduced during the Great recession were nothing more than the adjustments in reserve requirement and liquidity ratios. Measures that were introduced as “macroprudential policies” before the crisis like limited credit growth and marginal reserve requirement were neither original nor effective. CNB even went as far as to openly admit that marginal reserve requirement have only boosted the imbalances in the economy. The lack of action and the glorification of the monetary policy conducted by CNB can be found in CNB’s own research with examples like Dumiˇci´c (2015, 2017). However, a different view on the monetary policy was presented in economic research both before and during the great recession with great examples of an alternative approach to the role of the central bank in the economy given by Radoševi´c (2001, 2009a). In spite of being passive before the COVID crisis during 2020 CNB has radically changed its transactional policy. It has started to purchase government bonds. The introduction of sterilization has allowed CNB to maintain both domestic currency liquidity and exchange rate stability. This is the most significant improvement in monetary policy in Croatia’s history. In the long run, the most significant change in the monetary policy is the fact Croatia has joined the ERM II system and is on the fast track to adopt Euro. The current projected date is January 1, 2023. This brings us to the main objective of this paper. We will review the two crises and the conduct of monetary policy in Croatia in the light of the COVID crisis and give some policy guidance especially now when Croatia is part of the ERM II mechanism.

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The lack of action in terms of monetary policy should not be confused with the significant improvements in terms of banking regulation where CNB has made significant progress implementing the latest regulatory practices and working closely with other EU bodies. Section two will review the monetary framework in Croatia, Sections three and four analyze monetary policy during the two crises while section five looks at the credit policy during the two crises. Section six explains the evolutionary process of monetary policy in Croatia and the implications of monetary policy during the COVID crisis. Part seven presents some policy recommendations and part eight concludes.

7.2

Monetary Policy Framework in Croatia

This part of the paper is briefly going to go over the monetary arrangement in Croatia. The main objective of the monetary policy in Croatia has been the stability of the exchange rate. CNB has long maintained that price stability can be achieved through exchange rate stability. The confusion between monetary policy instruments and monetary policy goal has from the onset been a major methodological problem with the monetary policy in Croatia. The exchange rate (a policy tool) has been mistaken for a policy objective (exchange rate stability). CNB has mistakenly believed that the exchange rate stability will lead to price (inflation) stability. This approach is dubious in both theory and practice. For a comprehensive study on the effect of monetary policy and inflation in a small open economy, see Vidakovi´c (2014). From a theoretical perspective, the assumption that exchange rate stability will provide price stability a priori assumes that the only source of inflation in a small open economy is the change in the exchange rate. Eliminating the volatility of the exchange rate should lead to price stability according to the CNB. This approach to the sources of inflation eliminates at least two other sources of inflation: supply-side the driven rise in prices which can create inflationary pressure and rise in inflationary pressures because of the increase in expectations of future inflation. CNB never considered these two sources of inflation as potential causes of inflation and has never created monetary policy tools to address those two sources of inflation. On a practical level assumption that exchange rate stability leads to price stability has increased the central bank’s complacency when it comes to central bank’s operations: monetary policy was largely conducted only

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through FX operations focusing monetary policy operations on only one source of inflation and never developing other tools in order to combat other sources of inflation. This methodological mistake has severely hampered monetary policy in Croatia. Let us look at the monetary arrangement the central bank has imposed. Following the framework used in Vidakovi´c (2016), there are three major markets central banks impact in a small open economy through monetary policy operations using only FX transactions. The first market is the domestic market for foreign currency market (FCM). The second is the domestic market for domestic currency market (DCM) and the third market is the domestic credit market. The first market represents the foreign currency liquidity in the economy, the second market represents the domestic currency liquidity of the banking sector in the economy and the third market is the credit market which represents changes in economic activity because credit should be tied with investments. When the central bank performs an FX transaction on the FCM, the exchange rate stabilizes, but the FX transaction of HRK and Euros changes the quantity of domestic currency on the DCM. The FX operations by the CNB are only money for money transactions so the transactions on the FCM have direct effects on the DCM. The methodological construct used by the CNB has only focused on the FCM and treating the DCM as irrelevant. The monetary policy is conducted based on the changes in the FX rate, not based on the domestic demand for money or the economy’s need for liquidity. So when there is a disturbance in the exchange rate, the CNB will perform a monetary operation, regardless of the state of the business cycle in the economy or domestic demand for currency at the time of the transaction. Figure 7.1 presents the FX transaction when the central bank purchases euros thus increasing the quantity of domestic currency in the economy. The setup of the monetary policy transactions is even more pronounced on a microeconomic level. The main participants on the DCM are domestic banks, so FX transactions change the domestic currency liquidity of domestic banks thus directly influencing bank’s credit policy on the domestic credit market. To better understand the effects of FX transactions on banks, we have to understand the banks’s liquidity structure. In the case of the domestic currency, banks in Croatia have four tiers of Croatian Kuna (HRK) liquidity needs.

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DomesƟc currency market

DomesƟc crediƟ market

S'

r

S' S

S

D

D

Q

Q

DomesƟc FX market

S

E

S’

D’

D

Q

Fig. 7.1 Decrease in the quantity of domestic money (Source Vidakovi´c 2016)

The first tier is liquidity needs for regulation. In Croatia, there is a reserve requirement for both domestic and foreign currency deposits. The percentage rate of reserve requirement is the same for both domestic and foreign currencies, but part of the reserve requirement for foreign currency is paid in domestic currency. So if a bank has the same amount of deposits subject to reserve requirement in both domestic and foreign currency, the funds used for reserve requirement will be higher in HRK because of the regulation which requires a portion of reserve requirement on foreign currency funds to be paid in domestic currency. This effectively increases the need for domestic currency for regulatory purposes. Second-tier liquidity needs are operational liquidity since HRK is the official means of payment in Croatia. This liquidity tier also includes currency in circulation. Banks use this liquidity to transact payments through a national clearing system.

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The third tier of liquidity needs is for lending. Loans in Croatia are predominantly in foreign currency clause. These types of loans are in the banks’ balance sheet valued as foreign currency loans, but in terms of liquidity, these loans are paid out in domestic currency. So increase in lending will increase bank’s demand for domestic currency. This also implies that the foreign currency has limited potential for lending since the most lending activity is done in domestic currency. The fourth tier is the liquidity needed for FX operations with CNB. This part is exceptionally important during times of economic stress. To keep the exchange rate stable, the central bank will perform the FX operations decreasing domestic currency liquidity in order to stabilize the exchange rate. The sale of FX reserves by the central bank will force banks to increase domestic currency liquidity to have domestic currency liquidity after FX operations. Since banks cannot decrease domestic currency used for regulation (unless the central bank decreases reserve requirement) and since they cannot decrease operational liquidity reserves, the only way to obtain domestic currency is by decreasing lending and preserving liquidity in domestic currency. Such behavior will lead to banks hoarding domestic currency and decreasing liquidity from the economy during times of financial stress. Since banks are aware of the monetary policy and how monetary policy has conducted any stress on the exchange rate or any currency outflow will automatically lead to the credit crunch in the Croatian economy because banks will start hoarding domestic currency. Depending on economic conditions, different tiers of liquidity will be the focus of the banks at different points in time, during different stages of the business cycle, and during different economic conditions. During stable economic times, banks will provide liquidity to the economy and entice borrowing, during economic distress banks will withdraw liquidity from the economy and maintain their liquidity regardless of the economic needs of the real economy. Depending on the economic situation, the banks will prioritize their liquidity focus. Economic instability with possible large FX operations will focus banks on the preservation of domestic currency and decreasing their lending activities. As we can see, the operational framework presented here is vastly different from the narrow view of a stable exchange rate. The central bank’s tunnel vision is what makes the Croatian economy so vulnerable. During economic shocks, CNB has relied only on one transaction.

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7.3

The Great Recession

Croatia came into a crisis in 2009 with a high level of macroeconomic imbalances. At the end of 2008, foreign debt was 44 billion Euros, as a percentage of GDP, it was 91%. Inflation in 2008 was 6.1%. The Household debt was around 18 billion EUR and in terms of households’ savings, the household’s debt was 118%. On aggregate, the Croatian households have borrowed more than they have saved. However, one thing was positive, very low government debt which was only 39% of GDP. These macroeconomic imbalances were only exasperated by the macroprudential measures imposed by the CNB. The regulation designed by CNB, especially the restrictions on lending has, by the admission of the CNB, increased Croatia’s foreign debt. The results of macro-prudential measures in Croatia were described in Vidakovi´c and Zbašnik (2014) and Radoševi´c and Vidakovi´c (2014). Flowing the debt crisis framework described in Soros (1998) cheap money that funded the credit boom in the period from 2000 to 2008 started to pull away from the economic periphery toward the economic center. Cheap money which was flowing toward emerging markets before 2007 and has funded housing boom and stock market boom with the start of the housing crisis in the USA started to pull out of the emerging economies. The effects of cheap money on developing and emerging markets can be found in Akyüz (2014) and Hoffmann (2014). The same boom-bust process which has happened in most developing and emerging economies has occurred in Croatia as well. Hot money which funded the credit boom with the onset of the global financial crisis started to leave the country. Mother banks which funded Croatian banks before 2008 and have loaned money to Croatian companies during the credit boom started to restrict capital flows to Croatia. With the onset of the global crisis, owners of Croatian banks also faced a liquidity crisis. Up to the global financial crisis which evolved into the great recession CNB assumed that foreign ownership of domestic bank was largely a stabilizing factor for a small open economy as determined in papers like Hofler and Payne (2006) and Galac and Kraft (2001). Especially due to the relative size of the Croatian banking sector vs. the banking sector of the countries where the mother banks are based. For example, at the end of 2008, two largest banks in Croatia Zagrebaˇcka banka and Privredna Banka Zagreb had assets of the approximate size of 14 and

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9.7 bln. Euros, respectively. But their asset size was almost irrelevant when compared to the total assets of the banking groups of which they are part of, Zagrebaˇcka bank was only 1.4% of the total assets of Unicredit Group and Privredna banka was only 1.5% of total assets Intesa Sanpaolo group at the end of 2008. However, such a small portion of assets in terms of the mother banks is a stabilizing factor when there is a banking crisis in Croatia because mother banks can provide capital and liquidity in case of the banking crisis in Croatia. But when the global crisis occurred, Italian banks were among the banks hardest hit by the crisis and became unstable themselves. The effects of this instability were evident inability to support their Croatian subsidiaries during the crisis. The combination of hot money leaving the country, economic instability due to global crisis, and distorted expectations about the future caused an exchange rate depreciation in Croatia. Using its existing monetary policy framework, the central bank focused on exchange rate stabilization. The central bank used two main tools to stabilize the exchange rate. The first tool changed in regulation especially reserve requirement and liquidity ratios, the second tool was the FX interventions. The main goal of both of these policy tools and implemented actions was to provide FX liquidity in order to stabilize the exchange rate, not to help the Croatian economy during the economic meltdown. The central bank decreased the reserve requirement from 17% in 2008 to 14% in December of 2008. By January 2014 the reserve requirement was 12%. Croatia also has regulations where a certain percentage of foreign currency deposits has to be kept in asset classes defined by the central bank. This regulation was called minimum foreign currency claims. Just like reserve requirement during the crisis, this regulation was also decreased from 32% in April of 2008 to 20% by February 2009 creating fresh foreign currency liquidity for the banks and consequent stabilizing the exchange rate of HRK vs. EUR. The change in regulation mostly created the FX liquidity, hence the exchange rate remained stable. But the domestic currency liquidity was decreased significantly. Over the course of fourth quarter 2008 to fourth quarter 2013, CNB has perfumed twenty-one FX interventions with the net effect of the decrease of 9.4 billion amount of HRK in Croatian economy, approximately 1.25 billion euros. Using the framework we have described in the previous section of the paper, we can see that in the case of the exchange rate depreciation, the central bank will use FX transactions to stabilize the domestic market

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for domestic currency. The result of FX operations will be a decrease of domestic currency in the economy an increase in interest rates and a decrease in the amount of credit. Banks knew what model the central bank is using and they hoarded domestic currency liquidity in order to participate in the FX transactions. In essence, it was a classical rational expectations equilibrium. Now we are going to look at the quantity of domestic currency in the economy during the crisis period. In the calculation of M4 in the economy, CNB uses foreign currency deposits, using the methodology proposed in Vidakovi´c (2020) which excludes the foreign currency deposits from the quantity of money we can see that total quantity of domestic money has decreased in the time period from 2008 to 2010 (Table 7.1). As we can see from the data, the monetary policy during the recession was exceptionally contractionary. Over the course of two years, CNB has decreased the domestic quantity of money in the economy by 18%, an exceptionally restrictive monetary policy. During the crisis, CNB has maintained its position that monetary policy was expansionary. Both statements are correct. CNB has maintained expansionary monetary policy in terms of the economy’s foreign currency liquidity, but it conducted restrictive monetary policy in terms of domestic currency liquidity because it sought to maintain the exchange rate stability, regardless of the effects on the real economy. Behavior is consistent with our model. Because of this approach, the Croatian economy has paid a severe price. Employment decreased by 150 thousand (July 2008 vs. March 2014), GDP decreased 11.6% during the 6 years of economic depression. As we can see the cure was worse than the disease. The real economy collapsed. We can now summarize the monetary policy during the first crisis. Because of the monetary framework oriented only on exchange rate stability when the crisis came the central bank followed it monetary Table 7.1 Quantity of money during great recession in bln HRK CNB M4 Transactional M4

2008

2009

2010

2011

2012

2013

2014

223.46 100.78

226.75 89.06

232.09 82.76

234.82 83.24

248.25 92.69

259.78 98.85

268.22 105.01

Source Author’s calculation, CNB4

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policy framework completely: it has maintained the exchange rate stability throughout the crisis. Because the focus of the monetary policy was never on other economic variables, the real results of the monetary policy were extreme.

7.4

The Second Crisis

The COVID-19 pandemic crisis was never seen in the globalized world we live in today. The epidemic spread from China and by March 2020 most global economies were in a quarantine protocol colloquially known as “the lockdown.” Effectively the economies shut down. The effects of the lockdown on the Croatian GDP were devastating, on annual level, GDP decreased 15.9% in nominal terms in QII and 10.5% in QIII of 2020. For Croatia, the 2020 crisis was completely different from the 2009 crisis. There was no long-term credit build-up and a lot of economic imbalances were decreased. Household’s debt to banks was cca. 18 billion EUR only 3% larger than in December of 2008. Croatia has had economic growth for 23 consecutive quarters from QIII 2014 until QI of 2020. However public finances were not in great shape as they were before the 2009 crisis. Prime Minister Andrej Plenkovi´c has decided not to use the fiscal surplus to decrease public debt but has instead decided to increase political privileges and maintain budget size. By the end of 2019, the public debt was 72.8% of GDP. So even though the public debt has somewhat decreased over time in terms of debt to GDP ratio in absolute numbers the debt has remained approximately flat for five years. Just like in 2009 after the lockdown announcement the exchange rate stability came under pressure and the central bank had to react. Again, the reserve requirement was decreased to 9% from 12%, but the foreign currency claims regulation was unchanged. This time around CNB introduced another transactional tool: it started to purchase government bonds. This new transaction has changed the monetary policy framework in Croatia. Using two monetary transactions, FX operations, and government bond purchases, CNB was now able to participate in two markets: the domestic market for foreign currency and the domestic market for domestic currency. When the economic shock occurred, CNB used the FX transactions to stabilize the exchange rate by purchasing HRK and selling EUR to the banks. The transaction decreased the quantity of kuna in the economy. Then CNB bought government bonds and

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has returned the quantity of domestic money back into the economy effectively stabilizing the exchange rate while maintaining the quantity of domestic money the same. This dual transaction provided both domestic and FX currency liquidity. Using our framework we can see that both domestic and foreign currency liquidity have been preserved and the domestic credit market was not affected by the monetary operations or domestic banks’ need for liquidity (Fig. 7.2). Again, the theoretical framework is strongly supported by the data. The total amount of FX transactions (net decrease of domestic currency) was negative 20.6 billion HRK. The total amount of government bonds purchased was 20.2 billion HRK. Approximately the same amount. From a transactional perspective, both domestic currency and foreign currency liquidity were preserved.

DomesƟc currency market

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S'

r

S S

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DomesƟc FX market

S

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Fig. 7.2 Sterilization operation (Source author)

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The effects of monetary transactions can also be seen in the quantity of money in the economy. Especially in the relationship of M0 to M1. Here we see a completely different picture from the one we have seen during the previous crisis. Figure 7.3 shows the M0 and M1 from the time period from January 2008 until December 2014. We can see that before the recession the M1 is greater than M0, a normal relationship for monetary aggregates. Once the crisis starts, M0 is greater than M1 for the period of six years. The inverse relationship of M0 and M1 is understandable on both theoretical and practical levels. The model predicts that the banks will hoard liquidity in order to be able to meet the CNB’s FX transactions for the exchange rate stabilization. Banks know the model used by the CNB to conduct monetary policy. Since they know the CNB will conduct restrictive monetary policy in domestic currency and expansive monetary policy in FX currency during times of crisis, the banks simply hoard domestic currency liquidity. The theoretical assumption is confirmed in practice when we compare the amount of domestic currency the CNB has taken out of the Croatian economy through the FX transactions. Once the global crisis has abated, the normal relationship between the M0 and M1 was restored. M0 vs. M1

70,000.0 65,000.0 60,000.0 55,000.0 50,000.0 45,000.0 40,000.0

M0

Fig. 7.3 M0 vs. M1 during Great Recession (Source CNB)

Sep-14

May-14

Jan-14

Sep-13

Jan-13

M1

May-13

Sep-12

Jan-12

May-12

Sep-11

May-11

Jan-11

Sep-10

Jan-10

Sep-09

Jan-09

May-09

Sep-08

Jan-08

May-08

30,000.0

May-10

35,000.0

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During the COVID crisis, we can see a completely different picture. Through the crisis M0 is smaller than the M1, the banks are no longer hoarding the domestic currency liquidity. This data is the direct result of new transactions introduced by the CNB. The liquidity taken by the FX transactions the CNB has returned by purchasing government bonds. The same analysis of M0 and M1 monetary aggregates can be done for the period of COVID crisis. We can see from our theoretical framework the monetary policy has drastically changed during the COVID crisis. The introduction of new transactions has changed the behavior of banks and the change of behavior can be seen in the data. We are dealing with the limited data, but in Fig. 7.4, it can be clearly seen that throughout the period of 2020 the M1 monetary aggregate is larger than the M0 monetary aggregate which is consistent with the monetary theory and is the direct result of the introduction of the new monetary operations. The effects of monetary policy on the real economy can not be analyzed at this time.5 The vaccination process has started but some countries are still in lockdowns. Because of the situation at this time, it is impossible to separate the real economic effects of a pandemic on the economy and the effects of monetary policy on the real economy. What we can see is that the behavior of the central bank, which resulted in changes in the quantity of money, has had different effects on monetary M0 vs. M1

160,000.0 150,000.0 140,000.0 130,000.0 120,000.0 110,000.0 100,000.0 90,000.0 80,000.0 Jan-20

Feb-20

Mar-20

Apr-20 M0

May-20

Jun-20

M1

Fig. 7.4 M0 vs. M1 during COVID (Source CNB)

Jul-20

Aug-20

Sep-20

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aggregates during the COVID crisis than it has during the great recession. The exchange rate stability was preserved during the COVID crisis, but not at the expense of the quantity of domestic money in the economy. Because of the introduction of the new transactions, CNB was able not to make the same mistake it did in the previous crisis.

7.5

Credit Policy During Two Crisis

During the great recession and the COVID crisis, providing liquidity to the economy has been presented as the main focus of monetary policy. However, in my view, it is much more important to focus on credit policy during recessions. Increasing the quantity of money without a clear understanding of how that money is circulating in the real economy is blinding the central bankers. Where the new money is being used (real investments or asset bubbles) should be the focus of the central bankers, not just price stability and interest rates. Figure 7.5 shows the development of credit in Croatia during two crises. We can see a significant change in the structure of banking loans over the course of the last 10 years. While loans to households have remained flat in the time period of 2008 to 2019, the loans to corporations have been surpassed by the loans to the government. Loans 2008 - 2019 140,000.0 120,000.0 100,000.0 80,000.0 60,000.0 40,000.0 20,000.0 0.0 12.08. 12.09. 12.10. 12.11. 12.12. 12.13. 12.14. 12.15. 12.16. 12.17. 12.18. 12.19. Companies

Households

Government

Fig. 7.5 Structure of loans 2008–2019 (Source CNB)

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This data clearly shows there was a significant change in the bank’s risk preference over the last 10 years and a crowding-out effect. During the COVID crisis, we can see a similar picture. Loans to households are flat, loans to corporations are decreasing and the loans to the government are increasing. Since the time period is very short, it would be interesting to see how the future changes in the quantity of loans will develop (Fig. 7.6). The credit data during the COVID crisis points to the continuation of the existing credit policy by the banks: lending to the government with no support for the private sector. It is hard to expect any significant economic growth without a change in the credit policy. There is another important point to be made here: low-interest rates have a negative effect on the structure of loans in the Croatian economy. Banks are not willing to take on credit risk and lend to the private sector. This is naturally decreasing investments and job creation. The future objective of the monetary policy should be the focus on changing the credit policy of the banks and skewing the new credit towards the private sector. Loans in 2020 140,000.0 130,000.0 120,000.0 110,000.0 100,000.0 90,000.0 80,000.0 01.20. 02.20. 03.20. 04.20. 05.20. 06.20. 07.20. 08.20. 09.20. 10.20. Companies

Households

Fig. 7.6 Structure of loans 2020 (Source CNB)

Government

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7.6

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The Evolution Process

As we saw from our analysis, the monetary policy in 2020 was vastly different from the monetary policy in 2009. For starters, the central bank has expanded its transactions and has started to purchase a new class of assets. It has started to purchase government bonds and has abandoned the FX transactions as the only way to change the quantity of money in the economy. The introduction of a new transaction created the opportunity to perform monetary sterilization. As we saw from the data in 2020, CNB has performed the FX operations in equal amount as it has purchased government bonds, thus leaving the quantity of domestic currency in the economy unchanged. Through the transactions of sterilization, CNB was able to maintain at the same time the economy’s liquidity in domestic currency and exchange rate stability. Another prof of this comes from the data. The fact that foreign currency claims the regulation was not changed during the COVID crisis. This represents a major revolution in the approach of CNB to monetary policy. This paradigm shift in effect represents the abandonment of exchange rate stability as the only goal of monetary policy. CNB for decades has been focused only on the exchange rate stability with only no other goal and with little regard for the real economy and the effects of the conduct of the monetary policy on the rad economy. The new transactions in practice show that CNB has added economic stability to exchange rate stability as the main focus of the central bank. The natural evolution of this approach is to create new transactions to focus on economic growth and job creation. Also for the first time, CNB officials have publicly started to separate domestic currency liquidity and foreign currency liquidity as presented in Vujˇci´c (2020). The focus of monetary policy has changed. CNB has implicitly acknowledged the monetary policy framework which was proposed in Vidakovi´c (2020)6 and has adjusted its monetary policy accordingly. The economic disaster was caused by monetary policy in 2009. In 2020 it has been averted. The change in monetary policy does represent a significant evolution from the previous three decades. CNB has become aware of the effects of monetary policy on the real economy, it also realized that exchange rate stability is pointless if the price of exchange rate stability is an economic disaster.

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At the same time, such evolution vindicates the criticisms of such economists like Radoševi´c (2009b) who have for decades advocated a change in monetary policy and further improvement of how monetary policy is conducted in Croatia. With the crisis of 2020, CNB has shown that the change and evolution of monetary policy are possible.

7.7

Monetary Policy Recommendations

Before we move into policy recommendation it is important to reflect on the paradigm shift which has occurred. CNB has started to introduce new transactions to conduct monetary policy, it has changed its rhetoric. Such policy should have been introduced much earlier. With the entrance into the EMR II mechanism and fast track to adopt Euro by 2023, the effects of the paradigm shift will have little long-term economic effects. The introduction of the process of sterilization has created a new powerful tool for the Croatian central bank. After decades of being dependent on only one policy transaction, the central bank now has a new tool. However, sterilization is a process that should be used sparingly because it changes the currency and the asset structure of the central bank’s balance sheet. If the CNB makes all of its transactions FX-Bond sterilization eventually it will run out of FX reserves. A whole new transaction methodology is needed. The new methodology should be focused on price stability and economic growth. This would entail a whole new monetary policy strategy as performed by Fed in its monetary policy review as described by Chairman Powell (2020), however, such policy strategies are impossible in ERM II and with the adoption of the Euro. The question also remains is CNB willing to undergo such a large and comprehensive monetary policy review. In terms of the policy recommendations for the post COVID world are as follows: • The main problem is the fact money does not flow from the banks to the real economy. Any measures implemented have to be created to change this. A comprehensive framework to change the credit policy of banks is needed. • Croatia is a member of the ERM II process and the process of adoption of the Euro has to continue. However, the timing of joining the Eurozone should be dependent on the overall stability of the Eurozone and Croatia. The key measure to increase the stability of the

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whole economy is to decrease the public debt in relative terms. Both sides have to adjust their imbalances. Croatia has reentered the European semester procedure and during this period those imbalances have to be adjusted. The problem with the first proposed measure is how to implement that goal without reducing the economy’s capacity for recovery. CNB should develop and communicate the development of new policy tools which should include the purchases of corporate bonds, direct lending to banks for specialized programs with the main objective of job openings. Further development of purchases of government bonds and coordination of the increase in the yield curve maturity. Croatia should have bonds with a maturity of 30 years and CNB should participate in the development and control of the yield curve structure and form. Not in terms of the interest rates at a particular point on the yield curve, but terms of the overall term structure of public debt in order to better control the future need for fiscal financing. Development of funding lines for the banks to provide medium- and long-term kuna funding (a T-LTRO like funding) with the focus on more balanced regulation. Current reserve requirement regulation penalizes HRK, while entices banks to lend in foreign currency and foreign currency clause. The policy paradox is to decrease the dependence on the Euro (euroization of the economy) while preparing the economy to join Euro. Creation of regulatory policies to decrease the crowding-out effect in banks’ balance sheet which has happened over the last decade where lending to corporations was replaced with lending to the government. Increase the independence of domestic banks that are in foreign ownership, particularly banks which are part of Italian banking groups. One such policy was the cessation of dividend payments as done by ECB. This regulation should also be extended to safeguard the liquidity of domestic banks from possible owner pillaging. Better communication with the general public by introducing forward guidance and regular press conferences from the governor of the CNB. This should also be followed up with more frequent parliamentary hearings and reports. Creating a comprehensive contingency plan for the possible breakup of the Eurozone and exit from the ERM II mechanism.

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The last policy recommendation might seem farfetched, but in reality, with the Brexit occurring, there is a possibility (but currently with a low probability) of a country leaving the EU and Eurozone. However, even a small possibility should not be dismissed offhand. The optimal future policy mix is the monetary policy with a focus on banks’ credit policy while maintaining/decreasing the public debt with improvement in the interest rate policy transmission to improve lending to the real economy.

7.8

Conclusion

What we have seen in this paper is that Croatian monetary policy has evolved over time albeit the evolution came late. During the great recession (the first crisis), CNB’s main focus was on the exchange rate stability, regardless of what adverse effects such monetary policy has had on the real economy. However, during the COVID crisis (the second crisis), the central bank has realized the error of its ways and has changed its narrative. Monetary policy has realized that there are two liquidities in the Croatian economy: the domestic currency and foreign currency liquidity. This understanding has changed the conduct of monetary policy. The central bank started to use sterilization methods in order to both maintain the exchange rate stability and the liquidity of the domestic economy. This evolution also opens possibilities for further changes in the monetary policy where the central bank will introduce new policy objectives like inflation rate targeting. Purchases of new instruments for the conduct of monetary policy and focus more on interest rates. The COVID crisis has shown that the central banks can adjust fast and react to changes in the economy. There is a need for one more major adjustment that is that for the central banks to focus on banks’ credit policy and create policy tools to improve the loan structure of the banks. Data shows the fiscal policy and government have become a major borrower from the banks’ crowding-out companies. This has to reverse.

Notes 1. September 2019 vs. September 2020 comparison. 2. ECB press conference on July 26 2012.

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3. https://www.tportal.hr/biznis/clanak/treba-mi-netko-objasniti-sto-znacida-hnb-bude-slicnija-ecb-u-20151208. 4. Monetary aggregates dana is in million HRK and annual averages. 5. The time of writing of this paper is December 2020. 6. Multiple copies of the book were delivered to the CNB and to key members (most significantly with the vice governor Vedran Šoši´c) of the monetary policy decision makers the main conclusions of the book were presented. Considering the fact the main conclusions of the book were implemented it is clear the book has had impact on the policy makers.

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Soros, George. 1998. The Crisis of Global Capitalism: Open Society Endangered. Public Affairs 228 pages. Vidakovi´c, Neven 2014. Exchange Rate Regimes: Choices and Consequences. LAP LAMBERT Academic Publishing, Vidakovi´c, Neven. 2016. Monetary and Credit Analysis. Zagreb: Effectus. Vidakovi´c, Neven, and Dušan Zbašnik 2014. New CNB Measures to Stimulate Credit Growth: Problems and Solutions. Banˇcni Vestnik 63 (3): 13–17. Vidakovi´c, Neven 2020. Quantity of money in Croatia—a transactional approach, working paper unpublished https://www.nevenvidakovic. com/pdf/Quantity%20of%20money%20in%20Croatia.pdf. Vujˇci´c, Boris 2020. Go on, Choose a Number, You Will Surely Fail! Macroeconomic Projections in Times of Pandemic. Presentation at the conference Challenge of change organized by Zagreb Stock Exchange and Association of Pension Funds and Pension Insurance, Rovinj, Croatia, October 21–23 2020. https://www.hnb.hr/documents/20182/2953147/hn22102020_p rezentacija.pdf/04f4a2bf-f47b-91d6-8de4-4f546c069f6b?t=1603435482864.

CHAPTER 8

Monetary Transmission in Croatia: A View from the Eurozone’s “Waiting Room” Manuel Benazi´c and Dean Uˇckar

8.1

Introduction

The analysis of aggregate demand components is specific because of the channels through which money supply affects economic activity. These channels are commonly called monetary policy transmission mechanisms (Mishkin 2010). The analysis is usually performed through equations and a structural model that describes the way the economy operates. The monetary transmission mechanism operates through the channels through which monetary policy affects aggregate demand. It is characterized by long, variable and uncertain time lags making it difficult to predict the effect of monetary policy actions and measures on the price level and economy as a whole (European Central Bank 2021a).

M. Benazi´c (B) · D. Uˇckar Faculty of Economics and Tourism “Dr. Mijo Mirkovi´c”, Juraj Dobrila University of Pula, Pula, Croatia e-mail: [email protected] D. Uˇckar e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_8

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According to Mishkin (2010), monetary transmission channels could be divided into traditional interest rate channels, other asset price channels and credit view. Traditional interest rate channel implies the effects of changes in the short-term nominal interest rate induced by a central bank on real short-term and long-term interest rates and the impact of changes in interest rates on investment decisions. Other asset price channels include the effects of exchange rate on net exports, Tobin’s q theory that explains how monetary policy can affect the economy through its effects on the valuation of equities (stock) and wealth effects which implies how consumers’ balance sheets might affect their spending decisions. Finally, credit view proposes two types of transmission channels as a consequence of financial frictions in credit markets such as those that operate through effects on bank lending, and those that operate through effects on firms’ and households’ balance sheets. Croatian National Bank (previously National Bank of Croatia) was established in 1991 after the collapse of SFRY (Socialist Federal Republic of Yugoslavia). At the same time, the Croatian Dinar was introduced as the legal and temporary currency of the Republic of Croatia. Since then, Croatian National Bank (CNB) independently determines and implements monetary policy, primary money issuance policy, controls operations of commercial banks, etc. (Perišin et al. 2001). The Croatian Kuna as a legal and permanent currency was introduced in 1994 after the so-called “Stabilization Programme” (or anti-inflationary programme) using the exchange rate as an anchor by which the inflation was reduced to acceptable levels (Lang and Krznar 2004). Namely, high degree of eurization/dollarization (at that time Deutche Mark) was the reason why the central bank has chosen the stability of the domestic exchange rate as a variable through which it indirectly influences the achievement of its basic goal, which is to maintain price stability. Croatia adopted a managed float exchange rate regime that leaves monetary policy some space for action in the highly seasonal Croatian economy. With the accession process to the European Union (EU), the CNB started with conducting open market operations. Their task is to establish a reference money market interest rate with the aim of stabilizing the variability in interest rates and to create the preconditions for the functioning of the interest rate channel as a dominant monetary transmission channel of the European Central Bank (ECB) and the European Economic and Monetary Union (EMU) (Vizek 2007). Croatia became a member state of the EU in 2013 and today Croatia is preparing for the adoption of the euro as a national

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currency and is currently waiting in the so-called Eurozone’s “waiting room”. During this time, Croatia is obliged to meet certain criteria. It is about the criteria of nominal convergence and they refer to price stability, exchange rate stability, long-term interest rates, the amount of public debt and the amount of fiscal deficit. For all these reasons, before the accession of some EU member states to the EMU, the analysis of the monetary transmission mechanism is performed in order to examine the compliance and readiness of the country for the common monetary policy. It is necessary to emphasize that the primary objective of the ECB’s monetary policy is to maintain price stability (European Central Bank 2021b). In order to maintain price stability for the euro area, the ECB implements monetary policy by steering short-term interest rates and influencing economic developments. The operational framework consists of open market operations, standing facilities, minimum reserve requirements for credit institutions and since 2009 it also includes non-standard monetary policy measures such as asset purchase programmes. The transmission mechanism of monetary policy functions in a way that the ECB provides funds to the banking system and charges interest. Because of its monopoly power over the issuing of money, the ECB can fully determine this interest rate. In that way, the ECB affects banks and money market interest rates, expectations, asset prices, saving and investment decisions, the supply of credit leads to changes in aggregate demand and prices and affects the supply of bank loans. In making decisions, the ECB relies on “two-pillar” approach through which it analyses economic and monetary developments. The paper is divided into two parts. The first part empirically analyses the functioning of the monetary transmission mechanism in Croatia by estimating the vector autoregressive (VAR) model while the second part discusses actual problems of transmission bearing in mind that Croatia as a European Union member state is preparing for the adoption of the euro as a national currency.

8.2

Literature Review

There is a vast literature dealing with the analysis of monetary transmission mechanism around the world whereby VAR and vector errorcorrection models (VECM) are often used to test the dynamic and causal relationships between the relevant macroeconomic and monetary variables. The use of VAR models for the analysis of monetary policy

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transmission mechanisms initially started by Sims (1980) followed by Leeper et al. (1998), Christiano et al. (1998), Peersman and Smets (2001), etc. In this section, the focus will be on papers that analyse the monetary transmission mechanism in Croatia. As we shall see, Croatian authors also commonly use these methods. Erjavec and Cota (2003) analysed the causal relationships between money, output, interest rate, prices and exchange rate in Croatia by estimating vector error-correction model (VECM) and Granger causality tests using monthly data in the period from 1994 to 2001. The results of cointegration tests indicate the existence of a long-run relationship between the variables. Obtained short-run causal relationships between the variables indicate that money supply is neutral and cannot stimulate economic growth. The VECM results indicate that interest rate and exchange rate are weakly exogenous in the short run further confirmed by the results of the forecast error variance decompositions and impulse response functions. Lang and Krznar (2004) analysed the transmission mechanism of monetary policy in Croatia by estimating VAR models using monthly data on interpolated real GDP, prices, the ratio of current account to GDP, exchange rate, excess liquidity and indicator of monetary policy stance. Obtained results lead to the conclusion that monetary policy variables have no significant impact on real activity whereby depreciation decreases real GDP and liquidity and has no effect on prices and current account. Regarding the monetary policy stance, they found that tightening has a negative effect on aggregate growth, positively affects prices and improves the current account. In addition, they also found the evidence of bank lending channel of monetary policy that operates through the ownership structure. Žigman and Lovrinˇcevi´c (2005) analysed monetary policy of inflation targeting with emphasis on the analysis of the transmission mechanism of monetary policy in the context of Croatia’s accession process to the European Union (EU). With regard to that, they give recommendations related to objectives, institutional preconditions, principles and valorization of inflation targeting policies by analysing monetary policies of inflation targeting in transition countries and EU member states. Regarding the transmission mechanisms of monetary policy in Croatia, they conclude that this field is insufficiently researched whereby Croatian economy faces a number of constrains such as underdeveloped financial market, high level of euroization and conducting direct monetary

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policy operations indicating the possibility that transmission mechanism primarily operates through the exchange rate channel and the bank loan channel. Lovrinovi´c and Benazi´c (2006) analysed the functioning of the monetary transmission mechanism in Croatia using quarterly data of real GDP, prices, money supply M1, money market interest rate and real effective exchange rate by estimating VAR model in the period from 1994 to 2005. Besides endogenous variables, the model also contains exogenous variables from the euro area such as real GDP and prices. The monetary transmission mechanism is analysed through two stages. The analysis of the first stage implies the transmission from the money market interest rate to commercial bank credit and deposit interest rates whereby the analysis of the second stage implies the link between conditions in the financial market and decisions on consumptions and investments by households and firms and their direct influence on the aggregate demand. The results suggest that both stages of transmission should be more efficient. Vizek (2007) examined the characteristics and functioning of monetary transmission in Croatia using the cointegration approach of time series in the period from 1995 to 2006 and monthly data on industrial production, money supply M1, overnight money market interest rate and average HRK/EUR exchange rate. The provided results suggest that monetary policy in Croatia had a significant influence on the real activity through the direct monetary transmission and exchange rate channel, whereby the interest rate channel is found to be inactive. In addition, the results of cointegration analysis indicate that exchange rate policy could have a weak effect on the cyclic movement of the economy showing that depreciation causes a decrease in the industrial production, while appreciation causes expansion. Dumiˇci´c et al. (2010) analysed monetary transmission in Croatia in the period from 1998 to 2009 using a cointegration approach. Within the analysis, they investigated the direct channel, interest rate channel and exchange rate channel of monetary policy transmission by using monthly data on industrial production, money supply, interest rate, exchange rate and euro area industrial production. The long-run results suggest that all variables are significant in explaining domestic income in the long run. Money supply and eurozone income positively affect domestic income whereby the impact of the exchange rate is negative. Variance decomposition results show that domestic income explains the largest part of

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its variation, followed by money supply, euro area income, exchange rate and interest rate. Finally, obtained results from impulse response functions show that the effects of shocks in variables on domestic income are rather twofold. Benazi´c and Uˇckar (2011) analysed and found evidence of the asset prices channel of monetary transmission in Croatia implementing the VAR framework. Using monthly data on industrial production, consumer prices, real estate prices, share prices and money supply, they estimated two VAR models. The first model includes real estate prices while the second model includes share prices. Variance decomposition analysis of the first model suggests relatively high importance of money supply in explaining the variation of other variables whereby the results of the impulse response functions analysis indicate that expansionary monetary policy increases demand and raises real estate prices. On the other side, variance decomposition analysis of the second model suggests greater significance of share prices and less significance of money supply in explaining the variation of other variables. As with the first model, obtained impulse responses from the second model indicate that expansionary monetary policy increases demand and raises share prices. Doležal (2011) investigated the efficiency of monetary policy transmission in Croatia through the effects of exchange rate, money stock and interest rate on real economic activity and prices in Croatia in the period from 1998 to 2010 using the vector error-correction model (VECM) and cointegration approach. Obtained results suggest the existence of a longrun relationship between monetary policy variables and real economic activity and price levels. The long-run analysis showed that the strongest channel of monetary transmission in Croatia is the exchange rate channel, while the channel of money stock is rather weaker. Furthermore, the results show the weak existence of the interest rate channel through the real overnight money market interest rate. Real exchange rate depreciation and the growth of money supply in the long run lead to a decline in real economic activity whereby an interest rate increase positively affects the growth of real economic activity. In the short run, none of the channels has a strong impact on real economic activity. Pali´c (2018) tested the coherence of monetary policy shock in calibrated dynamic stochastic general equilibrium (DSGE) model that includes financial frictions with the empirical impact of monetary policy shock in Croatia. Firstly, the DSGE model is calibrated and after that, a VAR model is estimated. By using quarterly data on overnight money

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market interest rate, inflation, house prices and GDP gap in the period from 2008 to 2017, the results showed that in both models, monetary policy shock has positive initial impact on interest rate and negative initial impact on house prices and output gap.

8.3

A VAR Analysis of Monetary Transmission in Croatia

The primary goal of this paper is to analyse monetary transmission in Croatia in the last two decades and to detect its possible inefficiency on the eve of entering the EMU. For these purposes, the VAR model is estimated.1 The VAR model includes quarterly data on real gross domestic product (RGDP ), consumer price index (CPI ), money M1 (M1), average lending interest rate on long-term household loans with a currency clause (INT )2 and real effective exchange rate (REER). In order to eliminate the influence of seasonal factors, all series are seasonally adjusted.3 In addition, all variables except the interest rate are expressed as indices in logarithmic form. Data covers the period from March 2000 to March 2020 and Fig. 8.1 shows their movement. It is visible that real GDP, prices and money achieve upward trends while the interest rate achieves downward trend during the observed period. On the other side, the exchange rate appreciates in the first decade and depreciates in the second decade. As well, all series have visible break during 2008. The main reason for that is the spillover effect of global crisis on the Croatian economy. The VAR methodology consists of Granger causality tests, variance decomposition and impulse response functions. Before defining the VAR model, it is necessary to examine the properties of time series. Since models with nonstationary series can lead to wrong conclusions (Österholm 2003) it is necessary to determine the degree of integration of time series. To do so, Augmented Dickey-Fuller ADF test (Dickey and Fuller 1979), Phillips and Perron PP test (Phillips and Perron 1988) and KPSS test (Kwiatkowski et al. 1992) are performed. Results of the unit root tests are shown in Table 8.1. Obtained results suggest that all the series are integrated of order I(1), i.e. that they are stationary in first differences. In addition, to be sure that the VAR model in levels is suitable for the analysis, the cointegration between the variables is tested using the methodology proposed by

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Fig. 8.1 Real gross domestic product, prices, money, interest rate and real effective exchange rate (Source The Croatian National Bank [2020a] and authors’ calculations)

Johansen (1991, 1995). Results of cointegration tests indicate that the long-run relationship between the variables exists.4 Based on the assumption of cointegration, the following unrestricted VAR model with variables in levels is estimated (Lütkepohl 2007): yt = A1 yt−1 + . . . + A p yt− p + C xt + εt

(8.1)

where y t is a vector of endogenous variables, x t is a vector of exogenous variables, A 1 , …, A p are matrices of lag coefficients, C is a matrix of exogenous variable coefficients and Et is a white noise innovation process.

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Table 8.1 Unit root tests Variable and test

Level Constant

ADF test LRGDP LCPI LM1 INT LREER PP test LRGDP LCPI LM1 INT LREER KPSS test LRGDP LCPI LM1 INT LREER

Prob. 0.0835 0.4739 0.9504 0.8018 0.2442 Prob. 0.2446 0.0737 0.4844 0.8046 0.3901 LM-stat. 0.746085 1.202188 1.155286 0.926132 0.263484

First difference Constant and trend

Constant

Constant and trend

0.5884 0.9767 0.8686 0.7912 0.7821

0.0015 0.0015 0.0002 0.0001 0.0000

0.0000 0.0039 0.0020 0.0000 0.0000

0.6808 0.9605 0.2708 0.7730 0.7570

0.0000 0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000

0.196311 0.285218 0.153615 0.141109 0.264678

0.292583 0.578688 0.285221 0.138410 0.433966

0.173249 0.073757 0.246179 0.138330 0.098193

Notes “L” indicates logarithm of the variable. For the implementation of ADF and PP test, the Schwarz information criterion has been implemented. KPSS test asymptotic critical values: constant: 1% level (0.739), 5% level (0.463), 10% level (0.347); constant and trend: 1% level (0.216), 5% level (0.146), 10% level (0.119) Source Research results

The vector of endogenous variables includes real GDP, prices, money, interest rate and the exchange rate while the vector of exogenous variables includes constant, trend and several dummy variables. The number of lags in the model is determined using standard information criteria (LR, FPE, AIC, SC and HQ 5 ). The criteria indicate that the optimal number of lags in the model is two. The model diagnostic tests presented in Table 8.2 include test for autocorrelation, normality and heteroscedasticity. Obtained results suggest that the model is adequately estimated with acceptable characteristics. In order to examine the causality between variables Granger causality/block exogeneity Wald tests are applied. Test results are shown in Table 8.3.

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Table 8.2 VAR diagnostic tests Autocorrelation LM

Normality (Joint)

Heteroskedasticity (Joint)

At lag 4: LRE stat. = 21.55431, df = 25, Prob. = 0.6613, Rao F-stat. = 0.858158, df = (25, 194.7), Prob. = 0.6627 Up to lag 4: LRE stat. = 88.82674, df = 100, Prob. = 0.7805, Rao F-stat. = 0.854187, df = (100, 185.2), Prob. = 0.8083 Skewness: Chi-sq = 1.809360, df = 5, Prob. = 0.8748 Kurtosis: Chi-sq = 3.698834, df = 5, Prob. = 0.5935 Jarque-Bera: J-B = 5.508193, df = 10, Prob. = 0.8548 Levels and Squares: Chi-sq = 421.4728, df = 420, Prob. = 0.4706 Cross Terms: Chi-sq = 1132.762, df = 1125, Prob. = 0.4296

Source Research results

Table 8.3 VAR Granger causality/block exogeneity tests Excluded

Chi-sq

Dependent variable: LRGDP LCPI 0.615206 LM1 8.936628 INT 4.739977 LREER 0.645892 All 34.01320 Dependent variable: LM1 LRGDP 0.477072 LCPI 13.09794 INT 5.241453 LREER 3.533296 All 28.55078 Dependent variable: LREER LRGDP 11.41942 LCPI 1.048266 LM1 4.353795 INT 0.736909 All 42.98507

df

Prob.

2 2 2 2 8

0.7352 0.0115 0.0935 0.7240 0.0000

2 2 2 2 8

0.7878 0.0014 0.0728 0.1709 0.0004

2 2 2 2 8

0.0033 0.5921 0.1134 0.6918 0.0000

Note “L” indicates logarithm of the variable Source Research results

Excluded

Chi-sq

Dependent variable: LCPI LRGDP 14.05207 LM1 1.129364 INT 12.46531 LREER 16.19148 All 57.84263 Dependent variable: INT LRGDP 0.313363 LCPI 1.103280 LM1 1.464626 LREER 0.490268 All 10.99099

df

Prob.

2 2 2 2 8

0.0009 0.5685 0.0020 0.0003 0.0000

2 2 2 2 8

0.8550 0.5760 0.4808 0.7826 0.2022

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The results indicate that real GDP causes prices and the exchange rate while prices cause money. On the other side, money causes real GDP while interest rate causes almost all variables except the exchange rate. Finally, the exchange rate causes only prices. The dynamic interdependence among variables in the model is analysed through the variance decomposition presented in Table 8.4. Variance decomposition results indicate that prices and interest rate had the greatest impact on the variability of real GDP while real GDP and interest rate had the greatest impact on the variability of prices. Real GDP and prices had the greatest impact on the variability of money whereby real GDP and prices had the greatest impact on the variability of the interest rate. In the end, real GDP and interest rate had the greatest impact on the variability of the exchange rate. It is noticeable that real GDP and interest rate had the biggest impact in explaining the variability of other variables. In order to analyse influence of variables order change, variance decomposition is performed with reverse order of variables in the model. The results are relatively similar.6 In order to trace each endogenous variable’s response overtime to shock in that variable and other endogenous variables, the impulse response functions are analysed. Figure 8.2 shows the impulse responses of the real GDP, prices, money and the exchange rate. An increase in real GDP increases prices and interest rate, decreases money and causes exchange rate appreciation. An increase in prices decreases real GDP and money, increases interest rate, initially causes exchange rate appreciation and after that depreciation. An increase in money increases real GDP, decreases interest rate, has no effect on prices and causes exchange rate appreciation. Finally, exchange rate depreciation decreases real GDP and money, increases prices and has no effect on interest rate. The results obtained by Granger causality tests, variance decomposition and the impulse response functions are very similar. From the results of Granger causality tests, it is interesting to observe that the interest rate causes other variables and that other variables do not cause the interest rate. Hence, the interest rate can be considered as an exogenous variable that significantly affects the Croatian economy, but not vice versa. Very similar conclusions regarding the exogeneity of the interest rate can be derived from the variance decomposition results and impulse response functions. The results obtained from variance decomposition clearly show that the interest rate had the greatest impact in explaining its own variability compared to other variables while at the same time significantly affected the variability of other variables. This is further confirmed by the impulse response functions, as it is obvious that

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Table 8.4 VAR variance decomposition (in %) Horizon (quarters) Variance decomposition 4 8 12 16 20 24 Variance decomposition 4 8 12 16 20 24 Variance decomposition 4 8 12 16 20 24 Variance decomposition 4 8 12 16 20 24 Variance decomposition 4 8 12 16 20 24

LRGDP of LRGDP 85 65 49 38 32 29 of LCPI 4 15 27 38 44 46 of LM1 0 1 3 6 12 20 of INT 0 0 1 4 8 13 of LREER 3 27 41 44 41 37

Note “L” indicates logarithm of the variable Source Research results

LCPI

LM1

INT

LREER

0 3 7 12 17 21

7 5 4 4 3 3

7 26 38 44 45 44

1 2 2 2 3 3

78 67 57 45 34 27

0 0 0 0 0 0

4 2 2 6 13 20

14 15 13 11 9 7

2 9 18 25 29 28

94 70 52 42 35 29

2 8 12 12 10 9

2 12 15 15 15 13

2 5 9 12 13 13

7 7 6 6 6 5

90 87 83 78 72 68

0 0 0 1 1 1

11 11 8 6 6 8

6 5 3 3 3 2

10 8 14 23 32 37

70 49 34 24 19 16

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Fig. 8.2 VAR impulse responses to Cholesky one S.D. (d.f. adjusted) innovations ± 2 S.E. confidence interval (Note “L” indicates logarithm of the variable. Source Research results)

an increase in the interest rate significantly affects other variables while simultaneously an increase in other variables has generally no effect on the interest rate. From a monetary policy standpoint, the possibility of influencing the commercial bank interest rate would be interesting. However, it is necessary to keep in mind that the simultaneous management of interest rate and the exchange rate is rather impossible. As so, the CNB has chosen the stability of the exchange rate as a variable through which it indirectly influences the achievement of its primary objective, i.e. the price stability. The reasons for this can be found in the fact that Croatia is a small and open economy, highly euroized, import dependent with high external debt. As stated by the Croatian National Bank (2008), the main constraint that reduces possibilities for independent setting of domestic interest rates and money supply stems from the relative freedom of international capital flows and the need to maintain the exchange rate stability in highly euroized Croatian economy. In that sense, an increase in interest rates under direct CNB control would be offset by capital inflows caused by higher interest rates.

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8.4 A View on the Monetary Transmission in Croatia from the Eurozone’s “Waiting Room” In the previous chapter, monetary transmission in Croatia is analysed through the econometric model using the data for the past two decades. In this chapter, more recent and detailed data will be employed to detect possible problems in monetary transmission present in the last few years while Croatia as a European Union member state is preparing for the adoption of the euro as a national currency. Figure 8.3 shows the movement of the velocity of M1 and M4 money stock7 together with the M1 money stock/GDP ratio. The velocity of money stock represents the number of times one Kuna is used to purchase final goods and services included in GDP. This is the number that shows the velocity of converting money stock into GDP. On the other side, the M1 money stock/GDP ratio shows the amount of money stock in relation to GDP. All indicators represent measures of liquidity of some economy (Perišin and Šokman 1992).

Fig. 8.3 Velocity of M1 money stock (V1), velocity of M4 money stock (V4) and the M1 money stock/GDP ratio (in %) (Source The Croatian National Bank [2020a, b] and authors’ calculations)

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It is clearly visible that the velocities V1 and V4 are falling in the observed period. In the last few years, the velocity V1 is falling more rapidly than the velocity V4 indicating that money stock M1 grows faster than M4. The M1 money stock/GDP ratio is rapidly growing in the last few years indicating that M1 money stock is growing significantly faster than GDP meaning that there is enough liquidity on the economy level. However, all these movements lead to the conclusion that the monetary transmission mechanism may not be functioning properly as it is obvious that the money supply is not converting adequately into the GDP. To detect possible problems, it is necessary to perform additional analysis. Figure 8.4 shows bank liquidity surpluses (including overnight deposits with the CNB)8 and the interbank overnight interest rate. It is noticeable that liquidity surplus and overnight interest rate have opposite movements, i.e. when liquidity surplus is growing overnight interest rate is falling. From 2012 liquidity surplus grows rapidly pushing the overnight interest rate towards zero. This means that the banking sector has sufficient excess liquidity that does not end in the real sector but is rather retained on bank accounts. This excess liquidity actually stems from raising demand deposits held by households and corporations on bank’s transactional accounts. These demand deposits are part

Fig. 8.4 Liquidity surplus (in billion EUR) and overnight interest rate (in %) (Source The Croatian National Bank [2020c])

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of money M1. As they grow, so does the money supply. Therefore, this explains Fig. 8.3 and indicates that the problems could be linked to the supply and demand for loans. Again, to detect the difficulties in transmission it is necessary to perform additional analysis. Figure 8.5 shows the distribution of other monetary financial institutions’9 deposits and granted loans by original maturity. Figure 8.5 clearly indicates the problem of mismatched maturity of other monetary financial institutions present in the last five years. It is evident that stable sources of funds (time deposits) are rapidly decreasing while less stable sources (demand and savings deposits) are rapidly increasing. On the other side, it is noticeable that granting of long-term loans (loans over 5 years) is increasing while granting of shorter-term loans (loans up to 1 year and loans over 1 and up to 5 years) is decreasing. For healthy and sustainable operating, banks must avoid problems regarding mismatched maturity in a way that long-term loans are granted from long-term sources of funds and shorter-term loans from shorter-term sources of funds. Just stated is part of maturity structure and liquidity risk management. The existence of a mismatched maturity problem is visible in the slower growth path of long-term lending. In addition, long-term loans are larger in size in relation to shorter-term loans making the problem even bigger when monetary transmission and GDP growth are considered. Namely, less lending leads to lower GDP growth. The problem of mismatched maturity primarily occurs due to low interest rates in the past years caused by the expansive monetary policies of central banks around the world in order to boost economic recovery

Fig. 8.5 Distribution of other monetary financial institutions’ deposits (left) and loans by original maturity (right) (in million EUR) (Source The Croatian National Bank [2020a])

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after the 2007 crisis. Low interest rates demotivate household and corporate savings in a way that excess liquidity is rather retained on transactional accounts. Although not presented here, data on deposits and loans indicate that space for granting loans exists since total deposits exceed the value of total loans. The problem could be a lack of long-term liquidity. In order to analyse the demand for loans, the following figure shows the movements of the confidence indicators. According to Croatian National Bank (2021a), consumer confidence indicators are based on monthly survey results examining the perception of the changes as regards everyday economic issues (Fig. 8.6). All confidence indicators obtain similar strong rising trend in the period from 2009 to 2020. There is a sharp fall in all indicators during 2021 caused by the coronavirus COVID-19 pandemic. With the exception of the coronavirus crisis, it is remarkable that confidence in the Croatian economy is continuously rising. Increase in confidence is usually associated with increasing demand for loans and spending. This is further confirmed by the results of the Bank lending survey. According to Croatian National Bank (2021b), the survey is intended for bankers, conducted four times a year (at the end of each quarter) and aims

Fig. 8.6 Confidence indicators (standardized values, seasonally adjusted index) (Source The Croatian National Bank [2020b])

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to provide an insight into the developments in bank lending standards and conditions (loan supply) and the changes in loan demand in Croatia. Thus, the following figures present changes in demand of enterprises and households for loans and/or credit lines over the past three months and expected changes over the next three months (Fig. 8.7). It is visible that changes in demand of enterprises for short-term and long-term loans and/or credit lines were generally positive during the observed period indicating increases in demand. In addition, changes in demand between presented loans and/or credit lines are quite similar. A sharp fall during the last quarters is caused by the coronavirus COVID-19 pandemic (Fig. 8.8). 80

60 100

40

80

60

20

40

0 20

-20 0

-40

-20

-40

-60 Q3 2012 Q1 2013 Q3 2013 Q1 2014 Q3 2014 Q1 2015 Q3 2015 Q1 2016 Q3 2016 Q1 2017 Q3 2017 Q1 2018 Q3 2018 Q1 2019 Q3 2019 Q1 2020 Q3 2020

Short-term loans

Q3 2012 Q1 2013 Q3 2013 Q1 2014 Q3 2014 Q1 2015 Q3 2015 Q1 2016 Q3 2016 Q1 2017 Q3 2017 Q1 2018 Q3 2018 Q1 2019 Q3 2019 Q1 2020 Q3 2020

Long-term loans

Short-term loans

Long-term loans

Fig. 8.7 Change in demand of enterprises for loans and/or credit lines over the past three months (left) and expected changes over the next three months (right) (Note In net percentage, positive value = increased demand, negative value = decreased demand. Source The Croatian National Bank [2021b]) 150

100

100

50

50

0

0

-50

-50

-100

-100

-150 Q3 2012 Q1 2013 Q3 2013 Q1 2014 Q3 2014 Q1 2015 Q3 2015 Q1 2016 Q3 2016 Q1 2017 Q3 2017 Q1 2018 Q3 2018 Q1 2019 Q3 2019 Q1 2020 Q3 2020

Loans for house purchase

Consumer credit and other lending

-150 Q3 2012 Q1 2013 Q3 2013 Q1 2014 Q3 2014 Q1 2015 Q3 2015 Q1 2016 Q3 2016 Q1 2017 Q3 2017 Q1 2018 Q3 2018 Q1 2019 Q3 2019 Q1 2020 Q3 2020

Loans for house purchase

Consumer credit and other lending

Fig. 8.8 Change in demand for loans to households over the past three months (left) and expected changes over the next three months (right) (Note In net percentage, positive value = increased demand, negative value = decreased demand. Source The Croatian National Bank [2021b])

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It is noticeable that changes in demand of households for loans for house purchase and consumer credit and other loans and/or credit lines were generally positive during the observed period indicating increases in demand. As well, changes in demand between presented loans and/or credit lines are quite similar. As before, a sharp fall during the last quarters is caused by the coronavirus COVID-19 pandemic. A possible solution to solve the problem of mismatched maturity can be found in CNB monetary policy instruments such as structural operations that are already being implemented. However, the usage of these operations is limited as they increase the amount of money in circulation thus making pressure on exchange rate depreciation. Another possible solution is to increase commercial bank’s passive interest rates although the question is whether there are possibilities for that since the interest rate margin is continuously falling. Issuance of debt securities by banks, e.g. bonds as non-deposit long-term sources can increase this type of funds. Although not free, these sources of funds could increase long-term lending and overcome the problem of mismatched maturity. Developed derivative market and its instruments in Croatia could be a further solution for mismatched maturity. Unfortunately, this market is still undeveloped and as such does not provide too many possibilities. Ultimately, it should be emphasized that other countries around the world are also facing similar problems.

8.5

Conclusion

The aim of this paper was to analyse the functioning of the monetary transmission mechanism in Croatia during the last two decades while taking into account the fact that Croatia as a European Union member state is preparing for the adoption of the euro as a national currency. The VAR methodology typically consists of Granger causality tests, variance decomposition and the impulse response functions analysis. Results from the VAR model indicate the strong significance of the commercial bank interest rate in terms of its impact on other variables in the model, i.e. the real gross domestic product, prices, money supply and the real effective domestic exchange rate. The results also indicate that the commercial bank interest rate is an exogenous variable not affected by other domestic variables. These findings are in accordance with the CNB monetary policy framework, which in the foreground places the exchange rate stability as a nominal anchor, rather than the impact on interest rates. From a

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monetary policy standpoint, the possibility of influencing the commercial bank interest rate would be quite interesting. The results obtained from Granger causality tests, variance decomposition and the impulse response functions are very similar. Regarding actual monetary transmission problems, with the exception of the coronavirus crisis, the analysis finds that despite high liquidity of the banking sector and the growth of optimism and confidence, the velocity of money is continuously decreasing indicating that excess liquidity does not end in the real sector but is rather retained on bank accounts. These problems generate the mismatched maturity that banks are facing in recent years caused by low interest rates that do not encourage savings making a lack of long-term liquidity required to meet the demand for long-term loans. Possible solutions can be found in monetary policy instruments, passive commercial bank interest rates, debt securities, derivative markets, etc. Acknowledgements This paper is a result of the scientific research project “Impact of Monetary and Fiscal Policy on Financial Markets and Institutions” supported by the Faculty of Economics and Tourism “Dr. Mijo Mirkovi´c”, Juraj Dobrila University of Pula. Any opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the Faculty of Economics and Tourism “Dr. Mijo Mirkovi´c” Pula.

Notes 1. The Eviews 12 (IHS Global Inc. 2020) econometric software is used for the multiple time series analysis. 2. The analysis of monetary transmission mechanisms of developed countries usually involve central bank official interest rates. In developed markets, commercial bank interest rates are generally affiliated with official interest rates. For example, in the European Union or in the United States, the money market interest rates corresponds to the central bank decisions, which are brought depending on the economic and financial conditions on domestic and global markets. In Croatia, the money market is undeveloped thus limiting the CNB’s role in determining the official interest rate (Benazi´c 2012). Due to this limitation, the analysis is performed by using the commercial bank interest rate for which it is assumed that has a greatest impact in the Croatian economy. Since the CNB does not announce overall average lending interest rate of Croatian banks, the decision fell on the

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average lending interest rate on long-term household loans with a currency clause. Namely, the majority of granted loans in Croatia are long-term household loans with a currency clause. Using the ARIMA X-12 method. The results are not shown in order to preserve space. LR: sequential modified LR test statistic, FPE: Final prediction error, AIC: Akaike information criterion, SC: Schwarz information criterion and HQ : Hannan-Quinn information criterion. The results are not shown in order to preserve space. Velocity of money (in this case income velocity of money) is calculated as a ratio of nominal GDP to the money supply M1 and M4. According to Croatian National Bank (2020b) liquidity surplus is the difference between the balance in bank settlement accounts with the CNB and the amount that banks are required to hold in their accounts after the calculation of reserve requirements. Other monetary financial institutions include credit institutions (banks, savings banks, housing savings banks and foreign bank branches) and money market funds.

References Benazi´c, Manuel. 2012. The Cost of Funds and Pricing Loans of Croatian Banks: Evidence from a Vector Error Correction Model. Paper presented at the 31st International Conference on Organizational Science Development, Quality. Innovation. Future, March 21–23, Portorož, Slovenia. Benazi´c, Manuel, and Dean Uˇckar. 2011. Asset Prices Channel of Monetary Transmission in the Republic of Croatia. In Toward Global Governance, ed. Lovre Božina, Marli Gonan Božac, and Sandra Krtali´c, 1–18. Pula: Juraj Dobrila University of Pula. Christiano, Lawrence J., Martin Eichenbaum, and Charles L. Evans. 1998. Monetary Policy Shocks: What Have We Learned and to What End? NBER Working Paper 6400: 1–77. https://www.nber.org/system/files/working_p apers/w6400/w6400.pdf. Accessed 5 Feb 2021. Croatian National Bank. 2008. Financial Stability. Croatian National Bank 1: 1– 48. https://www.hnb.hr/en/-/financijska-stabilnost-1. Accessed 6 Jan 2021. Croatian National Bank. 2020a. Statistical Data. https://www.hnb.hr/en/statis tics/statistical-data. Accessed 8 Nov 2020. Croatian National Bank. 2020b. Bulletin. Croatian National Bank 263: 1–124. https://www.hnb.hr/en/analyses-and-publications/regular-publicati ons/bulletin. Accessed 6 Jan 2021.

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Croatian National Bank. 2020c. Standard Presentation Format. https://www. hnb.hr/en/analyses-and-publications/regular-publications/spf. Accessed 15 Nov 2020. Croatian National Bank. 2021a. Confidence Indices. https://www.hnb.hr/ en/statistics/statistical-data/selected-non-financial-statistics/confidenceindices/-/asset_publisher/3IZEthXO6zFd/content/indeksi_pouzdanja. Accessed 21 Jan 2021. Croatian National Bank. 2021b. Bank Lending Survey. https://www.hnb.hr/ en/statistics/statistical-surveys/bank-lending-survey. Accessed 21 Jan 2021. Dickey, David A., and Wayne A. Fuller. 1979. Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association 74 (366): 427–431. https://www.jstor.org/stable/ pdf/2286348.pdf?refreqid=excelsior%3Afa0127a09d14b549c62e9a4c6911 244f. Accessed 5 Feb 2021. Doležal, Velimir. 2011. Efikasnost mehanizma monetarnog prijenosa u Hrvatskoj. Privredna kretanja i ekonomska politika 128: 27–54. https:// hrcak.srce.hr/index.php?show=clanak&id_clanak_jezik=110023. Accessed 24 Nov 2020. ˇ Dumiˇci´c, Ksenija, Irena Cibari´ c, and Nikolina Horvat. 2010. The Analysis of Monetary Transmission in Croatia Using Cointegration Approach. Croatian Operational Research Review 1: 210–220. https://hrcak.srce.hr/index.php? show=clanak&id_clanak_jezik=139835. Accessed 21 Jan 2021. Erjavec, Nataša, and Boris Cota. 2003. Macroeconomic Granger-Causal Dynamics in Croatia: Evidence Based on a Vector Error-Correction Modelling Analysis. Ekonomski Pregled 54: 139–156. https://hrcak.srce.hr/25291. Accessed 21 Jan 2021. European Central Bank. 2021a. Transmission Mechanism of Monetary Policy. https://www.ecb.europa.eu/mopo/intro/transmission/html/index. en.html. Accessed 21 Jan 2021. European Central Bank. 2021b. Objective of Monetary Policy. https://www. ecb.europa.eu/mopo/intro/objective/html/index.en.html. Accessed 21 Jan 2021. IHS Global Inc. 2020. EViews 12 User’s Guide. Irvine, CA, USA: IHS Global Inc. Johansen, Søren. 1991. Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica 59 (6): 1551–1580. https://www.jstor.org/stable/pdf/2938278.pdf. Accessed 5 Feb 2021. Johansen, Søren. 1995. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Econometric Theory 14 (4): 517–524 (1998). https://www.jstor.org/stable/pdf/3533216.pdf?refreqid=excelsior%3Ad52a 0a7c6a91ce628197b8b02a40b8da. Accessed 5 Feb 2021.

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Kwiatkowski, Denis, Peter Phillips, Peter Schmidt, and Yongcheol Shin. 1992. Testing the Null Hypothesis Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root? Journal of Econometrics 54 (1–3): 159–178. https://debis.deu.edu.tr/use rweb/onder.hanedar/dosyalar/kpss.pdf. Accessed 5 Feb 2021. Lang, Maroje, and Ivo Krznar. 2004. Transmission Mechanism of Monetary Policy in Croatia. Paper presented at the Tenth Dubrovnik Economic Conference, Croatian National Bank, June 23–26, Dubrovnik, Croatia. https://www.hnb.hr/documents/20182/120763/lang-krznar.pdf/ c8fca7fb-be89-4daf-8ca3-91f528605b11. Accessed 11 Nov 2020. Leeper, Eric M., A. Christopher Sims, and T. Tao Zha. 1998. What Does Monetary Policy Do? Brookings Papers on Economic Activity 2: 1–78. https://www.brookings.edu/wp-content/uploads/2016/07/1996b_ bpea_leeper_sims_zha_hall_bernanke.pdf. Accessed 5 Feb 2021. Lovrinovi´c, Ivan, and Manuel Benazi´c. 2006. The Monetary Transmission Mechanism in the Republic of Croatia. Paper presented at the 11th International Conference on Operational Research (KOI 2006), September 27–29, Pula, Croatia. Lütkepohl, Helmut. 2007. New Introduction to Multiple Time Series Analysis. USA: Springer-Verlag. Mishkin, Frederic S. 2010. Ekonomija novca, bankarstva i financijskih tržišta. Zagreb: Mate d.o.o. Österholm, Pär. 2003. The Taylor Rule: A Spurious Regression? Uppsala University Working Paper Series 20: 1–28. http://uu.diva-portal.org/smash/get/ diva2:129274/FULLTEXT01.pdf. Accessed 5 Feb 2021. Pali´c, Irena. 2018. The Empirical Evaluation of Monetary Policy Shock in Dynamic Stochastic General Equilibrium Model with Financial Frictions: Case of Croatia. International Journal of Engineering Business Management 10: 1–11. https://journals.sagepub.com/doi/pdf/10.1177/184797901875 8740. Accessed 23 Jan 2021. Peersman, Gert, and Frank Smets. 2001. The Monetary Transmission Mechanism in Euro Area: More Evidence from VAR Analysis. European Central Bank Working Paper 91: 1–36. https://www.ecb.europa.eu//pub/pdf/scp wps/ecbwp091.pdf. Accessed 21 Jan 2021. Perišin, Ivo, and Antun Šokman. 1992. Monetarno-kreditna politika. Zagreb: Informator. Perišin, Ivo, Antun Šokman, and Ivan Lovrinovi´c. 2001. Monetarna politika. Pula: Faculty of Economics and Tourism “Dr. Mijo Mirkovi´c”. Phillips, Peter C.B., and Pierre Perron. 1988. Testing for a Unit Root in Time Series Regression. Biometrika 75 (2): 335–346. https://www.jstor.org/sta ble/pdf/2336182.pdf?refreqid=excelsior%3Aba0c06cf5f0b5791234d1ddbb 35a7f8f. Accessed 5 Feb 2021.

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Sims, Christopher A. 1980. Macroecomics and Reality. Econometrica 49: 1– 48. https://www.jstor.org/stable/pdf/1912017.pdf?refreqid=excelsior%3A8 cb820295e2a5576726a137c97a1f913. Accessed 5 Feb 2021. Vizek, Maruška. 2007. Econometric Analysis of Monetary Transmission Channels in Croatia. Croatian Economic Survey 10: 11–44. https://hrcak.srce.hr/ 21927. Accessed 26 Jan 2021. Žigman, Ante, and Željko Lovrinˇcevi´c. 2005. Monetarna politika ciljane inflacije i transmisijski mehanizam – iskustva za Hrvatsku. Ekonomski pregled 56 (7–8): 433–457. https://hrcak.srce.hr/index.php?show=clanak&id_clanak_ jezik=15814. Accessed 24 Nov 2020.

CHAPTER 9

Monetary and Fiscal Policy Response During COVID-19 Crisis in Bosnia and Herzegovina: Constraints and Potentials Sead Kreso, Lejla Lazovi´c-Pita, and Selena Durakovi´c

9.1

Introduction

Bosnia and Herzegovina (BiH) implements rigid monetary regime, called currency board, which disables central bank to react during the crisis, but it helps keeping the stability of prices and trust in the local currency. Consequently, it contributes to overall macroeconomic stability in the country. In this paper we argue that in small open economies monetary policies should be focused on maintenance of stable exchange rate,

S. Kreso · L. Lazovi´c-Pita · S. Durakovi´c (B) School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina e-mail: [email protected] S. Kreso e-mail: [email protected] L. Lazovi´c-Pita e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_9

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low prices and, potentially, financial stability, if central bank’s mandate and available tools allow it, in order not to jeopardize monetary stability. Experiences of Western Balkan (WB) countries1 show that regardless of the chosen monetary regime small and open economies should focus on exchange rate stability in order to maintain monetary stability and contribute overall macroeconomic stability (Besimi 2004; Miškin 2006). The great and increasing importance of trade (and specifically with European Union countries) and intention of WB countries to join the European (Monetary) Union (E(M)U) imposes a quest for exchange rate stability against the euro as one of the bases for the price stability, which is the primary goal of most central banks in the region. Consequently, there is a very little space for discretion in monetary policy and to react to crisis by using monetary policy instruments in these countries. Hence, the spotlight of macroeconomic policies in small open economies (with or without economic crises) ought to be on fiscal policy. In this paper we examine the implementation of monetary and fiscal policy in BiH during the two economic crises, Global financial crisis of 2008 (GFC) and the current COVID-19 crisis. So, the purpose of this paper is to analyse and answer three questions: • To what extent do the established mechanisms of monetary and fiscal policy have the capacity to adequately respond to the situation created by the economic crisis? • Are the established mechanisms of monetary and fiscal policy appropriate intervention mechanisms within the existing legal-institutional framework in BiH? • If the two mechanisms are insufficient, what alternatives could be used to reach desired results? The paper is organized as follows: after a brief introduction, we analyse and compare the implementation of monetary policy in BiH and WB countries during the crises. We elaborate the reasons why fixed exchange rate regime and less active monetary policy is a good option for small open economies. We further go into a detailed examination of the effectiveness of BiH Central bank’s only instrument, reserve requirements, and investigate the financial potentials within the banking system which could have been used, as well as the necessary upgrade of the financial infrastructure (establishment of new financial institutions), to stimulate the economic

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activity. Since monetary policy cannot adequately react to crisis by using monetary policy instruments extensively without jeopardizing monetary stability, in the next section, we examine the possibilities offered by a fiscal policy in BiH. After providing a brief overview of the implementation of fiscal policy in BiH and WB countries, we focus on the operationalization of the fiscal policy in BiH. We determine several limitations to an effective implementation of fiscal policy in BiH, primarily found in complex constitutional and institutional organization of the country which in turn results in large and inefficient public spending. We also present simple and effective means of introduction of fiscal discipline measures that could result in freeing significant public resources. Freed public funds could then be used to speed up infrastructural and capital projects in the country and could bring necessary economic growth. In the final section, we provide an overview of current interventions in fiscal policy during COVID-19 crisis and in the conclusions and recommendations section, we suggest several measures for a more effective implementation of both policies in BiH.

9.2 Monetary Policy in Small Open Economies with Reflection on Western Balkan Countries Currently all WB countries have some type of fixed (or tightly managed) exchange rate regime which means that their central banks are very limited in implementation of their monetary policies, as they all have free capital movement. Besides, small open economies such as WB countries, cannot have more benefits from active monetary policy compared to stability which is gained due to passive monetary policy (and maintenance of controlled exchange rate), especially if the political situation in the country is not stable and if there is a potential for political pressures to monetize debt and possible misuse of monetary reserves for promotional political purposes. Moreover, all of these countries are on their way to join E(M)U which means that monetary and exchange rate stability are beneficial as it can easily be integrated in European monetary system. The rationale behind this statement is explained further in this section.

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9.2.1

Inability to Conduct (the Appropriate) Discretionary Monetary Policy in Small Open Economy

In the recent literature there has been a debate whether the impossible trinity (Mundell-Fleming trilemma)2 became a dilemma as the global financial cycle (i.e. widespread co-movement in capital and credit flows across countries) imposes constraints on monetary policy regardless of the chosen exchange rate regime. Rey (2013) argues that monetary autonomy is possible only if the capital account is managed, therefore suggesting reduction of trilemma to dilemma. However, as argued by Klein and Shamboug (2013), Obstfeld (2015) and Anaya and Hachula (2016) the trilemma should not be disregarded, as independent monetary policy in open economies with floating exchange rates is possible and effective, but has limited effects in longer term as open economies are also affected by so-called global financial cycle. We further explain the case of small open WB economies and the rationale for adopting more fixed exchange rate regimes and more rigid monetary regimes in these countries. All WB countries are very much connected with the EU through high level of trade with the EU countries (for all of the WB partners, the EU is the leading trade partner accounting for almost 70% of the region’s total trade3 ), high financial integration with EU (the share of banking sector assets in the WB owned by EU-headquartered banks was 57% in June 2018, Comunale et al. 2019) and all countries are in the process of EU (EMU) integration, at different stages: Croatia is already in the EU and since 2020 in ERMII; Albania, Serbia, Montenegro and North Macedonia have a status of EU candidates; Bosnia and Herzegovina and Kosovo have potential candidates’ status. Considering the above, it is reasonable for these countries to try to stabilize their local currencies against the euro (EUR). Consequently, countries are losing the discretion when conducting their monetary policies. Therefore, there is very little space for monetary policy to stimulate economic growth or to react when crisis hits. Additionally, maintenance of stable exchange rate against the currency of its main trading partner and the region (union) to which they aim to integrate might be a good option for a small open economy as it brings credibility to the central bank, increases trust in their own currency (Begovi´c et al. 2016) and decreases inflation (Wolf et al. 2008; Begovi´c et al. 2019). Link between exchange rate (regime) and inflation is important here as almost all of the central banks in WB have price stability

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as their primary goal and exchange rate stability have been proven to provide the price stability (Ghosh et al. 1996). Experiences of Serbia showed that fluctuation of the exchange rate is likely to cause shocks in price developments (Bungin 2016), while countries which maintained relatively stable exchange rate did not experience such shocks (Croatia, ´ c et al. (2015) argue that price stability Bosnia and Herzegovina). Cori´ in Croatia is achieved through the exchange rate stability and Begovi´c et al. (2019) argue that currency board arrangement (which is implemented in BiH) has decreased inflation. Furthermore, Begovi´c and Kreso (2017), through empirical analysis, showed that in small open economies depreciation of domestic currency tends to negatively affect trade balance (increases its deficit) which is contrary to the expected effect. This could be explained by high import dependence and low export capacity of these countries. Consequently, policymakers should think twice before using exchange rate policy to improve trade balance (Perišin 2006). These economies are also usually politically unstable, and they lack trust in public institutions, so more discretion in monetary policy might result in distrust in local currency and eventually (hyper)inflation, if public starts to doubt the independence of central bank from political pressures or if distrust in government translates to central bank as well. According to the Eurobarometer (European Commission 2019) and Euro Survey conducted by Austrian National Bank (2019) WB countries have among the lowest level of trust in their governments. All of this imply that small open economics, such as WB countries, should opt for some kind of fixed exchange rate and restricted monetary policy in order to achieve price and monetary stability. However, this is a very expensive way of implementing monetary policy. Great amount of foreign reserves from the central banks in these countries are invested abroad, while these economies struggle with many problems: slow development, high unemployment, emigration of youth, political controversies and non-transparency. Consequently, “rebellions” to engage these reserves more efficiently are frequent, even among experts. On the other hand, these “rebels” do not consider the importance of these reserves for maintaining trust in the local currency, financial system stability and low inflation rate, which, if lost, would cause enormous costs for the economies (loss of motivation to save money, uncertainty of credit arrangements in the country, as well as with foreigners), etc.

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Central banks of some WB countries had more discretion, but over time, due to above mentioned reasons (and also questionable effectiveness of available and used instruments) moved towards lower discretion and more fixed exchange rate regime. However, there are still differences in the level of strictness between region’s central banks, as some have more discretion and available instruments (such as National Bank of Serbia, Bank of Albania4 ) while others have one or no instruments available (Kosovo, Montenegro, Bosnia and Herzegovina, North Macedonia and Croatia5 ). However, central banks of all countries in WB conducted expansionary monetary policies during the GFC and crisis caused by pandemic COVID-19 simultaneously taking care of the exchange rate stability. 9.2.2

Reaction of Western Balkan Central Banks to Crises

Central banks of WB countries had limited possibilities to react to crisis since they are all trying to keep their currencies (relatively) fixed against the euro and since instruments which they can use were usually ineffective, when it comes to their effect on the real sector, due to high level of euroization and high exposure and dependence on foreign markets (European Commission 2009). However, although limited in their policies, all regional central banks were conducting expansionary monetary policy and tried to increase bank liquidity by using available instruments during GFC. All central banks that can use open market operations decreased their central bank interest rates6 (Fig. 9.1). Most countries decreased reserve requirement rate, although this instrument had been proven ineffective, since commercial banks have been increasing their excess reserves during the crisis, due to increased uncertainty, lack of secure investment and increased capital requirements (as a result of new banking standards imposed by Bazel III), so the banks have been holding approximately the same level of average reserves, regardless of the decrease in the reserve requirement rate (this will be investigated in more details for BiH). National bank of Serbia and Croatian National Bank intervened on international exchange market to “defend” their depreciating local currencies due to high deposit withdrawal. The responses of all WB central banks to GFC have been limited by rigidity of their monetary regimes and by trying to keep the exchange rate stable. Besides the traditional instruments these central banks also introduced macroprudential policy tools, which are aimed at assessment

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of systemic risk and test of financial system resilience to macroeconomic shocks and some central banks implemented measures that contributed to the increase of financial stability and decrease of risks.7 All countries from the region are oriented towards EU macroprudential policies, but the stage and the pace for the implementation of the required framework differs between the countries (Barisitz and Hildebrandt 2020). When the “new” crisis caused by the pandemic COVID-19 hit in March 2020 local currencies of Western Balkan countries again started depreciating (with Albanian lek depreciating the most), signalling capital outflow and worsening conditions in international trade and investment. This has a direct negative effect on loan/debt repayment which are denominated in foreign currency, which is problematic, as loans denominated in foreign currency consist 58% of total loans (excluding Kosovo and Montenegro). Serbia, which has more than 70% loans denominated in foreign currency is especially fragile to its national currency depreciation. National Banks of Serbia and North Macedonia intervened on the exchange market in order to decrease short-term volatility (OECD 2020a). Barisitz and Hildebrandt (2020) note that this crisis initiated relaxation of some macroprudential measures and regulatory standards,

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which may (temporarily) undermine the economic substance of capital buffers. We do not go into more details on the specific activities of each central bank or the potentials in the financial systems of each country to react to crisis, but we further focus on BiH and the potentials within its financial system.

9.3 Monetary Policy in BiH and (In)ability of Central Bank of BiH to React in Crisis Central bank of Bosnia and Herzegovina (CBBiH) implements very rigid monetary regime, currency board, which requires 100% backing of its monetary base with foreign reserves and fixed exchange rate (against the euro). Moreover, CBBiH cannot finance government or commercial banks and cannot act as a lender of last resort. The only monetary policy instrument available to CBBiH is reserve requirement. CBBiH decreased the minimum required reserve rate from 18 to 14% in October 2008, as a reaction to GFC. Besides, new credit lines withdrawn from abroad by commercial banks are exempted from the base on which the reserves are imposed. In January 2009 CBBiH introduced decreased reserve requirement rate on time deposits with maturity of more than one year was decreased first to 10%, and later to 7%, while it stayed 14% on deposits with short-term maturity until 2011 when it was lowered to 10%. In 2016 the rate was equalized for all deposits at 10%. However, this instrument has been shown not to be an effective tool in stimulating banks’ credit activity and consequently economic growth. Lowering the reserve requirement rate did not significantly8 lower the average reserves that commercial banks hold on CBBiH account (see Fig. 9.2), neither it increased banks’ loans (see Fig. 9.3). High level of excess reserves is likely the consequence of inexistence of lender of last resort under the currency board and rigid regulations on deposits-loans maturity matching, as well as the increased capital requirements and lack of safe investments. As it can be seen from Fig. 9.3 there has been a decline in growth rates of claims on households. Especially problematic was the decrease in longterm loans and increase of short-term loans which were used for covering long-term obligations. We can see downward trend in 2020, as a result of COVID-19, and again it is likely that the banking system will behave as in the previous crisis.

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Fig. 9.2 Reserve requirement and average reserves held by commercial banks in CBBiH (Source CBBiH [2021], own interpretation)

During the crisis caused by pandemic COVID-19 CBBiH did not use its only instrument, so far (as the paper is written in the midst of the crisis). Moratorium on loans’ and interest rates’ repayment is introduced by the banks but this is more palliative measure which does not ease the burden of debt repayment but even increases future repayment burden after moratorium. 9.3.1

Potentials in the BiH’s Banking System

Even though CBBiH has had high foreign exchange reserves9 these cannot be used to stimulate the economy due to strict rules imposed on CBBiH by the currency board. Monetary base has been covered with foreign reserves around 110% since the introduction of currency board. The coverage of the broadest monetary aggregate (M2) with foreign reserves has been around 55% (there were no significant changes in these ratios since the introduction of the regime). These reserves are needed to defend the fixed exchange rate, as well as to maintain trust in the local currency. However, besides these reserves in the CBBiH (which are

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Fig. 9.3 Growth rates in loans to enterprises and households (selected items from the consolidated balance sheet of commercial banks in BiH) (Source CBBiH [2021], own interpretation)

invested outside the country) a lot of funds from the commercial banks are held outside the country as well and could represent a potential within the financial system in the country. If we observe foreign assets and excess reserves of commercial banks, we can see that there has been an increase in these funds since 1997 (with decreases during the crises) (Fig. 9.4). In 2019 these funds together were approximately 3.6 billion EUR and present a potential which could have been used to stimulate economic activity. Additionally, there has been an increase in cash in vaults, which represents another unused potential. In 2019 there was approximately 435 million EUR in banks’ vaults (Fig. 9.5). However, these available potentials cannot be used due to un(der)developed financial market and lack of clear strategy for their development. In order to engage these resources into more effective use the state should initiate strategies for development of financial institutional infrastructure which could result in the possibilities to use this money, which is currently (mostly) invested abroad, for the domestic

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Fig. 9.4 Commercial banks’ foreign assets and excess reserves (Source CBBiH [2021], own interpretation) 600

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Fig. 9.5 Cash in commercial banks’ vaults (Source CBBiH [2021], own interpretation)

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loans and development. Kreso (2019) suggests to overcome this through creation of a financial institution, in public and private partnership, which could attract part of available short-term financial assets and made them available for businesses’ (short- and long-term) needs. The motivation for depositors could come from the state through liberation or decrease of taxes for those who invest their funds on longer period. In order to increase investors’ trust Kreso (2019) suggests the creation of guarantee fund for the potential coverage in the case that a segment of securities issued by this newly created financial institution (partially) losses collateral based on portfolio of approved loans and significant losses/bankruptcies of debtors that face any liquidity problems (Fig. 9.6).10

9.4 Fiscal Policy in a Small Open Economy---Literature Review and Comparison of BiH and Western Balkan Countries In the past twenty-five years, most (if not all) of the strategic decisions in fiscal policy being implemented in BiH and other WB countries are under direct supervision or suggestions and recommendations from international financial institutions such as the World Bank, the International Monetary Fund (IMF) and most recently, the European Commission. On one side, these especially relate to (necessary) tax policy reforms and other reforms in taxation, whereas, on the other side, efficient and rational usage of collected tax revenues through public expenditures is usually missing or is insufficient. Unfortunately, this is the case in BiH, too. The size of public expenditures to GDP in most of the WB countries (including Croatia) with or without economic crises is very high, and during the years of economic crises, prudent public spending is mostly missing. In Table 9.1, the size of public expenditures and public debt to GDP over 2006–2019 period is presented. From Table 9.1 we can determine that BiH, Croatia, Montenegro and Serbia have had, on average, relatively high share of public expenditure to GDP and therefore a lower capacity to use fiscal policy for effective intervention in case of external shocks such as economic crises. Except for BiH and North Macedonia, most of the WB countries also face high levels of public debt to GDP which additionally puts pressure on efficient use of public revenues.

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M2 m2

„Export“ of short-term funds

Foreign financial market

MB

M1

m1

Financial markets mediaƟon/maturity matching of financial assets

245

„Import“ of long-term funds

New insƟtuƟonal financial infrastructure created by government intervenƟons on financial markets (mechanism for financing small and medium enterprises)

Fig. 9.6 Suggestion for the use of existing potentials in financial system (Source Kreso 2019)

The literature that deals with fiscal policy in the WB solely is very scarce. The results from the Web of Knowledge database with two keywords (topic search): fiscal policy and Western Balkans provide only five results where only three are relevant. Causevic (2012) discusses what type of fiscal policy would be adequate for the WB countries during the crisis of 2008–2009 and concludes that all countries require fiscal discipline. However, fiscal discipline is related to limitation of the public expenditures on public administration and does not mean restrictive fiscal policy. He concludes that public resources ought to be used for

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Table 9.1 Public expenditures and public debt to GDP, in WB countries (including Croatia), in percentage Country

Albania Bosnia and Herzegovina Croatia Kosovo Montenegro North Macedonia Serbia

Public expenditures to Public debt to GDP, GDP, average 2006–2019 average 2006–2019

Gross domestic product per capita, average 2006–2019 (current prices, Purchasing power parity; international dollars)

29.8 45.3

63.7 33.0

10,777.3 11,187.4

47.5 26.5 46.4 32.0 42.5

64.4 n/a n/a 34.5 54.8

22,737.9 8846.4 15,852.2 12,849.2 14,499.4

Source IMFWEO (2020), own interpretation

enhancing cross-border cooperation especially cross-border investment projects. Krajišnik et al. (2019) examine the effects of fiscal consolidation in WB countries. By using a dynamic panel analysis with a pooled mean group estimator for years 2004–2016 and six WB countries, the authors conclude that fiscal consolidation has a positive impact on economic growth but highlight the need for implementing responsible public finances as a precondition for such positive process to occur (Krajišnik et al. 2019). The final paper from Jusufi and Gashi-Sadiku (2020) analyses the impact of fiscal policies in WB SMEs’ growth in the example of Kosovo. They conclude that fiscal support to SMEs through fiscal incentives due to the devastating effects of the COVID-19 pandemic should be greater in the coming years. Results from Scopus database research with the same keywords also generate five results, two from Web of Knowledge database and three new. Malush (2014) briefly analyses the design and management of fiscal policy in Kosovo and how it could bring economic growth. The results from Golemi and Muço (2020) indicate positive impact of tax revenues on economic growth in the analysed eight WB countries over 2005–2018 period. Shehaj (2020) provides analysis of the possible effects of the EU financial role and possible post-pandemic democratic prospects in Western Balkan countries in the long term. The

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search within the two databases and hence available literature does not solely deal with the analysis of fiscal policy in BiH economy. We hope that this brief analysis will contribute to the scarce literature that deals with fiscal policy in BiH.

9.5

Fiscal Policy in BiH

In this section we attempt to briefly analyse the trends in most important areas of fiscal policy in BiH over the period of 2006–2019. After a brief analysis of the trends and structure of public revenues in BiH (2006–2019), our focus is on the structure of public expenditures classified under functional classification (2014–201911 ). In this section, we also provide a brief analysis of introduction of stricter public spending rules that ought to contribute towards responsible use of public finances. Based upon experiences and practice of GFC of 2008, we suggest that BiH under COVID-19 crisis should introduce a strategy of fiscal discipline which should limit the growth of two highest public expenditure categories: general public services and social protection. We conclude our analysis with the overview of the government activities and measures to curb the economic effects of COVID-19 crisis in 2020 (latest available data) and lessons that ought to be learned from previous GFC crisis and implemented now and in the following years. 9.5.1

Constitutional and Institutional Organization of BiH

In order to evaluate whether the established mechanisms of fiscal policy are the appropriate intervention mechanisms within the existing legalinstitutional framework in BiH, we begin our analysis with the presentation of the constitutional organization of BiH. As a small open economy located in South-Eastern Europe at the Balkan Peninsula, BiH is organized as an asymmetric (con)federation. According to the latest available data, BiH has a population of 3.5 million inhabitants (BHAS 2019). The Dayton Peace Agreement (Annex 4, Article I (9)) which is BiH’s Constitution states that BiH consists of two entities: Federation of BiH (FBiH) and Republika Srpska (RS).12 FBiH is fiscally decentralized with two sub-central levels of government—cantons and local communities (municipalities and cities) and RS has only one sub-central level of government—local communities (municipalities and cities). Figure 9.7 shows the organization of BiH under the current constitution.

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From Fig. 9.7 we can see a complex organization of BiH where each level of government, apart from its budgetary responsibilities, it also has constitutional rights. Implementation of fiscal policy under such circumstances is constitutionally and therefore institutionally very complex and faces several deficiencies in its implementation. Unlike monetary policy, which is specifically defined under BiH Constitution (Article III), only segments of fiscal policy were included in the BiH Constitution, namely customs policy. Hence, currently, BiH tax policy is divided between institutions at the level of BiH and entity institutions. Figure 9.8 shows fiscal structure of BiH since 2006 (with the introduction of the value-added tax (VAT)) until today. From Fig. 9.8 we can determine that all indirect taxes are legally regulated and collected at the level of BiH. The independent tax authority called Indirect tax authority (ITA) is the responsible institution for administering all indirect taxes in BiH that is VAT, customs, excise duties and road duties. Direct taxes (personal and corporate income taxes and

Fig. 9.7 Constitutional organization of BiH (Note N.B. As of 2014, total number of local communities in RS is increased to 63 when Stanari obtained a status of municipality. Source Kreso 2005)

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Indirect taxes

Direct taxes and SSC

249

B&H

RS

FB&H

DB

Fig. 9.8 Fiscal structure of BiH (Source Lazovi´c-Pita 2015, p. 174)

Fig. 9.9 Organization of fiscal institutions in BiH (Source Lazovi´c-Pita and Stambuk 2016, p. 2109)

some property taxes) together with extrabudgetary funds of social security contributions (SSC) are under entity’s regulation and responsibility, i.e., Ministries of finance and corresponding Tax administrations in each entity. Two entity constitutions that must comply with BiH constitution specify, inter alia, authorities and organization in each entity. Primarily due to federal organization of FBiH, in BiH there are fourteen ministries of finance (ten cantonal, one at the level of each entity, DB and Ministry of Finance and Treasury of BiH). Hence, with such an organization in place and inevitably overlapping of authorities, the entire system is administratively too demanding and complicated. This imposes a direct violation of the first precondition for an efficient implementation of fiscal policy— simplified tax system. Figure 9.9 shows the corresponding organization of

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tax administrations in BiH. Theory suggests (for example, Ott 1998) that successful tax administration reform in terms of functional organization should revolve around activities (such as calculation or supervision and control). This is administratively not possible in BiH. Particularly, from the perspective of the taxpayer that operates in both entities, it will face at least three tax audits: one from ITA and the remaining two from the two entity’s tax administrations. In each audit, the taxpayer was not classified uniquely but rather left to each tax administration to define its own methodology and classification of the taxpayer(s) accordingly. 9.5.2

The Implementation of Fiscal Policy in BiH and the Constraints to React in Crisis

50

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0

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total revenues

Tax revenues

SSC

Taxes on income, profit and capital gains

Share of specific tax types to GDP

% of revenues to GDP

Even with a complex constitutional and institutional organization of BiH, there has been an increase in the collection of tax revenues reported by all tax administrations in BiH in the past period (200513 –2019, except in 2009 in comparison to 2008 due to GFC). Figure 9.10 shows the share of total revenues and the share of tax revenues and SSC to GDP as two major sources of revenues in a country. From Fig. 9.10 we can determine that, on average (2006–2019), the share of total revenues to GDP was 43.3% and that the highest share is taken by tax revenues (on average 23%). Tax revenues on average take 53.3% of total revenues over the observed period. In the structure of tax revenues, the dominant position is taken by revenues from taxes on

Taxes on goods and services

Fig. 9.10 Total revenues: taxes and SSC in BiH, 2005–2019 (Source International Monetary Fund GFS-revenues [2020], own interpretation)

MONETARY AND FISCAL POLICY RESPONSE DURING COVID-19 …

% Public expenditures

40.0%

20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0%

35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% 2014

2015

2016

2017

2018

251

% GDP

9

2019

General public services

Social protecƟon

General public services to GDP

Social protecƟon to GDP

Fig. 9.11 Selected categories of expenditures in FBiH, share to total expenditures and GDP (Source Federal Ministry of Finance [2020], own interpretation)

goods and services (indirect taxes). The sharp rise in indirect taxes in Fig. 9.10 from 2005 to 2006 was due to the introduction of the VAT in BiH which replaced retail sales tax. Within the structure of tax revenues, share of revenues from indirect taxes (VAT, excise duties, customs and road duty) to total revenues from 2006 until 2019, was on average 44.8%. Hence, indirect taxes take the highest share of total revenues. The share of revenues from direct taxes to total revenues was on average (2006– 2019) only 6.3%. Low share of taxes on income, profits and capital gains to GDP was also shown in Fig. 9.10 and on average amounted to 3%of GDP (2006–2019). Social security contributions (SSC) as extrabudgetary funds that include pension, health and unemployment funds (and in RS, child protection fund) take on average 14.7% of GDP (2005–2019). Since we have already established high public spending in BiH, measured as the share of public expenditures to GDP, we want to analyse the structure of public expenditures based upon functional classification of government expenditures. We were only able to obtain the data from 2014 until 2019 because prior to 2014 it was not legally binding to collect and classify public expenditures under functional classification. In Figs. 9.11 and 9.12 we present the share of two functional classifications

S. KRESO ET AL.

45.0%

18%

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16%

35.0%

14%

30.0%

12%

25.0%

10%

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8%

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2%

0.0%

% GDP

% Public expenditures

252

0% 2014

2015

2016

2017

2018

2019

General public services

Social protecƟon

General public services to GDP

Social protecƟon to GDP

Fig. 9.12 Selected categories of expenditures in RS, share to total expenditures and GDP (Source Ministry of Finance of RS [2020], own interpretation)

of interest—general public services and social protection to total expenditures and to GDP. The data is presented separately for FBiH and RS since these expenditure assignments are under entities supervision. From both figures (Figs. 9.11 and 9.12) we can determine similar patterns in the movements of the two analysed categories. Social protection is the category in both entities that takes the most public expenditures, on average (2014–2019) 36.2% in FBiH and 35.6% in RS. Due to decentralized structure of administrative organization of FBiH, general public services in FBiH on average (2014–2019) take 21.4% of public expenditures whereas in RS they take on average 13.5%. Similarly, the share of social protection expenditures to GDP in FBiH on average amounted to 16%, while in RS it amounted to 14%. General public services to GDP on average took 9.4% in FBiH whereas in RS they were set on average to 5% to GDP. Since both categories are mostly unproductive expenditures, we wanted to test if introduction of responsible spending with clear limitations in growth of these two categories could bring savings and more responsible public finances. In the past twenty-five years, BiH is witnessing a long-term practice of the political elite in power in BiH (regardless of the political option/party) which aims at creating a voting machine by establishing

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a wide base of dependent individuals from the ruling government. This is mostly done through the direct or indirect allocation of public revenues to political clientelism. This way, a kind of specific long-term “resilience” in irresponsible public spending has been created. We analyse how a rigid structure of public spending in BiH has been created which unfortunately results in inefficient public spending and hence directly affects the reduction of the capacity of fiscal policy to act in terms of development and/or stabilization. Firstly, “implicit grants” or created tax arrears have been (with tacit decisions of certain levels of government) established over the years, so the inconsistencies in tax collection are continuous and are almost becoming an accepted rule. Unequal treatment of the taxpayers in terms of accumulated tax arrears for one group of taxpayers and rigid rules for paying taxes for others acts in the direction of violating the market principles in the functioning of BiH economy and society. The non-payment of taxes is a kind of politically approved “invisible debt” by which many companies, mostly public, are protected from bankruptcy. In essence, this is the way to subsidize non-economic, market-unacceptable employment. From the available data from three tax authorities (ITA and two entities tax administration 2021, ITA 2021; Tax Administration of FBiH (TAFBiH) 2021; Tax Administration of RS (TARS) 2021), the total amount of tax arrears at the end of 2020 amounted to approximately 2.045 billion EUR. This amounts to 26.6% of total consolidated public revenues in BiH (latest available data for 2019). Secondly, over time, BiH has experienced very high increases in the two expenditure categories: war veterans and pensioners. Both categories faced an unjustified increase in the size of beneficiaries (Obrenovi´c 2017) over time and currently there are some 570,000 war veterans from FBiH and 230,000 from RS (Obrenovi´c 2017). In terms of the number of pensioners, there are more than 400,000 pensioners in FBiH with an average pension of as little as 219 EUR and more than 250,000 pensioners in RS with an average pension of 201 EUR (Pension and disability fund of FBiH and RS 2020). In both entities, pensioners with very low pensions are virtually living in poverty and therefore are in the status of social need. As noted previously, pensions in both entities are financed through SSC that are being paid by some 800,000 employed persons in both entities. The employer/pensioner ratio is currently 1.13 and has had an increasing trend over time (Hodži´c and Lazovi´c-Pita 2014). Since pension system in BiH is organized as pay-as-you-go system

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(PAYG), in the future, both pension funds might be fiscally unsustainable. However, both entities (RS in 2011 and FBiH in 2018) have conducted necessary pension system reforms which have, inter alia, introduced the points system for calculation of pensions which directly brings the number of pensions in relation to the amount of paid contributions and the length of insurance. Still, large number of pensioners and therefore pensions that need to be paid out put pressure on pension funds in both entities so reoccurring deficits in pension funds are covered directly from the budget. However, other fiscal issues remain such as that there are more than 400,000 unemployed persons in BiH (MCP BiH 2020) for which health insurance is also funded from SSC. In addition to the described rigid structures that absorb a large amount of public revenues, high administrative expenditures were also previously shown (Figs. 9.11 and 9.12). The rigid structure in public spending leaves little or no space for BiH budgets to invest public revenues into capital and infrastructural projects and/or better provision of other services, for example, in the health or education sector. So, the position and financing of public goods remains uneven and creates additional frictions and tensions between budgetary users. 9.5.3

The Potentials of the Fiscal Policy in BiH

Finally, we consider the way in which long-term inefficient management of both public revenues and expenditures in BiH has contributed towards maintaining the rigid and inefficient fiscal structure in BiH. By using the data provided by the statistics of the (CBBiH), the dynamics and growth rates of the size of compensation of employees in the public administration (sector O, NACE 2 classification) and social benefits were analysed. The purpose of the analysis is to compare the actual growth of the two expenditure categories with the projected growth according to the nominal GDP growth rates (Kreso and Lazovi´c-Pita 2013, with updates in 2017 and 2021). In the developed model, Kreso and Lazovi´cPita (2013) suggest that nominal GDP growth rates should serve as a benchmark for the growth of the two expenditure categories. This method could be introduced as a fiscal discipline and sustainability rule and could in turn limit an inefficient and wasteful use of public revenues. In case nominal GDP growth rates are negative, the two expenditure categories will remain at the same level from the previous year (stabilizing and social aspect). Fiscal scenario that was analysed and presented aimed at

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fiscal sustainability and not austerity and was called Fiscal Discipline and Sustainability Strategy (FDSS, Kreso and Lazovi´c-Pita 2013). The analysis covered the years starting from 2005, the year of the beginning of the effective functioning of ITA until 2018 (latest available data CBBiH 2020). The results show that over the observed period (2005–2018), actual growth of wages and social benefits have surpassed the nominal GDP growth rates by a total of 6.65 billion EUR. Hence, if the FDSS had been implemented from 2005, BiH could have freed and saved more than 6 billion EUR. With that amount of “saved” public revenues, BiH could have built 400 kilometres of highway through the country since the cost of this vital infrastructural project is estimated at 6.4 billion EUR. Additionally, the latest available data indicates that total public debt of BiH amounts to 6.25 billion EUR (Ministry of Finance and Treasury of BiH 2020). These are the key findings that make the fiscal mechanism in BiH rigid and incapable of moving in the direction of stabilization especially in the event of an economic crises. Similarly, with the outbreak of COVID-19 pandemic and complete lockdown of BiH as of March 2020, BiH government tried to tackle the economic issues and inevitable economic downturn through several measures. As per available literature (OECD 2020a, b), three dimensions of aid were provided under fiscal policy: • Support to the firms • Support to the population • International support. As part of support to the firms and to the individuals, both entity governments have implemented several activities (establishment of funds to help entrepreneurs (or certain industries most affected by the crisis, direct assistance to individuals in certain industries in terms of financing SSC, etc.). BiH received international support in medical equipment from several governments and financial support from the EU as a package of EUR 80.5 million to tackle COVID-19 crisis (EUR 7 million of immediate support for the health sector, and EUR 73.5 million for economic and social recovery). In April 2020, IMF approved a EUR 330 million loan under the Rapid Financing Instrument (RFI) and quite possibly another loan of EUR 750 million which is currently under negotiation with the

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IMF. BiH has also applied for the additional loan from the EU in the amount of EUR 250 million. Similar trends in the increases in public debt were noted in 2009 with the outbreak of GFC which clearly indicates BiH’s fiscal policy inability to react in the times of crises.

9.6

Conclusions and Recommendations

In the paper we first argue that for small open economies, such as the Western Balkans’ countries, there is no choice offered by impossible trinity theory. Namely, they have to opt for the option where central bank has (very) limited discretion and exchange rate is fixed if they want to be integrated in international relations and maintain their monetary stability. The reasons behind this argument are that these countries are in progress towards E(M)U integration, that they have a high level of trade (as well as high import dependence and low export capacity) with EU countries, as well as high financial connection with EU countries, high level of euroization, questionable effectiveness of available instruments and lack of trust in public institutions in these countries. We further investigate the effectiveness of Central Bank of Bosnia and Herzegovina’s only instrument, reserve requirement, during the GFC. Our analysis shows that this instrument was not effective since its decrease did not lead to decrease of average reserves of banks or increase in credit growth. Therefore, this instrument has not been used in the crisis caused by pandemic. We further extend our analysis to potentials in the financial system, namely high foreign assets, which are held outside the country, and cash and excess reserves, which could have been used for stimulating economic growth, if there was developed financial infrastructure in the country. After the analysis of monetary policy and its limitations and potentials, we switch our focus to the implementation of fiscal policy in Western Balkan countries and BiH. We establish that most Western Balkan countries have high shares of public expenditures to GDP and that BiH is one of those countries too. After the analysis of the constitutional and institutional set up of the fiscal policy in BiH, we found that fiscal policy is fragmented and implemented in a complex and dissimulating environment. These facts act as major constraints to a more efficient implementation of fiscal policy in BiH. We further investigate the reasons behind high public spending in BiH and find a rigid and inefficient fiscal structure that unfortunately has little or no manoeuvre to be more progrowth orientated. This gloomy picture is worsened by accumulated tax

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arrears coming mostly from public companies together with increasing public debt. An increasing public debt as the only available fiscal instrument has unfortunately been used the most in BiH as a response to any economic crisis, so COVID-19 as well. Our analysis also indicates potentials of BiH fiscal policy which ought to be found in the implementation of fiscal rules that should bring necessary fiscal discipline, infrastructural and capital projects, and possibly, higher rates of economic growth.

Notes 1. Western Balkan countries are Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia and Serbia. Croatia become EU member country in 2013 and since then is usually not included in the international reports on Western Balkan countries. However, we considered it here due to close economic and political relations with other WB countries. 2. Impossible trinity (Mundell-Fleming trilemma) explains limitations in options that country has: namely, country can choose two out of three options when making decisions about the international monetary arrangements and its own policies. These options are fixed exchange rate regime, free capital movement with foreign countries and autonomous (discretionary) monetary policy. Therefore, small open country can choose between fixed exchange rate and restricted monetary policy and more discretion in monetary policy with flexible exchange rate regime, as they have free capital flows. 3. Trade with the region has grown by almost 130% over the past 10 years, with the total trade between the EU and the Western Balkans reaching EUR 55 billion in 2019. This trade expansion has overall been to the benefit of the Western Balkan partners; in the last 10 years, the region increased its exports to the EU by 207% against a more modest increase of EU exports to the region of 94% (European Commission 2020). 4. In these countries, an inflation targeting is currently implemented monetary regime. 5. Albania and Montenegro are euroized countries while Bosnia and Herzegovina implements currency board arrangement (which will be elaborated further in text). North Macedonia is targeting the exchange rate and Croatia entered ERMII in 2020 which sets the requirement for keeping the exchange rate within limits. 6. Croatian National Bank held interest rates on domestic market at high level at the beginning of the GFC through limited supply of domestic liquidity. Although these measures were restrictive Croatian National Bank took other measures to increase liquidity, such as decrease of the reserve

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7.

8.

9. 10.

11.

12. 13.

requirement rate in postcrisis period. Later it decreased interest rate until it reached the interest rate on Eurozone market. Banking systems in WB countries are described as well capitalized and liquid, but level of non-performing loans is relatively high and high unofficial euroization is a potential treat to financial stability for the countries with their own currencies. Moreover, as Comunale et al. (2019) found, the funding of long-term lending via long-term deposits has declined in recent years and maturity mismatches appear most problematic in foreign currencies, where the central bank cannot fully act as a lender of last resort. For more details on banking sectors in WB countries see also World Bank (2016) and International Monetary Fund (2017). There was some decrease but did not last long. Further increases in the average reserves exceeded the average reserves before the decrease in the rate. These reserves were 6870 million EUR in December 2020. Kreso (2019) explains that this fund could be created by financial assets of investors who would also be stimulated by decrease of income or profit taxes or by receiving a part of profit that this newly created financial institution generates. Still, small and medium enterprises should have a collateral for their debt to this institution, as is the case in other credit arrangements. It is important that this procedure should not be bureaucratised and that the institution and the way it functions is attractive to small and medium enterprises as well as for investors. Before 2014, functional classification was not legally binding under the Law on budgets in FBiH and similarly, in RS, functional classification became legally binding from 2013 (Law on budgetary system of RS). District Brˇcko (DB) was by arbitration put under administration of BiH and will not be analysed in detail due to the scope of the paper. In this figure we start the analysis from 2005 due to explanation of the sharp increase in revenues from taxes on goods and services, see later.

References Austrian Central Bank. 2019. Last modified: 2019. https://www.oenb.at/ en/Monetary-Policy/Surveys/OeNB-Euro-Survey/Main-Results/Household s–Trust-and-Expectations.html. Accessed 20 Jan 2021. Anaya, Pablo, and Michael Hachula. 2016. The Dilemma or Trilemma Debate: Empirical Evidence. DIW Roundup – Politk in Focus Nr. 95; Deutsches Institut fuer Wirtschaftsforschung, Berlin. https://www.diw.de/de/diw_ 01.c.532274.de/publikationen/roundup/2016_0095/the_dilemma_or_tril emma_debate__empirical_evidence.html. Accessed 17 Mar 2021.

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Bank for International Settlement. 2021. Central Bank Policy Rate. Last modified: 20 January 2021. https://www.bis.org/statistics/cbpol.htm?m=6% 7C382%7C679. Accessed 23 Jan 2021. Barisitz, Stephan, and Antje Hildebrandt. 2020. Macroprudential policy in the Western Balkans: The Last Five Years and COVID-19 Crisis Response. Focus on European Economic Integration Q4 (20): 80–94. Begovi´c, Selena, Geoff PUGH, and Nick ADNETT. 2019. The Effect of Currency Board Arrangements on Inflation Performance in Transition Countries Before and During the Global Financial Crisis. Finance a úvˇer-Czech Journal of Economics and Finance. Begovi´c, Selena, Nick Adnett, and Geoff Pugh. 2016. An Investigation into the Credibility of Currency Board Arrangements in Bosnia and Herzegovina and Bulgaria. Journal of Comparative Economics 44 (3): 787–799. Begovi´c, Selena, and Sead Kreso. 2017. The adverse effect of real effective exchange rate change on trade balance in European transition countries. Zbornik radova Ekonomskog fakulteta u Rijeci: cˇasopis za ekonomsku teoriju i praksu 35 (2): 277–299. Besimi, Fatmir. 2004. The role of the exchange rate stability in a small and open economy: The case of the republic of Macedonia.National Bank of the Republic of Macedonia. Working Paper No. 10. BHAS (Agency of Statistics of BiH). 2019. Bosnia and Herzegovina in Numbers 2019. http://www.bhas.gov.ba/data/Publikacije/Bilteni/2020/ NUM_00_2019_TB_0_EN.pdf. Accessed 5 Feb 2021. Bungin, Sanja. 2016. Deset godina ciljanja inflacije u Srbiji. Bankarstvo 45 (2): 140–157. Causevic, Fikret. 2012. What Type of Fiscal Policy for the Western Balkans During the Crisis. Southeast European and Black Sea Studies 12 (2): 357–372. CBBiH (Central Bank of Bosnia and Herzegovina). 2020. Bulletin no. 2. 2020. https://www.cbbh.ba/Content/Archive/35. Accessed 12 Jan 2021. CBBiH (Central Bank of Bosnia and Herzegovina). 2021. Last modified: 2021. http://statistics.cbbh.ba/Panorama/novaview/SimpleLogin_en_html. aspx. Accessed 5 Feb 2021. Comunale, Mariarosaria, André Geis, Ioannis Gkrintzalis, Isabella Moder, Éva Katalin Polgár, and Li Savelin. 2019. Financial Stability Assessment for EU Candidate Countries and Potential Candidates. ECB Occasional Paper 233. ´ c, Tomislav, Hrvoje Šimovi´c, and Milan Deskar-Škrbi´c. 2015. Monetary and Cori´ Fiscal Policy Mix in a Small Open Economy: The Case of Croatia. Economic Research-Ekonomska Istraživanja 28 (1): 407–421. European Commission. 2009. The Western Balkans in Transition. European Commission Occasional Papers, No. 46. https://ec.europa.eu/economy_fina nce/publications/pages/publication15155_en.pdf. Accessed 10 Jan 2021.

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European Commission. 2019. Last modified: 2019. https://ec.europa.eu/com mfrontoffice/publicopinion/index.cfm/Chart/getChart/themeKy/18/gro upKy/98. Accessed 20 Jan 2021. European Commission. 2020. Last modified: 2020. https://ec.europa.eu/ trade/policy/countries-and-regions/regions/western-balkans/. Accessed 5 Jan 2021. Federal Ministry of Finance. 2020. Funkcionalna klasifikacija javnih rashoda 2014–2019 [Functional Classification of Public Expenditures 2014–2019]. Ghosh, Atish R., Anne-Marie Gulde, and Jonathan D. Ostry. 1996. Does the Exchange Regime Matter for Inflation and Growth? vol. 2. International Monetary Fund. Golemi, Ela, and Klodian Muço. 2020. Fiscal Policy’s Impact on Economic Growth—An Estimation on Eight Balkan Countries. International Journal of Economic Policy in Emerging Economies 13 (5): 514–525. Hodži´c, Sabina, and Lejla Lazovi´c-Pita. 2014. Evasion of Social Security Contributions: Example of Croatia and Bosnia and Herzegovina. Zagreb, June 20: 25. International Monetary Fund. 2017. Banking Challenges in the Western Balkans: Prospects and Challenges. Last modified: 2017. Accessed 5 Feb 2021. IMFWEO. 2020. International Monetary Fund World Economic Outlook Database. Last modified: January 2021. https://www.imf.org/en/Publicati ons/WEO/weo-database/2020/October. Accessed 15 Dec 2020. ITA (Indirect Tax Authority). 2021. Debtors of Indirect Taxes. Last modified: January 2021. http://www.new.uino.gov.ba/en/Debtors%20of%20indirect% 20taxes. Accessed 20 Jan 2021. Jusufi, Gezim, and Fillorete Gashi-Sadiku. 2020. Impact of Fiscal Policies on Western Balkan SMEs’ Growth: Evidence from Kosovo. Central European Public Administration Review 18 (2): 135–164. Klein, Michael, and Jay Shamboug. 2013. Is There a Dilemma with the Trilemma. https://voxeu.org/article/dilemma-financial-trilemma. Accessed 18 Mar 2021. Krajišnik, Milenko, Dragan Gligori´c, and Biljana Gojkovi´c. 2019. Effects of Fiscal Consolidation in Western Balkan Countries. Zbornik radova Ekonomskog fakulteta u Rijeci: cˇasopis za ekonomsku teoriju i praksu 37 (2): 527–551. Kreso, Sead. 2005. Fiscal Decentralization in B&H. In International Symposium: Bosnia and Herzegovina from Past to Present, Çanakkale Onsekiz Mart University, Çanakkale, April. Kreso, Sead. 2019. Možemo li efikasnije iskoristiti naše raspoložive financijske resurse? In Zbornik radova „Svjetski financijski vrtlog – 30 godina poslije“. Znanstveni skup „Svjetski financijski vrtlog – 30 godina poslije“ povodom 10. godišnjice smrti akademika Ive Perišina održan 05. decembra 2018. godine, Hrvatska akademija znanosti i umjetnosti, Odsjek za ekonomska istraživanja,

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Znanstveni skupovi svezak 12, Ekonomski fakultet Sveuˇcilišta u Zagrebu, 23– 49. Kreso, Sead, and Lejla Lazovi´c-Pita. 2013. Is Fiscal Discipline and Sustainability Strategy (FDSS) an Appropriate Option for Bosnia and Hercegovina? Economic Research-Ekonomska Istraživanja 26 (sup2): 132–148. Lazovi´c-Pita, Lejla. 2015. Income, Personal Income Tax, and Transition: The Special Case of Bosnia and Herzegovina. BERG-Verl. Lazovi´c-Pita, Lejla, and Ana Stambuk. 2016. What Are the Opinions of Tax Administration Official Regarding Tax Policy Reforms in Bosnia and Herzegovina? Journal of Advanced Research in Law and Economics 7: 2106. Malush, Krasniqi. 2014. Management and Design of Fiscal Policy Towards Economic Development. Mediterranean Journal of Social Sciences 5 (20): 990. MCP BiH (Ministry of Civil Affairs of BiH). 2020. Last modified: January 2021. http://mcp.gov.ba/publication/read/rast-nezaposlenosti-uzrokovansmanjenom-ekonomskom-aktivnoscu-uslijed-pandemije-covid-19?pageId=0& lang=en. Accessed 4 Feb 2021. Ministry of Finance and Treasury of BiH. 2020. Kvartalni pregled javnog duga BiH [Quarterly Overview of Public Debt of BiH]. Last modified: November 2020. https://www.mft.gov.ba/bos/images/Kvartalni_pregled_j avnog_duga_BiH_-_III_kvartal_2020_Bos.pdf. Accessed 6 Feb 2021. Ministry of Finance of RS. 2020. Program ekonomskih reformi Republike Srpske [Program of Economic Reforms of Republic of Srpska, Different Years]. Last modified: January 2021. https://www.vladars.net/sr-SP-Cyrl/Vlada/Min istarstva/mf/PPP/Pages/Program-ekonomskih-reformi-2016-2018-godina. aspx. Accessed 5 Feb 2021. Miškin, Frederik S., Biljana Lalovi´c, Dejan Eri´c, Boško Živkovi´c, and Dušan Ili´c. 2006. Monetarna ekonomija, bankarstvo i finansijska tržišta. Data Status. Obrenovi´c, Mladen. 2017. Registar c´ e pokazati ko je (bio) lažni borac, July 2017. https://balkans.aljazeera.net/teme/2017/7/21/registar-ce-pokazatiko-je-bio-lazni-borac?qt-view__news_taxonomies__news_taxonomies_panel_ pane=1&qt-view__programs__programs_mega_menu_panel_pane=3?gb=true. Accessed 5 Feb 2021. Obstfeld, Maurice. 2015. Trilemmas and Tradeoffs: Living with Financial Globalisation. BIS Working Papers No. 480. OECD. 2020a. COVID-19 Crisis Response in South East European Economies. Last modified: November 2020. https://read.oecd-ilibrary.org/view/?ref= 129_129649-tclugxbw4j&title=COVID-19-Crisis-Response-in-South-EastEuropean-Economies. Accessed 3 Feb 2021. OECD. 2020b. The COVID-19 Crisis and BiH. Last modified: April 2020. http://www.oecd.org/south-east-europe/COVID-19-Crisis-in-Bosnia-andHerzegovina-archive.pdf. Accessed 15 Dec 2020.

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Ott, Katarina. 1998. Tax Administration Reform in Transition: The Case of Croatia. Institute of Public Finance. Pension and disability fund of FBiH. 2021. Struktura penzija iz redovne isplate za decembar 2020 (Structure of pensions from regular payments for December 2020). Last modified: December 2020. http://www.fzmiopio.ba/images/sta tistika/strrasbos122020.pdf. Accessed 4 Feb 2021. Perišin, Ivo. 2006. Hrvatska u svjetskom vrtlogu. Zagreb: Razlog. Rey, Helene. 2013. Dilemma Not Trilemma: The Global Financial Cycle and Monetary Policy Independence. Global Dimensions of Unconventional Monetary Policy. Proceedings of the Federal Reserve Bank of Kansas City Jackson Hole Symposium. Shehaj, Albana. 2020. The Perils of Succor: The European Union’s Financial Role in the Western Balkans During COVID-19. European Policy Analysis 6 (2): 264–276. Tax Administration of FBiH (TAFBiH). 2021. Pregled poreznih obveznika dužnika sa iznosom duga po osnovu poreza, doprinosa, taksi i drugih naknada (Debtors of direct taxes, SSC and other fees). Last modified: January 2021. http://pufbih.ba/v1/public/upload/files/DUG%20PREKO%205000 000%20KM%20NA%20DAN%2031_12_2020_.pdf. Accessed 20 Jan 2021. Tax Administration of RS (TARS). 2021. Debtors of Direct Taxes. Last modified: January 2021. https://poreskaupravars.org/author/purs/?lang=lat. Accessed 20 Jan 2021. Wolf, Holger C., Atish R. Ghosh, Helge Berger, and Anne-Marie Gulde. 2008. Currency Boards in Retrospect and Prospect. Cambridge: MIT Press. World Bank Group. 2016. Financial Systems in Western Balkans: Present and Future. World Bank.

PART III

Broader Impact of COVID-19

CHAPTER 10

Emergency Financial Mismanagement in Croatia During COVID-19 Crises Robert Bari´c

10.1

Introduction

In any crisis, it is important to have not only sound economic policies to respond to a particular disaster but also developed an overall emergency management framework for implementation of those policies. Today financial preparedness represents a crucial component of emergency planning that addresses the actions necessary to mitigate economic losses incurred during any kind of crisis. Long before a crisis occurs, there is a need for identification, recognition, and preparation of necessary measures for minimization of economic losses and effective recovery afterward. In recent years there are numerous examples of a large-scale range of natural and man-made catastrophes creating a broad range of direct and indirect consequences on affected societies, including significant financial and economic losses. In 2005 hurricane Katrina in the United States caused USD 125 billion in overall losses and over 1300 fatalities. In 2008 R. Bari´c (B) Faculty of Political Science, Zagreb University, Sesvete, Croatia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_10

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Sichuan earthquake in the People’s Republic of China caused USD 85 billion in damages and an estimated 84,000 fatalities. In 2011 earthquake in Japan caused USD 210 billion in overall losses and almost 16,000 fatalities. During 2019 the 409 natural catastrophe events created direct economic losses and damage of USD 232 billion (Impact Forecasting 2019, pp. 2–5). In 2020 economic losses from natural disasters and prolonged impacts from the COVID-19 pandemic are estimated at USD 268 billion (Impact Forecasting 2020, pp. 4–7). The current COVID-19 global pandemic is an example of those trends. The COVID-19 pandemic is unique; it isn’t only a global public health crisis. It is also a global financial crisis caused by non-economic factors (containment measures introduced to the stop spread of pandemic): As such, the COVID-19 pandemic has seriously affected the global economy creating numerous negative economic consequences (reductions in income; unemployment rise; major disruptions in the manufacturing industries, service industries, and transportation sector; global supply chains disruptions, global financial markets disruptions).1 Those negative outcomes were strengthened by the fact that most governments of the affected countries underestimated the consequences of a rapid COVID19 spread and were mostly reactive in their response to the pandemic crisis. The second characteristic of the COVID-19 pandemic is simultaneous disruptions to both supply and demand in an interconnected world economy, followed by the extreme uncertainty about the duration, magnitude, and impact of the pandemic. The economic consequences of the pandemic have been felt everywhere, even in countries where health consequences were minimal. Current events highlight the importance of a comprehensive and coordinated strategic response to the pandemic at the national level for ensuring timely deployment of medical resources, restoration of the normal functioning of financial markets, and implementation of other measures for supporting firms and households during the crisis. Part of such response is the development of emergency financial management (EFM) as a component of the overall national emergency management.

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From Tactical to the Strategic EFM

Although financial preparedness is a component of emergency management2 and disaster risk management3 planning for decades, usually focus was on funding for the response and the recovery phase of comprehensive emergency management.4 The traditional framework of emergency management has been designed mostly to ensure rapid and effective recovery from natural and man-made disasters and catastrophes in affected areas. In that context, EFM task is the preparation of financial support for the recovery process (creating conditions for rebuilding of critical infrastructure and renewal of economic activity, calculating and justifying the overall cost of those activities, prioritization, and funding of recovery projects). A key issue of financial preparedness on this level is the concept of fiscal federalism (distribution of tax and expenditure powers between different vertical levels of government) which demands that the local authorities recognize the ultimate responsibility of the state in resolving financial problems created by adverse events.5 The global financial crisis of 2007–2009 has significantly enlarged the scope of EFM. Consequences of a crisis created policy the priority of strengthening financial resilience to disasters, with the goal of developing measures to prevent or reduce the effects of future financial crises. The problem was the absence of preventive financial measures and the need to create institutions and procedures for diagnosing and preventing recurrence of conditions that created a crisis. Analysis of implemented measures in different countries between 2008 and 2018 in many cases indicates the enhancement of abilities to deal with certain kinds of financial problems (modest financial shocks, the failure of individual institutions). But the problem of degraded abilities to deal with major financial crises that have the greatest potential for causing widespread economic harm to society (systemic shocks, international contagion, threats from new vectors such as cyber-attacks) is still unresolved.6 Despite still present problems and challenges, the global financial crisis of 2007–2009 has opened a door for the expansion of EFM activities. From its traditional role in organizing responses to natural and man-made disasters and catastrophes in affected regions, EFM gained a broader role in addressing the consequences of a major financial crisis at the national and international level. The current economic crisis created as a result of the COVID-19 pandemic also emphasizes the significance of the strategic EFM. In

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comparison with the previous two global economic crises (the Great Depression 1929–1930 and the Great Recession 2007–2009) current crisis is unprecedented regarding simultaneous speed and decline of economic activities across the globe. Governments are faced with the simultaneous multi-dimensional effects of the pandemic—impacts on public health systems and its consequences for every sector of the economy. High transportation connectivity, globalization, and economic interconnectedness is making it extremely difficult and costly to contain the global spread of the COVID-19 virus and prevent the disruption of economic activities and volatility of financial markets on global and regional levels. In such conditions, EFM tasks aren’t limited only to preserve the robustness of financial systems or funding for the response and recovery phase in cases of natural and man-made disasters and catastrophes. EFM is now an important part of a comprehensive economic policy response to the COVID-19 pandemic. International Monetary Fund recently published recommendations for preparing public financial management systems for emergency responses (IMF 2020). Based on experience with recent heath emergencies (SARS, Ebola) identified are following challenges for governments in emergency response (IMF 2020, p. 1): 1. Reassessing fiscal policy needs and identifying additional financial resources. 2. Ensuring timely availability of funds to service delivery units. 3. Tracking, accounting for, and reporting in a transparent manner the resources deployed for emergency response. 4. Ensuring business continuity when faced with absences of staff. Four mentioned goals for resolving mentioned challenges are also a framework for EFM activities (IMF 2020, pp. 1–2): • Supporting the delivery of emergency health services (including the direct provision of health care services); purchase of supplies and equipment; putting in place the human resources needed to monitor, contain, and mitigate the COVID-19 outbreak. • Ensuring the ongoing delivery of essential public services that may come under stress during an outbreak.

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• Implementing new fiscal measures (including various support mechanisms) to assist businesses and people experiencing economic hardship. • Ensuring smooth public financial management services despite absences of staff across the government. Organizing EFM for tasks in a pandemic situation requires a different approach than organizing response in cases of other natural and manmade hazards. In cases of those hazards (which are usually occurring within a limited period in confined areas) four CEM phases (mitigation, preparedness, response, and recovery) are linear. Pandemics like COVID19 tend to come in multiple waves over protracted intervals, which mean that instead of a linear sequence of events some phases of the CEM cycle could occur parallel (for example, the response phase in some regions could be parallel with transition and recovery phase in other regions where is a significant decrease of the infections). Another possible scenario is the need for a fast transition from recovery back to response phase in case of a new pandemic wave. This means that in an EFM cycle critical time to act is before the situation becomes an emergency, assuming that there are the political will and administrative authority in place. Also, preventive EFM planning in the first two phases of the CEM cycle should be focused not only on anticipating measures for immediate financial relief in the response phase but also on the mid-and long-term economic recovery planning. An example of insufficient preventive EFM is criticism of the UK’s failure to consider in advance ways to deal with its economic response to the first wave of the COVID-19 pandemic. On 23 July 2020 report issued by the House of Commons Public Accounts Committee severely criticized the UK government’s economic response to the pandemics. The main points of the report are7 : 1. The government’s pandemic planning had only taken into account health consequences and ignored the economic effects of the pandemic. 2. Economic response had “no plan” and taken measures were late, rushed, and reactive. Lack of prior planning led to delayed implementation of proposed measures. The lack of economic preparation

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led to whole sectors of the economy being left behind, which could have long-term economic consequences. 3. Report called for more transparency in government decisionmaking, which was in some areas poorly coordinated and didn’t take into account the long-term impact of implemented measures. There’s also a need for the detailed review of contingency planning for the most serious risks, using the whole-of-government approach and economic modeling. 4. The report also criticized the procurement process for personal protective equipment (PPE), noting that the government failed to prepare adequate stocks of PPE in advance although pandemic was being identified as the government’s top non-malicious risk. 5. Report called for greater involvement with businesses community regarding their needs. It recommended the Treasury should engage with key sectors and industries to develop measures for mitigating the ongoing effects of the pandemic. Development of the preventive EFM asks for clear articulation of the role of financial preparations in the first two phases of the CEM cycle. Based on disasters risk financing practices and emergency preparedness frameworks surveys8 it is possible to define four steps that should be incorporated in the mitigation and preparedness phase: 1. Recognizing risks. Creation of more comprehensive scenario-based risk assessment which needs to evaluate and give answers on the following issues: • Definition of possible financial risks for different types of crises and catastrophes. • Assessment of the expected financial impacts of disasters on the economy and the capacity of economic sectors and population to absorb and recover from incurred financial losses. The next issue which needs to be addressed is the creation of an early warning mechanism for possible forthcoming disasters and their financial consequences. As a result of the global financial crisis in 2007–2009, many countries established organizations tasked with the identification of risks and appropriate response to emerging threats to their financial stability. An example of such an organization is US Financial Stability

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Oversight Council (FSOC). Created in 2010 FSOC represents a team of regulators from federal agencies charged with identifying risks to the financial system. A recent example of FSOC activity is warning about possible serious consequences of the COVID-19 pandemic for the US short-term funding market.9 2. Defining objectives. Depending on the characteristics of a possible crisis, it is necessary to formulate specific financial and economic countermeasures to counter its effects. The chosen strategy should address key factors that created fiscal distress, and develop clear goals for minimizing or avoiding expected negative consequences. 3. Organizing emergency response planning. Governments need to evaluate their capacity to manage the financial costs of identified disaster risks (costs and losses linked to emergency response, and changes in macroeconomic conditions). The next step is to precisely define realistic plans of action, instruments, disaster management authorities, and their responsibilities for all areas of the emergency management, including its financial component. Of critical importance is inter-agency coordination of preparedness and emergency response plans at all levels of government to avoid unnecessary fragmentation or duplication in planning processes and preparations. 4. Ensuring government accountability. The accountability of leaders and government institutions is critically important to ensure that actions and decisions taken by public officials are subject to oversight. Oversight is necessary to guarantee that government actions meet their stated objectives and respond to the needs of the public. Accountability also connotes a legal obligation on the part of those holding leading positions to carry out their responsibilities or functions. One of the results of the COVID-19 pandemic is the weakening role of parliamentary oversight over the government actions during a pandemic. This situation forced many parliaments in Europe to adopt new practices to ensure continuity of executive oversight, but it is an open question will they be able to fully perform their role in the future (Griglio 2020). The implementation of these four steps in the first two phases of the CEM cycle should enable rapid response and mobilization of all financial resources in the early stages of the crisis. Also, this would create a framework for adapting EFM to changes in crisis dynamics that require modification or even complete alternation of the pre-crisis plans. Examples of such unforeseen situations are cases of natural disaster occurrences during the COVID-19 pandemic: earthquakes in Croatia (in March and December 2020) or locust swarms in East African and South Asian countries (in March 2020).

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10.3 Financial Response to the Pandemic Crisis in Croatia Economic activity in Croatia has been severely affected by the COVID-19 pandemic. After economic recovery between 2015 and 2019 with annual growth of 3%, in 2020 a sharp decline is underway. The latest projections made by the Croatian National Bank are indicating a decline in economic activity in 2020 and a possible slow recovery in 2021 (Croatian National Bank 2020, pp. 3–5): • Real GDP might fall by 8.9% in 2020, and then rise by 4.9% in 2021. • Employment is expected to fall by 1.5% in 2020 while the ILO unemployment rate might go up from 6.6% in 2019 to 7.5% of the labor force. • The average annual consumer price inflation might slow down to 0.2% in 2020 (from 0.8% in 2019), and rise to 1.0% in 2021. • Revenues from foreign tourist consumption in Croatia might be cut by more than a half in 2020 from the previous year. • The general government budget surplus in 2019 was 0.4% of GDP. In 2020 a general government deficit might amount to 8.0% of GDP. It should be noted that these forecasts were made on the basis of data before the autumn pandemic wave when it seemed that Croatia had a chance for a faster economic recovery in 2021. Such an optimistic scenario is less and less likely. Instead, the warnings of economic analysts emphasize that the COVID-19 pandemic will have more lasting and severe consequences on the Croatian economy and that the economic recovery in 2021 will be slower than previously expected.10 Negative economic developments weren’t caused only by the consequences of the COVID-19 pandemic. The long-term structural imbalances of the Croatian economy also have a significant impact. This is the reason why Croatia has been put under close EC monitoring mechanism within so-called “European Semester”, “Macroeconomic Imbalance Procedure” (European Comission 2020, pp. 52–53). Positive economic growth achieved between 2015 and 2019 was strongly driven by private consumption, tourism, and “good fortune” (favorable global conditions that allowed a tourist boom).11 But numerous economic and financial analyses also indicate the following weak spots of the Croatian economy:

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1. Need for improving the investment climate. Some progress has been made in improving business regulations and administrative burden. Despite that barriers to regulated professions and remaining parafiscal fees (especially for small and medium enterprises) are still high. Another serious problem is the need for more effective promotion of investment policy (lack of comprehensive promotion strategy, fragmented institutional set-up, insufficient capacity for corruption, and other forms of misconduct).12 2. Need for reformulating the existing growth model of “financedominated capitalism” which is a key factor of macroeconomic instability in Croatia.13 3. Croatia lacks the capacity for rapid economic growth and convergence. A report of the Croatian Employers’ Association published in 2018 mentions indicators that slightly deteriorated between 2017 and 2018. As key indicators are mentioned investment and business barriers (the number of procedures required for starting a business, building permit fees and local rates to be paid by investors), negative entrepreneurial climate, and investment growth.14 4. The excessive dependence on tourism. Tourism is a key sector of the Croatian economy. International tourists’ expenditure in Croatia amounts to almost 20% of GDP. The problem is the fact that the current tourism model may be unsustainable in the future.15 The current crisis has exposed the danger of relying on one or two key sectors and emphasized the need for diversifying the Croatian economy with the goal of decreasing Croatia’s dependence on tourism. 5. Weak performance of the Croatian State-Owned Enterprises (SOEs). Croatian SOE performance is weaker than in private firms. SOEs generally show low productivity and profitability due to inefficient use of labor, and weak governance. As such, Croatian SOEs inefficiency has a negative effect on national economic growth.16 6. Significant regional development disparities. Most of the Croatian counties are far below the EU average GDP level: exceptions are the City of Zagreb (approximately 103% of the EU average), Istria and Primorje-Gorski Kotar (almost 75% of the EU average) and Dubrovnik-Neretva County (about 60% of the EU average). The worst situation is in the Slavonia region (five counties with GDP of a mere one-third of the average EU GDP).17

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Mentioned structural problems indicate that measures to combat the consequences of the COVID-19 pandemic can’t be limited only to ensure business continuity. Proposed financial and economic measures should be used as an opportunity to induce structural changes necessary for solving problems of the Croatian economy. Unfortunately, the measures taken so far don’t indicate a willingness for resolving long-term structural imbalances in the Croatian economy. The first case of COVID-19 infection in Croatia was registered on 25 February 2020. Croatian government announced the first restrictive measures for combating pandemic on 12 March 2020. They were followed by the first rescue package for offsetting lockdown damage to the economy adopted on 17 March 2020.18 The first rescue package worth EUR 3.9 billion set 63 compensatory measures with the aim of retaining jobs and ensuring funds for wages.19 Croatian National Bank (CNB) also took measures for maintaining the stability of the exchange rate of Croatian currency and providing liquidity to the banking sector.20 The second set of compensatory measures was adopted on 2 April, continuing efforts for saving the jobs and to support the tourism sector.21 In late June 2020, the government announced that it would support the preservation of jobs through part-time work for the second half of the year. In September 2020 government adopted a new rescue package. This package included COVID loans for improving the liquidity of companies in distress. Government assistance for a job-retention scheme was continued. The last rescue package was announced in December 2020. The government intends to introduce a scheme to help cover fixed costs of businesses (costs of rent, utilities, the Internet and landline telephony, accounting and bookkeeping services, the public television subscription fee) in part or in full, but only for enterprises whose turnover in December drops by at least 60% compared to December 2019.

10.4 Three Major Issues in Policy Response in Croatia The analysis of described financial and economic measures indicates several problems in their implementation. The first problem is a late response to the pandemic and insufficient early warning mechanism for EFM. Although the first case of COVID-19

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infection in Croatia has been confirmed on 25 February, the government announced plans for the first rescue package only after three weeks. This delay connotes the non-existence of EFM plans and preparations. In such conditions, the government needed time for the design of proposed financial and economic measures from the scratch. Such a hastily approach prevented detailed comprehensive EFM planning and made necessary incremental approach in adopting the following rescue packages. Significant response delay in adopting financial measures is also an indicator of insufficient EFM early warning mechanism in Croatia. As a result of the experience of 2007–2009 global financial crisis in January 2014 has been established the Financial Stability Council (FSC). The FSC is an inter-institutional body with representatives of the CNB, the Ministry of Finance, the Croatian Financial Services Supervisory Agency, and the State Agency for Deposit Insurance and Bank. Its main tasks are to identify, assess, and address systemic financial risks and to ensure effective cooperation and exchange of information between the financial regulatory institutions. The FSC meetings are held twice a year and aren’t open to the public. Only annual reports22 and announcements of the content of the meetings23 are open to the public access. Looking at those sources it is obvious that the main task of the FSC is only to observe the current macroeconomic situation of Croatia and on that basis propose macroprudential measures. This is confirmed by a statement of the CNB current Governor Boris Vujˇci´c made in 2017 during the Agrokor crisis.24 The FSC isn’t charged with the task of modeling potential financial crises and on that basis proposing the implementation of preventive measures. Its role is limited to the tasks of monitoring the current financial situation in Croatia and annunciation of general warnings without explicit proposals of measures for dealing with potential financial risks. The second problem is the limited extension of the initial reaction. The government’s initial response was made without a full understanding of overall pandemics’ economic consequences for the Croatian economy. The first and following rescue packages were aimed primarily at shortterm measures (retention of jobs, postponement of liabilities of economic subjects) instead of a broad set of measures needed to alleviate the longterm consequences of a large decline in economic activity. The ongoing COVID-19 pandemic has seen many Croatian companies struggle to survive, suffering previously hard to imagine liquidity loss and the threat of total closure. Small and medium enterprises (SMEs) in several economic sectors (tourism, transportation, skilled crafts, entertainment)

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were hit especially hard. Despite their importance25 the Croatian Small Business Agency (HAMAG-BICRO) has given loans totaling EUR 93 million to support the liquidity of small businesses for a limited time at the beginning of the crisis (those loans were again restarted in December 2020 in the amount of EUR 173 million, also for a limited period). From the start of the pandemic, SMEs are constantly asking for two types of support measures. The first proposed measure is non-repayable business improvement assets intended for the introduction of new products and services. The second proposed measure is working capital loans with favorable conditions that will enable SMEs to avoid or bridge the liquidity gap and create new stocks. Another proposed measure is the reduction of the 20 highest parafiscal taxes, whereas other parafiscal charges should be either revoked or reduced by 70%. According to the Croatian Employers’ Association (HUP) in 2019 entrepreneurs, craftsmen, and citizens paid more than HRK 9 billion for over 500 parafiscal levies. Limited compensatory measures proposed in December are also evaluated as insufficient to help SMEs.26 The third problem is focusing on the short-term economic measures without consideration of medium- and long-term economic recovery strategies. Emphasis is on the measures for the preservation of jobs and maintaining companies’ liquidity. The government did not present a plan or started with mid-to-long-term broader measures necessary for achieving sustainable economic recovery and growth. Those measures should be focused on means for solving Croatian economy structural weaknesses. For achieving that, they need to be part of a broader recovery strategy which should include reorganization and rationalization of public administration, legal reforms, and the new territorial organization of Croatia. Up to now, the government did not present any strategy regarding those issues. Problems are also visible in the traditional EFM activities. On 22 March 2020 Zagreb and surrounding counties were hit by an earthquake with a magnitude of 5.5 on the Richter scale. The earthquake caused serious material damage estimated at HRK 42 billion. Since then, ten months after the earthquake, the reconstruction still didn’t start. Despite the adopted legal framework detailed financial plan for the reconstruction of destroyed infrastructure still doesn’t exist. Also is missing an overall assessment of the necessary financial resources, as well as the answer to the question of whether the forthcoming budget deficit will force Croatia to postpone the introduction of the Euro.27

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In conclusion, the fiscal response by the Croatian authorities in the ongoing pandemic crisis showed a focus on immediate financial relief instead of creating and implementing a comprehensive long-term financial recovery strategy, necessary for minimizing economic losses. This indicates the existence of underdeveloped emergency financial management in Croatia. This is also part of a wider problem of uneven and nonsystematic development of the overall national emergency management system in Croatia.

10.5 Structural Roots of the Inefficient EFM in Croatia The listed shortcomings in the development of emergency financial management are a result of broader problems in the organization of the public administration in Croatia. There are three key problems in the organization and operation of the Croatian public an administration that affected the inability of Croatian authorities to create and implement an effective EFM system.

10.6 Underdeveloped Emergency Management System The first problem is the discretionary national emergency management system. Croatia doesn’t have a systematically developed emergency management system. Instead, at the start of the COVID-19 crisis, Croatian authorities were forced to improvise emergency management system from the ground up (Bari´c 2020). In the last thirty years, Croatia hasn’t followed the global trend of transforming civil defense systems into integrated crisis management systems. After gaining independence in 1991, Croatia inherited the civil defense system developed in the former Yugoslavia. The civil defense system was reorganized in 1993 and divided between the Ministry of the Interior and the Ministry of Defense. The reorganization intended to develop civil protection system within the Ministry of Interior, while the further development of the civil defense would be left to the Ministry of Defence. But instead of mutually reinforced development, the ability of both components was gradually degraded. In 2005 was established new government agency—the State Administration for Protection and Rescue

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(DUZS)—with a goal of introducing coordination of activities for all state institutions in charge of different aspects of protection and rescue tasks in order to avoid overlapping of their competencies. DUZS was unable to achieve this goal, and in 2018 the idea of turning it into a central institution of state administration for civil protection was abandoned. Therefore, a decision was made to abolish the DUZS and replace it with a new organization, the Civil Protection Directorate (organized within the Ministry of the Interior) in 2019. The new institution was organized as an administrative organization for the civil protection system which prepares plans and manages the operational forces. The next attempt to create a comprehensive national emergency management system has been the development of the Homeland Security system between 2017 and 2020. Croatian National Security Strategy adopted in 2017 states goal of creating a framework for “coordinated preparation and implementation of regulations determining measures and procedures for security protection vital to national security, particularly the protection of critical infrastructure”.28 This attempt also didn’t yield the required outcomes. The reasons for failure were as follows (Bari´c 2020): 1. Lack of the organizational concept of the Homeland Security system. 2. Absence of a central institution tasked with development and management of the Homeland Security system. 3. The work of the entire system was limited to the issue of coordination of activities between different state institutions. Until the outbreak of the COVID-19 pandemic, Croatia was left without an effective emergency management system. After the pandemic outbreak it was necessary to trigger the urgent development of an improvised emergency management system. This was done with the creation of the National Civil Protection Headquarter on 20 February 2020. Despite initial successes, the following shortcomings of the improvised system soon became apparent (Bari´c, 2020): • Underdeveloped institutional framework of the emergency management system. • Undeveloped legal framework of the emergency management system

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• Insufficient preparations and non-existence of education for emergency management in public administration. • Lack of effective crisis communication. Described problems prevented the development of EFM as a component of the Croatian national emergency management system. The EFM component for monitoring the financial stability (FSC) was developed as part of the Croatian financial system. Regarding the planning of financial preparedness for natural and man-made hazards, there isn’t a permanent legal and institutional framework that would enable preventive planning before the crisis and quick post-crisis reaction. Instead, the practice of adopting a legal framework for financing reconstruction after each disaster has been established. This was done after the great floods in Slavonia in 2015,29 and the same approach was used after last year’s earthquake in Zagreb. The first disadvantage of this approach is the slow response in providing financial assistance. The second disadvantage is focusing on the financing reconstruction of communal and housing infrastructure, but not on achieving post-crisis business activity recovery. Instead of integrated financial preparations for natural and man-made disasters and catastrophes, within the Croatian state the administration is preserved as a fragmented and uncoordinated approach to EFM activities.

10.7

Deficient Strategic Planning

The second problem is the neglected development of the strategic planning capabilities in the Croatian public administration. The creation of an emergency management system is a result of the process of strategic planning in public administration which defines the concept, goals and tasks, and means for its development. Two key issues that are preventing the establishment of effective strategic planning are the inefficient development of the coordination instruments and the “paper strategy” paradox. The development of coordinating instruments in Croatia has been marked by inefficiency and influenced by politically motivated considerations. The consequences of this approach are: intense and often informal political influence; lack of strategic planning in government action; neglected substantive professional analysis of evidence-based policies and their impacts; negative coordination between ministries; financial, technical, and legal restrictions

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on information access. The central government lacks sufficient expertise and capacity for detailed policy analysis (Kopri´c 2018, p. 113). The second issue is the “paper strategy” paradox. There are many strategic documents but their implementation lacks political support and execution capacity. According to the European Commission, Croatia is the worst country in the EU in terms of two indicators—implementation capacity and inter-ministerial coordination (Kopri´c 2018, p. 136). Described situation is a consequence of the collapse of the strategic planning system after Croatian independence in 1991. Following the abolishment of the previous institutional framework,30 the capabilities of strategic planning in Croatian public administration have disappeared. This was the result of the perception of strategic planning as a relic of the former socialist system and thus inadequate for the role of an instrument for the further development of Croatia. Only the beginning of preparations for achieving EU membership led to a partial restoration of the strategic planning capabilities. Between 2003 and 2011 strategic planning was resurrected but only to fulfill the limited role of preparation of strategic documents required for the use of EU pre-accession funds. This role has not changed even after Croatia achieved membership in the EU. This created the current situation in which all activities and capabilities of the public administration strategic planning are focused on obtaining funds from the EU instead of comprehensive strategic planning for defining and achieving national development goals of Croatia.31 Such a narrow focus on strategic planning led to the neglect of other areas of planning, including the planning of establishment and development of national emergency management system and consequently the creation of an effective EFM system.

10.8

Public Administration Politicization

The third problem is the high level of politicization in the Croatian public administration. Politicization32 is a constant feature and one of the main problems of public administration in Croatia (Kopri´c 2018, p. 123). Attempts to depoliticize public administration are limited only to the policy of reducing the number of political appointments with public competition procedure. But, given the fact that government retains complete control over the selection procedure, putting the greatest emphasis on the formal interviews rather than on the elements of merit didn’t significantly change the situation. This has allowed a large number

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of politically appointed members of the public administration to be reappointed using new procedures, indicating the failure of depoliticization measures. At the local levels of government politicization has intensified since the adoption of the law on the direct election of mayors in 2009, and the appointment of politically appointed persons to management positions in SOEs remains a constant problem. The consequence of politicization is the avoidance of the comprehensive reform of Croatian public administration. Political unwillingness to support public administration overhaul in combination with lack of administrative capacities for managing reforms, insufficient reform preparations (weak policy design, formal monitoring, and almost non-existent evaluation), and bureaucratic resistance to changes is resulting in repeating reforms without substantial changes in the effectiveness of the public administration (Kopri´c 2019, pp. 7–26). The result of this situation is the preservation of a politicized and less efficient administrative system that is unable to formulate and implement timely and effective public policies, including policies of financial preparedness for natural and man-made disasters and catastrophes. The combination of these factors is preventing the creation of an efficient EFM in Croatia. Inconsistent development of the emergency management system is impeding the successful development of its component for financial preparedness. Also, the development of an effective emergency management system requires an efficient strategic planning framework necessary for defining its parameters. Poorly developed strategic planning focused on only one area isn’t able to achieve that goal. Finally, the strong politicization of public administration makes it impossible to create effective public policies that would enable the successful development of the emergency management system.

10.9

Conclusion

The current COVID-19 pandemic represents a major challenge for the government’s capacity to lead societies through a crisis. During pandemics, the government must respond to emergencies by organizing rapid responses and mobilizing resources. This also includes a timely response in providing fiscal resources for taking care of emergencies and crises during an ongoing global pandemic. Modern approach in macroeconomic policy response is unconventional and Keynesian, both in fiscal and monetary policy. One example of such thinking is a proposal for the

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future US fiscal policy framework that would be better adapted to deep uncertainty in crisis situations than current American budgetary structures (Orszag et al. 2021). Similar is the IMF proposal for allowing central banks (under specific conditions) limited funding to the government in unexpected and severe emergency situations (IMF 2021). It is a framework for policy response measures of the Croatian Government and the Croatian National Bank. In this context, during the last three decades is the visible growing importance of EFM as an instrument for developing financial preparedness in cases of a broad range of natural and man-made disasters and catastrophes. The scope of EFM has expanded from its traditional role of supporting the recovery process after natural and man-made disasters and catastrophes. During the global financial crisis between 2007 and 2009 EFM scope has expanded to the role of an instrument for stabilizing the financial system. A further impetus for the evolution of EFM is the ongoing COVID-19 pandemic. Compared with previous financial crises nature of current distress is unusual. Instead of solving the problem of the demand deficiency created by economic imbalances, in the current global crisis emphasis is on providing bridge financing and resources to the firms and households during the emergency created by consequences of extended lockdowns. The length and consequences of the current crisis depend on unpredictable non-economic factors. Because of that, it is hard to predict how to resolve its near (increase in private and public sector debt) and long-term (possible long-lasting changes in demand patterns) economic consequences. In such circumstances visible is the growing importance of further EFM development as a framework for financial preparedness in crises. Although the scope of its activities has expanded, EFM is still frequently analyzed within its role at the level of local government and as part of the concept of fiscal federalism (see Kasdan 2015). The challenge for the further development of EFM is in defining means for its activities at the strategic level, as a framework for organizing preventive financial preparedness and acting decisively in cases of sudden outbreaks of complex crises with global consequences. There is currently no systematic EFM development in Croatia. The financial measures taken in response to the COVID-19 pandemic are reactive rather than proactive, focused on short-term financial relief instead of implementing a comprehensive long-term financial recovery strategy. Of

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particular concern is the lack of systematic development and the preparation of preventive measures in the event of financial crises. In terms of developing capabilities for a comprehensive scenario-based financial risk assessment and effective early warning mechanism, the existing institution (FSC) is not capable to effectively fulfill these roles. Croatia is also lacking a permanent framework and procedures for organizing EFM planning. Finally, Croatia doesn’t have institutional public oversight of government activities during emergencies. The current situation is caused by wider problems present in the Croatian public administration. Three key challenges—improvised national emergency management system, underdeveloped capabilities for strategic planning, and high level of public administration politicization in Croatia—are impeding the development of an effective EFM system. The combination of the above-mentioned problems is the main reason for so far unsuccessful attempts of developing EFM as a component of the overall national emergency management system in Croatia.

Notes 1. For global economic consequences of COVID-19 pandemic see Pak et al. (2020). 2. The term emergency management means “the governmental function that coordinates and integrates all activities to build, sustain, and improve the capability to prepare for, protect against, respond to, recover from, or mitigate against threatened or actual natural disasters, acts of terrorism, or other man-made disasters” (FEMA 2010, p. 17). It is different from the term crisis management which is hierarchically lower. Crisis management can be defined as the planning, implementation, and monitoring of strategies that are put in place to help an organization deal with a significant negative event (see Elliott 2014). This definition indicates that emergency management involves a planning process and institutional framework for the comprehensive and coordinated efforts of government, non-government sector, voluntary and private agencies to respond in crises. 3. Disaster risk management is a collective term encompassing all aspects of planning for and responding to emergencies and disasters, including both pre-and post-event activities. It refers to the management of both the risk and the consequences of an event. It is a systematic process aimed at reducing the negative impact and/or consequences of adverse events (Baas et al. 2008, pp. 7–8).

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4. Comprehensive emergency management (CEM) encompasses four phases of disaster management (Etkin 2016, pp. 202–203): 1. Mitigation—Activities are undertaken in the long term, before disaster strikes, that is designed to prevent emergencies and reduce the damage that results from those that occur, including modifying the causes of hazards, reducing vulnerability to risk, and diffusing potential losses. 2. Preparedness—Activities are undertaken in the shorter term, before disaster strikes, that enhance the readiness of organizations and communities to respond to disasters effectively. 3. Response—Activities are undertaken immediately following a disaster to provide emergency assistance to victims and remove further threats. 4. Recovery—Short- and long-term activities undertaken after the disaster that is designed to return the people and property in an affected community to at least their pre-disaster condition of well-being. 5. For an overview of fiscal federalism theory see Chandra (2015). 6. For the overview of implemented measures see: G30. 2018. “Managing the Next Financial Crisis: An Assessment of Emergency Arrangements in the Major Economies ”. The Group of Thirty. Washington, DC. 7. House of Commons. 2020. “Whole of Government Response to COVID19, Thirteenth Report of Session 2019–21”. House of Commons Public Accounts Committee HC 404. Published on 23 July 2020. London. https://committees.parliament.uk/committee/127/public-accountscommittee/content/136854/public-accounts-committee-the-uk-govern ment-response-to-the-covid19-pandemic/. Accessed on 10 January 2021. 8. See: 1. OECD (2015, pp. 16–53). 2. WHO (2016, pp. 7–12). 9. Egan, Matt. 2020. “Trump Regulators Leave a Warning for the Biden Team”. CNN. December 7. https://edition.cnn.com/2020/12/07/inv esting/wall-street-biden-trump-regulation-fsoc/index.html. Accessed on. 10. HINA. 2020. “Analysts Say Croatia’s GDP Dropped by About 10% in Q3 2020”. 22 November. https://www.croatiaweek.com/croatias-gdpdrops-by-around-10-in-q3-2020-analysts-say/. Accessed on 25 December 2020. 11. IMF. 2019. “Republic of Croatia: Staff Concluding Statement of the 2019 Article IV Mission”. December 16. https://www.imf.org/en/News/Art icles/2019/12/16/Republic-of-Croatia-Staff-Concluding-Statement-ofthe-2019-Article-IV-Mission. Accessed on 25 December 2020. 12. OECD. 2019. “OECD Investment Policy Review of Croatia: An Overview Assessment”. Paris. www.oecd.org/investment/OECD-Invest ment-Policy-Review-of-Croatia-Overview-Assessment.pdf. Accessed on 28 December 2020. 13. See: Krniˇc, Branko and Radoševi´c, Dubravko. 2014. “Macroeconomic Imbalances in Croatian Economy: Duality Between Financial and Real

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14. 15.

16.

17. 18.

19.

20.

21.

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Sector”. Ekonomski pregled 65(1): 3–34. For a broader view of this problem in South-East Europe see Radoševi´c and Cvijanovi´c (eds.) 2015. BTI 2020 Country Report —Croatia: 19. Orsini, Kristian and Ostoji´c, Vukašin. 2018. Croatia’s Tourism Industry: Beyond the Sun and Sea. European Economy Economic Brief 036. European Commission, Directorate-General for Economic and Financial Affairs. Luxembourg. Richmond, C., P. Dohlman, J. Miniane and J. Roaf 2019. “Reassessing the Role of State-Owned Enterprises in Central, Eastern and Southeastern Europe”. Departmental Paper No. 19/11. International Monetary Fund (Washington, DC). June 18, 2019 pp. 27–28. BTI 2020 Country Report —Croatia: 17–18. For the overview of financial and economic measures for combating effects of COVID-19 pandemic up to January 2021 see: European Commission. 2021. “Policy Measures Taken Against the Spread and Impact of the Corona Virus —14 January 2021”. Directorate General—Economic and Financial Affairs. Brussels: 39–40. The government has decided to provide minimum wages for employees affected by the crisis (EUR 425, HRK 3250) for three months under certain conditions (the business must experience a drop in revenue of at least 20%), the tax exemption for companies that suffered a drop in turnover of over 50% for March, and a postponement of taxes for companies that have lost between 20 and 50% of their turnover. In March the CNB sold a total of EUR 2.25 billion and released HRK 3.8 billion to the banks. In April HRB agreed with the European Central Bank a precautionary currency agreement which allowed HRB to borrow up to EUR 2 billion from the ECB in exchange for Croatian currency. In September 2020, the ECB’s euro liquidity line was extended by six months. On 20 March the CNB adjusted its regulatory framework and monitoring activities to support the liquidity of financial institutions. On 23 March, the CNB reduced its mandatory reserve requirements from 12 to 9%, lowering the total amount of mandatory reserve by HRK 10.45 billion EUR 1.3 billion. Minimum wage was increased to EUR 725 (HRK 4000) for the period from April to June. The government also partly or fully exempted some businesses from paying taxes (from April to July) and allowed companies to defer VAT payments. The Government also announced the exemption on payments of income tax and contributions for entrepreneurs with an annual income of less than HRK 7.5 million (representing 93% of firms), whose revenue declined by more than 50%. Companies with an annual income above the mentioned threshold will be only partially exempted. Accessible on the FSC website in Croatian language (https://www.vfs. hr/izvjestaji). Accessed on 25 December 2020.

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23. Accessible on the FSC website in English language (https://www.vfs.hr/ en/press-releases). Accessed on 25 December 2020. 24. Asked why the FSC didn’t issue a warning of the possible financial consequences that may arise from the business practices of the Agrokor company, Governor Vujˇci´c emphasized the reactive rather than preventive role of the Council. He also said the FSC had fulfilled its role. Despite the financial collapse of the Agrokor, the country’s financial stability was preserved. See: Gatari´c, Ljubica. 2017. “Napadi na HNB poklapali su se s nadzorom banaka bliskih skupinama povezanih s Agrokorom”. Veˇcernji list. 4 November. https://www.vecernji.hr/premium/napadi-na-hnbpoklapali-su-se-s-nadzorom-banaka-bliskih-skupinama-povezanih-s-agroko rom-1205535. Accessed on 10 January 2021. 25. In 2018 the SME sector has the largest share in the number of enterprises (99.7%). The SMEs employ almost three-quarters (72.2%) of all employees in business entities in Croatia. In 2018 SMEs accounted for 58% of total income generated in Croatia. In the total exports of Croatian enterprises in 2018, the small and medium enterprise sector participates with a share of 53%. Source: Small and Medium Enterprises Report Croatia—2019: 13–14. 26. Hr.turizam. 2020. “UGP: The New Economic Measures Are Not Adequate and Do Not Help Entrepreneurs in the Long Run”. 9 December. https://hrturizam.hr/en/ugp-nove-gospodarskemjere-nisu-adekvatne-i-ne-pomazu-poduzetnicima-dugorocno/. Accesed on 10 January 2021. 27. Blaškovi´c, Ana. 2021. “Nitko još ne zna koliko c´ e snažno potres ‘urušiti’ javne financije: “Svjesni smo rizika”“, Poslovni dnevnik. 1. February. https://www.poslovni.hr/hrvatska/nitko-jos-ne-zna-koliko-cesnazno-potres-urusiti-javne-financije-4270397. Accesed on 10 January 2021. 28. “The Republic of Croatia The National Security Strategy”. 2020. Zagreb: 24. 29. See: Bobovec, Borka and Mandi´c Ružica. 2014. “Housing Stock Reconstruction and Remediation of Consequences of the Disastrous Flood in the Territory of Vukovar-Srijem County”. Polytechnic & Design 2(2): 248–254. 30. In the former Socialist Republic of Croatia central institution for all aspects of strategic planning has been Republic Institute for Societal Planning. In 1991 Institute was transferred in the newly established Ministry for economic development and was limited to the role of office for economic analytics. Institute was finally abolished in 1996. 31. For the development of the public administration strategic planning capabilities in the Republic of Croatia see: Kralji´c (2016, pp. 128–148).

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32. Politicization is defined as “the substitution of political criteria for merit-based criteria in the selection, retention, promotion, rewards and disciplining of members of the public service” (Peters and Pierre 2004, p. 2).

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Radoševi´c, Dubravko, and Vladimir Cvijanovi´c (eds.). 2015. Financialisation and Financial Crisis in South-Eastern European Countries. Frankfurt am Main: Peter Lang GmbH. Singer, Slavica, and Mirela Alpeza, eds. 2019. “Small and Medium Enterprises Report Croatia – 2019”. CEPOR – SMEs and Entrepreneurship Policy Center. Zagreb. The Federal Emergency Management Agency. 2010. The Federal Emergency Management Agency Publication 1. Washington, DC. The Republic of Croatia The National Security Strategy. 2020. Zagreb. https:// www.uvns.hr/UserDocsImages/dokumenti/nacionalna-sigurnost/THE%20R EPUBLIC%20OF%20CROATIA%20NATIONAL%20SECURITY%20STRA TEGY.pdf. Accessed on 10 January 2021. World Health Organization. 2017. A Strategic Framework for Emergency Preparedness. Geneva.

CHAPTER 11

Modern Monetary Theory and COVID-19 Crisis Tihomir Domazet

11.1

Introduction

The most important event in the history of money, which has more than 4000 years, occurred in 1971, when US President Nixon unilaterally decided to abandon the gold convertibility and ended the system of fixed exchange rates. The broken Bretton—Woods system was replaced by fluctuation currency system and most governments issued their own currencies by legislative fiat under the fiat money system. Under the new system, which created the new international financial system, currencies were not convertible into anything of value and were floated and traded freely in foreign currency markets. Most people including economic and political experts are unaware of what meant abandoning the old system and introducing a new one based on fiat money as well as sowed seeds of disaster, which consequences are brought to light after the Great recession (2008) and currently the COVID-19 crisis.

T. Domazet (B) University for Peace—ECPD Established by UN, Zagreb, Croatia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_11

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After abandoning Bretton—Woods system and applying for the fiat money, however, the economic and financial system continues to operate as there was not any change. Then the system was replaced or modified by financialization and other parts of neoliberal economics until its collapse by the Great recession (2008) and more recently by COVID-19. Successfully solving the greatest economic crisis ever, the Great Depression, from the 1930s as well as the establishment of the new Bretton— Woods economic system (1944) and prosperous after WWII the West likes to attribute to their capability and ideology. It is great the question, like mystery, how the new system based on legislative fiat under the fiat money system survived with old tools although a currency regime can range through a continuum from fixed exchange rate systems to floating exchange rate systems with varying degrees of exchange rate management in between. In addition, most of the educational notions or analysis appearing in macroeconomics textbooks as well as public debate and underpins the cult of austerity, is derived from “gold standard” logic and does not apply to modern fiat monetary systems. Economic policy ideas that dominate the current debate are artifacts from the old system, which was abandoned in 1971. Taking into account that most of the relevant economists worldwide accepted ideas that the main Keynes’ role in his 1930s activities was to save the system therefore after the global financial crisis, GFC (2008) and the most recent economic crisis caused by COVID-19, with the acknowledgment that later crises have their root in the Great Depression, more and more questions raised—how to save the system now? The fiat-based monetary system has functioned in this form since the demise of Bretton Woods, with only minor innovations (Future of Money—Compilation of Papers 2019). It would be to conclude as long as will take a time to understand how functioned fiat money system after Bretton Woods collapse then it will be acceptable and understandable to implement and use Modern monetary theory. The shift in interest pre-dates the COVID-19 crisis, but the virus has given MMT a huge boost. Governments around the globe have been quick to dramatically expand their budgets in response to the crisis, with deficits of 10% of GDP becoming routine. Modern Money Theory (MMT) is now discussed in all the major newspapers and by politicians around the world.

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COVID-19 outbreak, however, brought on light as follows: i. The COVID-19 vaccine has to be available for all residents of any country regardless of social, national social, or other status and independently the person insured for the medicine is not paid. Such an approach has never been before, all countries practically perform the same and it can also be concluded that the treatment of the disease is treated according to the common good principle. ii. COVID-19 brought the workers who are in the global level. Globalization meant not only new markets but, more importantly— through the global labor arbitrage—the appropriation of huge surplus economies from the overexploitation of low-wage labor in the periphery that ended up in the financial coffers of multinationals and wealthy individuals in the rich countries. iii. At the micro-level or at the level of enterprises (companies) in the future, profit is not the only goal, but the goal is social responsibility, primarily for the sake of the environment and because the existing corporate governance system does not ensure the development of the overall society. iv. At the macro level, there are more ideas for changing the system as well as the system of measuring performance and condition. Thus, COVID-19 has led to the absurdity that the actors of the health system to the limit and the ability of staff—primarily doctors and nurses—as well as equipment directly contribute to the possibility of the functioning of the economy, while some parts of the non-financial sector (for example transport) do not operate in their capacity, and should finance, general and joint affairs, including health care. There were wrong and inappropriate politics in the last decades hence a number of scientists and great thinkers already submitted attentions, as Anne Case and Angus Deaton concluded “American capitalism is not serving most Americans,” due to “two-thirds of the population – are dying younger and struggling physically, economically, and socially” (Deaths of Despair and Future of Capitalism). Paul Krugman recently summarized “2020 was the year Reaganism died.” These changes could lead to a conclusion as the Schumpeter’s self-destruction capitalism, but they inevitably lead to a new social

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and economic system as Schumpeter’s socialism. One of the greatest economists ever, Joseph Schumpeter, once wrote that capitalism would perish not because of “the weight of economic failure,” but rather because its “very successful” in pursuing its narrow economic ends, had undermined the sociological foundations of its existence. Capitalism, Schumpeter exclaimed, “‘inevitably’ creates conditions in which it will not be able to live and which strongly point to socialism as its heir apparent.” In any case, it should be looking for a new system. In parallel, most others are looking how to save the system—as Keynes did it in the 1930s—but that would be the same as the search for a new system as they have together the path to avoid revolution. The claim to save system, from the West perspective is based on the huge shifts that happened in the last decades or so as follows: i. Neoliberalism as an ideology and economics school of thoughts theoretically and empirically failed. The main goal was the defense of concentrated corporate capital and class dynasties, which were portrayed as representing free-market competition and entrepreneurship. The very virulence of neoliberal anti-socialism meant that it represented the drive to a complete market privatization of social life. In Margaret Thatcher’s London and Ronald Reagan’s Washington, figures like Hayek and Friedman became the symbols of the neoliberal era, sometimes called the age of Hayek. In addition, the Nobel prize in economics was controlled from its inception by ultraconservative neoliberal economists and seven members of the Mont Pèlerin Society, including Hayek, Friedman, Stigler, and Buchanan received the prize between 1974 and 1992, while even mildly social-democratic economists were all but excluded. ii. State was changed—the state too became subject to the financialization policy, shifting its overall role to protecting the value of money. In the crisis labeled Great recession (2008), almost all big banks and corporations were bailed out, but the population was not. iii. Externalities of this capitalist system exceed any future economic benefits. It should emphasize that from the last two decades and further the externalities of this the irrational system, such as the costs of war, the depletion of natural resources, the waste of human lives, and the disruption of the planetary environment, now far exceed any future economic benefits that capitalism offers to society as a

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whole. Consequently, the accumulation of capital and increasing of wealth are more occurring at the expense of an irrevocable social divides that govern conditions of human life everywhere. iv. Economics laws, some of them, failed what will be provided in some details later. As a consequence existing parallel double economic system—one based on fiat money and another with economic tools implementing before ended Bretton Woods—economic laws—some of them—failed (Domazet, 2015). John Maynard Keynes almost single-handedly “saved” capitalism from the twin dangers of “revolution” and “orthodoxy” (By which he meant the economic disaster that was nourishing fascist movements everywhere in the 1930s). Revisionist history has tried but must ultimately fail to erase the truth of this. The fog of ideology may persist a while longer, but it will eventually lift. It is an insult to the intelligence of any serious student of economic history to place Keynes’ world-historical works of economic and philosophical genius next to the ponderous, self-referential mathematizing of the neo-classical school. Much less the failed, useless meanderings of Whatchamacallit Economics. Granting the validity of such a comparison would be like taking the time to weigh Ayn Rand’s view of the history of philosophy—which was that the only two philosopher’s worth reading were herself and Aristotle. It is breath-taking to think that people as influential as Allen Greenspan and Paul Ryan are adherents of this cultic caricature of a “philosophy” (Pierce 2013).

11.2

Post-Keynesian Economics

Post-Keynesian economics (PKE) is an economic school of thought, based on ideas and thoughts of John Maynard Keynes (1883–1946), Michal Kalecki (1899–1970), Roy Harrod (1900–1978), Joan Robinson (1903–1983), Nicholas Kaldor (1908–1986), and many others, but Hyman Minsky (1919–1996) was the main who contributed established the PKE’s new economic theory. PKE also reject neoclassical economics, hence it is necessity to build a new economic theory, in order to cope with modern economic challenges fields ranging from short-run macroeconomics (unemployment, economic output and inflation), long-run macroeconomics (growth and

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distribution), monetary economics, finance and the international monetary system to microeconomic approaches to the theory of the firm, theory of consumption, exchange rate theory, financialization, and much more. Minsky had a great role in above mentioned, but also behavioral economists of post-Keynesian tradition as well as the Modern Money Theorists and their focus on the institutional framework of government, banks, and central banks. Minsky liked to call his approach “financial Keynesian,” rather than “Post Keynesian” because this better reflected his extensions of Keynes’s General Theory. All over the globe many are proclaiming the “return of Keynes,” but I think that Minsky would find many of the analyses invoking Keynes’s name to be deficient. Thus, they have turned against “efficient markets” beliefs that asset prices always reflect fundamentals. Many have called for some re-regulation of the financial sector. And most economists and policymakers have become “Keynesian in the trenches,” arguing for fiscal stimulus packages. Minsky would welcome these developments, but he would want more. Minsky always insisted that there are two essential propositions of his “financial instability hypothesis.” The first is that there are two financing “regimes”—one that is consistent with stability and the other that subjects the economy to instability. The second proposition is that “stability is destabilizing,” so that endogenous processes will tend to move even a stable system toward fragility (Wray 2011). Heterodox economics though post-Keynesian economics is the study of social creation and social distribution of society’s resources while neoclassical economics is the study of the allocation of scarce resources among unlimited wants. Heterodox economics is quite opposite from orthodox economics but for most readers it is not easy to understand differences among the two economics as well as their protagonists.1 Effective demand is one of the main parts of as it thought that economic activity is demand-driven as well as it searches for full employment and full utilization of capacities, because the capitalism as a system do not ensure it. The principle of effective demand, and the claim of its validity for a monetary production economy in the short and in the long run, is the core of heterodox macroeconomics , as currently found in all the different strands

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of post-Keynesian economics (Fundamentalists, Kaleckians, Sraffians, Kaldorians, Institutionalists) and also in some strands of neo-Marxian economics, particularly in the monopoly capitalism and under consumptionist school. … The principle of effective demand, and the claim that economic activity in a monetary production economy is demand determined, is therefore the core of heterodox macroeconomics, as currently found in all the different strands of post-Keynesian economics. From these considerations it follows that the long-run level of output and employment in a monetary economy is not determined by available resources, but by effective demand. And an important part of effective demand, investment, is determined by monetary criteria: Entrepreneurs have to achieve a minimum rate of return on monetary advances, which is given by a monetary rate of interest. In a monetary economy, Say’s law is therefore replaced by the principle of effective demand. Aggregate spending determines output and employment while investment, which itself is determined by monetary criteria, determines saving. (Hein 2015)

Employment, according to PKE, is not determined in the labor market but rather labor demand is determined by aggregate demand in the goods market and not by the real wage rate. The labor market, however, determines nominal wages and therefore nominal unit labor costs. Full employment is the debate that has been occupied by economists for years. Given that the main idea in economics whether it is microeconomics or macroeconomics is efficiency—getting the best out of what you have available, here is how to implement PKE’s full employment. Although there are many disputes, there is a consensus among economists that at the macroeconomic level, the “efficiency frontier” is commonly summarized in terms of full employment. Despite some disputes, the concept of full employment is a central focus of macroeconomic theory, therefore using the available macroeconomic resources such as labor to the limit is a key goal of macroeconomics. More important, the macroeconomic challenge is to maintain full employment in parallel achieving price stability. Full employment is also associated with structural rigidities related to a number of undesirable consequences, therefore very often central banks and national governments have resisted it. There are some disputes on disputes in private and public sector, but public sector serves a different purpose than the private sector activity hence they require different criteria.

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Inflation. These have an influence on the general price level and hence inflation, as well as on income distribution. In contrast to orthodox economics, the level of prices is not determined by the level of the money supply. The rate of inflation is not determined by the growth rate of the money supply, therefore, PKE does not regard inflation as being a monetary phenomenon. Instead, inflation is regarded as the outcome of the unresolved distributional conflict. This conflict is caused by conflicting claims over the distribution of income between the main social classes, wage-earners in different industries or sectors, entrepreneurs, and rentiers (i.e. people who earn capital income from property or financial assets), and the foreign sector in an open economy. The Bank of England, the world’s oldest central bank, recently has explained, central banks do not control the money supply, nor do they have the tools to forcibly choke off an expansion of bank credit to fight inflation. Profit and the dynamic, the pursuit for it is at the heart of capitalism as a dynamic system and investment and technical change lead to growth. Growth dynamics are regarded, however, as strongly influenced by the short-run economic performance which is mainly driven by aggregate demand. Temporary adverse shocks may therefore reduce potential output permanently, just as well as a high unemployment rate might push up the non-accelerating inflation rate of unemployment (NAIRU). Debt outstanding is a great challenge for a number of countries. A global collapse in economic activity during the COVID-19 pandemic has significantly increased the risk of debt distress in many countries, pushing the poorest ones to the brink. In response, various international organizations have unveiled a number of initiatives to forestall circumstances necessitating between responding adequately to the public health crisis and servicing existing debts (Subacchi 2020). Debt relief is a very important issue that is already well theoretically and practically prepared in current circumstances (Domazet 2017). Interest rate, according to post-Keynesians embraced an endogenous money approach (Basil Moore the introduced term “horizontalism”) therefore both the supply of money as well as the supply of reserves are horizontal at an exogenously set interest rate. Contrary to that, the monetarist “verticalist” approach saw the money supply as exogenous (set by the central bank) and the interest rate as endogenously determined by the market. Marc Lavoie has revived a circuit approach to money based on earlier work by so-called Franco-Italian circuities approach, which

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revived the real bills doctrine (money is created to finance the production process). Above is consistent with the monetary theory of production (production begins with money to produce commodities to sell for more money) adopted by the three great “fathers” of the various strands of heterodoxy: Marx, Veblen, and Keynes. Both approaches rejected the textbook deposit multiplier story, insisting that money is created ex nihilo (“out of thin air”). Central banks provide reserves used by banks for clearing purposes (and, in the horizontalist story, they must always accommodate the demand to hit their overnight interest rate target). In both approaches, the government’s role is downplayed (Wray 2020). Government deficits do not drive interest rates up (as in the crowding-out and loanable funds stories); all else equal they put downward pressure on the overnight interest rate as they lead to net credits of bank reserves. This was Mosler’s original insight: bond sales drain excess reserves to help the central bank keep interest rates from dropping below the target. It could be true that if the treasury chooses to issue bonds of a particular maturity that markets do not want to buy it could push up rates of that maturity. But that is a “debt management” mistake, not an inevitable outcome of deficits. Once the central bank pays interest on reserves, bond sales are no longer necessary for the purpose of maintaining target rates. (Wray 2020)

Interest for PKE is raising worldwide as mainstream economics has no appropriate answer on crucial questions solving the economic and social crisis also in Croatia first book on PKE was published in the year 2014 (Domazet 2014).

11.3

Modern Money Theory

Money had always one of the main roles in development and forming national, economic, and societal relations. Nevertheless, it is not necessary, here to explain the history of money. Modern Money Theory (MMT) is the main part of post-Keynesian economics. MMT is a relatively new approach to macroeconomics that focuses on building an understanding of the operation of sovereign currency systems and on developing a policy framework based on that understanding, especially after fiat money is established. Modern monetary theory, MMT, just describes the new system that most countries in the world live under and

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have lived under since 1971, but it is not clear why and how most of small open economies are forced to use the neoliberal monetary system despite existing fiat money. In a fiat currency system, the currency has legitimacy because of legislative fiat: the government normally explains that’s the currency and then legislates it as such. The currency has no intrinsic value, but all tax obligations are denominated in and have to be extinguished with that currency therefore that gives it value as well as motivates to use the currency that the government suggests. When it is understandable that the government has the monopoly of issuing that currency, but more importantly, according to MMT government then can never be short of that currency. The national government can never run out of money, it means it doesn’t need to borrow money to finance the government, but all the taxpayers are obliged to pay taxes only just and exclusively by that currency. As a precondition collusion government is not constrained in its spending by a need to raise revenue. The origin of the MMT is going back is the 1990s discussions on PKE, but the establishment of the new theory belongs to several economists as follows: i. Warren Mosler, who laid out the basic principles of the analysis of a sovereign currency and new taxes view on sovereign’s currency. ii. Basil Moore, associated with the horizontalist view of endogenous money. iii. Paul Davidson, among the “fundamentalist” Keynesians. iv. Bill Mitchell, who developed a “buffer stock” approach to unemployment. v. Mat Forstater, economic historian. vi. Pavlina Tcherneva, who wrote a review of Mosler’s paper. And vii. Randall Wray, professor, who made the greatest contribution in establishing MMT as theory, practice, including the number of books, studies, presentations, and speeches worldwide, as well as recently testimony before US Congress committee on MMT useful. This theory borrowed the main issues from, Keynes, Marx, Innes, Schumpeter, Lerner, Minsky, Godley, and Knapp. Today there are thousands of economists worldwide who support and belong to the MMT, but the Levy Economics Institute of Bard College,

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founded in 1986, as nonprofit, nonpartisan, public policy research organization (NY, US) is the world center of all PKEers and MMTers. Given the economic and financial point of view, MMT is a main part of the theory in Keynes’s monetary tradition that includes great thinkers such as Hyman Minsky and Wynne Godley, but it describes how modern work of governments and central banks. In Croatia there are also a number of researchers and economists as PKE and MMT followers, but among them, it is necessary to mention Stjepan Zduni´c, Dubravko Radoševi´c, and Tihomir Domazet, and recently Grdeši´c and Sajter. The most important characteristics of MMT, based on the economic and the financial situation facing any national government with a sovereign currency that is entirely different from that faced by a household, a firm, or a government that does not issue a sovereign currency, hence MMT provides assurance that sovereign currency issuer: 1. does not face a “budget constraint,” 2. cannot “run out of money,” 3. can always meet its obligations by paying in its own currency, and 4. can set the interest rate on any obligations it issues. MMT also provides assurance in the world, which is changing in fundamental ways, and the actions to be taken soon will be critical to lay the groundwork for a sustainable, secure, and prosperous future. It is also important that MMT revives the State theory of money (or Chartalism) and integrates it with a variety of heterodox approaches to macroeconomics such as endogenous money, functional finance, budgeting, financial instability hypothesis, and the sectoral balances. Most essentially of MMT are as follows: i. A government that issues its own sovereign currency can never run out of money and, to pay for any debts by creating more money. ii. Inflation will not kick in if such a government runs a budget deficit, as long as there is spare productive capacity in the economy. iii. Taxes do not fund public spending, meaning a government does not need to tax first in order to spend later. The real process at play is the opposite, however, because governments spend on goods

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and services, and then adjust tax rates to manage demand in the economy. It is interesting, while mainstream economists do not support MMT, it is not clear why and where they disagree, because central banks everywhere are abandoning old conventions and funding fiscal deficits by buying government bonds (that is often called “printing money”) therefore it seems as they use MMT approach such as run deficits to maintain full employment and fund them by printing money. The world is on crossroad or/and the cliff and current situation leads to the conclusion that a new global economic system has to be based on MMT. There are a number of resilience against MMT, but all united in opposition to it what all have in common is that what their critique has nothing to do with this new theory. The main goal of macroeconomics is using the available macroeconomic resources including labor to the limit, however, the discussion is what is the real limit. In that sense, the great challenge of macroeconomic is to achieve and maintain full employment as well as price stability. The latter is the way to achieve prosperity and welfare by ensuring real output. In addition, it should underline the key determinants of these aggregate outcomes: (i) economic growth; (ii) full employment; and (iii) the rate of inflation, what is a framework of the monetary system of the nation (government). All economies use currencies as a way to facilitate transactions. The arrangements by which the currency enters the economy and the role that the currency issuer, the national government, has in influencing the outcomes at the aggregate level, is a crucial part of macroeconomics. Modern Monetary Theory (MMT), develops a macroeconomic framework that incorporates the unique features of the monetary system. (Mitchell et al. 2019)

Modern monetary theory and some old theory of money are complementary in that both are endogenous theories of money and they both reject the quantity theory of money. It means that inflation or deflation is not dependent on the decisions by central banks in creating credit money, because the demand for money drives the supply. Therefore, the banks make loans and as a result, deposits and debts are created to fund the

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loans, not vice versa, hence MMT recognizes the role of money in the modern (capitalist) economy while as Milton Friedman and his supporters of neoliberal economics suggest different like “helicopter money.” It should remind that under capitalism money is the representation of value and thus of surplus value. In M-C-P-C’-M’, M can exchange with C because M represents C and M’ represents C’.2 The State, therefore, comes in first of all as the authority of law which enforces the payment of the thing which corresponds to the name or description in the contracts. But it comes in doubly when, in addition, it claims the right to determine and declare what thing corresponds to the name, and to vary its declaration from time to time – when, that is to say, it claims the right to re-edit the dictionary. This right is claimed by all modern states and has been so claimed for some four thousand years at least. (Keynes 1936)

MMT strongly suggests that the quantity theory of money as introduced earlier by Friedman, which dominated in the early 1980s, is wrong, because governments and central banks cannot determine boom and boost by controlling the money supply. The evidence of that is quantitative easing (QE) programs adopted by major central banks to try and boost the economy confirms that and since the crisis in 2008 the central bank balance sheets have climbed the highest amount ever but without results: real GDP growth has not and neither has bank credit growth. Capitalism is a monetary economy. Capitalists start with money capital to invest in production and commodity capital, which in turn, through the expanding of labor power (and its exploitation), eventually delivers new value that is realized in more money capital. Thus, the demand for money capital drives the demand for credit. Banks create money or credit as part of this process of capitalist accumulation, but not as something that makes finance capital separate from capitalist production. MMT/Chartalists argue that the demand for money is driven by the “animal spirits ” of individual agents (Keynesian) or by the state needing credit—Chartalist (Roberts 2019). After multiple rounds of trillions of dollars of QE, it should now be obvious that so far as inflation goes, there is no difference between leaving reserves in banks or draining them through bond sales. Reserves remain within the banking system and cannot get out to cause inflation havoc— all the excess reserves can do is to push the overnight rate to zero or

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the support rate paid by the central bank. QE was effectively a duration trade—it reduced the maturity of the government’s outstanding debt— from longer-term bonds to reserves, lowering bank earnings. To the extent that central banks bought troubled assets (i.e., uninsured mortgage-backed securities) this could have made an insolvent bank solvent—but unless the government was ready to force such banks into resolution, this made very little difference to their operations. In short, as we argued from the beginning, QE was not likely to boost lending and spending, so by itself asset purchases by the central bank would not be inflationary (cursive by TD). (Wray 2020)

Modern states are, however, essential to the reproduction of money and the system in which it circulates. But their power on money is limited, hence Schumpeter said that the limits are clearest in determining the value of money. Therefore, the state cannot print any numbers on its bills and coins, because it is determined by countless price-setting decisions by mainly private firms, reacting strategically to the structure of costs and demand they face, in competition with other firms. Then it is necessary to conclude that the value of state-backed money is not stable, which is acknowledged by the Chartalist theory. According to it, the main mechanism by which the state provides value to fiat money is by imposing tax liabilities on its citizenry and proclaiming that it will accept only a certain thing (whatever that may be) as money to settle those tax liabilities. Randall Wray, the most influential by knowledge and one of most active writers on MMT, however, admits that if the tax system breaks down “the value of money would quickly fall toward zero.” When the state’s creditworthiness is seriously questioned, the value of national currencies collapse, and demand shifts commonly to the gold that is from history always a hoard for storing value. Very recently the gold price jumped to inappropriate levels as the financial crisis started (2008) and another case was in early 2010 when the debt crisis of the southern Eurozone deteriorated stance.

11.4

Endogenous Money Theory

Most of the heterodox authors argue that the most important contribution of post-Keynesian economics and MMT as well is its notion of endogenous money. The study of how this endogeneity is achieved has given rise to a protracted discussion between the structuralist and the horizontalist conceptions of endogenous money. The structuralists argue

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that money is endogenous because banks can avoid the constraints of compulsory reserve requirements imposed by the central bank. The horizontalists argue, on the other hand, that money is endogenous due to the fact that the central bank provides all the needed reserves at the short-term interest rate of its choice. Hyman Minsky, the first name of post-Keynesianism, had also contributed in creating endogenous money theory but in that sense is an important contribution by Nicholas Kaldor and Basil Moore among others. Therefore modern central banks implement monetary policy so they announce an explicit target short-term rate (usually the overnight rate), “as well as a corridor delimited by lending and deposit facilities, and supply a number of reserves that will equate the demand for reserves at the target interest rate. Horizontalists argue that this was already the case when central banks were claiming to be targeting monetary aggregates. While there is no doubt that financial innovations are important, reverse causation appears to be a more relevant justification for endogenous money and provides a clearer break with the mainstream monetary theory” (Lavoie 2020). In any case, endogeneity meaning endogenous money is the most important part of MMT. Endogenous money is one, a particularly important segment of money, i.e. today money is created in a completely different way than before and differently than many books and authors describe: (1) instead of banks taking deposits when households save and then grant them loans, banks create deposits by providing loans and (2) under normal conditions, the central bank does not determine the amount of money in circulation nor is central bank money multiplied into even larger loans and deposits. It should be known that, in addition to the state, other money can be created by banks as well as by keeping surpluses in the current account of the balance of payments. As it stands out, these three ways are also known as endogenous money (Domazet 2016). Endogenous Money and the Circuit—An Entry for post-Keynesian economics into MMT is possible to find in the French-Italian PK circuit approach what is especially particularly important in order to understand that the finance for spending household must come from somewhere. In discussions on how to finance the typical neoclassical source of finance is saving, but the problem is raising when saving has to be generated by someone another. Therefore, it should conclude, when the circuit begins with a bank loan to finance the purchase of commodities (to be used

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to produce commodities) all problems are resolved. Spending and the creation of “money” in the form of a bank deposit are linked. In parallel, it is known that the banks must meet reserve requirements, and banks use reserves for clearing. Therefore, then “horizontal reserves” come into play and the central bank that administers an overnight interest rate target must supply reserves on demand, otherwise, it would lose control of the interest rate. In addition, a central bank accommodates the demand for reserves, but this demand is highly interest-inelastic, and there is no way for it. It seems it is generally accepted that modern central banks operate with an overnight interest rate target and accommodate bank demand for reserves. The money of account, at least today, is virtually always a state money of account—a “dollar” chosen by the authorities. It should repeat that MMT’s approach is based on the notion that the modern central bank sets the overnight rate target (that is in the case of US Fed from 1994). the Fed did not announce its target, so the market had to find it; since the Fed now announces any changes to its target, the Fed funds rate moves quickly to the target. Some fluctuation, however, still occurs because some institutions that hold reserves do not have all information. All of this is consistent with the post-Keynesian endogenous money and horizontal views. What Mosler introduced was “the idea that we should view treasury bond sales as part of monetary policy, that is, as a reserve drain instead of a borrowing operation. MMT argues that all treasury spending takes the form of a credit to bank reserves, with the receiving bank then crediting the deposit account of the recipient of the government’s spending. In a fractional reserve system, this creates excess reserves. Before the central bank paid interest on reserves, systemic excess reserves would place downward pressure on the central bank funds rate and, if that were not relieved, the rate could fall toward zero. Bond sales led to debits of bank reserves, relieving that pressure” (Wray 2020). It is interesting to research that leads to the conclusion that endogenous money views were common or even dominant until Keynes’s General Theory. After the WWII both Keynesians and the monetarists adopted the exogenous money and deposit multiplier model. A revival of endogenous money can be traced from Nicholas Kaldor and the Radcliffe Committee (1959), the work of John Gurley and Edward Shaw in the late 1950s, James Tobin (1963), and Minsky (from the late

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1950s). Moore and other horizontalists interpret Keynes’s treatment of money in the General Theory as exogenous (fixed by the central bank) and claim that his liquidity preference theory is inconsistent with endogenous money. I integrated Keynes’s liquidity preference theory with his endogenous money approach. I argued that while chapters 13 and 15 can be interpreted along the lines that led to the orthodox ISLM analysis (with an exogenous money supply), Keynes’s 9 chapter 17 approach to asset pricing provides the rigorous exposition of his liquidity preference theory and this is perfectly consistent with endogenous money. (Wray 2020)

In the modern economy, most money takes the form of bank deposits. Those bank deposits, however, are created is often misunderstood, due to the principal way is through commercial banks making loans. The Bank of England, the oldest central bank, explains that whenever a bank makes a loan, it simultaneously creates a matching deposit in the borrower’s bank account, thereby creating new money. The reality of how money is created today differs from the description found in some economics textbooks: • Rather than banks receiving deposits when households save and then lending them out, bank lending creates deposits. • In normal times, the central bank does not fix the amount of money in circulation, nor is central bank money ‘multiplied up’ into more loans and deposits. (Bank of England—Monetary Analysis Directorate 2014)

It should note that also exists state money and credit money (Domazet 2016). State money is related to the attitudes and explanations given by Knapp (1924), Keynes (1930), and Lerner (1947), while credit money is tied to Schumpeter (1934) with which the explanation of endogenous (and exogenous) money is associated, but endogenous money is more attached to French and Italian economists who are the creators of the money roundabout theory, and endogenous money is also tied to Mine. Innes (1913, 1914) explained the integration of state money and credit money, although his work was forgotten.3 Post-Keynesians and to a lesser extent, institutionalists are the creators of the revival of modern endogenous money, which was present as early as the nineteenth century, although most modern endogenous authors do not explore this in terms of linking it to credit state money.

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11.5

Avoiding Fiat Money

Modern economies, including European union member states whether are part of the Eurozone, are based on fiat money where central banks issuing this fiat money. That is also explained by European Central Bank.4 All the European countries have used the same, whether they are EU member or not, they use fiat money. Recently also Court of Justice of the European Union (ECJ) confirmed the euro fiat currency as legal tender status, but it is not necessary to go in further explanation on this issue. The ECJ’s Opinion underscores that monetary policy regarding “the creation and functioning of the single currency, a legislative dimension relating to that single currency, which comprises the definition and regulation of its status and legal tender” (143) is the EU’s exclusive competence. Only currency issued by a central bank is legal tender (October 1, 2020). More important is, however, from the perspective of this study, how the fiat money had continued, after the Bretton Woods collapse, using as previously representative money although they are not compatible. If the fiat currency “has no intrinsic value” and “the paper used for banknotes are worthless” and modern money, like Euro, “has been based solely on trust” as well as on “strength, potential, and efficiency of the functioning of a particular national economy” the most important question then is raising, how the currency is valuing. Above explanation, on inappropriate using some part of fiat money, the approach could lead to the conclusion that this is not valuing of the currency rather than valuing, in the best case, the national economy, but without any agreed criteria. Previously enacted assume is more than dramatic because it is a great difference between currency and national economy or in other words economic and financial decisions based on this data are not valuable and the right way. It is, therefore, necessary to find out the answer why was the abandonment of the implementation of fiat money? Further research is leading to assessment or doubt that the stronger or the larger economy could use some type of enforcement to influence on another currency meaning smaller economy. The consequence is easy to discover. Before any further explanation, there is no evidence of serious studies on this issue.

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Fiat money is not fully implemented, and in parallel, the representative money used before until Bretton Woods collapse is still tried to use, but the systems are not compatible and couldn’t co-exist. With the collapse of the world monetary system, i.e. Bretton Woods, therefore, with the collapse of the gold standard (1971), the basis for the emission of additional amounts of currency money is fiat money itself, so the emission of money has since been based solely on trust, i.e. on the law. Modern money is based on trust in the strength, potential, and efficiency of the functioning of a particular national economy. Fiat money becomes the basis for banks’ credit money emissions. Primary money emissions in modern conditions become a key temptation for central banks and the economic policies that lean on them. Therefore it should remind, as mentioned earlier, some economic laws failed, mostly due to quantity monetary theory no longer is valid, as follows: (i) S (national savings) no longer determines I (Investments); (ii) Phillips curve no longer applies; (iii) Say’s law doesn’t work; (iv) Modigliani-Miller’s theorem is not valid and (v) The labor market (labor force) is not working, and (vi) The market has collapsed, for example, with the price of oil, and less and less can be talked about the efficiency of market action, which in particular came to the force in the crisis caused by COVID-19. It is expected further studying whether some of the economic laws that failed are in connection related to them (not-)fiat money implementation, like the Phillips curve. Another view of avoiding fiat money implementation could lead to analyses of introducing the Euro as a common currency in the Eurozone and its influence on member states. According to one study that analyzes euro implementation of the effects of the introduction of the euro on prosperity for the entire period since the year of introduction—1999 in all countries—until 2017 (the effects on prosperity are determined by adding the annual percapita figures and multiplying the resulting amounts by the average national consumption rate of the relevant Eurozone country) in the preintervention period and result of a selected member state (Gasparotti and Kullas 2019). 20 years since its introduction and the euro remains controversial. The study has used the synthetic control method to analyze which countries have gained from the euro and which ones have lost out.

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In Italy, therefore, the introduction of the euro led to a drop in the prosperity of around e 74,000 per capita or e 4.3 trillion for the economy as a whole, over the period 1999 to 2017. For France, the loss amounts to almost e 56,000 per capita or e 3.6 trillion respectively. Germany achieved an increase in prosperity of e 23,000 per capita and e 1.9 trillion respectively, while the Netherlands achieved an increase in prosperity of e 21,000 per capita and e 346 million respectively. Another view of analysis could lead to the conclusion that both avoiding fiat money implementation and euro introduction on this manner in the greatest way contributed that EU27 in the period 2009– 2020 has achieved only economic stagnation because real BDP increased only 0.2% averaged per year (or cumulative just 2.4%).

11.6

MMT in Eurozone

The starting point of this issue is fiat money implementation, as it is explained in previous section. In order to find out comparability, there is a similarity between EUEurozone and the United States in currency using as well as between the individual US states and Eurozone member states, however, the latter are lacking the policy space. The reform of the Eurozone could be executed by easing the fiscal deficit rules because installing a fiscal authority for the time being is not a real option. The idea that the European economy can prosper by the ECB’s interest rate and nothing else is both theoretically and empirically wrong. It means a macroeconomic policy based on ECB’s set of interest rates will no longer have a large effect on investment decisions. Therefore, MMT suggests that fiscal policy should be used focusing on government spending but in the EU this new economic policy requires new rules concerning fiscal deficits and public debts. From an MMT point of view, fiscal deficits are nothing else than an increase in the nominal amount of tax credits held by the private sector, while the public debt is the total number of outstanding tax credits in the private sector. More important, since the government does not “payback its debt” as private borrowers do but only promises to take back its own money in the form of tax payments, fiscal deficits, and debts should understand in this MMT’s view. The next explanation of current rules are as follows: ECB as the currency issuer faces no purely financial constraints and no solvency risk

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while Eurozone member state as the currency users, on the contrary, does face financial constraints and is subject to default risk—related to the sectoral balances applying to the fiscal deficit rules. These rules have to understand that income equals expenditure, therefore any surplus of income over expenditure by three imageable sectors of the economy: (i) private, (ii) public, and (iii) external—must be balanced by deficits what is explained by the equation below:   Sp−I = (G−T) + CAB where: Sp = private saving; I = private investment; G = government spending; T = taxes; CAB = current account balance. Currently, the ECB expansionary policy is easing the financial constraints for its member states, but the monetary policy design is biased to the disadvantage of external deficit members as the fiscal deficit rules heavily constrain their sustainable policy space. Consequently, this leads to a lack of aggregated demand resulting from high rates of unemployment and output gaps, which is unacceptable. EU monetary policy has to be improved by buying Eurozone member state government bonds by ECB, but by default the risk was basically zero. The first step in concrete EU monetary reform, in line with MMT, has to be buying EU agreed on amount individual member states bonds related to the Next Generation EU of e750 billion temporary recovery instrument by ECB instead of financing by the recovery borrowing on the markets by European Commission. ECB policy provides some easing to its member states through QE obviously it is required reform monetary policy to fix the fundamental flaws, but because of the requirement by the socio-ecological transition, it would be inline with MMT. In respect of applying in Eurozone, it should study this possibility as follows: “MMT argues that central banks should permanently buy bonds from the government. But this way of financing government spending would come at the high price of giving up on monetary policy. While the central bank could pay interest on reserves to keep its power, this would be equivalent to government borrowing and would save nothing. Second, according to MMT, governments do not need to issue bonds to fund themselves. However, because MMT has given up on monetary policy, it is forced to manage the case of excess demand in other ways.

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It accomplishes this by altering the supply of reserves to banks through borrowing in the bonds markets, which in its theory leads to a change in short term interest rates and thus dampens consumption and investment. However, this analysis is deeply flawed and disproven by the actual behavior of central banks. In real life, during and after a government bond auction, the supply of reserves remains constant, and hence short-term interest rates do not increase and can therefore not dampen investment and consumption in case of excess demand. Third, proponents of MMT overlook the political economy of permanent monetary finance in their endeavor to side-line central banks and to place the power to create, allocate, and spend money permanently in the hands of politically elected governments” (Schlotmann 2020). The next option is issuing tax-backed bonds especially in the case of increasing debt Tax-backed bonds would be similar to standard government bonds except that they would contain a clause stating that if the country issuing the bonds does not make its payments—and only if the country does not make its payments—the tax-backed bonds would be acceptable to make tax payments within the country in question, and would continue to earn interest. (Pilkington and Mosler 2012)

In the circumstances of increasing sovereign debt, it is very important to understand here that modern money can be regarded as a tax credit. This means that the euro is purely and simply a promise by the state to accept it in the future for payments to the state. Therefore, most of these payments, modern money can treat it as tax credit and money is a creature of law as the state defines the currency, and it accepts payments via its monetary system. Hence, users accept the money in order to pay tax. Other users, however, also need it for tax payments and would exchange goods and services or assets such as property or shares for the money. It follows to conclude that modern money is not a scarce resource. It should remind that under the gold standard, things were rather different. The fact that many current economic-policy assumptions are still based on this old model of the gold standard is a self-imposed restriction that keeps society from using all the economic policy options at its disposal. This means that the state, as the creator of money, puts the money into circulation in its own currency first in the form of tax credits before we

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use it to pay our taxes later. Although this understanding is fundamental, it supersedes the widespread view that tax payments fund state spending. In a modern monetary system, taxes are not needed to fund state spending. The state first spends money that it practically forces acceptance of through taxes. State spending is not technically limited here. In other words, the state can print as much money as it deems sensible. As it creates the money, it doesn’t rely on an income before it spends anything. Moreover, this does not apply, or applies only to a limited extent, to the eurozone countries. (Ehnts 2020)

In any case, it is necessary to find out the solution for Eurozone member state, as this study tries it here.

11.7 MMT in European Union: The Case of Croatia To consider MMT implementation in European union, here are intentionally selected two of their members: Italy and Croatia. Italy is one of the oldest member and the third-largest economy, and Croatia is the youngest member and small open economy currently in ERM2 status. They both have in common that in their case convergence totally failed, as shown data: i. Croatia’s index relatively developed against average EU27, measured by GDP/s in 1986 was 85.1, but in 2020 it was 59.5 (that is decreased 30.1% points). ii. Italy’s index relatively developed against average EU27, measured by GDP/s in 1986 was 117.3, but in 2020 it was 91.3 (that is decreased 22.9% points). Both Croatia and Italy have the worst above shown economic results among EU27 member states in the period 1986–2020. There is not any study to put in place reasons for that. From the perspective of this study point of view the preliminary conclusion led to conclusions are that (i) model success in one country may couldn’t be in another and (ii) EU monetary policy and euro implementation (in case of Croatia that is peg currency linked to euro) contributed significantly to this economic results for both member states.

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It should underline that Croatia has the capacity to issue Eurobonds, which was strengthened when Croatia joined the ERM2 on 10 July 2020. The earliest date for euro adoption, which requires two years of ERM participation is 1 January 2023. There is an official assessment by ECB that “the Croatian kuna5 traded under a managed float and its exchange rate vis-à-vis the euro displayed low volatility” (Convergence Report 2020). Immediately after that Croatia has issued an 11-year, e2bn Eurobond with a coupon of 1.5% and a yield of 1.643%, on June 11, 2020. The next step to be done is to redeem this bond by ECB via CNB. Under ERM2 transitional monetary arrangement agreed between Croatian central bank and ECB, Croatia government has power to issue the Eurobond. In Croatia, more precisely in Zagreb and Sisak Moslavina County in 2020 two earthquakes happened with huge consequences what also is agreed by EU. To rehabilitate this natural catastrophic event Croatia under ERM2 has power and capacity to issue bonds, which will be bought by ECB via CNB. Croatia also options issuing tax-backed bonds particularly in case of increasing debt, because of rehabilitation of catastrophe in terms of earthquakes. Issuing and redeeming tax-backed bonds would be like standard government bonds as explained earlier. These circumstances related to implementation of MMT in EU clearly led to the conclusion that ECB has an obligation from Eurozone member states to buy bonds related to cover the fiscal deficit in the amount to be agreed. This bond is just a government debt which it owes to itself, hence it is easy to conclude that MMT suggests it could be deleted from the balance sheet of the central bank by offsetting the accounts payment/claim of the government and the central bank.

11.8

Conclusions

MMT as well as post-Keynesian economics narrative fit within the development of the mainstream macroeconomic thinking. The global financial crisis (2008), however, was the catalyst in bringing the MMT story toward the mainstream, but COVID-19 outbreak (2020) and economic crisis has even more influences. One of the essential elements of the rethink was the fiscal deficit and its constraints on economy and solution are leading to MMT.

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The endogenous money theory is the main part of MMT that is quite different from most recently textbooks related to the money creating. There is a long literature that does recognize the “endogenous” nature of money creation in practice (see, for example, Moore, Lavoie, Tobin, Wray, Dylan, Domazet and others). Huge problems and obstacles in functioning financial system emerged after abandoning Bretton Woods system and applying for the fiat money, however, the economic and financial system continues to operate as there was not any change. Next issue related to the MMT is possibilities on its implementation in EU. It is well known that Eurozone member states do not meet MMT’s requirements on its implementation, however, this study has been emphasized how and in which circumstances could apply ECB and member states. In addition, Croatia recently joined ERM2 and therefore has the capacity to issue Eurobonds, which would be redeemed by ECB via CNB that is implementation of MMT in practice.

Notes 1. Other examples of orthodox dissent may include the work of authors as diverse as Robert Shiller, Richard Thaler, Colin Camerer, Harvey Leibenstein, Dan Rodrick, Herbert Simon, Ronald Coase, Wassily Leontief, Amartya Sen, George Akerlof, Paul Krugman, Joseph Stiglitz, Oliver Williamson or William Vickrey, the last nine economists having won the Nobel Prize in economics. Some have explicitly stated that they certainly did not want to rock the mainstream boat. For instance, Thaler, the behavioral economist, is cited as saying that he did not want ‘to lay waste to the entire mathematical, hard science apparatus that economists had built after World War II’. Others, like Simon and Vickrey, have turned towards heterodox economics (Mitchell, William, L. Randall Wray and Martin Watts, Macroeconomics, London, UK, Red Globe Press, 2018). 2. Money could not make the exchange possible if exchangeability were not already inherent in commodity production, if it were not a representation of socially necessary abstract labor and thus of value. In that sense, money does not arise in exchange but instead is the monetary representation of exchange value (MELT), or socially necessary labor time (SNLT). 3. See Wray 2004 for analysis of the contributions of Innes; see Keynes (1914) for a favorable review of 1913 article by Innes. 4. The nature of money has evolved over time. Early money was usually commodity money—an object made of something that had a market value,

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such as a gold coin. Later on, representative money consisted of banknotes that could be swapped against a certain amount of gold or silver. Modern economies, including the euro area, are based on fiat money. This is money that is declared legal tender and issued by a central bank but, unlike representative money, cannot be converted into, for example, a fixed weight of gold. It has no intrinsic value—the paper used for banknotes is in principle worthless—yet is still accepted in exchange for goods and services because people trust the central bank to keep the value of money stable over time. If central banks were to fail in this endeavor, fiat money would lose its general acceptability as a medium of exchange and its attractiveness as a store of value. What is money? (europa.eu). 5. The central rate of the kuna was set at 1 euro = 7.53450 kuna within ERM2 transitional monetary arrangement agreed between Croatian central bank the and ECB.

References Bank of England—Monetary Analysis Directorate. 2014. Money Creation in the Modern Economy by Michael McLeay, Amar Radia and Ryland Thomas, London, UK. Convergence Report, ECB, June 2020. Domazet, T. 2014. Economics of Growth and Full Employment in Croatia. Zagreb: Croatian Chamber of Economy and Croatian Institute of Finance and Accounting. Domazet, T. 2015. Twenty First Century Economics, Transformation Science. Zagreb, Croatia: Croatian Institute of Finance and Accounting. Domazet, T. 2016 Endogenous Money—The Biggest Challenge in Establishing a Modern Economic and Financial System. In Proceeding International Symposium, Banja Vru´cica, Bosnia and Herzegovina. Domazet, T. 2017. Through a Modern Debt Jubilee to Sustainable Economic Growth. In Proceeding International Symposium, Banja Vru´cica, Bosnia and Herzegovina. Domazet, T. 2019a. New Growth Theory—Specifically by Small Open Economies. Zagreb (non-published manuscript). Domazet, T. 2019b. CEECs Facing Historical Challenges to Define New Economics. Zagreb: The China-Croatia Think Tank Forum. Ehnts, D. 2020. Modern Monetary Theory and European Macroeconomics (Routledge International Studies in Money and Banking), 1st ed., Amazon. Future of Money—Compilation of Papers. 2019. European Parliament, Study, Policy Department for Economic, Scientific and Quality of Life Policies Directorate-General for Internal Policies, Requested by the ECON Committee Monetary Dialogue, 88.

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Gasparotti, A., and M. Kullas. 2019. 20 Years of the Euro: Winners and Losers an Empirical Study, cepStudy. Hein, E. 2015. The Principle of Effective Demand—Marx, Kalecki, Keynes and Beyond. Institute for International Political Economy Berlin, Working Paper, No. 60. Keynes, J.M. 1936. The General Theory of Employment, Interest and Money. London: Macmillan. Lavoie, M. 2020. Was Hyman Minsky a Post-Keynesian Economist? Review of Evolutionary Political Economy. Mitchell, W., L.R. Wray, and M. Watts. 2019. Modern Monetary Theory and Practice: An Introductory Text. Pierce, D. 2013 Mar, 12. What Is Modern Monetary Theory, or ‘MMT’’? New Economic Perspectives blog, What Is Modern Monetary Theory, or “MMT”? (truthout.org). Pilkington, P., and W. Mosler. 2012. Tax-Backed Bonds—National Solution to the European Debt Crisis, Levy Economics Institute of Bard College, Policy Note 2012/4. Roberts, M. 2019. Modern Monetary Theory—Part 1: Chartalism and Marx. New Economic Perspectives Blog: Modern Monetary Theory—Part 1: Chartalism and Marx—Michael Roberts Blog (wordpress.com), downloaded 01.12.2020. Schlotmann, O. 2020. The COVID-19 Pandemic: Is Now the Time for Modern Monetary Theory or Permanent Monetary Finance? Professor for Monetary Economics and Banking Brunswick European Law School (BELS), Ostfalia, Wolfenbüttel/Germany, [email protected]. Stipeti´c, V. 2012. Two Centuries of Development of the Croatian Economy (1820– 2005). Zagreb: Croatian academy of sciences and arts. Subacchi, Paola. 2020. A Good but Incomplete Start to Debt Relief, Syndicate: A Good but Incomplete Start to Debt Relief by Paola Subacchi—Project Syndicate (project-syndicate.org), downloaded 01.12.2020. Wray, R. 2020. The “Kansas City” Approach to Modern Money Theory. Levy Economics Institute of Bard College. Wray, R. 2011. Financial Keynesianism and Market Instability, Levy Economics Institute of Bard College, Working Paper No. 653, 2.

CHAPTER 12

Impact of COVID-19 on Working from Home in Serbia: Possibilities and Consequences Mirjana Radovi´c-Markovi´c and Jovica Jovanovi´c

12.1

Introduction

Labour markets and employer–employee relations have been redefined around the world. New models of work usually involve new jobs, which will continue to be created in the formal economy. However, when determining new models of work, we must not neglect the informal economy (Radovi´c Markovi´c 2007), which has begun to gain increasing importance in the conditions of the employment and employment crisis in many countries. Namely, in the conditions of the economic crisis caused in 2008, as well as the latest crisis caused by COVID-19, the informal economy has become a wide-open market for personal skilled work and service provision.

M. Radovi´c-Markovi´c (B) Institute of Economic Sciences, Serbia and South Ural State University, Chelyabinsk, Russia e-mail: [email protected] J. Jovanovi´c Faculty of Medicine, University of Niš, Niš, Serbia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 N. Vidakovi´c and I. Lovrinovi´c (eds.), Macroeconomic Responses to the COVID-19 Pandemic, https://doi.org/10.1007/978-3-030-75444-0_12

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The aim of our research is to examine how the pandemic has affected the operations of organizations in Serbia and the scope of their operations, as well as how it has affected employees who work from home and remotely. Moreover, we explore both subjective and objective dimensions of job quality, such as job satisfaction, motivation, changes in working hours, along with issues related to physical and mental health and work–life balance. Our research is based on testing three set hypotheses: H1 The crisis caused by the COVID-19 virus will have the most negative impact on the volume of operation of small companies that employ up to 10 people. H2 Employees from home find the greatest benefit of working from home in the balance of private and business activities. H3 Working from home carries a high health risk.

12.2

Literature Review

As new types of non-standard employment arrangements appear in the form of short-term engagement in the gig economy. Platform work is an arrangement that uses a digital platform through which organizations or individuals contact and hire a third party (natural or legal person) to provide a product or service in exchange for payment. Digital platforms provide 24-hour access to the workforce. Namely, one of the main differences between this type of employment and the traditional work arrangement is that in this case the workers are paid only for that particular job. Therefore, jobs are not performed on the basis of permanent employment of people who have certain knowledge, but a contract on the provision of a specific service is concluded (Radovi´c-Markovi´c and Tomaš 2019). From an employment policy perspective, working on the platform can be a source of employment for young people, employees with family responsibilities, employees with disabilities, or other groups facing difficulties in securing traditional full-time employment. Working on the platform can also benefit employees in the need of flexibility in terms of their work manner (Nilles 2007). Various terms are used to describe this arrangement, such as “platform work”, “work on demand”, “work on-demand through an application”,

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or “digital work”. Some recent research takes particular account of the gender dimension of platform work. According to them, it has been established that those who work on the platform as the main source of income are primarily men, while those who work on the platform as a secondary source of income are primarily women (ILO 2020). Working from home is a general trend in the world that will continue in the future, as more and more people are leaving “corporate life” and replacing it with business, which they do in a much more relaxed environment of their home and family. Namely, although for many years, in addition to the mentioned, for example, remote working has been known, managers were not in favour of this type of work dominating for fear that productivity would fall if their teams worked from home. Therefore, they persistently insisted that employees travel to the office. That changed abruptly in March 2020, when the global pandemic of COVID-19 left companies with no choice but to switch from work to work from home or to be completely closed. Even companies that have never thought a home-based business was possible had to make a change. This statement is confirmed by some research which indicates that every ten seconds in the world a new business is started within one’s home (Radovi´c-Markovi´c et al. 2021b). In the United States alone, home-based businesses have the highest growth rate (10% per year on average) compared to other types of businesses. According to research by Godlewski (2020), 69% of newly established businesses in the United States in 2019 are those lead from home. Further, recent research shows that 73% of men work under the roof of their home in the United States, while 25% are women (Mansfield 2019). In the European Union in 2019, 5.4% of employees worked from home (EUROSTAT 2019). Since 2017, when employment from home was 3.1% in Serbia, that percentage has risen to 4.9% in 2019, which is about 5 below the European average. This trend continued to grow in Serbia in the total number of employees in the second quarter of 2020, i.e., it amounted to 12.1%, which is by 2.9% more than in the first quarter of 2020 (RZS 2020). Found in the literature are numerous advantages of working from home, which are primarily related to reducing operating costs (Grant et al. 2013), then to greater motivation and efficiency in fulfilling work tasks (Lewis and Cooper 2005; Golden et al. 2006). However, due to the drastic changes in the way of working that was conditioned by the occurrence of the pandemic, many employees faced various problems working from home. Some of them faced a lack

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of equipment and the necessary tools, knowledge, and optimal home conditions for remote work.

12.3

Research Method

The research was based on qualitative and quantitative methods. It was performed from February to October 2020 on a sample of 393 respondents. All the respondents in the sample stated that they used at least one digital device (computer, laptop, tablet, smartphone) in their usual work activity in the situation before COVID-19. The demoFigureic structure of the respondents showed that male respondents had the highest share in the sample with 53.6% (Fig. 12.1). Of the total number of respondents, 166 or 42.2% were freelancers. Our survey included two questionnaires out of a total of 30 questions, with basic information on company characteristics (including company size and industry), questions on the current response to the COVID-19 crisis and beliefs about the future course of the crisis. The second questionnaire aimed to examine how the crisis affected freelancers and other employees working from home. Observing the structure of respondents working from home by the level of education (Fig. 12.2), as many as 53% of respondents had a high school or university degree, while 35% had a secondary school degree.

46% 54%

female

male

Fig. 12.1 Structure of respondents by gender (Source Radovi´c-Markovi´c et al. 2021a)

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2%

Primary

35%

Swcondary

42%

High school University

21%

Fig. 12.2 Structure of respondents who work from home by level of education (Source Radovi´c-Markovi´c et al. 2021a)

The number of those with the primary school who work from home is negligible (2%). 12.3.1

Research Results and Discussions

The first question from the survey referred to the operability of companies in crisis conditions. We offered four opportunities to provide answers: the company increased its operation volume, maintained the existing level, reduced operating activities and was temporarily or permanently closed (Fig. 12.3). This research showed that the consequences of the pandemic in 2020 are most visible in organizations that employ from ten to a hundred people, i.e., their business has decreased in as many as 52% of organizations. On the other hand, about 36% of companies that employ between one hundred and two hundred employees increased their operating volume in the same period. The research also showed the vitality and flexibility of small companies that employ up to ten people, i.e., only 7% of them stopped working temporarily or permanently. The reason for this is the fact that some small firms, due to their volume of operation,

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D) Over 200 employees

C) From 100 to 200 employees

B) From 10 to 100 employees

A) Up to 10 employees

0 A) The volume of work has increased

0.2

0.4

0.6

B) The scope of work remained the same

0.8

1

C) The volume of work has decreased

1.2

1.4

D) No business ac vi es

Fig. 12.3 Influence of COVID-19 on the volume of operating activities in organizations of different sizes

did not require large-scale planning and a larger transition of business arrangements. Withal, this finding did not confirm hypothesis H1. The analysis of the number of employees from home by activities (Fig. 12.4) shows that the largest number of respondents worked in trade (27.5%), followed by education (17.2%). The least of them worked in health care, art, and production. Although most people worked in trade, the volume of business decreased in 78% of companies in the observed period. By crossing the data on the level of education and the type of activity that the respondents perform (Fig. 12.5), it can be concluded that out of 116 employees in trade, those with secondary education or 57.7% are the most represented. At the same time, our research showed that in Serbia, most of those who work from home are employed in trade. Immediately following the trade, according to the representation of work from home, there is education with 67 employees. This activity is dominated by persons with higher education or 49%. It is important to note that persons with higher and secondary education are also engaged in this activity, whose share in the total number of employees is equal to 25%.

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30%

25%

20%

15%

10%

5%

0%

Fig. 12.4 Work from home by activities in Serbia (Source Radovi´c-Markovi´c et al. 2021a) 120%

100%

80%

60%

40%

20%

0% Educa on

Traffic

Trade

Tourism primary

IT sector

secondary

high

Construc on

Finance

Industry

Service

university

Fig. 12.5 Work from home by level of education and type of activity (Source Radovi´c-Markovi´c et al. 2021a)

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To a much lesser extent, among the respondents are those who deal with tourism and catering at home, i.e., 29 people. Among them, 65% are people with college and university degrees, and 35% with high school. In traffic, 52.9% of university graduates work from home, while in construction and industry this percentage is equal and amounts to 53.5% of persons. A small number of employees dealing with finance work from home (only 9 respondents). Of that number, those with secondary, higher, and university degrees are almost equally represented. The quality of work is a crucial issue when analysing work from home. Therefore, one of the questions was “Does remote work have a direct impact on the feeling of motivation and their productivity?” Respondents felt more or less motivated and productive for a variety of reasons, which we regrouped into four factors: a. Work/home environment b. Possession of appropriate work equipment c. Possession of knowledge and readiness to work from home d. Time management abilities. Giving the answer to the question “What are the advantages of working from home”? freelancers and other employees from home were harmonized. Namely, they put “more time spent with the family” in the first place, while “permanent earnings” and “control over personal life” were of equal importance for the respondents, which confirmed the hypothesis H2 (Fig. 12.6). However, the higher educated are more difficult to establish a balance between business and all other life activities than the less educated (Radovi´c-Markovi´c et al. 2021a). Based on the analysis of factor scores, there are no significant differences between the genders when it comes to work satisfaction from home (Table 12.1). As the main disadvantage of working from home, the respondents singled out “alienation” (30%), followed by “overwork” (24%). However, what our research showed in particular is the fact that a larger number of respondents find the benefits of working from home and as many as 38% of those who think they “have no problems” and want to continue working in this way even after the pandemic passes (Fig. 12.7). However,

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IMPACT OF COVID-19 ON WORKING FROM HOME IN SERBIA …

327

120

100

80

60

40

20

0 Addi onal income

Family

Constant earnings

Personal life

Fig. 12.6 Advantages of working from home (Source Radovi´c-Markovi´c et al. 2021a)

Table 12.1 Assessment of gender differences in terms of work satisfaction from home

REGR factor score 1 for analysis 1 REGR factor score 2 for analysis 1 REGR factor score 3 for analysis 1

Gender numeric 1

N

Male Female

228 180

Male Female Male Female

Mean

Std. deviation

Std. error mean

0.01778 – 0.0225

0.99736 1.00567

0.06605145 0.07495827

228 180

– 0.0023 0.00291

1.04377 0.94452

0.06912538 0.0704007

228 180

0.05868 – 0.0743

1.04087 0.94333

0.06893334 0.07031151

Source Radovi´c-Markovi´c et al. (2021a)

it is difficult to determine in advance whether their organizations will enable them to do so. On the one hand, many employers are concerned about labour productivity and control, so they are likely to ask to either combine work from home with the traditional way of working or return

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8% 24% a lot of work aliena on no problem

38%

other

30%

Fig. 12.7 Disadvantages of working from home (Source Radovi´c-Markovi´c et al. 2021a)

to the previous system of work. On the other hand, employees are afraid of wage cuts if they continue to work from home. In any case, it should be borne in mind that any form of remote work rests on structural relationships that have already been established in traditional work (Massimo 2020). This research can also be used to examine many health risks, the results of which we also present in this paper. Namely, at the time of the COVID pandemic, a significant risk to human health, apart from the SARS-COV-19 virus itself, is stress caused by fear of infection, economic crisis, social isolation, new work organization, but also professional risks caused by organizational changes in the way a large number of companies and institutions operate. During the COVID pandemic, quarantine, social isolation, fear of infection, frustration, inadequate information, financial loss, and stigma are significant sources of stress for residents (Brooks et al. 2020) but also for employees of all profiles (Yin et al. 2020). Man is a social being who constantly, especially in difficult situations, needs human contact, comfort, the presence of dear people, and social connection. The absence of warm human contact, direct conversation, touch, and the usual way of greeting is a significant stress factor. Restriction of physical contact, wearing protective masks, protective clothing and gloves, but also home isolation results in feelings of psychological isolation, sadness, and helplessness. Social isolation and loneliness of people are associated

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with an increased risk of developing mental and physical health disorders (Courtin and Knapp 2017). Fear of infection by droplets, contaminated surfaces, and direct contact with other people leads to distrust of people, avoidance, and withdrawal from daily activities, which limits opportunities for human contact and social support. Due to the fear of infection, some people, despite the present health problems, risk getting worse and turning into a phase of significant complications, avoid visiting the doctor. During a pandemic, people’s lives change, there is an increase in the number of lonely and depressed people, the number of people who consume alcohol and drugs, and the rate of self-harm and suicide increases (Mark et al. 2020). Feelings of helplessness, loneliness, and depression are especially pronounced in people with disabilities. Due to the presence of fear, stress, and uncertainty, the health condition of people is permanently endangered and long-term consequences of the imposed isolation can be expected. In times of crisis, there is a decrease in physical activity, which leads to a deterioration in physical health and the degree of anxiety. Employees are largely afraid of losing their jobs and the threatening economic crisis. Younger people can more easily endure isolation, better cope with grocery shopping, and fill the day with work, various activities, and hobbies, as well as communication through social networks. There is uncertainty and fear for the health of friends and family members. They find it difficult to tolerate the reduction of social activities, they are worried about older members of their family, which is a particularly vulnerable and risky group. Fear of the unknown leads to a higher level of anxiety in healthy people as well, especially in the elderly, the sick, and those enclosed in cramped spaces. Caring for loved ones, fear of illness and death, uncertain future and economic situation, fear of the consequences of illness, additionally leave consequences on already impaired health and lead to permanent psychological trauma and stress. Increased levels of stress and anxiety during a pandemic significantly worsen the mental health of the population (Szcze´sniak et al. 2021). Stress at work has been significantly present in almost all sectors of the economy before (Jovanovi´c et al. 2013). The pandemic and fear of coronavirus infection at work further increased the existing level of stress at work. In times of crisis such as a pandemic, stress caused by insufficient or incorrect information of the population is very important. In times of any community crisis, people search for information related to current events in order to be informed about what is happening and what awaits

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them. The media is obliged to place only verified and accurate information, while unverified headlines additionally lead to harassment, feelings of fear and stress in the reader. Our previous research has shown that stress leads to impaired health of exposed individuals, potentiating the occurrence of high blood pressure, psychosomatic diseases, elevated cholesterol and triglycerides, elevated levels of stress hormones and weakened immune system (Jovanovi´c et al. 2008, 2018a; Kühnel et al. 2020; Dubey et al. 2020). It has been determined that the imbalance of stress hormones, increase in serum cortisol concentration leads to accelerated heart rate, increase in blood sugar levels, increase in blood pressure, drop in immunity, which ultimately results in the development of severe diseases (Jovanovi´c et al. 2011). All this leads to a decrease in working ability, an increase in the rate of absenteeism and injuries (Jovanovi´c et al. 2018b, 2020). During the COVID pandemic, there were organizational changes in the way of doing business, so that many companies and individuals started working from home. This way of working involves the use of information and communication technologies (desktop computer, laptop, smartphone, and tablet) that allow performing work outside the employer’s premises. Work from home has become one of the legally prescribed ways of working if it is possible to organize it taking into account the activity of the employer. The transition to this way of working, in many cases was not accompanied by adequate changes in the system of safety and health at work and the ability of employees to separate business from family life and responsibilities, a large number of companies and institutions did not have the necessary knowledge and experience in implementing preventive measures in order to protect health at work at home. Work from home is most often done through screen equipment, i.e., the use of desktops or laptops, which significantly facilitate the work of modern man. However, despite all the benefits, scientific research has shown that excessive use of computers can adversely affect the physical and mental health of users (Jovanovi´c et al. 2021; Jaiswal et al. 2019). Working on a computer significantly affects the cognitive, social, physical, and health parameters of users of computer technologies. Working at a computer involves sitting in an often forced position for a long period of time and requires repetitive movements, increased mental activity with relatively low energy consumption, which leads to obesity and disorders of the musculoskeletal system (Borhany et al. 2018). The health risk is inadequate body position while sitting at the computer,

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i.e., incorrect posture, poor ergonomic solutions of the desk, chair, keyboard, and mouse, incorrect distance of the eyes from the computer screen, unfavourable colour scheme and screen reflection, and inadequate room lighting. Improper posture when using a computer poses a risk of disorders of the musculoskeletal system in various parts of the body, especially in the upper extremities (Calik et al. 2014). The most common health problems associated with computer use are related to visual, musculoskeletal, and neurological symptoms and disorders. The most common visual symptoms include headache, eye strain, double vision, dry eyes, and eye fatigue, which are combined under the name “Computer Vision Syndrome”. Prolonged sitting reduces blood circulation in muscles, tendons, and ligaments and leads to stiffness and pain. In addition, computers emit various radiations such as visible light, ultraviolet, X-ray, and radio frequency radiation (Akinbinu and Mashalla 2014). Musculoskeletal problems that occur when using a computer can range from mild muscle fatigue or neck and back pain to cumulative traumatic disorders. There is evidence that musculoskeletal symptoms can be significantly reduced by an ergonomic approach and education (Hakala et al. 2010). Proper workplace placement, appropriate furniture, regular rest breaks, and stretching exercises can increase flexibility, reduce the risk of injury, and solve the problem of muscle imbalance (Chym 2014). The length of work at the computer is also very important because long holding of an incorrect position of a certain part of the body additionally contributes to damage to the musculoskeletal and vascular system, and long sitting without rest increases intra-disc load and weakens the lumbar spine (Ferguson and Marras 2005). Taking frequent breaks while using the computer has been shown to increase efficiency, because breaks usually relax the eye’s accommodation system, reducing fatigue and headaches. The application of various antistress programs significantly reduces the health effects of stress-induced health disorders.

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12.4

Method of Researching the Effects on Health

The research of health effects was performed on 110 employees who performed their work from home and 105 employees who worked in the premises of the employer, and it was realized by applying two questionnaires with a total of 48 questions. One questionnaire contained 19 questions and aimed to examine the subjective difficulties of the surveyed employees. The second questionnaire aimed to examine working conditions, working environment, and the application of safety and health measures at work while working from home and working at the employer’s premises. 12.4.1

Research Results

Subjective feeling of helplessness is somewhat more often present in the group of employees working from home (68.2 vs. 60.9%), but the difference is not statistically significant. Further, between these groups, there is no statistically significant difference in the number of employees who needed psychological support (62.7 vs. 58.1%). Subjective feeling of fear of infection is statistically significantly more common in employees working at the employer’s premises (70.5%) compared to the group of employees working from home (49.1%). Other subjective difficulties that indicate damage to the locomotor system and organs of sight are statistically significantly more often present in employees working from home compared to the group of employees working in the employer’s premises (Table 12.2). The analysis of data related to the self-assessment of the occupational safety and health system shows that there was no statistically significant difference in terms of cleaning the workplace, safety of electrical installations, and fire risk between the workplaces of employees working from home and those working at the employer’s premises. Almost equal number of employees in both groups were referred for preventive health examinations (93.3 vs 86.4%). The presence of other occupational risks that adversely affect the health of employees was statistically significantly more common in the group of employees who do work from home compared to the group of employees who work at the employer’s premises (Table 12.3).

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Table 12.2 Analysis of subjective difficulties of employees who work from home and at the employer’s premises Subjective difficulties

Feeling of helplessness presence Feeling of fear of infection presence Psychological help and support necessary Neck pain Pain in the upper back Shoulder pain Elbow pain Wrist pain Pain in the fists Lower back pain Hip pain Knee pain Ankle pain Headaches Eye fatigue Tingling in the eyes Red eyes Double vision Sleep disorder

Employees who work from home N = 110

Employees working at the employer’s premises N = 105

p

Number

%

Number

%

75

68.2

64

60.9

n.s

54

49.1

74

70.5

p < 0.01

69

62.7

61

58.1

n.s

65 45

59.1 40.1

44 30

41.9 28.6

p < 0.01 p < 0.05

28 20 31 32 34 12 28 27 59 45 37

25.5 18.2 28.2 29–Jan 30.9 10.9 25.5 24.5 53.6 40.9 33.6

10 5 13 16 20 4 14 14 37 17 20

9.5 4.8 12.3 15.2 19 3.8 13.3 13.3 35.2 16.2 19

p p p p p p p p p p p

32 37 68

30.5 33.6 61.8

20 24 50

19 22.8 47.6

p < 0.05 p < 0.05 p < 0.01

< < < < < < < < < <