Banking, Risk and Crises in Europe: From the Global Financial Crisis to COVID-19 2022050521, 2022050522, 9781032397429, 9781032397436, 9781003351160

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Banking, Risk and Crises in Europe

European economies have been plagued by successive crises, from the Global Financial Crisis (GFC) to the COVID-19 pandemic, through to the economic and geopolitical instability in Ukraine. These events, the uncertainty they generate combined with dynamic technological progress and significant sociocultural changes, have profoundly modified the character of modern finance. Understanding what happened, what mechanisms worked, and the reaction of the banking sector, bank customers, and policymakers require an in-depth and structured analysis. This book critically assesses the impact of these events, notably the COVID-19 pandemic, on the performance of the banking sector in Europe and serves as a compendium of knowledge on recent changes in European banking from two perspectives: firstly, European banking transformation, analyzing the process of what has already taken place, in particular the GFC and COVID-19 crises; secondly, challenges facing the operations and strategic management of European banks. It identifies specific areas of impact on the activity of commercial banks and the determining factors that will shape the economic and financial condition of banks and their customers – borrowers – in the future. Risk management, particularly credit risk, is a key focus of this volume. Each chapter, implicitly or explicitly, address a variety of questions that can help the reader to understand the complex nature of the transformation of the banking sector. The book provides a structured reference for those concerned with the impact of volatility on the business models of modern banks. As such, it will find a broad audience among students, academics, banking, financial, business, and industry professionals, policymakers, and market regulators. Renata Karkowska, Ph.D., is Associate Professor at the University of Warsaw, Faculty of Management. Zbigniew Korzeb, Ph.D., is Associate Professor at the Bialystok University of Technology, Faculty of Engineering Management. Anna Matysek-Jędrych, Ph.D., is Professor at the Poznań University of Economics and Business, Institute of International Business and Economics. Paweł Niedziółka Ph.D., is Associate Professor at the SGH Warsaw School of Economics, Collegium of Socio-Economics.

Routledge International Studies in Money and Banking

Negative Interest Rates and Financial Stability Lessons in Systemic Risk Karol Rogowicz and Małgorzata Iwanicz-Drozdowska Digital Finance and the Future of the Global Financial System Disruption and Innovation in Financial Services Edited by Lech Gąsiorkiewicz and Jan Monkiewicz Sovereign Debt Sustainability Multilateral Debt Treatment and the Credit Rating Impasse Daniel Cash Environmental Risk Modelling in Banking Edited by Magdalena Zioło Money, Debt and Politics The Bank of Lisbon and the Portuguese Liberal Revolution of 1820 José Luís Cardoso The Digital Revolution in Banking, Insurance and Capital Markets Edited by Lech Gąsiorkiewicz and Jan Monkiewicz Activist Retail Investors and the Future of Financial Markets Understanding YOLO Capitalism Edited by Usman W. Chohan and Sven van Kerckhoven Banking, Risk and Crises in Europe From the Global Financial Crisis to COVID-19 Renata Karkowska, Zbigniew Korzeb, Anna Matysek-Jędrych and Paweł Niedziółka For more information about this series, please visit: www.routledge.com/Rout ledge-International-Studies-in-Money-and-Banking/book-series/SE0403

Banking, Risk and Crises in Europe From the Global Financial Crisis to COVID-19 Renata Karkowska, Zbigniew Korzeb, Anna Matysek-Jędrych and Paweł Niedziółka

First published 2023 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10158 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2023 Renata Karkowska, Zbigniew Korzeb, Anna Matysek-Jędrych and Paweł Niedziółka The right of Renata Karkowska, Zbigniew Korzeb, Anna Matysek-Jędrych and Paweł Niedziółka to be identified as authors of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Karkowska, Renata, author. Title: Banking, risk and crises in Europe : from the global financial crisis to COVID-19 / Renata Karkowska, Zbigniew Korzeb, Anna Matysek-Jędrych, Paweł Niedziółka. Description: Abingdon, Oxon ; New York, NY : Routledge, 2023. | Series: Routledge international studies in money and banking | Includes bibliographical references and index. Identifiers: LCCN 2022050521 (print) | LCCN 2022050522 (ebook) | ISBN 9781032397429 (hardback) | ISBN 9781032397436 (paperback) | ISBN 9781003351160 (ebook) Subjects: LCSH: Banks and banking—Europe. | Financial risk management—Europe. | Financial crises—Europe—History—21st century. Classification: LCC HG2974 .K37 2023 (print) | LCC HG2974 (ebook) | DDC 332.1094—dc23/eng/20221020 LC record available at https://lccn.loc.gov/2022050521 LC ebook record available at https://lccn.loc.gov/2022050522 ISBN: 978-1-032-39742-9 (hbk) ISBN: 978-1-032-39743-6 (pbk) ISBN: 978-1-003-35116-0 (ebk) DOI: 10.4324/9781003351160 Typeset in Bembo by Apex CoVantage, LLC This book is the result of research realised under the Agreement concluded by the University of Warsaw (Faculty of Management), the Bialystok University of Technology (Faculty of Engineering Management), the Poznan University of Economics and Business (the Institute of International Business and Economics) and the SGH Warsaw School of Economics (Collegium of Socio-Economics).

Contents

List of figuresvi List of tablesviii List of authorsx 1 Introduction: European banking system transformation (the COVID-19 impact)

1

2 COVID-19 versus historical pandemics: economic, social, and political impact

9

3 Banking crises: theory, practice, and the special case of a pandemic as a source of a banking crisis

28

4 European banking sector performance: from Global Financial Crisis to COVID-19 pandemic

53

5 Policy response in the banking sector in the context of the COVID-19 epidemic

68

6 Changing the business model of banking operation

86

7 Transforming credit risk in the light of the COVID-19 pandemic

107

8 Challenges of other banking risks management in the context of the COVID-19 pandemic

131

9 Post-COVID-19 European banking sector: what is the ‘new normal’?

159

Index180

Figures

3.1 Cumulative confirmed COVID-19 cases per million people in selected European countries 43 3.2 Cumulative confirmed COVID-19 deaths per million people in selected European countries 44 4.1 Operating income vs. operating expenses in total assets for the European banking sector over the years 2007–2021 (in %) 62 4.2 Interest income vs. noninterest income in total assets for the European banking sector over the years 2007–2021 (in %) 62 4.3 Interest income vs. fee and commission in total income for the European banking sector over the years 2007–2021 (in %) 63 5.1 Economic impact of the COVID-19 pandemic 70 5.2 Value of stimulus packages introduced in selected countries in 2020 (% of 2019 GDP) 72 5.3 Change in general government gross debt expressed as % GDP in Q2, 2020 relative to the previous quarter in selected EU countries 73 5.4 Changes in interest rates of central banks in selected European countries78 6.1 Structure of interest and noninterest income in banks’ total income in selected European sectors (average for the period 2015Q3–2020Q3)90 6.2 Changes in the share of interest and noninterest income in banks’ total income in the European sector from 2015Q1 to 2020Q3 91 6.3 Average changes of cost-to-income ratio in the European banking sectors in relation to ROA efficiency ratio 94 6.4 Preferred channels in product research vs. sales (%, by region) 100 7.1 Impact of COVID-19 pandemic on credit risk 108 7.2 Value of outstanding loans for nonfinancial corporations in selected EU countries in 2020 (millions of EUR) 109 7.3 Value of outstanding consumer loans for households in selected EU countries in 2020 (millions of EUR) 110

Figures vii

7.4 Value of outstanding mortgages for households in selected European Union countries in 2020 (millions of EUR) 7.5 Resilience of credit collateral to the effects of COVID-19 7.6 Forbearance and classification of exposures 8.1 Key COVID-19 cyberthreats types (in %) 8.2 Interactions between climate and banking risks 8.3 Climate stress test model in the Netherlands Bank 9.1 Shaping of stock indices in selected European countries 9.2 Shaping of crude oil and natural gas futures prices (USD) 9.3 Shaping of gold futures prices (USD) 9.4 USD/PLN and USD/EUR volatility 9.5 Consolidated positions of residents of Russia (foreign banks) 9.6 Share of banks’ IT spending on new technology in North America and Europe from 2013 to 2022 (percentage) 9.7 Number of employees in EU credit institutions (in thousands)

111 116 123 135 140 150 168 169 169 170 172 175 175

Tables

2.1 Mortality and depopulation process versus pandemics 11 2.2 How different is COVID-19? 23 3.1 Review of selected theoretical concepts behind the banking crisis 29 3.2 List of selected global pandemic and epidemic events 43 4.1 Banking sector performance – review of industry and bank-specific drivers 54 4.2 Descriptive statistics of the banking sector performance in the EU 60 5.1 Selected European central banks’ response to COVID-19 – first wave 77 6.1 Descriptive statistics 93 6.2 Correlation matrix 94 6.3 COVID-19 and bank interest income in commercial banks in the European countries (full sample), over the period 2020Q1–2021Q195 6.4 COVID-19 and bank noninterest income in commercial banks in the European countries (full sample), over the period 2020Q1–2021Q195 7.1 Sectors most negatively afflicted by lockdown and pandemic effects in Poland 113 7.2 List of the most and least resilient economic sub-sectors to the COVID-19 crisis in terms of rates of return differentials and coefficients of variation 114 7.3 Collateral adjustment ratios used by banks 117 7.4 Credit moratoria in selected European countries 118 7.5 Loans and advances with non-expired EBA compliant moratoria121 7.6 Loans and advances with expired EBA compliant moratoria 121 8.1 The bank system of the climate risk management 141 8.2 Reporting climate risk in banks – an overview of methods 143 8.3 Selected initiatives relating to commercial banks in the context of their role in environmental and climate protection 144

Tables ix

8.4 Selected sources of financing for the energy transformation in the European Union (“European Green Deal”) 8.5 Sources of funding for New Generation EU program (in EUR b) 9.1 European banks in Russia (daughter banks and branches registered in Russia) 9.2 European banks in Ukraine

152 154 171 173

Authors

Renata Karkowska, Ph.D., is Associate Professor at the University of Warsaw, Faculty of Management. Her research activity includes areas of capital markets, banking, derivatives, and portfolio management. She is the author of about 80 scientific publications, including papers, chapters, and monographs. Currently, she is a lecturer for bachelor’s, master’s, and Ph.D. courses. For many years she has been a CFA mentor at the University of Warsaw, and a member of editorial and reviewer boards for North American Journal of Economics and Finance, Journal of International Financial Markets, Institutions and Money, International Review of Financial Analysis, and Emerging Markets Finance and Trade. She was involved with practitioners and experts in the capital market and banking. In the years 1999–2009 she worked as a chief specialist in the Departments of Treasury and International Markets at BPH and PEKAO banks; in 2010–2013 she was an advisor in structuring capital companies planning public offers in the capital market. Prof. Karkowska is an expert on currency risk and interest rates for Polish companies for GreenCapital.pl, and is Warsaw Stock Exchange School Coordinator at the Faculty of Management at the University of Warsaw. Zbigniew Korzeb, Ph.D., is Associate Professor at the Bialystok University of Technology, Deputy Head of Department of Management, Economy, and Finance, and a lecturer on subjects connected with banking and banking risk. He is an author of over 100 scientific publications, including books, chapters, and articles, on banking, mergers and acquisitions, and the creation of shareholder value. Prof. Korzeb is also a reviewer for journals related to banking and finance for Elsevier, Springer, Palgrave Macmillan, SAGE, and Taylor & Francis. He has several years of experience as an expert working for Bank Pekao SA. Anna Matysek-Jędrych, Ph.D., is Professor at the Poznań University of Economics and Business, Department of International Competitiveness. Her main research areas include macroeconomics and political aspects of international economics. She is Director of the Executive MBA Program held in cooperation with Georgia State University in Atlanta, United States. Prof. Matysek-Jędrych’s expertise covers financial markets, institutional

Authors xi

framework, and its impact on the economy’s performance. Recently, she joined a research team on projects studying Brexit consequences on EU-27 cohesion and COVID-19 impact on a company’s adaptative behavior, and she conducts research on institutional determinants of macroprudential policy efficiency. She is the author of more than 50 scientific articles, chapters, and monographs, including two research projects for the National Bank of Poland (winner of a grant competition among economists from Poland). She is also a member of the editorial and review board of the Journal of Eastern European and Central Asian Research (Webster University), the International Journal of Emerging Markets, and Cross-Cultural & Strategic Management. Paweł Niedziółka, Ph.D., is Associate Professor at the Warsaw School of Economics, having graduated from the Warsaw School of Economics in 1998 with a major in finance and banking. In 2000, he was awarded a doctoral degree in economics at the Collegium of Management and Finance of the Warsaw School of Economics, and in 2010, he became an assistant professor. Currently, he is employed at the Institute of Banking of the Warsaw School of Economics, where he heads the Financial Risk Management Department. His main research areas include credit and market risk management, derivatives, project and structured finance, and financial stability. Prof. Niedziółka is a member of the Polish Association of Finance and Banking, and the Committee on Financial Sciences of the Polish Academy of Sciences, the Second Prize Winner in the Contest of the President of the National Bank of Poland for the best post-doctoral thesis, and the winner of other prizes for his scientific and educational work. He is the author of about 140 scientific publications (including four books) and a lecturer at bachelor’s, master’s (supervisor of approximately 300 master’s theses), postgraduate, and Ph.D. courses (supervisor of seven doctoral theses). He is a member of review boards and reviewer of several international journals indexed by Scopus and Web of Science. He also is an expert at the Polish Agency for Enterprise Development (PARP), representing the Polish Banks Association, and a lecturer at Polish and international conferences and training courses. Combining his work at the Warsaw School of Economics with practical banking, he manages the Structural Financing Team at Bank Millennium S.A. (previously, he was associated with Credit Lyonnais Bank Polska and Bankgesellschaft Berlin). He was an independent member of the Supervisory Board of Grupa Kęty S.A. (one of the biggest Polish companies) from 2014 to 2020, and during 2017–2020 he was Deputy Chairman of the Supervisory Board and Chairman of the Nomination and Remuneration Committee.

1 Introduction European banking system transformation (the COVID-19 impact)

Introductory remarks No one likes changes. The change we now have to confront due to the COVID-19 pandemic came to us unexpectedly. That is why they are harder to come to terms with and accept. At first, everything was more accessible and more predictable. Then, suddenly, it turned out that not everything is possible. We cannot plan everything or even resign from many of our previous activities. Fear for health and life and stress resulting from the suddenly introduced restrictions became the new reality. Once again, it turned out that we are helpless in our encounter with nature, despite the vast knowledge in the fields of medicine, psychology, management, and others. We have started living in the actual VUCA world, a world that is volatile, uncertain, complex, and full of ambiguity. Daily, we all began to be surprised: international institutions, governments, most economic sectors, individual companies, and ordinary individuals. The lack of preparation for this specific type of crisis that the world faces is also characteristic. The enormity of the human tragedy is frightening and forces us to redefine the game’s rules that have accompanied us so far. According to World Health Organization (WHO), the number of pandemic victims at the end of 2020 was 1,798,352 people, and at the end of 2021, the number amounted to 5,446,753, far exceeding the figures resulting from the many tragic events of recent decades. People began to realize quickly that this pandemic’s social, psychological, economic, and political consequences would be more far-reaching than the pandemic itself. Perhaps even everyday life will never return to the way we knew it before. But it is up to us to be better prepared for future crises, similar to the current one, and their global impact. In many ways, COVID-19 was an exogenous, sudden shock to the economies of individual countries, their governments, and societies. The impact of the pandemic affected highly developed countries as well as developing and underdeveloped economies. However, the nature of the crisis caused by the pandemic is entirely different from previous global financial crises, the first of them being caused by subprime lending and the second related to the debt problems of eurozone countries. They both had their origins in the financial DOI: 10.4324/9781003351160-1

2  Introduction

sector. Now the root of the problem is different. Banks are not the cause of the recession. The good economic situation of recent years and regulatory measures have made commercial banks more stable and resilient to market shocks. Following previous crises, banks have dramatically improved asset quality, built a more extensive capital base, strengthened liquidity levels, and reduced nonperforming loans. As a result, they have resumed better shape in the current situation than they did previously. While the aid schemes implemented by individual countries did not directly affect the banking sector, the main support lines dedicated to corporate finance and job protection indirectly affected it. Although governments, central banks, and regulators across Europe responded quickly to the pandemic by taking emergency measures to limit the worst effects of the crisis, the true extent of the economic damage will become apparent only when these emergency measures are scaled back. There is no doubt that the pandemic is going to be reflected in the materialization of credit risk: deterioration of the loan portfolio, an increase in the number of insolvent borrowers, and an increase in writedowns on specific provisions will lead to losing some of the banks’ income and profitability. However, there is still a lot of uncertainty about the future. As a result, the ability to adapt to current and future conditions will become the main factor determining the success of banking activity.

The caveats of conceptualizing the European banking system transformation Like other sectors of the economy, the European banking sector has had to deal with the crisis triggered by COVID-19. This crisis is undoubtedly multifaceted, affecting not only the health of Europeans. It is reflected in the changing habits of society (keeping a social distance, refraining from excessive consumption; cf. Eftimov et al., 2020; Chen et al., 2021; Jiang et al., 2021); in the deterioration of macroeconomic indicators (Fernández-Villaverde & Jones, 2020; Boissay  & Rungcharoenkitkul, 2020; McKibbin  & Fernando, 2021); and  – finally – in the adoption of many nonstandard decisions aimed at limiting the impact of the crisis (Loayza & Pennings, 2020; Matysek-Jędrych & MroczekDąbrowska, 2021; Kowalski, 2021). Beyond the COVID-19 pandemic crisis itself, European banks must consider the global and regional trends shaping the new business environment. Among these trends, the most important are: •

demographic changes, including the aging of the European population and the influx of migrants to Europe; • institutional changes within the European Union, including Brexit in particular (cf. Mroczek-Dąbrowska & Matysek-Jędrych, 2021;Gorynia et al., 2022); • the post-pandemic variable pace of growth in the global and European economies;

Introduction 3

• •

the “slowbalization” phenomenon that has reduced integration processes and materialization of the benefits of operating in the common European market; and the scale of the technological transformation of financial services over the past decade cannot be overstated, and banks can no longer take customer loyalty for granted amid competition from FinTech (Petralia et al., 2019) and BigTech (BIS, 2019; Frost et al., 2019; Boissay et al., 2021) players but also aggressively from Chinese banks.

The aforementioned tendencies, phenomena, and trends forced the banking sector to initiate adjustment processes. At this stage of the pandemic, however, it is already possible to conclude that banks are by no means the cause of the current crisis. On the contrary, they may be an essential element – alongside the applied state interventionism – in the reconstruction of real economies, the recovery of the economy, and thus the return to the “regular days” before the epidemic. In other words, instead of initiating the crisis as in previous cases, banks can play a significant part in finding a solution to the existing problems. The pandemic has exacerbated other challenges already faced by European banks. Bank-generated costs are too high given a period of zero or negative interest rates, resulting in bank profits below their cost of capital. The economic slowdown triggered by COVID-19 has put even more pressure on the bottom line, and loan demand remains uncertain. This will force some banks to book higher loan loss provisions and deplete capital buffers, ultimately affecting their ability to provide sufficient funding to support the economic recovery. Banks in Europe need to take action in at least five different areas, all of which are familiar to banks but need to be reviewed and reidentified to capture the mechanisms of influence on the bank’s strategy and operating model. These areas cover the following topics: 1 Bank lending activity: the need to understand the dynamics of recovery from the COVID-19 crisis across different markets and industries to be prepared for an increase in loan defaults. Banks, therefore, need to identify key risk factors and develop a new business model and capital protection strategy. This will be possible by implementing risk management tools in the core business of banks (credit risk). 2 Costs: banks must dramatically change their operating strategy to radically transform the business, with the potential to reduce costs by dozens of percentage points, which will allow banks to reallocate selected resources to more profitable business lines. 3 Consolidation process: competition from new players in the European financial market, including FinTech, BigTech, and banks from emerging markets, will force a new wave of mergers and acquisitions (M&A) processes to strengthen the competitive position of European banks.

4  Introduction

4 Technological advancement: particularly in the competition from BigTech and FinTech, banks need to create scalable digital platforms that offer personalized digital services to customers while making the organization more flexible and agile (use of AI-based technologies). 5 Environmental, social, and governance (ESG) area: at least three trends are converging ESG as the new litmus paper of sound banking practices. First is climate change and the need to finance the decarbonization of economic activities; second is reputational, where banks and businesses that do not measure up to their ESG pledges risk being accused of greenwashing; and the third is regulation, which will require banks to measure and disclose ESG risks in their loan portfolios and other banking activities, as well as the impact of their activities across a broad set of environmental, social, and governance considerations. Genuine change necessarily requires a rethinking of the entire banking business model, leading to a massive transformation in work patterns and required skills. The sooner banks in the eurozone begin the change, the sooner they can close the long-term performance gap.

Key arguments advanced in this volume: questions and objectives The transformation of the banking sector in Europe seems inevitable. COVID19 only accelerates this process and forces adjustments in areas that banks considered less sensitive. The chapters included in this volume address several issues and developments that seem crucial in understanding the direction, scale, and pace of change. The authors attempt to guide the reader through the intricate issues involved in the operations of banks in Europe, particularly from the perspective of the impact of the COVID-19 pandemic. The main objective of this monograph is to systematize knowledge and assess to what extent the effects of the COVID-19 pandemic have affected and how they will affect the European banking sector in the coming years. Achieving the main objective requires, first of all, understanding the heart of the pandemicrelated crisis, identifying specific areas of its impact on commercial banks, and determining factors that will shape the economic and financial condition of banks in the coming period. Risk management, particularly credit risk, is also a focus of this volume. This is undoubtedly a sphere of bank operations that significantly affects the performance of banks while managing the challenges arising from the impact of the COVID-19 pandemic on borrowers’ financial situation. The chapters in this volume, implicitly or explicitly, address the variety of questions that can help the reader to understand the complex nature of banking sector transformation. Some of these questions are: •

What is the impact of the COVID-19 pandemic on the banking sector in Europe, and what are the main mechanisms of its effects on banks?

Introduction 5

•

In a historical context, what is the scale and magnitude of the COVID-19 pandemic in economic, social, and political dimensions? • How does a banking crisis caused by a pandemic differ from the banking crises we know from history? What is the anatomy of this crisis? • What measures have governments and central banks used to address the crisis caused by COVID-19, and how successful they have been? • Is a change in the business model of banks in Europe taking place now, and what is expected regarding the business model, given the challenges posed by the COVID-19 pandemic? • What are the mechanisms for the impact of COVID-19 on the core business of commercial banks in Europe, i.e., on banks’ credit risk management and on the other risks that banks manage?

The structure of the volume The book consists of nine chapters, including this introductory chapter and the concluding one. The chapters, sequenced in a logical structure, address various issues consistent with the volume’s objectives. This logical structure covers problems in a top-down approach, where the next chapter deals with issues related to the COVID-19 pandemic (Chapter 2); the following chapters analyze the banking sector in Europe from a macroeconomic and meso-economic level, stressing the COVID-19 impact on the sector (Chapters 3, 4, and 5), and later chapters address the issues of the banking business models (Chapter 6) and the concept of risk and its management by banks (Chapters 7 and 8). Capturing how the pandemic is affecting the banking sector in Europe, and understanding the transformation mechanisms that COVID-19 is forcing, would not be possible without an in-depth analysis of the pandemic itself. This phenomenon is unusual, causing profound changes in economic, social, and political terms. Embedding considerations in a historical context provides an even better understanding of the nature of the pandemic. These issues are discussed in detail in Chapter 2. The COVID-19 pandemic should be considered as a crisis situation. In addition, the nature of this crisis is significantly different from the banking, financial, or economic crisis we know from the historical context. The elaboration on this issue was undertaken in Chapter 3, starting with the concept of “banking crisis.” Then, a short history of crises over the centuries is presented. It was emphasized that the complex specificity of processes related to the occurrence of banking crises and the individualized nature of most of them make the research on this issue quite extensive. The chapter also aims to characterize the main determinants accounting for the causes of emerging crises and draws attention to capturing the specificity of the crisis caused by COVID-19 in the context of existing theoretical models. In Chapter  4 the authors present the results of a comprehensive performance analysis for the European banking sector. The analysis is carried out in three separate but complementary dimensions: efficiency, productivity, and

6  Introduction

profitability. The inclusion of two crises of a different nature in the research period allowed for comparative studies. Thus, we assess the impact of the crisis of the banking sector and investigate whether the shock nature had a differential impact on banks’ performance. The comparative analysis carried out for the period defined by dates of Global Financial Crisis and the COVID-19 pandemic focuses on changing sources of fragility of banking sectors. Chapter 5 presents the situation in the analyzed European countries from the point of view of implemented aid measures. First of all, it indicates support programs initiated by governments, central banks, and banking supervision institutions. It also highlights the activities of the banks themselves, which, on the one hand, aim to provide customers with conditions and facilities for servicing existing loans and, on the other, guarantee safe, direct service in traditional branches. Chapter 6 seeks to explain the need to reorient existing business models used by banks in the context of the impact made by the pandemic. It is emphasized that the pandemic fundamentally affects society’s psychological and emotional state, contributing to changes in existing behavior among bank employees and customers. This puts pressure on bank boards to reshape their strategy for managing bank assets and liabilities in a low-interest-rate environment. It should be expected that banks will be forced to adopt even more innovative and flexible rules of conduct, especially solutions in the field of information management, security, and customer communication. In particular, the increased importance of remote communication with customers and remote working of bank employees in times of pandemic is an issue that requires significant changes in the banks’ existing business model. This will undoubtedly be reflected in the optimization of the banks’ branch network, further employment restructuring, and rationalization of administrative costs. Chapter  7 is devoted to analyzing an increase in credit risk in the wake of the pandemic. It specifies this risk both in terms of counterparty risk and transaction risk. It also seeks to explain the differential impact of the effects of the pandemic on different sectors of the economy, as well as how banks made adjustments to adapt to the new circumstances by creating funding constraints for the industries most affected by the pandemic and remodeling decision-making and lending procedures. At the same time, the section highlights threats resulting from the loss or decrease in the value of credit collaterals accepted by banks in so-far-granted loans and credits. The importance of customer and transaction monitoring as a means of reducing credit risk is also emphasized. Chapter 8 highlights a sharp increase in threats arising from operational risk during the pandemic. It follows that organized criminal communities quickly recognized and exploited intensified remote communication and the exchange of sensitive information by both bank employees and customers. The chapter discusses the primary attack methods and specific forms of cybercrime targeting bank customers who are users of web and mobile applications that enable online contact. New forms of fraud are also presented, such as the use of

Introduction 7

pandemic-related fake news, identity theft on social networking sites, as well as phishing for aid funding by unauthorized individuals and companies. Another issue addressed in the chapter concerns the impact of climate change on operational risk in banks. Chapter 9 draws conclusions from the discussion and opinion raised throughout the book to highlight the volume’s value added and suggest new research areas.

Concluding remarks The monograph is innovative in its subject matter and, in a way, fills a gap in the area of scientific research devoted to the issue of the impact of global pandemics on the banking sector. It is the first to present comprehensively the challenges faced by European banking sectors in the context of the situation resulting from the effects of COVID-19. Understanding the mechanisms of processes in dynamically changing conditions should make it possible to provide additional knowledge on the phenomena occurring in commercial banks during the pandemic, to identify more precisely the problems of the banking sector, and to define new tasks facing supervision institutions in the aftermath of a highly complex situation.

References BIS (2019). Big tech in finance: Opportunities and risks. Annual Economic Report 2019, Chapter III, June. Boissay, F., Ehlers, T., Gambacorta, L., & Shin, H.S. (2021). Big techs in finance: A new trade-off between efficiency and privacy. SUERF Policy Briefs, No. 250, December. Boissay, F., & Rungcharoenkitkul, P. (2020). Macroeconomic effects of Covid-19: An early review. BIS Bulletin, 7. Bank for International Settlements. Chen, H., Qian, W., & Wen, Q. (2021). The impact of the COVID-19 pandemic on consumption: Learning from high-frequency transaction data. American Economic Association Papers and Proceedings, 111, May, 307–311. Eftimov, T., Popovski, G., Petković, M., Koroušić, B., & Kocev, S.D. (2020). COVID-19 pandemic changes the food consumption patterns. Trends in Food Science  & Technology, 104, October, 268–272. Retrieved from: https://doi.org/10.1016/j.tifs.2020.08.017 Fernández-Villaverde, J., & Jones, C.I. (2020). Macroeconomic outcomes and COVID-19: A progress report. Brookings Papers on Economic Activity, 2020(3), 111–166. Frost, J., Gambacorta, L., Huang, Y., Shin, H.S., & Zbinden, P. (2019). BigTech and the changing structure of financial intermediation. BIS Working Papers, No. 779, April. Gorynia, M., Jankowska, B., & Mroczek-Dąbrowska, K. (eds.) (2022). Brexit and the Future of the European Union. Firm-level Perspectives. London & New York: Routledge. Jiang, P., Van Fan, Y.,  & Klemeš, J.J. (2021). Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities. Applied Energy, 285. Retrieved from: https://doi.org/10.1016/j.apenergy.2021.116441 Kowalski, T. (2021). The economy battling Covid-19: A macroeconomic approach. In: E. Mińska-Struzik & B. Jankowska (eds.), Toward the ‘New Normal’ after COVID-19 – A Posttransition Economy Perspective. Poznan: PUEB Press.

8  Introduction Loayza, N., & Pennings, S.M. (2020). Macroeconomic policy in the time of COVID-19: A primer for developing countries. World Bank Research and Policy Briefs, No. 147291. Matysek-Jędrych, A., & Mroczek-Dąbrowska, K. (2021). Central bank policy toward the COVID-19 pandemic: Seeking patterns among the most powerful central banks. In: E. Mińska-Struzik & B. Jankowska (eds.), Toward the ‘New Normal’ after COVID-19 – A Posttransition Economy Perspective. Poznan: PUEB Press. McKibbin, W., & Fernando, R. (2021). The global macroeconomic impacts of COVID19: Seven scenarios. Asian Economic Papers, 20(2), 1–30. Retrieved from: https://doi. org/10.1162/asep_a_00796 Mroczek-Dąbrowska, K., & Matysek-Jędrych, A. (2021). ‘To fear or not to fear?’ The nature of the EU-27 countries’ vulnerability to Brexit. European Planning Studies, 29(2), 277– 290. Retrieved from: https://doi.org/10.1080/09654313.2020.1745761 Petralia, K., Philippon, T., Rice, T.,  & Veron, N. (2019). Banking disrupted? Financial intermediation in an era of transformational technology. Geneva Reports, No. 22.

2 COVID-19 versus historical pandemics Economic, social, and political impact

Introductory remarks Like financial crises and other sociopolitical shifts, contagious diseases have changed the economics and sociopolitics of the world throughout history. The world has witnessed many such challenging situations so far. In this chapter, we chronologically present selected epidemics that affected humanity. At the same time, we set two goals for such a comparative analysis. The first is to show that specific mechanisms, behaviors, and stereotypes do not change over time, and that pandemics are similar in some ways. This may, in turn, provide meaningful guidance for efforts to find alternative routes out of the COVID-19 pandemic crisis. The second objective is to highlight the strictly economic, social, and political effects of the pandemics that occurred in the past.

Epidemic versus pandemic Modern definitions of pandemic include among other the following: “extensively epidemic” (Stedman’s Medical Dictionary, 2006), “epidemic . . . over a very wide area and usually affecting a large proportion of the population” (Last, 1988, 94), or “distributed or occurring widely throughout a region, country, continent or globally” (University of Maryland, 2009). The principal, intuitive differences between an epidemic and a pandemic are that in the case of an epidemic, the disease develops in a particular area (rather than worldwide or in a significant number of countries) and is periodic (it appears at certain times of the year and dies out after a few weeks or so). A pandemic (from Greek: pan – all; demos – people) is, therefore, a particular type of epidemic characterized by widespread impact and a relatively long duration. Pandemics with varying frequency, extent of occurrence, and duration have accompanied humanity since its inception. Therefore, they cannot be treated as unexpected and unpredictable events like the famous black swans, about which Popper (1934) wrote in the 20th century, and which concept was propagated during the Global Financial Crisis by Taleb (2007). The international community should be prepared for periodic outbreaks of infectious diseases; hence, epidemics and pandemics are rather called gray rhinos (Wucker, 2016). DOI: 10.4324/9781003351160-2

10  COVID-19 versus historical pandemics

A pandemic is distinguished by the following features (Morens et al., 2009): • •

• •

• •

wide geographic extension, as almost all uses of the term pandemic refer to diseases that extend over large geographic areas – transregional, interregional, and global; relatively low mortality among infected people, usually not more than 3%, but in countries with a low level of socioeconomic development and inadequate prevention, mortality can be much higher; a general rule of thumb can be taken in this case that the wider (geographically, population-wise) the scope of the pandemic, the lower the percentage mortality; high attack rates, explosiveness, and contagiousness; novelty and, as its consequence, lack of natural immunity of the affected population because the source of the disease is an external biological factor (usually zoonotic) or a virus strain that has not been present for a long time or has never been recognized before; a long infectious period; the ease of infection due to the disease being asymptomatic in many cases.

In this chapter, despite being aware of definitional differences, we use the terms epidemic and pandemic interchangeably. This is due to the intention to present the phenomenon from its inception to its extinction. During this period, an epidemic may turn into a pandemic. The causes of modern pandemics (excluding speculative theories about the intentional creation of the virus in medical laboratories and its subsequent use for political or economic purposes) can be sought in (Morens et  al., 2009; Antrás et al., 2020): • human expansion and the proximity of human habitats to wildlife species, which promotes the transmission of the virus to livestock and later to humans; • globalization associated with the intensification of migration of people and goods as well as the use of new technologies to increase the speed of movement of people between countries and continents at a systematically diminished cost; once the process of opening borders to people and goods has begun, it is difficult to stop it rapidly in a short period; this in turn, greatly undermines the effectiveness of individual governments’ measures of countering the virus; • misdiagnosis of the disease (which originally occurred, for example, in the case of the Spanish flu in the early 20th century) and the application of solutions inadequate to the threat.

The effects of the pandemic In the case of a pandemic, the rapid growth of mortality and depopulation come to the fore (cf. Table 2.1). However, these are not the only effects of the disseminating disease – among the other effects are (Kuliszer, 1961):

COVID-19 versus historical pandemics 11

• sometimes a long period of convalescence for those infected, putting a strain on health care and the social security system – this problem in the case of COVID-19 was highlighted by Honigsbaum and Lakshmi (2020) comparing the recent pandemic to Russian influenza (1889–1892); • the difficulty of maintaining continuity in the activities of entrepreneurs; • additional expenditure by companies on measures to protect employees, customers, and other stakeholders from infection; • changes in the structure and level of consumption; • alteration of work and leisure patterns; • sometimes a reduction in work efficiency; • uncertainty and sometimes pessimism about the future situation of the economy and stability of one’s income, resulting in stagnation of consumption (households) and investment (companies); • increase in the budget deficit and public debt; • radicalization of public sentiment; • polarization of the economic and financial situation of individual sectors of the economy and economic entities within these industries. Most of the consequences of a pandemic are negative, but some benefits should not be overlooked, which, however, can be achieved only by adapting to the new situation. Among them is the digitalization of various processes, which often means a significant simplification, shortening of the time of their implementation, and saving resources. Digitalization concerns the relationship of individuals with public institutions and businesses, and the interaction of businesses with each other and with public institutions. Science and health care are also subject to digitalization. However, in these areas of social life, negative evaluations of the change in the model of their functioning prevail. Thus, given the aforementioned factors and the growing operational risks (especially for credit and financial institutions), digitalization cannot be unambiguously positive, but without it, life in a pandemic would be much more difficult. If certain behaviors acquired during the pandemic also become widespread after its expiration, this can be counted as a benefit from this difficult social experience. Table 2.1  Mortality and depopulation process versus pandemics Pandemics Plague of Justinian Black Death Spanish Flu Asian Flu SARS Swine Flu Ebola COVID–19

Dates

Number of victims

Global population size

% of global population

541–542

30–50M

0.21B

19.1%

1347–1351 1918–1919 1957–1958 2002–2003 2009–2010 2014–2015 2019–

200M 40–50M 1.1M 770 200,000 11,300 5.4M

0.39B 1.82BB 3.03B 6.3B 6.9B 7.25B 7.9B

51% 2.5% 0.036% ~0% 0.0029% 0.0002% 0.068%

Source: Authors’ compilation based on WHO data, Encyclopedia Britannica, and Johns Hopkins University estimations.

12  COVID-19 versus historical pandemics

First and foremost, it is about limiting the consumption of nonessential goods, the production of which leads to overexploitation of resources, often nonrenewable. Also, leveraging the lessons learned from the mass adoption of remote working can yield cost-reduction benefits. However, this is not a continuation of the model in place during the pandemic crisis, but an evolution towards a hybrid solution. It will maintain social links and achieve high efficiency by interacting and sharing experiences on an ongoing basis while reducing the need to travel to offices, with the positive effects of saving time and reducing carbon emissions into the atmosphere. While the demand for office space shrinks, the decrease in lease rates will bring an additional reduction in operating costs for tenants. Finally, each pandemic brings some technical advances and medical developments that can become engines of economic recovery from a pandemic crisis. When analyzing the impact of a pandemic, there is a clear distinction between immediate (short-term) and long-term (if not permanent) consequences. The latter group is far more important, especially from an economic point of view. When examining the economic impact of contemporary pandemics (especially COVID-19), it is important to note a fundamental difference from earlier periods, especially the Spanish flu (De Santis & van der Veken, 2020). First, there were no government actions restricting economic activity at the time (e.g., lockdowns of varying industry scope and duration). Second, the theory and practice of economic policy immediately after World War I  did not assume state support of enterprises and individuals (at least not on such a scale as was and is observed during the COVID-19 pandemic). This was both because the budgets of the states involved in the war had weakened considerably, and as mentioned previously, also for doctrinal reasons. Third, the COVID-19 crisis also affects developed and wealthy countries, unlike many 20th-century plaques, which were smaller in scope and mostly confined to poorer regions of the world. Fourth, a period of crisis caused by infectious disease is usually followed by economic prosperity, but the variants for returning to growth are at least several. Given the active role of the state in the recovery from COVID-19, it is likely that the path will differ from that of previous pandemics. Considering these differences in economic policy conditions and practices, conclusions comparing the economic impact of pandemic crises should be treated with caution. At this point, it is worth asking about the possibility to define at least a framework scenario for the economy’s behavior during and immediately after the end of the pandemic. In other words, it is a question about the economics of a pandemic. With each plaque, economists identify both demand and supply shocks. The former is inherently short-term in nature and associated with a decline in consumer spending on nonnecessity goods and all consequences of reduced mobility that ultimately reflect a decline in oil prices. Supply shocks, on the other hand, should be identified with a diminishing of labor supply, lowering of production and sales as a result of forced periodic business closures, reduced availability of intermediate things or raw materials, or lockdowns

COVID-19 versus historical pandemics 13

experienced by counterparties. Demand and supply shocks as well as the takeover by the state of the role of preventing the weakening of economic growth and increasing unemployment contribute to the growth of the budget deficit and public debt. Due to the simultaneous fall in GDP, the figures reflecting the budget deficit and public debt against GDP show an even greater deterioration compared to the pre-pandemic period. Whether all countries can afford fiscal expansion remains another question, as the consequences of the subprime crisis, which for some countries soon turned into a sovereign debt crisis, are fresh in the mind (Sieroń, 2020). The economic impact of a pandemic can be categorized into three groups, i.e., costs resulting from (Jonas, 2013): • • •

mortality (12%); employee absenteeism (28%); changes in consumer habits and behavior (60%).

Pandemics in antiquity Rapidly spreading diseases have affected mankind since the beginning of time. Around 430 BC, a typhus pandemic swept through ancient Greece. It resulted in the deaths of about 70,000 people, including Pericles. The plague did not spare the Athenians during the war with Sparta, which contributed to a significant economic and political weakening of today’s Greek capital in the Mediterranean (Piechowiak, 2014a). In the second half of the second century AD, the Antonine plague took place, resulting in the deaths of about 5  million people. In some regions of Italy, Gaul, and Egypt, losses reached about 20% of the population. The plague particularly affected densely populated cities. It is likely that a similar epidemic had reached China earlier, which, together with the aforementioned weakening of the position of cities, adversely affected the scale of trade. At that time there was recorded a great famine resulting from failure to sow a significant portion of fields (mainly in Egypt). The depopulation and impoverishment of the population also brought a sharp decline in tax revenues, which weakened the military potential of the empire. The pandemic decimated the Roman army, then fighting against barbarian tribes, which, together with the death of one of the most prominent Roman emperors Marcus Aurelius and his co-ruler Lucius Verus, many consider to be the beginning of the decline of the Roman Empire or at least the period in which its expansion ended (Duch, 2020b; Murphy, 2005). The first plague occurred during the reign of Emperor Justinian (who also caught it) between 542 and 543. The pandemic broke out in the Byzantine Empire (its outbreaks are believed to have been in Ethiopia and Egypt) and led to the death of about 40% of the inhabitants of Constantinople. Archaeologists have discovered numerous towns and villages that were abandoned during this period. The probable cause of the origin and later spread of the disease was a famine that preceded it several years earlier and was determined by a natural

14  COVID-19 versus historical pandemics

disaster, which physically devastated the population and lowered its resistance as well as a plague of rats spreading the germs. The Plague of Justinian swept through almost the entire world at that time from Europe (including Scandinavia and the Mediterranean) and southern and central Asia, through North Africa to Arabia. Although the apogee of the pandemic fell on the mentioned years of the 40s of the 6th century AD, the disease returned in more or less intense waves until the middle of the 8th century and then made itself known only 600 years later. Justinian’s plague destroyed the Byzantine Empire’s chances of reclaiming Italy, which remained divided and in the hands of the barbarian tribes for centuries to come. The Byzantine Empire’s military power was never recovered thereafter, and the part of the Western Roman Empire previously conquered was fairly quickly lost to the barbarians and the Arabs. A certain remnant of the epidemic is the simplified inheritance law, which has been a component of the reform of legislation initiated even earlier. Justinian’s plague is also believed to have had mainly cultural and religious effects, contributing to the transformation of the Eastern Roman Empire into the Byzantine Empire (Meier, 2016; Mordechai et al., 2019). Against this background, the long-term economic impact is estimated to be moderate, although it should be borne in mind that the population recovered very slowly after each wave of the pandemic. At the same time as in the case of other pandemics, immediately after its end real wages grew quite rapidly (it is estimated that the real increase in wages between the years 540 and 580 was as high as 30%), which led to an amplification of consumption and an improvement in the standard of living of those who survived. The Justinian Plague and the Black Death, described later in the book, also contributed to an increase in the purchasing power of unskilled workers, as analyzed for Egypt and Iraq by Pamuk and Shatzmiller (2014). The aforementioned authors concluded that the increase in real wages that followed the Justinian Plague contributed to the Islamic Golden Age by creating demand for higher-income goods.

The Black Death In the middle of the 14th century, Europe was struck by the plague known as the Black Death. This was the second pandemic of the disease, after Justinian’s plague. Its origin is linked to Central Asia or China. The plague via the Silk Road reached Italian cities via Crimea and Byzantium. In addition to Western Europe, the Middle East, North Africa, and India experienced its effects. Between 1346 and 1353 the Black Death claimed about half the population in Europe, and in some regions (Italy and Spain) it may have been as high as 80%. The population did not return to its pre–Black Death status until 200 years later. The countries of Central and Eastern Europe were relatively little impacted. Particularly high levels of depopulation affected cities where contagiousness and mortality due to residential density were the highest. The cities became impoverished due to the decrease in population, but also due to looting carried

COVID-19 versus historical pandemics 15

out in the absence of their inhabitants, who left their homes in fear of the plague. During the epidemic, the price and wage scissors were opened. As already mentioned, the decimated and impoverished urban population showed significantly less demand for agricultural goods. This resulted in the overproduction of food and a fall in grain prices. On the other hand, the number of craftsmen traditionally residing in cities dropped significantly, which led to an increase in their wages and the prices of industrial goods. This in turn slowed down technical progress and contributed to the stagnation of agricultural production efficiency. Rural residents, although relatively mildly affected by the pandemic in terms of mortality compared to the bourgeoisie, experienced a decline in their standard of living to a far greater extent. They were getting fewer and fewer revenues and forced to pay more and more for industrial goods. This resulted in the abandonment of farms and the migration of peasants to towns, where they were apprenticed to craft professions (Duch, 2020a). This was possible due to the disappearance of serfdom and significant restrictions on the movement (mobility) of peasants in England and Western Europe. The Black Death is perceived as a significant factor that changed the role of the working class and led to the refurbishment of capital accumulation structures and welfare distribution. The production structures shifted from labor to capital based, and productive centers shifted from rural to urban during the medieval period, and the plague had significant effects on these challenges (Bell & Lewis, 2004; Pamuk, 2007, 2020). Ultimately, the consequence of this process was an amplification of the wealth of both towns and villages despite quite frequent initiatives to limit wages through legislation (Penn & Dyer, 1990). Cities that developed after the Black Death showed a rise in demand for food, which, with a lower supply of food compared to the pre-pandemic time, led to higher prices of eatables. This took place in conditions of falling prices of arable land, for which there was no one to sow, and with increasingly lower rents paid by peasants. The lack of manpower in the countryside forced a change in the structure of agricultural production towards the growth of the share of cattle breeding on farmland converted into pasture. The larger scale of livestock farming had in turn contributed to an increase in meat and dairy consumption (O’Brien & Roseberry, 2020). The aforementioned rural depopulation became a stimulus to seek production methods based less on human capital, which meant technical progress and increased efficiency (Economist, 2013). In all Western European countries, the above scenario of falling prices of agricultural goods during the pandemic did not occur. In Central and Eastern Europe change took the opposite direction, in the form of raised burdens on the peasantry and stricter laws limiting mobility. Central and Eastern Europe became the granary of Western Europe, which, however, entailed the preservation of archaic social relations and lack of incentives to improve the efficiency of agricultural production as well as to develop industrial sectors. The Black Death also brought an escalation of anti-Semitic sentiment, especially in Western Europe. Jews were suspected of spreading the

16  COVID-19 versus historical pandemics

plague, hence the frequent cases of expulsion of Jewish communities from cities or even pogroms.

The Spanish flu Between 1918 and 1919 an influenza pandemic called Spanish influenza or Spanish flu swept through Europe, Africa, Asia, and North America. Influenza had primarily extremely significant political effects. Its development is believed to have contributed to the balance of power between the Entente and the bloc of Central Powers during World War I and, ultimately, significantly impacted tipping the scales in favor of France and Britain. This was due to the far higher mortality rate among German and Austrian soldiers compared to the British and French armies (Price-Smith, 2008; Murray et al., 2006). The defeat of Austria-Hungary and Germany led to the disintegration of the first of these powers, and the second was territorially truncated, imposing heavy contributions This, in turn, caused an economic crisis. However, the situation encouraged the radicalization of public sentiment, ultimately elevating the Nazi Party to power. Italy experienced a similar scenario. Social consequences of the Spanish flu are an enhanced interest in the health professions, including the growth of nursing schools. Another effect was to augment the level of hygiene and awareness of the transmission mechanisms of infectious diseases. In the economic sphere, most sectors recorded a significant recession, which was linked not only to the pandemic but also to the effects of the First World War. The impoverishment of the population and the decline in the size of the population, combined with the lack of demand from warring states, led to a sharp collapse in corporate revenues, causing mass unemployment. In fact, the only sector that gained from the pandemic was health care. Drawing on data from 42 countries and ending their time series analysis in 1929, Barro et al. (2020) concluded that on average, in each pandemic-affected country, the Spanish flu caused a cumulative decline in GDP per capita of about 6% and in consumption of 8%, respectively. Similarly, Barro and Ursúa (2008), using similar data but relying on long-run trends, indicated that the Spanish flu was the fourth consecutive economic shock in terms of its impact on GDP and consumption, following World War II, World War I, and the Great Depression. Using a nonlinear model and the same dataset applied by Barro et al. (2020), De Santis and van der Veken (2020) essentially confirmed these calculations, showing that the cumulative decline in economic activity in a typical pandemic country was 7%, with as much as 70% of the economic losses occurring in the first year of the crisis. An important finding of De Santis and van der Veken’s (2020) research is that the pandemic crisis that began in the final phase of World War I exacerbated income inequality both within countries (the crisis disproportionately burdened the low-skilled workers) and between countries (the epidemic developed more rapidly in poorer countries with lower public spending on health and disease control). The cumulative loss estimated for

COVID-19 versus historical pandemics 17

lower-income countries reached as much as 9.8% of GDP, while for developed countries it was about 4.7%. Unlike COVID-19, the Spanish flu engulfed a world at war, which was crucial not only because of the need to divert budget revenues primarily to military action but also because of the government’s information policy regarding the pandemic and the fight against it. The scale of the problem tended not to be disclosed in the states being parties to the conflict, which undoubtedly did not help in the fight against the epidemic. In neutral states, there were no such restrictions on mass media. For this reason, the flu, even though it originated much earlier in another country and at a later stage reached Spain (not involved in the war), was thereafter called the Spanish flu. De Santis and van der Veken’s (2020) study, however, does not confirm the impact of information policy on the economic impact of the pandemic crisis in individual countries. According to Barro et al. (2020), the Spanish flu also brought a significant but periodic escalation of inflation. In addition, these authors found that the mortality rate was negatively correlated with shares’ and Treasury bonds’ rates of return.

Pandemics of the second half of the 20th century In 1956 or early 1957, a pandemic of so-called Asian flu broke out. Its origins were to be found in China. At that time China was not a member of the WHO and did not inform other countries of the threat, with the result that the pandemic spread quite rapidly to Hong Kong and Singapore, then to India, and from there to the UK. As early as mid-1957 the first cases of infection were reported in the United States and in Western Europe (mainly in Germany). The pandemic was particularly dangerous for the young and elderly people (Lionello, 2017), it lasted until 1958, and its containment is due to a vaccine developed by a team led by M. Hilleman (1919–2005). The pandemic mainly affected Asian countries, causing a decline in investment and a slowdown in economic growth in the 1960s (Bergeaud et  al., 2015), but other regions of the world were also impacted. The Asian flu is credited with the collapse in world stock markets evidenced by the Dow Jones Industrial Average index losing as much as 15% of its value in the second half of 1957 (Pinsker, 2020). The stock market slump was merely a reflection of the situation in the real sphere of the economy, where many factories, offices, and mines were closed for several months due to worker absenteeism and the threat of a spreading pandemic. The Asian flu also hit public finances. The decline in economic activity triggered a drop in tax receipts, with a sharp increase in sickness benefit payments (Jackson, 2009). In 1957 the British economy was in very good condition, but the pandemic changed things enough to record a 2.4% drop in GDP already in 1958 (Partington, 2020). The Asian flu was also the first pandemic to be deterred thanks to international cooperation under the aegis of the WHO. Nevertheless, its total cost to all affected countries is estimated to be as high as 3.1% (Jonas, 2013), meaning that developing countries suffered relatively

18  COVID-19 versus historical pandemics

greater losses. The Asian influenza virus, despite the containment of the pandemic, was subject to mutations. It was named the Hong Kong flu because of the discovery of a strain of the virus in that country in 1967. In a relatively short period of time due to soldiers returning from the Vietnam War, the disease reached the United States and then Japan and Europe. Influenza had a fairly mild course, although it was particularly badly endured by children, and the mortality rate among them was the highest. Economic took a relatively low value, hovering around 0.5% of GDP (Jonas, 2013). These were mainly related to staff absenteeism and periodic university closures. School closures and forced quarantines were not applied. The Hong Kong flu was also the first pandemic, the spread of which was aided by the development of air transport (SaundersHastings & Krewski, 2016). In May 1977, the disease later named the Russian flu (because it took its greatest toll in the Soviet Union), affecting mostly people under the age of 26, was detected in northern China. The plaque soon reached Britain and the United States, with outbreaks mainly in schools. The pandemic did not cease until 1979. As with COVID-19, the Russian flu was suspected to have escaped from medical laboratories (Gregg et al., 1978). In 2003, the SARS pandemic broke out. The focus of this pandemic was China, where already in November  2002 the first patient was reported in Guangdong province. The disease crossed China’s borders, reaching Vietnam, Canada, and some other countries. Chinese authorities banned press releases about the pandemic, and medical services provided information about the disease with long delays, allowing SARS to spread. Although SARS lasted less than a year, it caused huge losses to air carriers (estimated at around 7  billion USD) and their related companies as well as to tourism. Other sectors were not spared either. For example, it impacted insurance companies, which were forced to cut back on typical direct sales. Consumption from individuals trapped in their homes during the pandemic also declined. Closed kindergartens and schools prevented parents of children from working, which affected the output and the efficiency of capital use. Essentially, all demand-oriented sectors had changed and affected other sectors due to the changing income levels and rising unemployment (Siu & Wong, 2004; Yang & Chen, 2009). A study carried out on the basis of data from Taiwan found that school closures caused 27% of households to have at least one person absent from work for that reason, and 18% of households saw their income fall. In contrast, a 2009 study by the Brookings Institution indicated that closing schools in the United States due to a pandemic would cost between 5.2 billion and 23.6 billion USD. If schools were not open for months, losses were estimated as high as 0.3% of GDP. School closure is considered by many studies to be the factor most responsible for the negative economic impact of the crisis (Keogh-Brown et  al., 2008). The fear of contagion discourages people from using cultural institutions, hotels, and sports and recreation centers. The pandemic primarily hit industries where the human factor is important and sectors that make money by moving customers around. The World Bank estimated that China’s

COVID-19 versus historical pandemics 19

losses from SARS reached 14.8  billion USD and at the global level it was 33 billion USD (Begley, 2013). Another source (Bell  & Lewis, 2004) indicated losses of 15  billion USD (0.5% of GDP) for all Asian countries gripped by the pandemic. Of these, Hong Kong was impacted the hardest with a 2.79% decline in GDP in 2003. Many economies experienced a sustained lowering of agricultural production, reaching 9% in China and 11% in South Korea (Ceylan & Ozkan, 2020). As already mentioned, the SARS epidemic, fortunately, lasted a relatively short time and claimed comparatively few victims, so the financial losses were not as great as, for example, in the case of the Spanish flu; however, they were long-lasting. However, the pandemic pertained not only to tourism (tourist traffic decreased in some areas by up to 70%) and catering (restaurant revenues in Japan and Hong Kong fell by about 50%), but also to other industries, not excluding the financial sector. The relatively rapid resolution of the pandemic threat was due to the widespread isolation of the infected (mainly health care workers), the self-discipline of the population, and vaccination. Asian countries then decided to reject international aid and defeated the epidemic by radical means. This ensured that the wave of tourists coming to these countries did not diminish and the investment inflows did not slow down (Lionello, 2017). Avian influenza was recognized and distinguished from other pandemics as early as 1878, and the number of outbreaks of the disease increased as the number of poultry grew. Before the 1990s infections were rather sporadic; however, they were accompanied by high bird mortality. The first cases of human infection with bird flu were reported in Hong Kong in 1997 from where the disease spread to other Asian countries. Only 2003 was recognized as the onset of the dissemination of avian influenza that affected as many as 60 countries over the next two years. The disease was transmitted by wild and farmed birds, but also by cats. Despite the periodic activation of different strains of avian influenza even in 2020, it can be considered that it has been brought under control thanks to the vaccination system and the process of annihilation of infected animals supported by public funds (although to a rather limited extent). Nevertheless, the disease has had a measurable negative economic and social impact. These include the crisis of traditional (backyard) poultry farming. It was considered more vulnerable to infection than poultry raised in specialized modern facilities, because the latter does not come into contact with wild birds and people, and because it participates in vaccination campaigns. At the same time, it should be mentioned that in some of the affected countries, domestic poultry production accounted for almost 100% of poultry consumption (Cambodia). In Indonesia and Vietnam, it was around 65%. Of the countries most affected by avian outbreaks, only China and Thailand represented a different poultry production structure, i.e., based on large specialized enterprises. However, this did not save Thailand from such a large drop in production that the country lost its position as the fifth-largest poultry producer in the world. The elimination of huge numbers of bird flocks had a negative impact on the balance of protein consumption of the Asian population, as up to 20% of it came from

20  COVID-19 versus historical pandemics

poultry. In 2005 losses to Asian countries from avian influenza were estimated at about 10  billion USD (McLeod et  al., 2005). They were permanent and mainly referred to small poultry producers. In some countries, no compensation was paid for cull animals, while in others the amounts were 60%–70% lower than would have been necessary to restore production. This was despite the Food and Agriculture Organization of the United Nations (FAO) recommendation that compensation should be at least 50% of the market value of the poultry killed. As already mentioned, the avian flu pandemic had its greatest impact on the economic situation of the poorest sections of society. In particular, this resulted in lower standards of living and development for children in Asian countries, which in turn translated into worse health outcomes and a decline in the proportion of children attending school (Alders et al., 2014). The pandemic did not spare egg producers, as the prices of eggs fell sharply. This led to a significant reduction in production, a decline in income, and an increase in corporate debt. After the pandemic, egg prices surpassed pre-pandemic levels in part due to market consolidation (Sariozkan et al., 2009). As with other pandemics, the psychological factor was not insignificant. In justified or unjustified fear of infection, consumers reduced their consumption of poultry meat (in France by 20%, in Turkey by 50%, and in some regions of Italy even by up to 70%), while the fall in prices was slowed down by the previously described culling of flocks where outbreaks were identified. Avian influenza also had and continues to have an international dimension, as it has been the practice to suspend imports from countries where influenza has been detected. Apart from the poultry sector, the tourism and hospitality industry also lost significantly from the pandemic, while pharmaceutical companies developing vaccines gained. The stock market reaction corresponded to a change in the level of a sector risk, which becomes particularly important during a pandemic. Noteworthy, however, was the increase in the stock prices of American poultry corporations and chains of restaurants serving poultry dishes, which can be explained by the expectation that these entities will take the place vacated by small poultry producers who did not manage to survive the crisis (Trębski & Zdziechowska, 2005). In 2009 came swine flu, the virus of which was isolated as early as 1930, while it began to be treated as a significant threat only after the escalation of cases of infection in North America between 1997 and 2002. In pigs, the disease is transmitted relatively easily, but the mortality rate is estimated to be quite low. However, the virus is particularly dangerous for the elderly, children, and immunocompromised people. The disease began to develop in earnest in 2009 in Mexico and the United States. The swine flu pandemic lasted for 19 months until 2010. Swine flu generally did not bring restrictions to the operation of passenger transport and tourism. In a relatively small number of cases, quarantine was applied for people arriving from countries where outbreaks were discovered. The governments did not introduce the obligation to wear masks and use social distance. Schools and workplaces remained open for the most part, although countries such as China, the United States, and the United Kingdom put detailed instructions in place in case an outbreak develops.

COVID-19 versus historical pandemics 21

As with any pandemic crisis, there was a decrease in the mobility of people who, fearing contagion, gave up travel. Airlines and tourism suffered significantly. As in the case of avian flu, the disease became a pretext for the temporary suspension of pork imports from countries where swine flu was detected. To the greatest extent, the pandemic hit the meat industry which also translated into the market valuation of companies related to this sector and a change in consumer behavior and their assessment of the prospects for the economic and financial situation (individual and economy). From an economic point of view, the latter two effects appeared to be more important than the shock immediately following a pandemic outbreak. At the same time, swine flu has confirmed that the key issue was to implement solutions to stop the spread of the pandemic in poor communities. Also, the effects in terms of reduced living standards and health care levels influenced developing countries the most (McKibbin, 2009). The total cost of swine flu is assessed at 0.5%–1.5% of the GDP of the affected countries. Accurate estimates are quite difficult because the pandemic coincided with the global financial crisis (Saunders-Hastings & Krewski, 2016). In 2012 the MERS (Middle East Respiratory Syndrome) virus developed. The outbreak was in the city of Jeddah, Saudi Arabia, and tests confirmed its zoonotic nature. MERS largely affected hospital workers, and they were health care units in which the disease spread most rapidly. This was the reason for the closure of many facilities, which further complicated the fight against the pandemic. MERS cases were reported in Qatar, Bahrain, Jordan, Kuwait, and Tunisia. The negative effects of MERS in the different countries experienced by the plague were far greater than those of SARS. According to Ceylan and Ozkan (2020), the decline in GDP mainly affected the following countries: Saudi Arabia (–16%), Qatar (–25%), United Arab Emirates (–12%), and Kuwait (–32%). Three years later, South Korea also became a region where the disease was growing rapidly. In this country losses from the pandemic to tourism and related sectors alone were estimated at 2.6 billion USD (i.e., approx. 0.2% of the GDP). These losses occurred because scheduled tourist trips were cancelled rather than postponed (Heesoo, 2019). At the same time, it should be noted that the SARS and MERS outbreaks were much smaller in scope than the Spanish and Asian influenza and did not result in such large economic losses (Pinsker, 2020). The Ebola virus was identified in Zaire and Sudan in 1976. Its name comes from the river in the vicinity of which it was discovered. Characterized by high contagiousness and mortality (about 4 million people died as a result of infection), the virus mainly affected countries in West Africa (the highest number of victims was recorded in 2014), and its containment is mainly due to the invention of a vaccine in 2016. It is estimated that the expenditure incurred to fight the Ebola virus epidemic in Africa alone reached approximately 32 billion USD. There were medical costs, business interruption, quarantine, insurance, and social costs associated with the loss of the main breadwinners for about 200,000 families. Some of the poorest regions in the world (Sierra Leone, Guinea, and Liberia) were further pauperized (Piechowiak, 2014b).

22  COVID-19 versus historical pandemics

In 2015 Brazil and other South American countries were attacked by the zika virus, first isolated already in 1947 in Uganda. The diagnosis referred initially to monkeys and in 1952 also to humans. For several decades, a dozen cases each were identified in African, Asian, and Pacific Island countries. However, it was not until French Polynesia in 2013 and Brazil in 2015 that the epidemic appeared to develop on a wider scale (WHO, 2016). While zika had a relatively low mortality rate, an extremely dangerous complication is microcephaly, the incidence of which had increased dramatically in pandemic areas. The zika virus impacted mainly the economy of Brazil, host of the 2016 Olympic Games. This is mainly due to a much lower-than-expected inflow of tourists to the country. This translated into a decline in the value of listed shares of companies linked to this sector of the economy (e.g., RCL). An extensive information campaign carried out by Brazilian authorities that only pregnant women were at risk had not helped much. Instead, consistent with all scenarios relating to previously observed pandemics in the 20th century, the value of pharmaceutical and health care–related companies increased substantially (Chesler, 2016).

COVID-19 versus selected pandemics Pandemics are viewed as specific crisis phenomena that affect the global economy, individual countries, sectors, or economic agents to varying degrees. It is characteristic that the primary source of a pandemic is located outside the economic or financial system; hence, it is more difficult for economists to identify it. Pandemics differ primarily in their scope, scale of impact, speed of spread, and duration. These are the elements of the “anatomy” of a pandemic that is most often pointed to as variably distinctive features of a pandemic. Nonetheless, the key to understanding the differences between individual pandemics and their impact on the socioeconomic environment seems to be to embed them in a broader context (cf. Table 2.2). Whereas previous pandemics have been more limited to particular regions or countries, the ongoing COVID-19 pandemic will undoubtedly have many devastating global effects. Undoubtedly, the process of globalization has been a key element that has accelerated the medical spread of COVID-19, but it has also made the dimension of the economic and social consequences of the pandemic so broad in scope. These global effects of COVID-19 concern, among other things, the labor market, international trade, investment, capital flows, and political consequences and are due, but not limited, to the numerous restrictions imposed in Europe and the United States on mobility and economic activities. Given this general historical overview, it can be firmly stated that governments, central banks, and international financial institutions should focus on three issues in the near future. First, from the perspective of long-term economic development, it is essential to control persistent distortions in the labor market and to support the industry and the service sector with financial tools.

COVID-19 versus historical pandemics 23 Table 2.2  How different is COVID-19? Feature

Influenza pandemic SARS (1918–1919) (2003)

COVID-19 COVID-19 (1 March 2020) (31 May 2021)

Number of fatalities Primary containment measure

Up to 50 million

774

2,996

3.9 million

Social distancing; solutions differ among jurisdictions Little

Social distancing (China, Hong Kong) Little

Local lockdown (Wuhan, Lombardy) Limited market selloff

Global lockdown

Real economy consequences

Little

Little

Supply chain disruption

Economies losses (est.)

6 ppt lower global 0.1% loss in 0.3–2.2% loss GDP growth annual global in global 18% decline in GDP GDP manufacturing 1–2 ppt loss (depending in Chinese on scenario) GDP World War I: Chinese growth Highly globalized economies, high share of accelerating integrated cross-border supply manufacturing chains; high share of service sector in GDP sector in GDP in advanced creation in economies; high leverage in advanced parts of real sector economies

Financial impact

Context

Sharp and radical tightening in financial conditions Global supply chain disruption; sudden stop in demand 3.4–7.6% global GDP decline

Source: Authors’ compilation based on Barro et al. (2020), Correia et al. (2020), Hai et al. (2004), Lee & McKibbin (2004), and Maliszewska et al. (2020).

The second issue concerns building economic and social trust, for which moral support for individuals and societies is essential. Without confidence, none of the sectoral impositions will be effective in economic recovery, both in terms of demand and supply. Third, the COVID-19 experience has shown the need to reorganize health care services. It is not difficult to say that the COVID19 experience will change many economic and social dynamics. Pain relief requires proper time management and financial planning, and we have learned the need to prepare for the future.

Concluding remarks Every pandemic has a negative effect in terms of a decrease in GDP; it also brings about serious social and financial losses and can therefore be perceived

24  COVID-19 versus historical pandemics

as a particular crisis situation (cf. Chapter  3). However, this does not mean that all industries incur losses. Some sectors experience unprecedented revenue and profit growth during this time. These primarily include health care, pharmaceuticals, telecommunications, and the manufacturing of necessities. Thus, as GDP declines, there is a significant change in its industry structure. Also, a downturn in financial markets does not mean losses for all investors, which is due to the emergence of financial instruments that make it possible to make profits in the environment of rapidly falling stock exchange indices. Pandemics have occurred and continue to occur, and they probably will not be avoided in the future either. However, they are marked by some similar scenarios and outcomes, which allows lessons to be learned for the future. Key issues in this context remain: identifying channels of the social and economic impact of the pandemic, adapting risk management systems to the changing reality, and developing a path out of the pandemic crisis. This solution should ensure not only a return to the values recorded before the outbreak of the plaque in the most important macroeconomic parameters, but also an improvement of quality of life. At the same time, the extent of the recession is determined by how quickly the world deals with the pandemic, the balance of casualties, and the social impact. Every pandemic also has the unquantifiable effect of significantly increasing risk aversion. Only a change in expectations and an improvement in sentiment provide a reasonable basis for concluding that the economy is on a path out of recession (Begley, 2013).

References Alders, R., Awuni, J.A., Bagnol, B., Farrell, P., & Haan, N. (2014). Impact of avian influenza on village poultry production globally. EcoHealth, 11(1), 63–72. Retrieved from: https:// doi.org/10.1007/s10393-013-0867-x. Antrás, P., Redding, S.J.,  & Rossi-Hansberg, E. (2020). Globalization and pandemics. NBER Working Papers, No. 27840. National Bureau of Economic Research, Cambridge. Barro, R.J., & Ursúa, J.F. (2008). Macroeconomic crises since 1870. Brooking Papers in Economic Activity, 39, 255–350. Retrieved from: https://doi.org/10.1353/eca.0.0000. Barro, R.J., Ursúa, J.F., & Weng, J. (2020). The coronavirus and the Great Influenza Pandemic. Lessons from the “Spanish Flu” for the Coronavirus’s potential effects on mortality and economic activity. NBER Working Paper, No. 26866. National Bureau of Economic Research, Cambridge. Begley, S. (2013). Flu-conomics: The next pandemic could trigger global recession. Reuters. Retrieved from: www.reuters.com/article/us-reutersmagazine-davos-flu-economyidUSBRE90K0F820130121 [28.02.2021]. Bell, C., & Lewis, M. (2004). The economic implications of epidemics old and new. World Economics, 137–174. Bergeaud, A., Cette, G., & Lecat, R. (2015). GDP per capita in advanced countries over the 20th century. Banque de France Working Paper, No. 549. Retrieved from SSRN: https:// ssrn.com/abstract=2602267 or http://dx.doi.org/10.2139/ssrn.2602267. Ceylan, R., & Ozkan, B. (2020). The economic effects of epidemics: From SARS and MERS to COVID-19. Economics: Research Journal in Advanced Humanities, 21–29. Retrieved from: https://doi.org/10.58256/rjah.v1i2.132

COVID-19 versus historical pandemics 25 Chesler, J. (2016). Gospodarcze skutki epidemii wirusa Zika. 5 February 2016. Retrieved from: www.paszport.ws/gospodarcze-skutki-epidemii-wirusa-zika [03.01.2021]. Correia, S., Luck, S., & Verner, E. (2020). Pandemics depress the economy, public health interventions do not: Evidence from the 1918 flu. Mimeo. De Santis, R., & van der Veken, W. (2020). Economic expected losses and downside risks due to the Spanish flu, VOX EU. CEPR. Retrieved from: https://voxeu.org/article/ economic-expected-losses-and-downside-risks-due-spanish-flu [04.03.2021]. Duch, W. (2020a). Czarna śmierć. Przyczyny i skutki epidemii dżumy, która była największą zarazą w historii świata. Retrieved from: https://historia.org.pl/2020/05/16/czarnasmierc-przyczyny-i-skutki-epidemii-dzumy-ktora-byla-najwieksza-zaraza-w-historiiswiata/ [18.02.2021]. Duch, W. (2020b). Zaraza Antoninów. Epidemia, która zdziesiątkowała rzymskie legiony i zabiła Marka Aureliusza. Retrieved from: https://historia.org.pl/2020/05/14/zarazaantoninow-epidemia-ktora-zdziesiatkowala-legiony-i-zabila-marka-aureliusza/ [10.03.2021]. Economist – the Economist (2013). Plagued by dear labour. The Economist. London, 21 October 2013. Retrieved from: www.economist.com/free-exchange/2013/10/21/plaguedby-dear-labour [30.11.2020]. Gregg, M.B., Hinman, A.R.,  & Craven, R.B. (1978). The Russian flu: Its history and implications for this year’s influenza season. JAMA, 240(21), 2260–2263. Retrieved from: https://doi.org/10.1001/jama.1978.03290210042022. Hai, W., Zhao, Z., Wang, J., & Hou, Z.G. (2004). The short-term impact of SARS on the Chinese economy. Asian Economic Papers, 3(1). Heesoo, J., Maskery, B.A., Berro, A.D., Rotz, L.D., Lee, Y-K., & Brown, C.M. (2019). Economic impact of the 2015 MERS outbreak on the Republic of Korea’s tourism-related industries. Health Security, 7(2), 100–108. Retrieved from: https://doi.org/10.1089/ hs.2018.0115. Honigsbaum, M., & Lakshmi, K. (2020). Taking pandemic sequelae seriously: From the Russian influenza to COVID-19 long-haulers. Perspectives. The Art of Medicine, 396(10260), 1389–1391. Retrieved from: https://doi.org/10.1016/S0140-6736(20)32134-6 Jackson, C. (2009). History lessons: The Asian flu pandemic. The British Journal of General Practice: The Journal of the Royal College of General Practitioners, 59(565), 622–623. Retrieved from: https://doi.org/10.3399/bjgp09X453882. Jonas, O.B. (2013). Pandemic Risk. World Bank. Retrieved from: www.worldbank.org/con tent/dam/Worldbank/document/HDN/Health/WDR14_bp_Pandemic_Risk_Jonas. pdf [18.01.2021]. Keogh-Brown, M., McDonald, S., Edmunds, J., Beutels, P., & Smith, R. (2008). The macroeconomic costs of a global influenza pandemic. Retrieved from: www.gtap.agecon. purdue.edu/resources/download/3828.pdf [10.02.2021]. Kuliszer, J. (1961). Powszechna historia gospodarcza średniowiecza i czasów nowożytnych, Warszawa: Książka i Wiedza. Last, J.M. (1988). A Dictionary of Epidemiology. 2nd ed. Oxford: Oxford University Press. Lee, J.W., & McKibbin, W. (2004). Estimating the global economic costs of SARS. In: S. Knobler, A. Mahmoud, S. Lemon, A. Mack, L. Sivitz, & K. Oberholtzer (eds.), Learning from SARS: Preparing for the Next Outbreak. Washington, DC: The National Academies Press. Lionello, L. (2017). Economics and epidemics: An historical analysis on the effects of infectious diseases on economic development of four major outbreaks. BSc thesis on Macroeconomics. Retrieved from: https://tesi.luiss.it/id/eprint/19837 [14.12.2020].

26  COVID-19 versus historical pandemics Maliszewska, M., Mattoo, A., & van der Mensbrugghe, D. (2020). The potential impact of COVID-19 on GDP and trade. Policy Research Working Paper, No. 9211. World Bank. McKibbin, W.J. (2009). The Swine flu outbreak and its global economic impact. Brookings, 4 May 2009. Retrieved from: www.brookings.edu/on-the-record/the-swine-fluoutbreak-and-its-global-economic-impact/ [22.12.2020]. McLeod, A., Morgan, N., Prakash, A., & Hinrichs, J. (2005). Economic and social impacts of avian influenza. FAO. Retrieved from: www.fao.org/avianflu/documents/Economicand-social-impacts-of-avian-influenza-Geneva.pdf [14.12.2020]. Meier, M. (2016). The ‘Justinianic Plague’: The economic consequences of the pandemic in the eastern Roman empire and its cultural and religious effects. Early Medieval Europe, 24(3), 267–292. Retrieved from: https://doi.org/10.1111/emed.12152 Mordechai, L., Eisenberg, M., Newfield, T.P., Izdebski, A., & Kay, J.E. (2019). The Justinianic Plague: An inconsequential pandemic? PNAS, 116(51), 25546–25554. Retrieved from: https://doi.org/10.1073/pnas.1903797116 [12.01.2021]. Morens, D.M., Folkers, G.K., & Fauci, A.S. (2009). What is a pandemic? The Journal of Infectious Diseases, 200(7), 1018–1021. Murphy, V. (2005). Past pandemics that ravaged Europe. BBC News, 7 November  2005. Retrieved from: http://news.bbc.co.uk/2/hi/health/4381924.stm. [10.12.2020]. Murray, C.J., Lopez, A.D., Chin, B., Feehan, D., & Hill, K.H. (2006). Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918– 20 pandemic: A  quantitative analysis. Lancet, 368(9554), 2211–2218. Retrieved from: https://doi.org/10.1016/S0140-6736(06)69895-4. O’Brien, J., & Roseberry, W. (2020). Golden Ages, Dark Ages: Imagining the Past in Anthropology and History. Oakland: University of California Press. ISBN: 9780520327443 (originally edited in 1991). Pamuk, S. (2007). The Black death and the origins of the great divergence across Europe, 1300–1600. European Review of Economic History, 11(3), 289–317. Pamuk, S. (2020). Economic impact and consequences of the plagues on the medieval middle east. Islamic Law Blog, 5 May 2020. Retrieved from: https://islamiclaw.blog/2020/05/05/ economic-impact-and-consequences-of-the-plagues-on-the-medieval-middle-east-2/ [04.01.2021]. Pamuk, Ş., & Shatzmiller, M. (2014). Plagues, wages, and economic change in the Islamic Middle East, 700–1500. The Journal of Economic History, 74, 196–229. Retrieved from: www.jstor.org/stable/24550555 [20.01.2021]. Partington, R. (2020). The UK’s biggest quarterly economic declines. Retrieved from: www.theguardian.com/business/2020/may/13/lessons-from-the-past-uk-biggest-quar terly-economic-declines [01.03.2021]. Penn, S.A.C., & Dyer, Ch. (1990). Wages and earnings in late medieval England: Evidence from the enforcement of the labour laws. The Economic History Review, 43(3), 356–357. Retrieved from: https://doi.org/10.1111/j.1468-0289.1990.tb00535.x. Piechowiak, Ł. (2014a). Czarna śmierć, tyfus, ospa i ebola – ekonomiczne skutki epidemii. 18 October  2014. Retrieved from: www.bankier.pl/wiadomosc/Czarna-smierc-tyfusospa-i-ebola-ekonomiczne-skutki-epidemii-7218980.html [21.02.2021]. Piechowiak, Ł. (2014b). Ekonomiczne skutki wybuchu epidemii Eboli. 23 October 2014. Retrieved from: https://dyskusja.biz/gospodarka/ekonomiczne-skutki-wybuchu-epidemiieboli-42494[03.01.2021]. Pinsker, J. (2020). How to think about the plummeting stock market. The Atlantic. Retrieved from: www.theatlantic.com/business/archive/2020/02/coronavirus-stock-market/607216/ [28.02.2021].

COVID-19 versus historical pandemics 27 Popper, K. (1934). Logik der Forschung. Wiesbaden: Verlag von Julius Springer, Vien. Price-Smith, A.T. (2008). Contagion and Chaos. Cambridge: MIT Press. ISBN: 978-0-26266203-1. Sariozkan, S., Yalçin, C., Cevger, Y., Aral, Y., & Sipahi, C. (2009). The financial impacts of the avian influenza outbreaks on Turkish table egg producers. World’s Poultry Science Journal, 65, 91–96. Retrieved from: https://doi.org/10.1017/S0043933909000075. Saunders-Hastings, P.R., & Krewski, D. (2016). Reviewing the history of pandemic influenza: Understanding patterns of emergence and transmission. Pathogens, 5(466). Retrieved from: https://doi.org/10.3390/pathogens5040066. Sieroń, A. (2020). Czy pandemia COVID-19 spowoduje zapaść globalnej gospodarki? 14 marca 2020. Retrieved from: https://mises.pl/blog/2020/03/14/sieron-czy-pandemiaCovid-19-spowoduje-zapasc-globalnej-gospodarki/ [02.03.2021]. Siu, A., & Wong, Y.C.R. (2004). Economic impacts of SARS: The case of Hong Kong. Asian Economic Papers, 3(1), 62–83. Retrieved from: https://doi.org/10.1162/1535351041747996 Stedman’s Medical Dictionary. 28th ed. (2006). Philadelphia: Lippincott, Williams & Wilkins. Taleb, N. (2007). The Black Swan: The Impact of the Highly Improbable. New York: Random House. Trębski, K.,  & Zdziechowska, M. (2005). Hossa na grypie. Wprost, 30 October  2005. Retrieved from: www.wprost.pl/tygodnik/82351/Hossa-na-grypie.html [18.12.2020]. University of Maryland Pathogenic Microbiology Web page (2009). Retrieved from: www. life.umd.edu/classroom/bsci424/HostParasiteInteractions/HostParasiteSummary.htm [24.08.2021]. WHO – World Health Organization. (2016). The history of zika virus. Retrieved from: www.who.int/news-room/feature-stories/detail/the-history-of-zika-virus [10.12.2020]. Wucker, M. (2016). The Gray Rhino: How to Recognize and Act on the Obvious Dangers We Ignore. London: St. Martin’s Press. Yang, H.-Y.,  & Chen, K.-H. (2009). A  general equilibrium analysis of the economic impact of a tourism crisis: A case study of the SARS epidemic in Taiwan. Journal of Policy Research in Tourism, Leisure and Events, 1(1), 37–60. Retrieved from: https://doi.org/10.1080/ 19407960902738313

3 Banking crises Theory, practice, and the special case of a pandemic as a source of a banking crisis

Banking crisis phenomenon Banking crises are probably the most well-recognized and documented type of economic crisis, and their anatomy is well-known, from the source through the channels of transmission of the crisis to the real sphere of the economy. This makes the subject of analysis – the impact of the COVID-19 pandemic on the European banking sector – even more interesting, as it allows us to look at the issue from the perspective of the banking crisis. This approach also lays the foundation for considering a change in the business model of banks in Europe (cf. Chapter 6). One of the most important questions for crisis situation researchers concerns the special nature of banks as economic entities, what features make banks different from other institutions, and what phenomenon makes them institutions of special concern on the part of supervisory and regulatory authorities. Table 3.1 summarizes selected theoretical concepts that provide the rationale for the special interest in the banking crisis and the measures aimed at stabilizing this economy sector. A banking crisis is identified as a situation in which a significant part of the banking sector loses its stability. The terminology of banking crises is systematically evolving. The multifaceted dimension of banking crises and their individual nature means that almost every new case expands the existing definitions with additional elements that detail the meaning of the processes taking place. Bordo et al. (2001) specify, for example, that for an episode to qualify as a banking crisis, one should observe financial distress resulting in the erosion of most or all of the aggregate banking system capital. According to the definition of the World Bank (2020), a banking crisis occurs when many banks in a country are in serious solvency or liquidity problems at the same time – either because they are all hit by the same outside shock or because failure in one bank or a group of banks spreads to other banks in the system.

DOI: 10.4324/9781003351160-3

Banking crises 29 Table 3.1  Review of selected theoretical concepts behind the banking crisis Concept

Author(s)

Description

Special role of bank

Benston (2004), Corrigan (1982)

Banks play a fundamental role in supporting economic development and growth and in the functioning of the payment and settlement system. They are the primary channel for monetary policy transmission. A characteristic feature of traditional commercial banking is that banks are highly susceptible to loss of liquidity and solvency (financing lending activities with short-term deposits, low cash to asset ratio). Banks are an important source of liquidity for market participants. The authors assume the existence of two equilibrium points in the banking sector, with the occurrence of each point depending on the formation of depositors’ expectations. A bank run occurs as a “selffulfilling prophecy” as a result of customers’ belief that the bank will fail. A deposit guarantee scheme is an effective instrument for counteracting the run of depositors, but its functioning is connected with the problem of moral hazard, as a result of which deposit guarantee may be a source of instability in the banking sector. A bank run occurs as a result of a correction in depositors’ perception of the risk of bank failure. The reason for this adjustment is the disclosure of negative information about the bank. An additional assumption in Gorton’s model is that there is a correlation between the value of macroeconomic indicators and the occurrence of a bank panic. A bank run is the result of business cycles. The worsening of the economic situation is a signal to some depositors (those who know about and anticipate a run on the bank) to withdraw their deposits early. Other depositors, observing the queues forming in front of the banks, join the run. In the banking sector, there is an uneven distribution of information between the bank and depositors (asymmetry of information). Depositor run occurs as a result of the inability of one group of depositors to identify the reason for increased withdrawals by another group of depositors.

Benston and Kaufman (1994)

Diamond and Dybvig (1983)

Bank run

Cooper and Ross (2002)

Gorton (1988)

Allen and Gale (1999)

Chari and Jagannathan (1988)

(Continued )

30  Banking crises Table 3.1 (Continued) Concept

Author(s)

Description

“Too big to fail” paradigm

Conover (Currency There are banks in the financial system that are so Comptroller) “large” or “important” that their failure can have systemic implications, threatening the stability of the entire financial system. Therefore, such banks must be subject to additional protection by institutions that stabilize the financial system. Stern and Feldman The TBTF problem is a manifestation of the (2004) so-called policy inconsistency over time and stems from the lack of credibility of economic politicians with respect to their commitment not to bail out large banks at risk of failure. Bank customers convinced of the propensity of politicians and institutions stabilizing the financial system to deviate from this commitment do not monitor the financial situation of banks, which further reinforces the TBTF problem.

Source: Authors’ compilation.

The authors of the definition also specify that such a situation may be effectuated by a large number of bankruptcies and corporate insolvencies, which in turn translate into the untimely servicing of credit debts, deterioration in the quality of the loan portfolio, the creation of specific provisions, and a downturn in banks’ capital adequacy. Marschall (2009) makes a distinction between “the classic banking crisis and the secondary banking crisis”. He claims that the classic crisis is that which develops in the banking sector and spreads to other areas of the economy, whereas the secondary banking crisis develops in areas outside the banking system, and banks enter into a crisis only as a result of forces external to them. He adds, however, that in most crises it is difficult to assess whether they can be classified as one type or the other. Laeven and Valencia (2013) define a banking crisis as: an event that meets two conditions: 1) Significant signs of financial distress in the banking system (as indicated by significant bank runs, losses in the banking system, and/or bank liquidations). 2) Significant banking policy intervention measures in response to significant losses in the banking system.

Banking crises 31

They therefore pay attention both to what is happening in the banking system itself, but also to the reaction of institutions stabilizing the banking sector (governments, central banks, supervisory authorities). Grossman (2016) claims that a banking crisis occurs when: (1) a high proportion of banks fail (e.g. the United States during the Great Depression, Austria following 1873); (2) an especially large or important bank fail (e.g. France’s Union Générale in 1881, Scotland’s City of Glasgow Bank in 1878, Austria’s Credit Anstalt in 1931); or (3) failures of the type described in (1) or (2) were prevented only by extraordinary and direct intervention by the government or some other actor, through the declaration of a bank holiday or a reorganization or nationalization of the banking sector (e.g. Italy’s banking reorganization following the crisis of 1931, the rescue of Baring Brothers in England in 1890). Grossman’s definition is vague, as it raises further questions, including what a large bank is, what intervention can be defined as extraordinary, etc., and thus does not allow one to understand the anatomy of a banking crisis. Demirgüc-Kunt and Detragiache (1998) propose a more precise definition. Their study assumes that a banking crisis occurs only if at least one of the following conditions exists: (i) “[t]he ratio of nonperforming assets to total assets in the banking system exceeded 10  percent”; (ii) “[t]he cost of the rescue operation was at least 2% of GDP”; (iii) “[b]anking sector problems resulted in a large scale nationalization of banks”; and (iv) “[e]xtensive bank runs took place or emergency measures such as deposit freezes, prolonged bank holidays, or generalized deposit guarantees were enacted by the government in response to the crisis.” Caprio and Klingebiel (1996) cite that one of the earliest crises on record goes back to 33 A.D. when a confluence of factors – the sinking of some ships loaded with uninsured commodities, a slave revolt, fraud, defaults on foreign debt, liquidity-draining government policies, and a bout of domestic and international contagion – shut down several banking houses in Rome. . . . Tiberius Caesar resolved the crisis by providing government funds to reliable bankers and certain debtors, forgiving some interest, and suspending government policies that had temporarily drained liquidity. Most of the institutions recovered. Although the origins of banking can be traced back to ancient times – the Sumerian civilization, Mesopotamia, Egypt, ancient Greece, and the Roman Empire – it is thought that the term bank is derived from the Italian word banco and comes from the 12th century, during which in Italian cities, and later throughout Europe, there occurred a widespread practice of depositing bullions with goldsmiths who charged a fee and could return the deposit at any time.

32  Banking crises

They became the prototype of today’s commercial banks. Credits in the Middle Ages were almost entirely of a consumer nature, specially granted to lords and cities, and were mainly intended for war or robbery operations. Merchant credits played a much less important role at the time. Caprio and Honohan (2012) note that the origins of the first significant problems of banks can be traced to the specifics of their functioning in the Middle Ages. They explain that clients’ trade was subjected to a variety of shocks – wars, plague, shortage of coins, losses in trade (e.g., ships sinking or being plundered), defalcation by borrowers, etc. – that made lending hazardous. And depositors faced the risk that their bankers would not survive these shocks, or would themselves abscond with funds. In order not to lose valuable trading privileges and to acquire new ones, Italian bankers were forced to grant large loans to kings and princes. The main problem, however, consisted in the refusal of the magnates to repay their debts. Dinesen (2020) reports that, for instance, the Peruzii lent 600,000 gold florins and the Bardi company 900,000 florins to King Edward III Plantagenet of England (at the same time Pope Clement VI bought the entirety of Avignon for 80,000 florins). Edward III’s insolvency in 1339 led to one of the greatest banking crises of the period and the collapse of many Italian banking houses, notably the Peruzzi and the Acciaiuoli in 1343 and the Bardi in 1346. Monarchs, especially Spanish kings, in order to get rid of their financial obligations, often resorted to state bankruptcy, most often invoking the canonical prohibition of usury. They deprived their creditors of their legitimate income (thus, for example, in Spain, the Fuggers were deprived of remittance for silver coming from “India”) and carried out forced consolidation in such a way that they assigned to their creditors an annuity whose real value was much lower than the nominal one. This solution was particularly eagerly and frequently used in Spain in the 16th and 17th centuries, and even as late as the 18th century. This method was equally widespread in France. One of the most famous events was the dissolution of the Knights Templar in 1312, ordered by King Philippe the Beautiful of France, which resulted from the desire to get rid of creditors and the possibility of confiscating their assets (Morawski, 2002). Later, other methods were also used: sometimes a form of forced consolidation of the current debt, sometimes – as happened in 1557 – payments were simply suspended, making all creditors’ demands ineffective. Another solution used by state rulers was simply to cancel the obligations they had incurred. However, modern-day banking crises already had a completely different nature and causes that determined their number, scale, and area of occurrence. Reinhart and Rogoff (2013) present a complete list of banking crises from 1800 until the end of 2007. They adopted two types of events as criteria for the occurrence of a banking crisis: bank runs that lead to the closure, merging, or takeover by the public sector of one or more financial institutions; and . . . if there are no runs,

Banking crises 33

the closure, merging, takeover, or large-scale government assistance of an important financial institution (or group of institutions) that marks the start of a string of similar outcomes for other financial institutions. They explain that the earliest advanced-economy banking crisis was France in 1802; early crises in emerging markets befell India (1863), China (several episodes during the 1860s–1870s), and Peru in 1873. In total, they point to 268 crises in the analyzed period: 22 in Africa, 44 in Asia, 112 in Europe, 65 in Latin America, 21 in North America, and 4 in Australia and Oceania. Laeven and Valencia (2020) identify 151 banking crises over the period 1970–2017. They used similar way to define banking crisis, as event that meets two conditions: 1) significant signs of financial distress in the banking system (as indicated by significant bank runs, losses in the banking system, and/or bank liquidations), 2) significant banking policy intervention measures in response to significant losses in the banking system. Most countries experienced at least one systemic banking crisis during 1970– 2017. However, only three countries experienced more than two systemic banking crises during the past 48 years: Argentina (4), the Democratic Republic of Congo (3), and Ukraine (3). There are many similar classifications in the literature, e.g., Bordo et  al. (2001), Caprio and Klingebiel (2003), Demirgüc-Kunt and Detragiache (2005), Grossman (2010), Kindleberger and Aliber (2011), Schularick and Taylor (2012), Romer and Romer (2017), Baron et  al. (2018), and others. However, any attempt to compare these studies is greatly hampered due to differences in the methodology, the very definition of a banking crisis, and the time horizon. The complex nature of the processes associated with the occurrence of banking crises and the individualized nature of most of them means that a bulk of research has been devoted to this issue. One of the oldest scientific theories explaining the emergence of banking crises was formed by monetarists (Friedman & Schwartz, 1963). According to them, banking crises result from depositors’ panic, characterized by irrational withdrawals of deposits, which contributes to excessive pressure on the liquidity situation of individual banks and the entire banking sector. As a consequence of bank runs, the bank is forced to dispose of its assets, often at undervalued prices.

Banking crisis anatomy – models, factors, and macroeconomic meaning First-generation banking panic models (Bryant, 1980; Diamond  & Dybvig, 1983; Jacklin & Bhattacharya, 1988) specify that panics are undesirable events caused by random deposit withdrawals. The probability of depositors joining

34  Banking crises

the run is based on an increasing number of other customers who panicked. Diamond and Dybvig (1983) explain that traditional demand deposit contracts which provide liquidity have multiple equilibria, one of which is a bank run. Bank runs cause real economic problems because even “healthy” banks can fail, causing the recall of loans and the termination of productive investment. They find that fully informed and insured depositors never withdraw their savings prematurely. In other words, a well-designed deposit insurance system can serve as an effective bank run prevention, providing full information to depositors. The second line of reasoning assumes that panics are motivated by information asymmetries between banks and depositors (Calomiris & Gorton, 1991; Allen & Gale, 2007; Dermine, 2015). Real macroeconomic shocks that affect the value of banking-system assets make banks gradually become insolvent. Depositors, fearing such a situation, guess that some banks may be insolvent, but they do not know which ones. This is because only a small number of depositors keep track of the information provided by banks, especially the quality of their loan portfolios. Growing queues at banks may therefore lead to superficial decisions to withdraw deposits and join the line, accompanied by piling up interpretations of the signals sent by uninformed depositors. Thus, even financially sound banks can experience panic during periods of economic instability triggered by depositors’ reactions to the news on the insolvency of other vulnerable banks. Depositors’ lack of knowledge leads to withdrawing deposits from all banks in the sector. In this regard, the contagion effect (Kaminsky et al., 2003; Brown et al., 2016) plays a significant part. The network of financial connections and the ease of transferring information accelerate the spread of crisis, which is compounded by fear, panic, and herd behavior. Still, Calomiris and Gorton (1991) claim that panic can be viewed as a form of monitoring of the banking sector because bank runs may be an optimal response of depositors. Iyer and Puri (2012) find that deposit insurance is only partially effective in preventing bank runs. In their view, however, another factor plays a big role – the length and depth of the bank-depositor relationship. Depositors with longer relationships and those who availed themselves of bank loans are less likely to run during a crisis. It seems that this aspect is highly underestimated both by banks themselves and in research. Meanwhile, the knowledge, skills, commitment, and empathy of a personal advisor or the person the customer interacts with within the bank sometimes play a much more important role than great customer retention programs developed by bank boards. Each customer would like to be treated on an individual basis, not just as one of the numbers in the bank’s anonymous population of customers. Subsequent models of bank panics (Gertler  & Karadi, 2011; Gertler  & Kiyotaki, 2011) show how reductions in bank capital adequacy as a result of economic downturns limit the ability of banks to perform their primary

Banking crises 35

function – intermediaries between investors who want to invest their savings and customers who seek funding. Banks play an important role in aligning the differing structures of supply and demand. Due to agency problems, a bank’s ability to raise funds depends on its capital. Portfolio losses experienced in a downturn accordingly lead to losses of bank capital that increase in the degree of leverage. In equilibrium, a contraction of bank capital and bank assets raises the cost of bank credit, slows the economy, and further depresses asset prices and bank capital. Due to a liquidity mismatch, bank runs may be possible. Whether or not a bank-run equilibrium exists will depend on two key factors: the condition of the bank’s balance sheets, and an endogenously determined asset liquidation price. Gertler and Kiyotaki (2015) emphasize that most models of bank runs, however, are typically quite stylized and not suitable for quantitative analysis. Furthermore, often runs are not connected to fundamentals. That is, they may be equally likely to occur in good times as well as bad ones. The authors present a model that integrates the “macroeconomic” approach which stresses financial accelerator effects with the “microeconomic” one which stresses a bank liquidity mismatch and runs. They explain that a negative shock then increases leverage and reduces liquidation prices, hence leading to a situation where a bank run is possible. The authors argue that a recession that constrains bank lending due to conventional financial accelerator effects also opens up the possibility of runs due to the associated weakening of balance sheets and reduced liquidity of secondary markets for bank assets. Gertler et al. (2020) also show that crises may occur even in the absence of large exogenous shocks to the economy. Analyzing the causes of the global subprime crisis, Morris and Shin (2016) conclude that “institutions such as Bear Stearns or Lehman Brothers that financed themselves through a combination of short-term and long-term debts, but where the heavy use of short-term debts made the institution vulnerable to a run by short-term creditors.” Thus, they imply that the run was liquidity-based instead of solvency-based. They define “illiquidity risk” as the probability of a default due to a run when the institution would otherwise have been solvent. The second theory explaining the emergence of banking crises is based on economic shifts and treats banking crises as a natural consequence of business cycles (Minsky, 1982; Gorton, 1988; Kindleberger, 1989; Aliber  & Kindleberger, 2015). Banking crises are thus the result of deteriorating macroeconomic factors. During the recovery phase, in which production, employment, investment, and demand increase, an expansion of banks’ lending activities is also noticeable. This arouses expectations of a wide group of economic entities and individuals. Since banks systematically create additional money for the economy, they stimulate optimism among investors and consumers. This is

36  Banking crises

conducive to the formation of speculative bubbles on selected groups of assets, financial pyramids, frauds, and scams. Therefore, the crisis is not only endogenous to the banking sector but is also a direct result of imprudent banking. The emerging depression phase accumulates negative events and leads to exaggerated pessimism. The deterioration of asset quality, the generation of losses, and the loss of liquidity result in bank failures. In other words, it is the procyclicality of the banking sector that becomes the cause of banking crises. Contrary to monetarists, there appears more room for state intervention, which should prevent the spread of the banking crisis to other sectors of the economy. This theory was refined by the creation of a financial crisis model based on three key concepts: information asymmetry, adverse selection, and moral hazard (Goldstein & Razin, 2015). The information asymmetry model defines a financial crisis as distortions occurring in financial markets that create problems of adverse selection and moral hazard, making it difficult for financial markets to efficiently transfer funds to entities with the greatest investment opportunities. The rationing of credits by banks prevents some of the funds from being directed to entities that truly need the infusion of foreign capital and that are able to repay it within the prescribed period. The banking crisis contributes to the inability of the entire economy to function effectively, leading to a sharp decline in economic activity. Still others see the sources of banking crises as a consequence of the simultaneous currency crises or emphasize that the banking crisis is often associated with the phenomenon of a simultaneous currency crisis. The combined occurrence of both crises in the economy at the same time is called a twin crisis (Kaminsky & Reinhart, 1999). According to the first-generation model, the source of the crisis is primarily an imprudent financial policy (Krugman, 1979). Financing the budget deficit with money emission contributes to a drastic increase in inflation. The trade balance deteriorates, and the level of foreign exchange reserves significantly decreases. The second-generation crisis model (Obstfeld, 1994, 1996), on the other hand, concerns countries that are characterized by a favorable economic situation and a stable financial policy, but that as a result of speculative attacks, their national currencies depreciate. Still, in the case of third-generation models (Krugman, 1999), the source of the crisis is not only a faulty macroeconomic policy or speculative attacks, but it is also inherent to the economy at the microeconomic level. According to this model, the sources of currency crises include structural weaknesses within a given country. The mechanism of these crises stems from asset sell-offs by investors who act in the belief that currency devaluation or its significant depreciation is very likely in the presence of a floating exchange rate. The rapid outflow of much of the foreign capital that flowed in during the economic expansion is usually accompanied by residents abandoning the domestic currency as a result of their lack of confidence in its stability. When the central bank raises interest rates to make local currency deposits more attractive, it increases the costs of service with regard to the existing bank loans. The deterioration of the loan portfolio

Banking crises 37

is effectuated by rapidly increasing bad debts that result from the increase in the number of companies that are unable to service their debts in a rapidly changing environment. Consequently, banks face a decline in the profitability of their operations and problems with servicing deposits. Depending on the school of economics, the causes of banking crises are classified into several main groups of factors: •

•

• •

• •

•

Macroeconomic – resulting from the very nature of the market economy in which business cycles occur, as well as those resulting from erroneous economic policy of the government, overly expansive policy or inappropriate monetary interventions of the central bank, and shocks taking place in other sectors of the economy. Specific causes include negative economic growth, inflation, exchange rate fluctuations, decrease in investment and consumption, increase in unemployment, etc. Systemic  – an overgrowth of the financial sector and detachment of the financial sphere from the real sphere – financialization, uncontrolled development of derivatives, lack of adequate financial regulation, supervision over financial institutions and markets, and lack of ownership supervision and a risk management system over an international financial conglomerate. Microeconomic – primarily covering basic risks accompanying banking operations: credit risk, market risk, liquidity risk, and operational risk. Institutional – lack of sufficient regulation and supervision of the banking sector and financial markets, unfavorable changes in the legal conditions for conducting banking activities as a result of acts of the legislative and executive power. Apart from the typical regulatory risk, it also involves a political risk, a country risk, a risk of regulatory change, and so on. Behavioral – resulting from irrational behavior of bank customers and investors, contributing to the formation of adverse events such as bubbles, bank runs, the decline in investor confidence, changing customer preferences. Moral hazard  – the use of extensive interventionism contributes to a demoralizing effect. Government aid and central bank support in crisisstricken countries add to maintaining the status quo. Launching rescue plans also carries a serious risk of discontinuation of internal restructuring of banking activity due to a growing conviction that in case of difficulties, private banks will be rescued by the state intervention policy. The boards of individual banks may continue to make risky investments and weaken their remedy efforts, hoping for support from the state. Moral hazards from bank bailouts have frequently planted the seed for the next crisis. External  – adverse impact on a country’s economy made by external, impossible, or almost impossible-to-predict events such as wars, domestic unrest, natural disasters, and pandemics, or resulting from restrictions imposed on the economy of one or several countries by other countries; for example, economic embargoes, economic sanctions, imposing customs duties and/or import or export quotas, and monetary restrictions.

38  Banking crises

One of the most frequently cited causes of banking crises, according to Minsky’s financial instability hypothesis, is the occurrence of banking crises after a credit boom. As Mendoza and Terrones (2008) state, “a credit boom is defined in general as an episode in which a credit to the private sector grows by more than during a typical business cycle expansion.” The identification of credit booms is a subject of constant inquiry and elaborations in scientific research. Their authors make attempts to explain the essence of banking crises, analyze the cognitive processes of crises, and determine the sources of their origin (Gourinchas et  al., 2001; Barajas et  al., 2009; Mendoza  & Terrones, 2012; Dell’Ariccia et al., 2016; Avdjiev et al., 2018; Richter et al., 2020). Castro and Martins (2019) note that there seems to be no right or wrong way to identify credit boom events; each approach comes with its advantages and drawbacks. Most of them compare a country’s real credit per capita or the credit-to-GDP ratio to their nonlinear trend. Gorton and Ordoñez (2020) find that credit booms are on average 11 years long and that these booms begin with a positive productivity shock. Dell’Ariccia et  al. (2012) claim that credit booms are often triggered by a financial reform, capital inflow surges associated with capital account liberalizations, and periods of strong economic growth. They tend to be more frequent in fixed exchange rate regimes when banking supervision is weak, and when macroeconomic policies are loose. They also suggest that not all booms are bad. Historically, only a minority of booms ended in crashes. Castro and Martins (2020) argue that understanding why some credit booms end up by seriously disrupting the banking system and the overall economy is of critical importance. Despite some advances that have been made in this field, findings tend to be mixed and significant differences between good and bad credit expansions have been hard to capture. The main reason for creating credits as a result of credit booms is a loosened credit policy in terms of lending requirements. Competition in the sector forces banks to adapt their business models to the existing conditions. One of the main elements of business evaluation is the growth in the value and volume of credits granted in a specific period. Banks have to compete in terms of applied credit-granting principles and price conditions – margins and commissions, level of accepted collaterals, limiting the number of documents submitted by applicants, etc. The relaxation of credit criteria usually contributes to an increase in lending. Thus, credits are also granted to customers whose creditworthiness is questionable. Consequently, this contributes to a deterioration in the quality of loan portfolios held by banks, an increase in specific provisions, and thus a deterioration in generated profits. The credit boom makes banks

Banking crises 39

less stable and thus more susceptible to financial difficulties in case of economic slowdown or recession. Another frequent explanation of banking crises is the formation of speculative bubbles in asset markets: currencies, stocks, commodities, real estate. Kindleberger (1991) defines them as a sharp rise in the price of an asset or a range of assets in a continuous process, with the initial rise generating expectations of further rises and attracting new buyers  – generally speculators interested in profits from trading in the asset rather than its use of earning capacity. The rise is usually followed by a reversal of expectations and a sharp decline in the price often resulting in financial crisis. Lind (2009) points to “an irrational expectations bubble. In this case actors on the market become overoptimistic and think the asset price will grow rapidly over a longer period. The growth is expected to be considerably higher than historical averages.” Thus, irrational investor enthusiasm contributes to the belief that future prices will be ever higher and the asset price movement will be difficult to explain by fundamental premises. This is the so-called “irrational exuberance” in investors’ behavior (Shiller, 2015). Brunnermeier and Oehmke (2013) clarify that the term bubble may refer to periods in which the price of an asset exceeds fundamentals because investors believe that they can sell the asset at an even higher price to some other investor in the future. The term bubble refers to large, sustained mispricing of financial or real assets. Therefore, according to another definition, bubbles are deviations from the fundamental value of an asset which equals the expected present value of the stream of dividends that the owner expects to receive (Brunnermeier, 2008). Thornton (2006) distinguishes three main views on the causes of bubbles. The dominating view among the general public and modern mainstream economists, including the Chicago school and proponents of supply-side economics, denies the existence of bubbles and declares that what is thought to be “bubbles” is the result of “real” factors. The second view, which is espoused by Keynesians and the advocates of behavioral finance, is that bubbles exist because of psychological factors. The third view is that of the Austrian school, which sees bubbles as consisting of real and psychological changes caused by manipulations of monetary policy. Czerniak et al. (2020) distinguish five determinants of asset price bubbles: monetary, macroeconomic, demographic, institutional, and cultural, as well as those arising from monetary integration. Monetary factors are related to monetary policy. Low interest rates are a determinant of a risk-free interest rate representing the rate of return on an investment alternative to stocks. Therefore, a negative relationship between short-term interest rates and

40  Banking crises

selected asset prices can be expected. In addition, low interest rates lead to searching for alternative ways to invest as compared to bank deposits. Demographic factors include the number and the income structure of households and their demand for different kinds of assets. Institutional and cultural factors are, among other things: the specifics of the financial system, credit availability, and transaction costs. The authors also distinguish factors associated with the entry of the country into the international monetary system. Once the common currency is adopted and the currency risk premium is eliminated, nominal interest rates decline and real interest rates fall below the level consistent with (initial) macroeconomic equilibrium. Moreover, a switch from a flexible to a fixed exchange rate regime can lead to higher inflation pressure due to the Balassa–Samuelson effect. Still, Laeven (2011) claims that sudden changes in prices cannot be explained based on a standard neoclassical theory or the efficient markets hypothesis. They require an element of irrational behavior, information asymmetry, market failure, or improper government intervention. The risk of a banking crisis peaks just after the bubble bursts. A period of self-perpetuating unsustainable growth in commodity prices is followed by a sharp decline in prices, the socalled ‘bubble burst’, which is most often associated with a dramatic decline in asset value. A sharp depreciation of prices may bring significant consequences in the banks’ credit portfolio, especially in the situation of a relatively high share of mortgages or loans used to finance capital investments in the loan structure and overlending to industries particularly vulnerable to asset depreciation. In addition, asset repricing contributes to a reduction in the value of credit collaterals, which in such a situation does not fully cover the existing indebtedness of borrowers, and to a reduction in the amounts of recovery obtained from the collateral held in the event of loan collection. It seems that a rather underestimated determinant of banking crises in scientific research is the current standard of conducting banking activities, subordinated to the maximization of value for shareholders. In modern times the pressure to achieve spectacular success is growing. In recent years, the optics of investors towards their invested capital has changed radically, clearly shortening the time horizon in which they expect satisfactory returns in the form of share price appreciation, payment of higher dividends, or other measurable benefits from their investments. This leads to unrealistic demands directed at management boards – permanent achievement of above-average profits in comparison with the average obtained by other banks in the sector. As a result, bank managers, whose incentive systems are increasingly correlated with financial performance, are more likely to engage in risky activities. Constant market pressure contributes to the intensification of unethical practices. The creation of an atmosphere of internal rivalry, the use of various forms of pressure and coercion, tolerating unethical activities of individuals driven by the illusion of promotion in the organizational hierarchy, and the prospects of high salaries all contribute to the violation of the fundamental principles of cooperation with clients, employees, and the bank’s other stakeholders.

Banking crises 41

Along with revelations on the functioning mechanisms of the largest banks, highlighting the weaknesses of the used warning systems and risk management models, inadequate assessments of rating agencies, and recommendations of specialized consulting firms, the entire philosophy of the priority model of banking activity ends in fiasco. Contemporary financial crises and numerous abuses and unethical behavior by banks made it clear that Systemically Important Financial Institutions (SIFIs) pose a real threat to the stability of banking sectors and even national economies of individual countries, contributing to the creation of excessive systemic risk. It turned out that the directions of development, which, according to theory, should contribute to the success of the banking sector, became the cause of major economic and financial problems. The unending losses of the world’s largest banks, the rapidly shrinking equity in their balance sheets, the melting market value of these companies, and the unprecedented scale of state intervention aimed at stabilizing the situation in deregulated financial markets under the impact of the crisis, made it clear how far banks had strayed from their basic functions and how radical measures should be taken to save modern banks. A few years later, it can already be said that the risks were very quickly forgotten. No supranational institutions, supervisory systems, legislation, monitoring, and control tools can cover and foresee all possibly risky situations, for example resulting from the scale of banks’ involvement in risky financial instruments. It is impossible to eliminate the natural drive of shareholders and managers to maximize their wealth. People focused on wealth multiplication, having egotistical tendencies, will always bypass even the most detailed regulations, focusing their decisions on achieving their particularistic benefits, while contributing to a significant deterioration of the bank’s financial situation. Demirgüc-Kunt and Detragiache (1998) explain in more detail the determinants of banking crises. They claim that crises tend to erupt when the macroeconomic environment is weak, particularly when growth is low and inflation is high. Also, high real interest rates are associated with systemic banking sector problems, and there is some evidence that the vulnerability to balance payments crises has played a role. Countries with an explicit deposit insurance scheme were particularly at risk, as were countries with weak law enforcement. The authors also emphasize that when these effects are controlled, neither the rate of currency depreciation nor the fiscal deficit is significant. Deposit insurance can give rise to moral hazard problems weakening financial system stability. Their research specifies that countries with better law-enforcement quality have fewer banking sector problems. Tests also indicate that vulnerability to sudden capital outflows, a high share of credit given to the private sector, and high past credit growth may be associated with a higher probability of a crisis.

42  Banking crises

For every financial crisis, experts have said repeatedly, “this time it’s different,” the old rules of asset valuation used so far no longer apply, and the new situation bears little resemblance to previous disasters. But, unfortunately, this is not the case – some mechanisms for the emergence and spread of crises are similar (Reinhart & Rogoff, 2009). It seems that the quintessential academic discourse on the issue of the factors leading to banking crises is the report of the special Financial Crisis Inquiry Commission (FCIC), set up by the US government to explain the reasons for the subprime crisis. According to the commission (FCIC, 2011), the main premises of the banking crisis are as follows: •

widespread failures in financial regulations and supervision proved devastating to the stability of the nation’s financial markets; • dramatic failures of corporate governance and risk management at many systemically important financial institutions were a key cause of this crisis; • a combination of excessive borrowing, risky investments, and lack of transparency put the financial system on a collision course with the crisis; • the government was ill-prepared for the crisis, and its inconsistent response added to the uncertainty and panic in the financial markets; • there was a systemic breakdown in accountability and ethics; • collapsing mortgage-lending standards and the mortgage securitization pipeline lit and spread the flame of contagion and crisis; • over-the-counter derivatives contributed significantly to this crisis; • the failures of credit rating agencies were essential cogs in the wheel of financial destruction.

Pandemic as a source of banking crisis The research on the effects of crises in the banking sector brought about by spreading diseases does not begin with the COVID-19 pandemic. Such studies have been done well before, on the Spanish flu of 1918, the Asian flu, the Hong Kong flu, SARS-CoV, A/H1N1, MERS-CoV, and Ebola (Table 3.2). However, it was not until the aftermath of COVID-19 that the perception of the impact of global pandemic threats on the functioning of modern countries and their economies completely changed (Figures 3.1 and 3.2). A growing number of academic and other studies highlight the impact of pandemic effects on particular groups of macroeconomic variables, such as the goods and services market (Bagchi et al., 2020; Song & Zhou, 2020; Usman et al., 2020), the labor market (Coibion et al., 2020; Dias et al., 2020; Fana et al., 2020), the money market (Botta et al., 2020; Hutchinson & Mee, 2020; Sarker, 2020), international trade (Chiach & Zhong, 2020; Jean, 2020; OECD, 2020), and environmental protection (Espejo et al., 2020; Malliet et al., 2020; Wang & Su, 2020). Cochrane (2020) notes that a pandemic may prove to be a permanent condition. This raises the need for strategic plans to handle the rapid development of the epidemic and the identification of significant increases in new infections.

Banking crises 43 Table 3.2  List of selected global pandemic and epidemic events Event name

Period

No. of affected countries

Total cases

Total deaths

Mortality rate

Spanish flu H1N1

1918–1920

N.A.

500 m1 500 m2

2–3%7

Asian flu H2N2 Hong Kong flu H3N2 SARS-CoV A/H1N1

1957–1958

N.A.

> 500 m7

1968–1970

N.A.

> 500 m7

2002–2003 2009–2010

284 2148

8 0965 6,724,1498 700 m–1.4 bn7

2012 2014–2020 2019–

276 104 22412

2,5626 28,6464 295,664,06910

50 m (about 3% of the global population)1 50–100 m2 1–4 m7 1–2 m3 1–4 m7 500,000–2 m3 7745 18,4498 151,700– 575,4008 8816 11,3234 5,474,81410

MERS-CoV Ebola COVID-19 (31.12.2021)

< 0.2%7 < 0.1%7 9.56% 0.03% 34.39% 39.53% 3.4%

Notes: 1 Johnson and Mueller (2002), 2 Taubenberger and Morens (2006), 3 Saunders-Hastings and Krewski (2016), 4 Ma et al. (2020), 5 WHO (2015), 6 WHO (2019), 7 WHO (2011), 8 CDC (2019), 9 WHO (2010), 10 WHO (2021), 11 European Centre for Disease Prevention and Control (2021), 12 CSSE & JHU (2021)

Figure 3.1 Cumulative confirmed COVID-19 cases per million people in selected European countries Source: COVID-19 Data Repository by the Centre for Systems Science and Engineering at Johns Hopkins University (retrieved 6 March 2021, from: https://github.com/CSSEGISandData/COVID-19).

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Figure 3.2 Cumulative confirmed COVID-19 deaths per million people in selected European countries Source: COVID-19 Data Repository by the Centre for Systems Science and Engineering at Johns Hopkins University (retrieved 6 March 2021, from: https://github.com/CSSEGISandData/COVID-19).

It especially applies to the introduction of complete lockdowns in the territory of a given country or region in the context of the functioning of the entire economy and the sectors most affected by the effects of coronavirus. It is also important to design economic support activities so that they do not induce moral hazard among beneficiaries. A separate stream of research is the work devoted to the banking sector. Hardy (2020) notes that there was high uncertainty about how the economic activity would be affected and whether banks could weather the potential losses as businesses closed, either temporarily or permanently. However, banks have so far proved to be a source of stability, remaining resilient while supporting the economy. Nevertheless, equity valuations remain depressed, credit rating outlooks are largely negative, and pockets of weakness and risk exist. The Financial Stability Board (FSB, 2020) indicates that the system entered the crisis more resilient and better placed to sustain financing to the real economy as a result of the G20 regulatory reforms in the aftermath of the 2008 global financial crisis. In particular, greater

Banking crises 45

resilience of major banks at the core of the financial system has allowed the system largely to absorb rather than amplify the macroeconomic shock. Demirgüc-Kunt et  al. (2020), analyzing the stock price behavior of 896 commercial banks from 53 countries, find a systematic underperformance of bank stocks at the onset of the COVID19 crisis, between March and April 2020. More precisely, for most countries, bank stocks underperform relative to other publicly traded companies in their home country, and relative to non-financial institutions. According to the authors, such investors’ behavior proves that banks will experience deeper and more protracted profit losses than other firms. Even within the financial sector, banks are expected to face greater losses than other financial institutions. Bigger declines in stock prices of larger banks, public banks, and, to some extent, better-capitalized banks are explained by their greater anticipated role in dealing with the crisis. The authors also attempt to assess the impact of government intervention on bank quotes. They note that liquidity support, borrower assistance, and monetary easing moderated the adverse impact of the crisis, but this is not true for all banks or in all circumstances. For example, borrower assistance and prudential measures exacerbated the stress for banks that are already undercapitalized and/or operate in countries with little fiscal space. A significant amount of research on the banking sector is devoted to examining the banking sector in a selected country. For instance, Barua and Barua (2020) suggest that all banks are likely to observe a fall in risk-weighted asset values, capital adequacy ratio, and interest income at the individual bank and sectoral levels in Bangladesh. However, estimates show that larger banks are relatively more vulnerable. Still, Korzeb and Niedziółka (2020) state that the largest banks operating in Poland are the most resilient to the effects of the pandemic. They add that the short-term effects of the pandemic crisis will affect the functioning of the banking sector with a rise in nonperforming loans and write-downs. The need to take drastic measures aimed at mitigating the effects of the crisis for the most affected borrowers through debt restructuring will entail the loss of some of the planned revenues. Also focusing on the Polish banking sector, Korzeb and Niedziółka (2021) found the scope and reasons for the volatility and differences in the cost of risk as well as the relation between pre-pandemic credit policy and provisions created in 2020. Boccaletti et al. (2020), focusing on the performance of Italian banks, found that the worsening of bank assets quality may be the main impact of COVID19 on the financial sector. They forecasted that at the onset of the pandemic, due to the incorporation of the unfavorable economic scenarios into the model used to compute expected losses, moderate growth of loan provisions may

46  Banking crises

be experienced. They also found that an increase in NPL may affect lending capacity, banking sector profitability, and its potential to raise capital. Therefore, the authors propose to develop and implement the idea of the European bad bank. Flögel and Gärtner (2020), analyzing regional banks in Germany, concluded that by providing liquidity, the aforementioned banks could support companies to overcome the social shutdown. This took place already during the Global Financial Crisis of 2007–2009, when regional banks in contrast to the large credit institutions extended lending to the real economy. The aforementioned and all other studies confirm the strong resilience of banking sectors to the pandemic crisis. This is also the case in Spain, where in the last decade, significant balance sheet quality and solvency improvements took place. The CET1 of the Spanish banking sector increased by 0.71%, and the NPL ratio fell by 0.4% in 2020. Similar to other European banking sectors the profitability was subject to significant decline as a result of the increase in provisions for impairment losses. These effects have not been even across banks due to the different structures of their exposures to the regions, sectors, companies, and population groups (de Cos, 2021). As regards, eurozone banks accommodated a significant liquidity shortage–induced credit demand increase due to the funding cost and capital relief of the pandemic response measures provided by central banks and supervision institutions. The close cooperation of monetary and prudential policy brought the amplification effect on lending (Altavilla et al., 2020). As a conclusion, the considerations dedicated to the influence of COVID-19 on the national banking sector can serve the findings of Beck and Keil (2021), who applied a novel measure to gauge US banks’ exposure to the pandemic and lockdown measures. They evidenced that banks are affected by COVID-19 economic consequences, although the effect was not so obvious due to the easing of regulatory requirements on loan classification and provisioning. Banks reported growth of lending, driven by government support programs accompanied by tightening in credit policy.

References Aliber, R.Z., & Kindleberger, C.P. (2015). Manias, Panics and Crashes: A History of Financial Crises. London: Palgrave Macmillan. Allen, F., & Gale, D. (1999). Bubbles, crises, and policy. Oxford Review of Economic Policy, 15(3). Allen, F., & Gale, D. (2007). Understanding Financial Crises. Oxford & New York: Oxford University Press. Altavilla, C., Barbiero, F., Boucinha, M., & Burlon, L. (2020). The great lockdown: Pandemic response policies and bank lending conditions. European Central Bank Working Paper Series, No. 2465. Avdjiev, S., Binder, S., & Sousa, R. (2018). External debt composition and domestic credit cycles. European Stability Mechanism Working Paper Series, No. 28. Bagchi, B., Chatterjee, S., Ghosh, R.,  & Dandapat, D. (2020). Impact of COVID-19 on global economy. In: Coronavirus Outbreak and the Great Lockdown. Springer Briefs in

Banking crises 47 Economics. Singapore: Springer. Retrieved from: http://10.1007/978-981-15-7782-6 [06.10.2020]. Barajas, A., Dell’Ariccia, G., & Levchenko, A. (2009). Credit Booms: The Good, the Bad, and the Ugly. Unpublished manuscript, International Monetary Fund. Baron, M., Verner, E., & Xiong, W. (2018). Identifying Banking Crises. Princeton University Manuscript. Retrieved from: www.systemicrisk.ac.uk/sites/default/files/images/5.%20 Baron_LSE_April2018.pdf [16.10.2020]. Barua, B., & Barua, S. (2020). COVID-19 implications for banks: The case of an emerging economy with a weak finance system. Retrieved from SSRN: http://dx.doi.org/10.2139/ ssrn.3646961 [06.10.2020]. Beck, T., & Keil, J. (2021). Bank performance in the time of COVID-19: Evidence from the US, CEPR. Retrieved from: https://voxeu.org/article/bank-performance-timeCovid-19 [29.04.2021]. Benston, G.J. (2004). What’s special about banks? The Financial Review, 39(1), 13–33. Retrieved from: https://doi.org/10.1111/j.0732-8516.2004.00065.x Benston, G.J., & Kaufman, G.G. (1994). Is the banking and payments system fragile? Working Papers Series, No. 28. Federal Reserve Bank of Chicago. Boccaletti, S., Bongini, P., Buzzacchi, C., & Cucinelli, D. (2020). The Italian economic and institutional systemin a pandemic situation. Safe Bank, 2(79), 60–80. Bordo, M., Eichengreen, B., Klingebiel, D., Martinez-Peria, M.S., & Rose, A.K. (2001). Is the crisis problem growing more severe? Economic Policy, 16(32), 5182. Botta, A., Caverzasi, E., & Russo, A. (2020). Fighting the COVID-19 crisis: Debt monétisation and EU recovery bonds. Intereconomics, 55, 239–244. Brown, M., Trautmann, S.T.,  & Vlahu, R. (2016). Understanding bank-run contagion. Management Science, 63(7), 2272–2282. Brunnermeier, M.K. (2008). Bubbles. In: S.N. Durlauf & L.E. Bluem (eds.), The New Palgrave Dictionary of Economics. London: Palgrave Macmillan. Brunnermeier, M.K., & Oehmke, M. (2013). Bubbles, financial crises, and systemic risk. In: G.M. Constantinides, M. Harris, & R.M. Stulz (eds.), Handbook of the Economics of Finance. Amsterdam: Elsevier. Bryant, J. (1980). A model of reserves, bank runs, and deposit insurance. Journal of Banking & Finance, 4(4), 335–344. Calomiris, C.W., & Gorton, G. (1991). The origins of banking panics: Models, facts, and bank regulation. In: R.G. Hubbard (ed.), Financial Markets and Financial Crises. Chicago: University of Chicago Press for the NBER. Caprio, G., & Honohan, P. (2012). Banking crises. In: A.N. Berger, P. Molyneux, & J.O.S. Wilson (eds.), The Oxford Handbook of Banking. Oxford: Oxford University Press. Caprio, G., & Klingebiel, D. (1996). Bank insolvency: Bad luck, bad policy, or bad banking? In: Annual World Bank Conference on Development Economics. Washington, DC: World Bank, 79–104. Caprio, G., & Klingebiel, D. (2003). Episodes of systemic and borderline banking crises. In: Managing the Real and Fiscal Effects of Banking Crises. Washington, DC: World Bank Publication, 31–49. Castro, V., & Martins, R. (2019). Political and institutional determinants of credit booms. Oxford Bulletin of Economics and Statistics, 85(1), 1144–1178. Castro, V., & Martins, R. (2020). The collapse of credit booms: A competing risks analysis. Journal of Economic Studies, 47(6), 1437–1465.

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Banking crises 49 epidemic threats. Science of The Total Environment, 747, 141314. Retrieved from: https:// doi.org/10.1016/j.scitotenv.2020.141314 [06.10.2020]. European Centre for Disease Prevention and Control (2021). Retrieved from: www. ecdc.europa.eu/en/publications-data/data-national-14-day-notification-rate-Covid-19 [07.01.2021] Fana, M., Torrejón Pérez, S.,  & Fernández-Macías, E. (2020). Employment impact of Covid-19 crisis: From short term effects to long terms prospects. Journal of Industrial and Business Economics, 47, 391–410. FCIC – Financial Crisis Inquiry Commission (2011). The Financial Crisis Inquiry Report. Final Report of the National Commission on the Causes of the Financial and Economic Crisis in the United States. Washington, DC: U.S. Government Printing Office. Retrieved from: www.govinfo.gov/content/pkg/GPO-FCIC/pdf/GPO-FCIC.pdf [30.10.2020]. Flögel, F.,  & Gärtner, S. (2020). The COVID-19. Pandemic and relationship banking in Germany: Will regional banks cushion an economic decline or is a banking crisis looming? Tijdschrift voor economische en sociale geografie. Retrieved from: https://doi.org/ 10.111.10.1111/tesg.12440. Friedman, M., & Schwartz, A.J. (1963). A Monetary History of the United States, 1867–1960. Princeton: Princeton University Press. FSB. (2020). Implementation and effects of the G20 financial regulatory reforms. 2020 Annual Report. Financial Stability Board. Retrieved from: https://www.fsb.org/2020/11/ implementation-and-effects-of-the-g20-financial-regulatory-reforms-2020-annualreport/ [20.12.2020]. Gertler, M., & Karadi, P. (2011). A model of unconventional monetary policy. Journal of Monetary Economics, 58(1), 17–34. Gertler, M., & Kiyotaki, N. (2011). Financial intermediation and credit policy in business cycle analysis. In: B.M. Friedman & M. Woodford (eds.), Handbook of Monetary Economics, Vol. 3A. Amsterdam: Elsevier Science, 547–599. Gertler, M., & Kiyotaki, N. (2015). Banking, liquidity, and bank runs in an infinite horizon economy. American Economic Review, 105(7), 2011–2043. Gertler, M., Kiyotaki, N., & Prestpino, A. (2020). A macroeconomic model with financial panics. The Review of Economic Studies, 87(1), 240–288. Goldstein, I., & Razin, A. (2015). Three branches of theories of financial crises. Foundations and Trends in Finance, 10(2), 113–180. Gorton, G. (1988). Banking panics and business cycles. Oxford Economic Papers, 40(4), 751–781. Gorton, G., & Ordoñez, G. (2020). Good booms, bad booms. Journal of the European Economic Association, 18(2), 618–665. Gourinchas, P.-O., Valdes, R., & Landerretche, O. (2001). Lending booms: Latin America and the world. Economía Journal, 1(2), 47–100. Grossman, R.S. (2010). Unsettled Account: The Evolution of Banking in the Industrialized World since 1800. Princeton: Princeton University Press. Grossman, R.S. (2016). Banking crises. In: Y. Cassis, C.R. Schenk, & R.S. Grossman (eds.), The Oxford Handbook of Banking and Financial History. Oxford: Oxford University Press. Hardy, B. (2020). Banks through Covid-19. BIS Quarterly Review, September  2020. Retrieved from: www.bis.org/publ/qtrpdf/r_qt2009w.htm [08.10.2020]. Hutchinson, J.,  & Mee, S. (2020). The impact of the ECB’s monetary policy measures taken in response to the COVID-19 crisis. ECB Economic Bulletin, No. 5/2020. Retrieved from: www.ecb.europa.eu/pub/economic-bulletin/focus/2020/html/ecb.ebbox 202005_03~12b5ff68bf.en.html [06.10.2020].

50  Banking crises Iyer, R., & Puri, M. (2012). Understanding bank runs: The importance of depositor-bank relationships and networks. American Economic Review, 102(4), 1414–1445. Jacklin, C.J., & Bhattacharya, S. (1988). Distinguishing panics and information-based bank runs: Welfare and policy implications. Journal of Political Economy, 96(3), 568–592. Jean, S. (2020). How the COVID-19 pandemic is reshaping the trade landscape and what to do about it. Intereconomics, 55(3), 135–139. Johnson, N.P.A.S.,  & Mueller, J. (2002). Updating the accounts: Global mortality of the 1918–1920 “Spanish” influenza pandemic. Bulletin of the History of Medicine, 76(1), 105–111. Kaminsky, G.L.,  & Reinhart, C.M. (1999). The twin crises: The causes of banking and balance-of-payments problems. American Economic Review, 89(3), 473–500. Kaminsky, G.L., Reinhart, C.M.,  & Végh, C.A. (2003). The unholy trinity of financial contagion. Journal of Economic Perspective, 17(4), 51–74. Kindleberger, C.P. (1989). Manias, Panics and Crashes: A  History of Financial Crises. New York: Basic Books. Kindleberger, C.P. (1991). Bubbles. In: J. Eatwell, M. Milgate, & P. Newman (eds.), The World of Economics. London & Basingstoke: Palgrave Macmillan. Kindleberger, C.P., & Aliber, R.Z. (2011). Manias, Panics and Crashes: A History of Financial Crises. 7th ed. New York: Palgrave Macmillan. Korzeb, Z., & Niedziółka, P. (2020). Resistance of commercial banks to the crisis caused by the COVID-19 pandemic: The case of Poland, Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(2), 205–234. Korzeb, Z., & Niedziółka, P. (2021). Determinants of differentiation of cost of risk (CoR) among polish banks during COVID-19 pandemic. Journal of Risk and Financial Management, 14(3), 110. Krugman, P.R. (1979). A model of balance-of-payments crises. Journal of Money, Credit, and Banking, 11(3), 311–325. Krugman, P.R. (1999). Balance sheets, the transfer problem, and financial crises. International Tax and Public Finance, 6(4), 459–472. Laeven, L. (2011). Banking crises: A  review. Annual Review of Financial Economics, 3(1), 17–40. Laeven, L., & Valencia, F. (2013). Systemic banking crises database. IMF Economic Review, 61(2), 225–262. Laeven, L., & Valencia, F. (2020). Systemic banking crises database II. IMF Economic Review, 68, 307–361. Lind, H. (2009). Price bubbles in housing markets: Concept, theory and indicators. International Journal of Housing Markets and Analysis, 2(1), 78–90. Ma, C., Rogers, J., & Zhou, S. (2020). Modern pandemics: Recession and recovery. Board of Governors of the Federal Reserve System, International Finance Discussion Papers, No. 1295. Malliet, P., Reynès, F., Landa, G., Hamdi-Cherif, M., & Saussay, A. (2020). Assessing shortterm and long-term economic and environmental effects of the COVID-19 crisis in France. Environmental and Resource Economics, 76, 867–883. Marschall, W.C. (2009). Origins of banking crises in Latin America: A critical view. Journal of Post Keynesian Economics, 31(4), 669–690. Mendoza, E.G.,  & Terrones, M.E. (2008). An anatomy of credit booms: Evidence from macro aggregates and micro data. NBER Working Paper, No. 14049. Mendoza, E.G., & Terrones, M.E. (2012). An anatomy of credit booms and their demise. NBER Working Paper, No. 18379.

Banking crises 51 Minsky, H.P. (1982). Can “It” Happen Again? Essays on Instability and Finance. Armonk: M.E. Sharpe. Morawski, W. (2002). Zarys powszechnej historii pieniądza i bankowości. Warszawa: Wydawnictwo TRIO. Morris, S., & Shin, H.S. (2016). Illiquidity component of credit risk. International Economic Review, 57(4), 1135–1148. Obstfeld, M. (1994). The logic of currency crises. NBER Working Paper, 4640. Retrieved from: https://doi.org/10.3386/w4640 Obstfeld, M. (1996). Models of currency crises with self-fulfilling features. European Economic Review, 40(3–5), 1037–1047. OECD (2020). COVID-19 and International Trade: Issues and Actions. Organisation for Economic Co-operation and Development. Retrieved from: www.oecd.org/coronavi rus/policy-responses/Covid-19-and-international-trade-issues-and-actions-494da2fa/ [06.10.2020]. Reinhart, C.M., & Rogoff, K.S. (2009). This Time Is Different: Eight Centuries of Financial Folly. Princeton: Princeton University Press. Reinhart, C.M.,  & Rogoff, K.S. (2013). Banking crises: An equal opportunity menace. Journal of Banking & Finance, 37(11), 4557–4573. Richter, B., Schularick, M., & Wachtel, P. (2020). When to lean against the wind. Journal of Money, Credit and Banking, Early View. Retrieved from: https://doi.org/10.1111/ jmcb.12701 [16.10.2020]. Romer, C., & Romer, D. (2017). New evidence on the impact of financial crises in advanced countries. American Economic Review, 107(10), 3072–3118. Sarker, P.K. (2020). Covid crisis: Fiscal, monetary and macro-financial policy responses. Theoretical & Applied Economics, 27(3), 41–54. Saunders-Hastings, P.R., & Krewski, D. (2016). Reviewing the history of pandemic influenza: Understanding patterns of emergence and transmission. Pathogens, 5(4), 66. Schularick, M., & Taylor, A. (2012). Credit booms gone bust: Monetary policy, leverage cycles and financial crises, 1870–2008. American Economic Review, 102(2), 1029–1061. Shiller, R.J. (2015). Irrational Exuberance: Revised and Expanded Third Edition. Princeton: Princeton University Press. Song, L.,  & Zhou, Y. (2020). The COVID-19 pandemic and its impact on the global economy: What does it take to turn crisis into opportunity? China  & World Economy, 28(4), 1–25. Stern, G.H., & Feldman, R.J. (2004). Too Big to Fail. The Hazards of Bank Bailouts. Washington, DC: Brooking Institutions Press. Taubenberger, J.K., & Morens, D.M. (2006). 1918 influenza: The mother of all pandemics. Emerging Infectious Diseases, 12(1), 15–22. Thornton, M. (2006). The economics of housing bubbles. In: B. Powell & R. Holcombe (eds.), America’s Housing Crisis: A Case of Government Failure. Ludwig von Mises Institute. Retrieved from: https://mises.org/system/tdf/The%20Economics%20of%20Hous ing%20Bubbles.pdf?file=1&type=document [16.10.2020]. Usman, M., Ali, Y., Riaz, A., Riaz, A., & Zubair, A. (2020). Economic perspective of coronavirus (COVID-19). Journal of Public Affairs. Retrieved from: https://10.1002/pa.2252 [06.10.2020]. Wang, Q., & Su, M. (2020). A preliminary assessment of the impact of COVID-19 on environment – A case study of China. Science of The Total Environment, 728, 138915. Retrieved from: https://doi.org/10.1016/j.scitotenv.2020.138915 [06.10.2020].

52  Banking crises WHO (2010). Pandemic (H1N1) 2009 – Update 112. World Health Organization. Retrieved from: www.who.int/csr/don/2010_08_06/en/ [10.11.2020]. WHO (2011). Implementation of the International Health Regulations (2005). Report of the Review Committee on the Functioning of the International Health Regulations (2005) in Relation to Pandemic (H1N1) 2009. World Health Organization. Retrieved from: https://apps. who.int/gb/ebwha/pdf_files/WHA64/A64_10-en.pdf [10.11.2020]. WHO (2015). Summary of Probable SARS Cases with Onset of Illness from 1 November 2002 to 31 July 2003. World Health Organization. Retrieved from: www.who.int/publications/m/ item/summary-of-probable-sars-cases-with-onset-of-illness-from-1-november-2002-to31-july-2003 [10.11.2020]. WHO (2019). Middle East Respiratory Syndrome Coronavirus (MERS-CoV). World Health Organization. Retrieved from: www.who.int/emergencies/mers-cov/en/ [10.11.2020]. WHO (2021). WHO Coronavirus Disease (COVID-19) Dashboard. World Health Organization. Retrieved from: https://covid19.who.int/ [7.01.2021]. World Bank (2020). Global Financial Development Report 2019/2020: Bank Regulation and Supervision a Decade after the Global Financial Crisis. World Bank Group. Retrieved from: www.worldbank.org/en/publication/gfdr/gfdr-2016/background/banking-crisis [16.10.2020].

4 European banking sector performance From Global Financial Crisis to COVID-19 pandemic

Introductory remarks The past two decades have been a period of profound, dynamic changes in the banking sectors, their operating environments, and the institutional frameworks within which they do business. Numerous external and internal factors influenced the structure of the banking sectors and their performance, including two massive crises: the first referred to as the Global Financial Crisis, and the second triggered by the COVID-19 pandemic. At the same time, there is a noticeable trend towards disintermediation in the financial sector, including in Europe, historically dominated by the bank-based banking model. This trend, although pronounced, has not affected the dominant role of commercial banks in financing economic activity in European countries. Therefore, the economic literature pays much attention to the bank’s performance phenomenon, expressed in different concepts of efficiency, profitability, productivity, concentration, and competition. The main reason for that interest is still the pivotal role banks play as loan providers; however, it must be stressed that banks significantly contribute to economic activity in several different ways. The concept of bank performance has a multidimensional nature; thus, it can be expressed “in terms of competition, concentration, efficiency, productivity and profitability” (Bikker & Bos, 2008). Due to the complexity and ambiguity of the concept of bank performance, it has become accepted to adopt much simpler and quantifiable measures as proxies. Most of the studies measure bank performance by parametric or nonparametric estimates of bank efficiency and productivity, while the most commonly used measures are bank profitability ratios (Bikker, 2010; Hasan et al., 2012; Tomuleasa & Cocrish, 2014): return on assets (ROA), return on equity (ROE), and net interest margin (NIM). However, the aforementioned multidimensional nature of the bank performance concept explains the existence of a wide range of its measures.

Drivers of bank performance – literature review A plethora of studies examined drivers of banks’ performance in particular countries and larger regions. While some studies focus on the understanding DOI: 10.4324/9781003351160-4

54  European banking sector performance

of bank performance in a single country (Berger et al., 1987; Berger, 1995; Neely & Wheelock, 1997; Athanasoglou et al., 2008; García-Herrero et al., 2009), others concentrate their studies on a panel of countries (Short, 1979; Bourke, 1989; Molyneux  & Thornton, 1992; Demirgüç-Kunt  & Huizinga, 1999; Abreu & Mendes, 2002; Jara-Bertin et al., 2014). The research on drivers of bank performance can be divided into two complementary approaches. In the first approach, authors emphasized the macroeconomic variables (Gerlach et  al., 2005; Jurevičienė  & Doftartaitė, 2013; Ongore & Kusa, 2013; Titko et al., 2015). In the second, which is dominating in the literature, authors explore both external (macroeconomic and/or industry-specific) and internal (bank-specific) factors affecting bank performance (Fraser et al., 1974; Athanasoglou et al., 2008; Gul et al., 2011; Titko & Dauylbaev, 2015). When analyzing which factors impact bank performance, we should consider, first, idiosyncratic features (like bank size, risk-liquidity combination, ownership, or external governance) and, second, institutional factors (legal, political, economic, and industry-specific), which may affect bank performance in an exogenous way. Two macroeconomic variables are indicated as important factors of bank performance: inflation and economic growth. Inflation was considered a particularly important determinant of bank profitability during periods of higher inflation (Revell, 1979; Perry, 1992), then almost disappeared from the analysis. The primary mechanism by which inflation deteriorates bank profitability relates to rising operating expenses across the whole banking industry (Revell, 1979). The second macroeconomic factor, economic growth, is perceived to have a positive influence on a bank’s performance (Short, 1979; DemirgüçKunt & Huizinga, 2000; Bikker & Hu, 2002; de la Torre et al., 2011). Most researchers indicate that GDP growth is important in promoting bank credit. Overall, the existing literature (cf. Table 4.1) provides a relatively comprehensive, albeit inconsistent, overview of banks’ performance drivers in the area Table 4.1  Banking sector performance – review of industry and bank-specific drivers Author(s) Industry-specific drivers Short (1979); Smirlock (1985); Bourke (1989); Molyneux and Thornton (1992); Berger (1995); Athanasoglou et al. (2008)

Edwards and Heggestad (1973); Heggestad and Mingo (1976)

Driver/determinant

Impact on performance (nature/ mechanism of impact)

Concentration

Positive impact on profitability (a greater concentration level within the industry implies higher monopolistic returns for its participants); only bank with a large market share and welldifferentiated products is able to generate noncompetitive profits; Negative impact on profitability (through the low risk aversion effect)

Concentration

European banking sector performance 55 Author(s)

Driver/determinant

Impact on performance (nature/ mechanism of impact)

Berg et al. (1992); Wheelock and Wilson (1999); Kumbhakar et al. (2001); Brissimis et al. (2008)

Deregulation

Deregulation has a positive impact on bank performance (channeled through the effect of competition and risk-taking of banks)

Bank size

Positive impact on profitability (through diversification and, thus, operational risk limitation; through the increase of low-cost capital) Negative impact on profitability (the effect of high operational and marketing costs, economies of scale disappear when size increases enormously) Negative impact of liquidity on profitability Positive impact of liquidity on profitability Privately owned banks are more efficient than mutual and publicowned financial institutions Ownership status is irrelevant for explaining profitability

Bank-specific drivers Smirlock (1985); DemirgüçKunt and Huizinga (2000); Bikker and Hu (2002); Anbar and Alper (2011); Masood and Ashraf (2012) Goddard et al. (2004); Athanasoglou et al. (2008); Gul et al. (2011); Singh and Sharma (2016)

Bank size

Molyneux and Thornton (1992) Bourke (1989)

Bank liquidity

Short (1979); Altunbas et al. (2001)

Ownership

Bourke (1989); Molyneux and Thornton (1992); Athanasoglou et al. (2008) Barth et al. (2007)

Ownership

Bank liquidity

External governance

Individual features of external governance (e.g., external ratings efficacy, auditing strength, financial statement transparency) have significant positive impact on bank performance

Source: Authors’ compilation.

of internal and industry-specific determinants. The ambiguity of the results is due to several reasons: first, the authors define performance differently and use diverse measures as proxies; second, they use different time dimensions for empirical studies, shorter and longer, sometimes too short to capture the effect of control variables; third, the authors use different methodologies for measuring the banks’ performance, both parametric and nonparametric approaches, which largely determine the results the authors obtain and the conclusions they formulate. A separate study on the performance of the banking sector addresses the specific situation of transition economies or evaluation of the significant financial reforms in developed countries. These studies were intended, first, to provide a basis for introducing reforms to enable the rapid and smooth creation of fully

56  European banking sector performance

efficient banking sectors as an important component of the market economy; and, second, to verify the appropriateness of conducting deep structural reforms in developed countries’ financial sectors (Keeley, 1990; Levine & Renelt, 1992; King & Levine, 1993; Berg et al., 1999; Grigorian & Manole, 2002; Brissimis et al., 2008). Undoubtedly, a key element in assessing the performance of the banking sector is the initial conditions prevailing in a transforming economy. Some economists argue that the influence of this factor is significantly diminishing over time (de Molo et al., 1997; Havrylyshyn & van Rooden, 2000). The results of studies conducted for transforming economies provide insights into potential drivers of banks’ performance (Grigorian & Manole, 2002; Brissimis et al., 2008). First, the performance of the banking sector depends on the architecture of the banking sector: larger, well-capitalized, and fewer banks potentially generate higher sector efficiency and higher rates of intermediation at the same time. Second, paradoxically, also supervisory regulations, which are generally perceived as a “corset” for the efficiency of the banking sector, in the long term, can contribute to the efficiency of the banking sector in particular: tighter minimum capital adequacy ratios are associated with stronger revenue generation capacity, thanks to the aggressive deposit taking behaviors, the single borrower-related limits do not affect the bank performance. Third, private ownership of banks, beyond those involving a transfer of controlling shares to foreign owners, does not result in significant improvements in bank efficiency.

The relevance of crises to bank performance The growing interconnectedness of the economies of countries and regions poses the threat of the transmission of negative phenomena to related economies and the global system of flows: factors of production, capital, goods, and services. Financial crises result from materializing various risks that affect the functioning of the entire financial sector. These risks include problems in the banking sector, which is responsible for 94% of financial crises. Banks are the core of the financial system and economy (Lo Duca et  al., 2021). They play an important role in economic development, as they act as intermediaries in transferring funds from surplus units to deficit units. Thus, bank efficiency is crucial, and more attention should be paid to it. However, crises can affect the smooth functioning of the financial system. A bank can be defined as safe when it is solvent, i.e., its claims exceed its liabilities. Additionally, in the banking sector, safety is determined by the ability to carry out banking operations without any major obstacles and act as a financial mediator. A synthetic expression of the impact of crisis effects on the economy is the reaction of financial markets. A  financial crisis is a situation in which financial markets emerge, usually related to insufficient liquidity or insolvency of banks, financial institutions, or other actors, leading to a decline in production or a worsening of the already-existing decline. In turn, a banking crisis is defined in the literature as a situation in which a significant part of the banking sector loses its security

European banking sector performance 57

(Iwanicz-Drozdowska, 2002, 35). The impact of the financial crisis has a significant impact on the global banking sector. Symptoms of crisis include the emergence of losses in the banking sector, as well as an increase in nonperforming loans. It should be noted that the safety of the sector can be determined by the situation of a particular bank, and problems with its solvency may affect the solvency of the entire sector. Most of the time, any business strategy becomes profitable during economic booms, and almost all government policies appear to be successful. In fact, during booms, the source of future problems is that most important mistakes are then made (Acharya  & Naqvi, 2012; Berger  & Demirgüç-Kunt, 2021; Berger & Udell, 2004; Rajan, 1994). The example of the 2007–2009 crisis showed that its spread was caused by at least two important trends in the banking sector: (a) a credit boom; and (b) housing madness. First, instead of storing loans on their balance sheets, banks used a new business model of transferring loans to various other financial actors. And by issuing “structured” products such as secured debt obligations (CDOs), they transferred risk. The transfer of the loan pool to off-balance sheet instruments and the subsequent allocation of a credit line to the pool in order to achieve an AAA rating have allowed banks to reduce their amount of capital. The popularity of structured investment vehicles was encouraged by regulatory and rating arbitrage. Second, banks increasingly financed their assets with instruments with shorter maturities, making them particularly vulnerable to a loss of funding liquidity (Choudhry & Jayasekera, 2012). Banks are hit by crises, mainly due to the deteriorating situation of their borrowers. Problems in the real economy lead to a significant number of bank failures or their financial losses. Banking capital is reduced by the credit losses of enterprises and households that have been unable to pay off their loans. Given the severity of the 2007–2009 Global Financial Crisis and the COVID19 pandemic crisis, it is essential that we analyze the impact of the recent crises on European banking sector efficiency. Dabrowski (2010) notes that the high exposure of European banks to toxic assets meant that the crisis revealed several systemic weaknesses of European banks. This opinion was also supported by Hardy et al. (2010), who noted that the financial crisis in 2007–2009 exposed shortcomings in international crisis management and burden sharing in the European Union. This disrupted the functioning of an effective single market and, as a consequence, showed the weaknesses in combining financial stability with fiscal responsibility. On the other hand, the COVID-19 pandemic, which caused the death and physical suffering of millions of people, also brought recessions that caused significant economic damage. The economic devastation is in some respects similar to the Great Depression of 1929 or the Global Financial Crisis of 2007–2009. Undoubtedly, the COVID-19 pandemic is characterized by the most unexpected and widespread exogenous economic shock of all time, affecting both developed and developing countries. The pandemic caused recessions around the world, translating into the efficiency of the banking sector (Berger & Demirgüç-Kunt, 2021). However, during the crisis, financial sector regulators introduced a number of changes to the way they

58  European banking sector performance

calculate Basel III regulatory capital ratios to help banks meet the requirements. In addition, greater leniency is allowed in the event of default on certain loans. Additionally, Berger and Demirgüç-Kunt (2021) believe that supervisors have temporarily reduced supervision during crises, which may result in some institutions reporting more favorable data in their financial statements. The economic downturn in the financial system usually leads banks to concentrate on their traditional activities (lending) or to diversify their activities by looking for sources of income other than interest (noninterest income). Although the effect of greater activity diversification on bank performance (profitability and risk) is well addressed in the literature, so far there is no consensus. Most studies dedicated to the banking sector emphasize that greater involvement in nontraditional activities leads to higher profitability but also to higher risk due to the increased volatility of these activities (Saghi-Zedek, 2016). Previous studies indicated that a shift towards noninterest activities worsens the risk–return trade-off (Stiroh & Rumble, 2006; DeYoung & Torna, 2013). Specifically, they show that greater involvement in diversification is associated with a higher probability of failure for financially distressed banks. On the other hand, Gallo et al. (1996) find that banks have potential benefits (improve profitability and reduce risk) to expanding their activities.

Trends in bank performance from the global financial crisis to the COVID-19 pandemic The Global Financial Crisis of 2007–2009 highlighted the risk of funding instability and maturity mismatches on banks’ balance sheets. The crisis led to the bankruptcy of several major investment banks, caused disruption and turbulence in many economies around the world, and hampered the development of the banking sector. The global crisis was a special phenomenon because it was not triggered by external factors but was the consequence of failures in the financial system. At the same time, it showed that banks stopped playing their role as financial intermediaries during the economic downturn. Most banks reduced their support for the economy and stopped granting loans, focusing primarily on protecting the value of their own assets and the level of efficiency achieved earlier. Inadequate risk management led to the outbreak of the biggest financial and banking crisis to hit the world economy in 2007–2008. The crisis started in the US mortgage market and then affected most countries in the world, especially highly developed ones in Western Europe. However, in the case of the European banking sector, the effect of the crisis was indirect, mainly caused by the economic slowdown. The collapse of the US bank Lehman Brothers and the systemic risk caused by the failure of other banks contributed to the spread of the crisis outside the United States. As a consequence of the poor situation of banks in the United States, a crisis of confidence occurred in the interbank market, and liquidity in access to funds was restricted. One of the reasons for starting the crisis was the incorrect identification of financial risk by banking institutions.

European banking sector performance 59

During the Global Financial Crisis, the contagion effect was an important element in developing instability in the banking sector. Globalization, which allowed large-scale cooperation between financial institutions and free capital flows, also was negatively affected during the crisis. Before the outbreak of the crisis in 2008, individual countries, to reduce costs and to stimulate bank innovation, carried out several deregulations that increased the freedom of banks to operate. After 2008, the focus turned to bridging the regulatory gaps that became apparent during the crisis. As a result, several microprudential standards were developed to strengthen banks’ resilience to liquidity and insolvency shocks. However, these measures had a twofold impact on the efficiency of the banking sector (Iwanicz-Drozdowska, 2017, 41). Following the Global Financial Crisis, banks in European countries faced the following problems: persistently low interest rates, high risks resulting from the interdependence between institutions, and excessively large sector structures. In light of persistently low interest rates in European countries, banks earned very little from selling loans and debt securities. Unfortunately, low interest rates encourage banks to invest in more profitable but risky assets. Low interest rates are particularly acute for banks focused on traditional activities. In addition, such a situation may generate a boom in the real estate market and, thus, create speculative bubbles. With the COVID-19 pandemic came the specter of bankruptcies and financial problems for both businesses and households. The coronavirus pandemic undermined the economic and financial stability of European countries. Significantly reduced investment activities and the increasing incidence of the disease and successive restrictions imposed led to increased unemployment and trade disruption. The effects of the pandemic have also affected the banking sector. One of the biggest problems for banks was the drop in liquidity resulting from customer panic and a sudden increase in cash demand. Furthermore, due to the growing risk aversion during this period, customers’ savings and investment habits changed. They more often decided to invest in safer assets or to place their funds in low-interest bank deposits. One of the most significant effects of the pandemic on the banking sector was the decrease in credit demand, particularly among households. In European countries, the decline in demand was influenced by psychological and economic factors resulting from fears about the economic situation and the workplace. An additional factor that limited customers’ credit activity was that banks increased credit requirements and credit margins. Thus, a significant effect of the pandemic on the banking sector is the decline in revenue from the main source of income, the interest margin. These major financial conditions encourage regulators, policymakers, and researchers to create a more efficient business model for the banking sector. Thus, banks are changing their business model to a more diversified one, focusing on a higher proportion of noninterest income. As of this writing, the COVID-19 pandemic and the decline in demand for credit was expected to trigger a shift in the balance between interest income and noninterest income due to different business activities.

60  European banking sector performance

The introduction of successive tight restrictions and then the outbreak of the COVID-19 pandemic forced all European central banks to act quickly and decisively to stimulate the economy. Although European central banks follow different monetary policy strategies, they used very similar monetary policy instruments in the pandemic crisis. The actions of central banks mainly concerned the purchase of issued securities and loans and advances. The creation of a pandemic emergency purchase program to buy back assets. The European Central Bank allocated a total of around 1850 billion EUR to the program. This program improved banks’ liquidity, thanks to which they did not have to reduce the number of loans they granted, and at the same time, they could offer beneficial interests. Open-market operations were another tool favored by central banks. In this case, banks’ actions were mainly based on: • • •

increasing the number of realized operations; extending the list of entities allowed to enter into open market operations; extending the list of acceptable collaterals.

Central and Eastern European central banks’ activities were primarily focused on “quantitative easing (QE),” i.e., the purchase of Treasury securities. They were introduced, among others, in Poland, Hungary, Croatia, and Romania. Among central banks that do not belong to the euro area, the Hungarian central bank used this tool most frequently, and the Polish central bank dominated in terms of the value of purchased assets. In Europe, the pandemic crisis resulted in lower loan sales revenues due to minimal interest rates, lower demand for most products, and the bank’s conservative policies. Also important was the introduction of credit vacations, which involved suspending or postponing installment payments for a certain period. Table  4.2 presents descriptive statistics of the EU banking profit and cost measures as well as interest and noninterest incomes for the period 2007–2021. We can observe that compared to the COVID-19 pandemic crisis, the 2007– 2009 crisis brought significant declines in bank profitability as measured by ROE and ROA. In 2009, we observed, respectively, an average ROA value of −0.08 and an average ROE value of −1.72, which deviated significantly from the Table 4.2  Descriptive statistics of the banking sector performance in the EU Full sample (2007–2021)

ROA ROE COST_INCOME INTEREST_INCOME_TA NETNONINT_INC_TA

Count

Mean

Median

SD

Min

Max

367 367 367 367 367

0.39 3.68 −58.24 3.50 0.98

0.49 6.47 −56.48 3.14 0.92

0.97 13.14 21.89 1.79 0.47

−7.99 −100.83 −412.21 1.01 −0.55

3.14 22.92 −18.67 16.42 2.96

European banking sector performance 61 2009

ROA ROE COST_INCOME INTEREST_INCOME_TA NETNONINT_INC_TA

Count

Mean

Median

SD

Min

Max

27 27 27 27 27

−0.08 −1.72 −53.21 4.78 1.09

0.24 4.68 −54.98 4.43 1.02

1.49 19.23 11.29 2.29 0.55

−3.97 −56.07 −76.74 2.07 0.29

1.85 22.68 −18.67 12.03 2.42

Count

Mean

Median

SD

Min

Max

27 27 27 27 27

0.37 3.78 −57.61 2.11 0.92

0.39 4.51 −57.08 2.07 0.85

0.41 4.42 7.66 0.57 0.29

−0.72 −7.84 −71.55 1.26 0.44

1.19 11.31 −42.60 3.55 1.82

2020

ROA ROE COST_INCOME INTEREST_INCOME_TA NETNONINT_INC_TA

Notes: ROA – Return on Assets, ROE – Return on Equity, COST_INCOME – cost-to-income ratio, INTEREST_INCOME_TA – bank interest income to total assets, NETNONINT_INC_TA – bank non-interest income to total assets. Source: European Central Bank database (https://sdw.ecb.europa.eu/, retrieved 15 June 2022), elaborated by the authors.

average values throughout the study period. The bank’s cost-to-income ratio remained stable throughout the analysis period and was close to −58%. Significant changes were verified in interest income and noninterest income. The COVID-19 pandemic resulted in significant declines in interest income, in particular, from 4.78 in 2009 to 2.11 in 2021. There was a smaller change in noninterest income, from 1.09 to 0.92, respectively. Going a step further, we compared the values of four different efficiency measures for the European banking sector and the average value for the whole sample (see Figures 4.1–4.3) for 2007–2021. Figure 4.1 shows the changes in the value of banks’ operating income compared to operating expenses in the European banking sector from 2007 to 2021. The analysis showed that both the 2007–2009 crisis and the COVID-19 pandemic had a significant impact on the decline in operating income in banks in Europe. In contrast, an analysis of interest vs. noninterest income over the 2007– 2021 period showed that the low level of interest rates in Europe brought a change in the trend of banks’ interest vs. commission income (see Figure 4.2). The pandemic crisis exacerbated this phenomenon even more. Banks began to decisively use commission fees to build revenues that fill an increasingly limited interest result. A more precise analysis of this phenomenon presented in Figure 4.3 showed a definite increase in the share of fees and commissions in the total result and a definite decrease in the result of interest. However, in the European banking sector, this trend was not triggered by the COVID-19 pandemic crisis but had already occurred since 2012. Our study leads us to

62  European banking sector performance

Figure 4.1 Operating income vs. operating expenses in total assets for the European banking sector over the years 2007–2021 (in %) Source: European Central Bank database (https://sdw.ecb.europa.eu/, retrieved 15 June 2022), elaborated by the authors.

Figure 4.2 Interest income vs. noninterest income in total assets for the European banking sector over the years 2007–2021 (in %) Source: European Central Bank database (https://sdw.ecb.europa.eu/, retrieved 15 June 2022), elaborated by the authors.

European banking sector performance 63

Figure 4.3 Interest income vs. fee and commission in total income for the European banking sector over the years 2007–2021 (in %) Source: European Central Bank database (https://sdw.ecb.europa.eu/, retrieved 15 June 2022), elaborated by the authors.

conclude that we may be facing a permanent change in the business model of banks in Europe.

Concluding remarks As a result of the crises of 2007–2009 and the COVID-19 pandemic, there was a slowdown in loan growth and, thus, a decline in the performance of banks in Europe. The process of contagion from the crises manifested itself mainly through: a decline in confidence in the banking sector by both individuals and businesses; the illiquidity of the interbank market, which was the result of a decline in confidence between banks; and a decline in lending, which hurt corporate financing. This process was accompanied by an increase in nonperforming receivables related to the deteriorating situation of borrowers. Factors that contributed to the reduction in lending by banks included an increase in credit risk, changes in central bank monetary policy, tighter prudential regulations by supervisory institutions, and an increase in the risk of insolvency of some banks in the banking system. On the demand side, factors limiting credit dynamics were declining domestic demand and consumption, and the deterioration in the labor market caused by the pandemic. However, the crises have led to a change in the model of bank operations. There is a significant trend to replace interest income in favor of the commission

64  European banking sector performance

income of banks. There has also been a marked qualitative development in the banking sector, expressed in the impact of new information technology, logistics, and communication solutions, which has fundamentally changed the organization of banks, the way they operate, and the way they provide financial services.

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66  European banking sector performance Hardy, D., Cortavarria-Checkley, L., Giustiniani, A., Fonteyne, W., Bossu, W., Gullo, A., & Kerr, S. (2010). Crisis management and resolution for a European banking system. IMF Working Papers, No. 1. Retrieved from: https://doi.org/10.5089/9781451982695.001 Hasan, I., Schmiedel, H., & Song, L. (2012). Returns to retail banking and payments. Journal of Financial Services Research, 41(3), 163–195. Havrylyshyn, O., & van Rooden, R. (2000). Institutions matter in transition, but so do policies. IMF Working Paper, No. 00/70. Heggestad, A.A., & Mingo, J.J. (1976). Prices, nonprices and concentration in commercial banking. Journal of Money, Credit and Banking, 8(1), 107–117. Iwanicz-Drozdowska, M. (2002). Teorie kryzysów bankowych. In: M. Iwanicz-Drozdowska (ed.), Kryzys bankowe. Przyczyny i rozwiązania. Warszawa: PWE. Iwanicz-Drozdowska, M. (Ed.). (2017). Zarządzanie ryzykiem bankowym. Warszawa: Wydawnictwo Poltext. Jara-Bertin, M., Arias Moya, J., & Rodríguez Perales, A. (2014). Determinants of bank performance: Evidence for Latin America. Academia Revista Latinoamericana de Administración, 27(2), 164–182. Retrieved from: https://doi.org/10.1108/ARLA-04-2013-0030 Jurevičienė, D., & Doftartaitė, D. (2013). Commercial banks’ activity dependence on macroeconomic indicators. European Scientific Journal, 9(31), 173–184. Kočani: European Scientific Institute. Keeley, M.C. (1990). Deposit insurance, risk, and market power in banking. American Economic Review, 80, 1183–1200. King, R.G.,  & Levine, R. (1993). Financial intermediation and economic development. In: Capital Markets and Financial Intermediation. Cambridge, New York  & Melbourne: Cambridge University Press. Kumbhakar, S.C., Lozano-Vivas, A., Knox Lovell, C.A., & Hasan, I. (2001). The effects of deregulation on the performance of financial institutions: The case of Spanish savings banks. Journal of Money, Credit and Banking, 33(1), 101–120. Retrieved from: https://doi. org/10.2307/2673874 Levine, R., & Renelt, D. (1992). A sensitivity analysis of cross-country growth regressions. The American Economic Review, 82(40), 942–963. Lo Duca, M., Koban, A., Basten, M., Bengtsson, E., Klaus, B., Kusmierczyk, P., & Lang, J.H. (2021). Occasional paper series a new database for financial crises in European countries ECB/ESRB EU crises database Developed by FSC MPAG and ESRB AWG. Retrieved from: https://doi.org/10.2866/902385 Masood, O., & Ashraf, M. (2012). Bank-specific and macroeconomic profitability determinants of Islamic banks: The case of different countries. Qualitative Research in Financial Markets, 4(2/3), 255–268. Retrieved from: https://doi.org/10.1108/17554171211252565. Molyneux, P.,  & Thornton, J. (1992). Determinants of European bank profitability: A  note. Journal of Banking and Finance, 16, 1173–1178. Retrieved from: https://doi. org/10.1016/0378-4266(92)90065-8. Neely, M., & Wheelock, D. (1997). Why does bank performance vary across states? Federal Reserve Bank of St Louis Reviews, 27–38. Ongore, V.O., & Kusa, G.B. (2013). Determinants of financial performance of commercial banks in Kenya. International Journal of Economics and Financial Issues, 3(1), 237–252. Perry, P. (1992). Do banks gain or loose from inflation? Journal of Retail Banking, 14(2), 25–30. Rajan, R.G. (1994). Why bank credit policies fluctuate: A  theory and some evidence. The Quarterly Journal of Economics, 109, 399–441. Retrieved from: https://doi. org/10.2307/2118468

European banking sector performance 67 Revell, J. (1979). Inflation and Financial Institutions. Financial Times, London. Saghi-Zedek, N. (2016). Product diversification and bank performance: Does ownership structure matter? Journal of Banking and Finance, 71, 154–167. Retrieved from: https:// doi.org/10.1016/j.jbankfin.2016.05.003 Short, B.K. (1979). The relation between commercial bank profit rates and banking concentration in Canada, Western Europe and Japan. Journal of Banking and Finance, 3, 209–219. Singh, A.,  & Sharma, A.K. (2016). An empirical analysis of macroeconomic and bankspecific factors affecting liquidity of Indian banks. Future Business Journal, 2(1), 40–53. Retrieved from: https://doi.org/10.1016/j.fbj.2016.01.001. Smirlock, M. (1985). Evidence on the (non) relationship between concentrationa dn profitability in banking. Journal of Money, Credit and Banking, 17, 69–83. Stiroh, K.J., & Rumble, A. (2006). The dark side of diversification: The case of US financial holding companies. Journal of Banking and Finance, 30, 2131–2161. Retrieved from: https://doi.org/10.1016/j.jbankfin.2005.04.030 Titko, J., & Dauylbaev, K. (2015). Testing quiet life hypothesis in the Baltic banking sector. In: Proceedings of the 19th World Multi-conference on Systemics, Cybernetics, and Informatics (WMSCI 2015), Vol. I, 118–123. Orlando: International Institute of Informatics and Systemics. Titko, J., Kozlovskis, K., & Kaliyeva, G. (2015). Relationship between concentration, competition, and efficiency in the Baltic banking sector. In: Proceedings of the 19th World Multi-conference on Systemics, Cybernetics, and Informatics (WMSCI 2015), Vol. I, 112–117. Orlando: International Institute of Informatics and Systemics. Tomuleasa, I.-I., & Cocrish, V. (2014). Measuring the financial performance of the European systemically important banks. Financial Studies, 4, 31–51. Wheelock, D.C., & Wilson, P.W. (1999). Technical progress, inefficiency, and productivity change in U.S. banking, 1984–1993. Journal of Money, Credit and Banking, 31(2), 212–234.

5 Policy response in the banking sector in the context of the COVID-19 epidemic

Introduction – state interventionism in theory No state or community can evolve if some of its citizens find themselves worse off than others, while at the same time, they fail to see the goodwill of those in charge to redress significant disproportions. The theoretical dispute about the existence of state interventionism was, and still is, among the most thoroughly debated issues in the history of economic thought. Among its greatest proponents were: the founder of French mercantilism Colbert (his thought was outlined inter alia by Ames, 2016); representatives of the German national school, including Fichte (1800), von Baader (his views on economy were presented by Adamson, 1878), Müller (1812), and List (1841); and leading figures of American protectionism, including Hamilton (Hamilton’s attitude to the trade, industry, and agriculture as well as state’s role in the economy are presented by Rusinowa, 1990), Raymond (1820; 1823), and Carey (1840). State intervention was advocated by Catholic socioeconomic doctrine (especially supporters of corporatism), Marx’s economic doctrine (1867), representatives of ordoliberal thought (Röpke, 1936; Rüstow, 1925; Erhard, 1957; Müller-Armack, 1946), and American institutionalists with the precursor of this direction, Commons (1934). Keynes (1936) and other scholars associated with the Keynesian and neo-Keynesian schools (Okun, 1975; Tobin, 1987) argue that state interventionism is necessary because influencing demand accelerates development and contributes to the stability of the economy. Even more radical views were presented by representatives of neoinstitutionalism – Galbraith (1967) and Melman (1985). Also, the trend of the so-called new active economic policy (Akerlof, 1984; Stiglitz, 1989), which developed in the late 1980s, tries to prove that the state is (besides the market) a necessary regulator of the economy. A completely different position is taken by economists, who advocate the efficiency of the market mechanism. They believe that the state should play only a marginal role in the economy and should not interfere in allocating production factors. The great supporters of liberalism were Smith (1776) and other representatives of the classical school: Malthus (1798), Say (1803), and Mill (1863). Also, the concepts of the neoclassical school, represented by Marshall DOI: 10.4324/9781003351160-5

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(1890), Schumpeter (1934), and Pigou (1920), and especially the liberalism of the Chicago School, equipped the state with only a modest role of creating the legal framework for the functioning market economy. Von Mises (1912) observes that under conditions of interventionism, the state, by interfering in certain spheres of the free market, replaces civic government – i.e., a government that looks after the interests of all citizens – with government exercised by various interest groups. Proponents of liberalism (neo-Austrian school: von Hayek, 1931; von Haberler, 1936; Machlup, 1962; monetarists: Andersen & Jordan, 1968; Sprinkel, 1971; Brunner, 1974; Meltzer, 1995; supply-side economics: Laffer, 1970; theory of rational expectations: Lucas, 1981; Kydland & Prescott, 1982; Barro, 1984; Sargent, 1987) believe that the market economy is stable in the long term and that state intervention is unnecessary and brings more harm than good. Friedman (1962) and Buchanan (Buchanan & Tullock, 1962) – Nobel Prize winners in 1976 and 1986, respectively – argue that in reality, it is the state and not the market that causes an inefficient allocation of resources. Although sectoral policies are still among the most controversial forms of state interference in the economic sphere, state interventionism is robust in the modern world. Unlike any other economic theory, state interventionism does not ensure economic success on its own. Only a balanced combination of this form of state aid with different development strategies can bring the expected results. Modern states are based on a mixed-type economy, where state aid for various sectors of the economy plays a prominent role alongside market mechanisms and private ownership. The only fundamental problem remains the scale of state intervention and the delineation of its main directions. One of its most important goals is to counteract the excessive polarization of society caused by the disproportion of income achieved by different professional and social groups.

Governmental support towards the COVID-19 crisis The applied calendar of aid systems depended primarily on the attitude of individual governments to the introduction of widespread restrictions – restrictions on movement; closure of hotels, restaurants, most shops in shopping malls, and some service providers; suspension of cultural and event institutions; suspension of teaching in schools and universities; and so on. In some countries, they were implemented quickly (Asian countries such as China, Singapore, and Taiwan); in others, governments delayed such a decision or adopted a different concept to fight the pandemic (United States, United Kingdom, Sweden). Still, other countries were forced to take drastic measures due to a very rapid increase in the number of confirmed cases and deaths (Italy, Spain). The vital issues became having a comprehensive plan to counteract the transmission of the pandemic, informing the public on further intentions, the attitudes of a given population to government action, and the responsibility and discipline of the country’s citizens to comply with the restrictions.

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The economic slump associated with the pandemic was primarily caused by the closure or reduction in the activity of several industries to flatten the incidence curve and limit the spread of the virus. Therefore, a need for relief measures emerged, mainly to keep businesses and individuals afloat and maintain employment levels. The spread of the SARS-CoV-2 virus, which causes the COVID-19 disease, has prompted the authorities to introduce support programs for businesses and individuals to mitigate the effects of the pandemic, as well as the consequences of implementing a series of restrictions and rigidities that dramatically changed the economic environment and the operating conditions for businesses, households, and the financial sector (Figure 5.1). The primary source of support for the EU economies is the Recovery Plan for Europe (EC, 2020), approved by the European Commission, the European Parliament, and the heads of state and government of the member states. This program, together with NextGenerationEU, a temporary instrument stimulating economic revival, is the most extensive package of measures so far financed

Figure 5.1  Economic impact of the COVID-19 pandemic Source: Authors’ elaboration.

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from the EU budget, amounting to a total of 1.8  trillion EUR. More than 50% of this amount will be dedicated to modernization through, among other things: research and innovation, via Horizon Europe; fair climate and digital transitions, via the Just Transition Fund and the Digital Europe Programme; and preparedness, recovery, and resilience, via the Recovery and Resilience Facility (rescEU) and a new health program, EU4Health (EC, 2020). NextGenerationEU is a 750 billion EUR temporary recovery instrument to help repair the immediate economic and social damage brought about by the coronavirus pandemic. The aim of its most crucial element, the Recovery and Resilience Facility, with a budget of 672.5 billion EUR in loans and grants, is to “mitigate the economic and social impact of the coronavirus pandemic and make European economies and societies more sustainable, resilient and better prepared for the challenges and opportunities of the green and digital transitions.” In addition, a new SURE (Support to mitigate Unemployment Risks in an Emergency) instrument was set up to help member states in need of bailouts, schemes for job retention and redundancy reduction, as well as those protecting against income loss. Furthermore, the European Union has made simplifications in the regulatory framework. Temporarily departing from the rules laid down in the Stability and Growth Pact, member states can deviate from the deficit reduction path agreed with the Commission, which in practice means allowing individual countries to increase their budget deficits. Other simplifications involved principles for granting state aid, including direct subsidies, loan guarantees, tax benefits, export credit insurance, and several other temporary measures during the pandemic. The main component of the targeted measures carried out to reduce the threat to public health and the economic impact of the spread of the virus were systemic solutions and measures allocated at the national level. Stimulus packages – both fiscal and monetary – implemented by individual countries were aimed at creating opportunities to ensure that industries at risk due to COVID-19 could survive the period of restrictions and to enable the fastest possible return to the growth path once the pandemic is overcome and restrictions are lifted. Aid funds were allocated primarily to finance public expenditure on health care support, development of vaccines, purchase of tests and personal protective equipment, protection of employees and consumers (subsidizing salaries and the social insurance system: idle time allowances, additional social benefits, exemptions from social security contributions), and assistance for the economic sectors most affected by the consequences of the pandemic. For the latter purpose, special capital, liquidity, or preferential financing schemes were created for enterprises. The offered assistance consisted of mechanisms of guarantees and sureties granted as security for repayment of working capital or investment loans. Another solution was the introduction of preferential loans for companies that have lost or are at risk of losing liquidity due to the economic situation caused by the COVID19 pandemic, with interest rate subsidies. Within this scheme, government

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institutions cover part of the interest payable by the borrower to the bank. Another solution involved using liquidity components to finance credit holidays for companies and individuals. Some countries also opted for rescue packages targeted at local authorities, providing compensation and indemnities for loss of revenue due to reduced tax revenue as a result of reduced economic activity in their area (GOV, 2020). Separate support was provided for job retention, with specific measures including wage subsidies for job retention and the possibility of working time reductions combined with wage subsidies for workers with reduced working hours, or even a ban on dismissing workers for reasons related to the coronavirus outbreak (e.g., in Spain it is not possible to invoke force majeure or economic, technical, and organizational complications resulting from the restrictions). Not surprisingly, large-scale measures to support businesses and protect jobs necessitated amending budgets at the national level as a result of significant unplanned increases in expenditure and decreases in revenue. It was soon widely acknowledged that the situation caused by the pandemic was extraordinary, and to contain it effectively, governments had to assign significant resources for expenditure related to the effects of COVID-19 and increased investment expenditure to stimulate economic growth (Figure 5.2). However, such support mechanisms contribute to a sharp increase in public debt, which has now become an inherent part of the used crisis aid schemes (Figure 5.3).

Figure 5.2 Value of stimulus packages introduced in selected countries in 2020 (% of 2019 GDP) Source: Authors’ compilation from Bruegel.org (retrieved 17 January 2021, from: www.bruegel.org/ publications/datasets/covid-national-dataset).

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Figure 5.3 Change in general government gross debt expressed as % GDP in Q2, 2020 relative to the previous quarter in selected EU countries Source: Authors’ compilation based on Eurostat database.

Anderson et al. (2021) classify applied aid measures into three groups: •

•

•

Immediate fiscal impulse: additional government spending (such as medical resources, employee retention, subsidizing SMEs, public investment) and foregone revenues (such as cancelling certain taxes and social security contributions). These measures immediately lead to the deterioration of the budget balance without any subsequent, direct compensation. Deferrals: several countries have decided to defer certain payments, including taxes and social security contributions, which in principle should be paid back later. These measures improve the liquidity positions of individuals and companies but do not cancel their obligations. Some of these deferrals lasted several months and expired in 2020, in which case they will not impact the overall 2020 budget balance, just some monthly budget balances. Those deferrals which expire in 2021 or later led to the deterioration of the budget balance in 2020 but will improve it later. A few countries have also deferred the servicing of loans or the payment of utility bills, which are also essential tools in enhancing the liquidity positions of those impacted, and hence we include them. These measures also have budgetary implications. Even if private banks and utilities grant the loans, the budget balance deteriorated in 2020 because of lower profits and consequent taxes, but still, it will improve at a later time. Other liquidity provisions and guarantees: these include export guarantees, liquidity assistance, and credit lines through national development banks. Some of these measures improve the liquidity position of the private sector.

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Still, unlike deferrals, which are automatic and generally apply to the target groups, credit lines require action from the impacted companies. Credit lines and guarantees might not weaken the budget balance in 2020 but may create contingent liabilities, which might turn into actual expenses either in 2020 or later. It should be noted that in 2009, during the recession resulting from the Global Financial Crisis, only five European Union member states – Denmark, Estonia, Luxembourg, Finland, and Sweden – maintained their deficit levels below 3% of GDP, while three countries – Greece, Ireland, and Spain – had deficits exceeding 10% of GDP. In 2010, the deficit of Ireland, which was struggling with a deep banking crisis, even exceeded 30% of GDP. Monetary policy measures applied by central banks have become another important source of assistance. Central banks aimed at stabilizing financial markets and maintaining favorable financing conditions for all sectors of the economy, providing crucial support for economic recovery and safeguarding medium-term price stability.

Central banks’ response to the COVID-19 crisis The activities of the European Central Bank (ECB) focused primarily on increasing funds to support the real sector and increasing liquidity in the banking system. The primary aid instrument was the extension of the existing Asset Purchase Programme (APP) with an additional Pandemic Emergency Purchase Programme (PEPP) worth 1.85  trillion EUR. Its primary objective was to lower borrowing costs and increase lending in the eurozone. This was supposed to translate directly into access to external financing for individuals, companies, and governments necessary to weather the crisis. Under the PEPP program, the ECB purchases various types of securities, whether from governments or banks – thus providing more funds to grant loans to customers and corporates – thereby constituting an alternative means of financing their activities. It covers various asset classes, including government bonds. At the same time, the group of assets eligible for the corporate sector purchase program (CSPP) has been expanded. The ECB also allows for nonfinancial commercial papers of sufficient credit quality to be eligible for CSPP purchases. Another instrument used by the ECB is refinancing operations. Their purpose is to improve the functioning of the monetary policy transmission mechanism by supporting lending to the real economy. The idea behind the TLTRO III long-term loan program for commercial banks was to provide banks with non-cash funds on favorable terms, which could be used to step up their lending at the time of the pandemic. Therefore, it was decided to reduce their interest rate to 50 basis points below the average interest rate on the Eurosystem’s main refinancing operations over their lifetime. A new series of untargeted pandemic emergency longer-term refinancing operations (PELTROs) have also been offered to support liquidity conditions in the eurozone financial

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system and preserve the smooth functioning of money markets. They are allocated based on tendering procedures at an interest rate which, in turn, is 25 basis points below the average interest rate on the main refinancing operations over their lifetime. The ECB also increased the amount of money offered to banks during the pandemic under the banking sector’s immediate borrowing option to mitigate temporary funding problems. Asset purchase and liquidity support schemes offered to banks were among the most essential nonstandard monetary policy measures. The negative interest rate environment in the eurozone prompted a focus on QE. According to the scheme’s assumptions, they should be directly reflected in improving the liquidity situation in the banking sector and thus improving financing conditions for bank customers. The ECB intended to stimulate, based on a credit impulse, consumption and investment and, as a result, economic growth and the maintenance of employment levels after the crisis. As the arsenal of measures at the ECB’s disposal was limited to quantitative easing, the eurozone central bank further proposed facilitating borrowing by relaxing collateral standards. To this end, the list of assets that can be used as collateral was temporarily extended. Less stringent requirements were applied to determine the value of these assets (determined by the haircut index). The ECB was also one of the initiators of the currency swap lines between central banks. The strengthening of cooperation in this area was primarily driven by the potential for increased demand for foreign currency assets in times of uncertainty. The applied instruments of QE, implemented through the purchase of financial instruments, mainly government and corporate bonds, are among the most controversial policies applied by central banks. Supporters of this type of intervention (B. Bernanke, M. Draghi, O. Blanchard) emphasize that aggressive monetary policy mitigates recession by reducing market disturbances occurring as a result of an extraordinary situation. The idea behind these operations is to increase the money stock held by banks and lead, through the mechanism of the monetary multiplier, to an increase in the total money supply in the economy. An additional effect of the policy of quantitative easing is a reduction in long-term interest rates because the purchase of securities by the central bank also causes an increase in market prices of securities, and thus a decrease in their profitability. This is extremely important from the point of view of increasing government debt. The opponents, on the other hand (C. Martin and C. Milas, D. Stockman, M. Friedman, and A. Schwartz), emphasize that central bank interference distorts market mechanisms and, as a result, some funds are inefficiently allocated. Such measures also reduce the pressure for necessary structural reforms and consolidation of public finances. They make it easier for governments to borrow more on financial markets and thus increase public debt. According to critics, QE policies lead, in an environment of low interest rates and easy access to credit, to suboptimal investments, contributing to an excessive increase in nonproductive assets on the market. This also applies to banks which, instead of

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active lending, allocate funds to risky investments in capital markets. Another issue is the impact of nonstandard measures on potential inflation, which may occur together with the release of demand after the removal of barriers that make it difficult or impossible to buy or use certain types of services. Both the impact of the realization of deferred consumption and pricing decisions taken by enterprises, which may compensate for a worse period of prosperity during a pandemic by increasing prices, remain unknown. Objections to the QE strategy were further strengthened after the verdict of the Federal Constitutional Court (German: Bundesgerichtshof, BGH) in Karlsruhe on 5 May  2020, which rejected part of an earlier 2018 ruling by the European Court of Justice in Luxembourg that the ECB’s actions in this regard were legal. The complainants of the ECB’s actions – a group of some 1,750 individuals led by German economists and law professors – claimed that the ECB finances the expenses of European Union governments, which is incompatible with the Treaty on the Functioning of the European Union. The Court ruled that the ECB had exceeded its powers in ordering the German government and parliament to have the ECB assess to what extent government bond purchases are part of the monetary policy and to what extent they serve the fiscal objectives of EU governments. It concluded that the ECB was interfering too extensively in the economic policies of the member states, which is a national and not an EU domain. Although the ECB provided explanations that the German government and parliament found sufficient, disputes about the legality of QE actions, the extent of interference in national economic policies, the ultimate impact of the intervention on taxpayers, and the size of the implemented operations, remained unresolved. Central banks worldwide are seeking to mitigate the immediate impact on the real economy through traditional monetary policy measures, but also some extraordinary monetary, financial, and macroprudential measures. Currency devaluation, capital controls, and bail-in are the main tools available to national financial authorities; however, there is no universal playbook. Basically, the tools used by the central banks can be classified into three different policies, which are entirely made up of central bank policies but are assumed to have slightly differently defined main objectives (cf. Table 5.1): • • •

monetary policy – focused on the objective of price stability, i.e., the strict and direct control of money supply and the promotion of stable economic growth as an additional objective; external policy – used to mitigate the effects of external economic shocks, and using the exchange rate tool; financial policy (macroprudential and microprudential)  – focusing on the stability of the banking sector and support for borrowers.

The use of the tools of the aforementioned policies depends primarily on the institutional and legal solutions adopted; for example, the participation of a country in the monetary union makes it impossible to use devaluation

Policy response in the banking sector 77 Table 5.1  Selected European central banks’ response to COVID-19 – first wave AUT BEL FIN FRA GER ITA POL SPA SWE GBR Monetary policy tools Policy rate cut CB liquidity support CB swap lines CB asset purchase Banking sector support Easing of countercyclical capital buffer Easing of systemic risk capital buffer Use of capital buffers Use of liquidity buffers Adjustments to provisioning requirements Financial policy tools State loans or credit guarantees Restructuring of bank loans

+ + +

+ + +

+ + +

+

+ + +

+ + +

+

+

+ + +

+

+ + +

+ + +

+ + + +

+

+

+ + +

+ + +

+ + +

+

+

+

+

+

+

+ + +

+

+ + +

+ + +

+ + +

+ + +

+ + +

+ + +

+

+

+

+

+

+

+

+

+

+

+ + +

+

Source: Authors’ elaboration based on central banks’ data.

as a tool of anti-crisis policy and on the identified channels for the spread of the crisis. The crisis triggered by the COVID-19 pandemic is not a classic financial or currency crisis (cf. Chapter 3); hence, the actions taken by central banks are often unprecedented and, for the most part, significantly ahead of the theoretical considerations in this area. Most central banks’ experience was based on previous global crises; thus, they were much better prepared to react in emergency situations, from both a theoretical and a practical point of view. Undoubtedly, the key in such situations turned out to be the speed of reaction and the comprehensiveness of undertaken actions (cf. Table 5.1). In addition to the policy of quantitative easing, central banks have, where possible, taken steps to reduce key interest rates (Figure 5.4). Such steps were taken by central banks of, among others: the UK, Sweden, Norway, Poland, the Czech Republic, Hungary, Romania, and Serbia. The situation was different in Turkey, where the central bank first cut rates several times before raising them in the last quarter of 2020. However, this was the result of its specific monetary policy in previous periods that kept interest rates as low as possible despite high inflation and a weakening currency. It is worth noting that central banks have not forgotten what their primary objective of the policy is, even in the face of the COVID-19-induced economic crisis. As long as the low-rate environment – conducive to creating economic growth – did not pose a threat in terms of inflation, central banks have systematically lowered interest rates. Faced with rising inflation, most central banks decided to take the radical step of raising interest rates, with some central

78  Policy response in the banking sector

Figure 5.4  Changes in interest rates of central banks in selected European countries Source: Own elaboration based on central banks’ data.

Policy response in the banking sector 79

banks reacting sooner and others a little later. These decisions will not leave the banks unaffected, especially their performance. In the case of Poland, for example, the National Bank of Poland (NBP) cut its key interest rates three times, reducing the reference rate from 1.50% to 0.10%. These were the first changes in interest rates in the last five years in this country. In addition, the central bank lowered the obligatory bank reserve rate on PLN and foreign currency funds held in bank accounts from 3.5% to 0.5%. The loosening of monetary policy has essentially contributed to lowering the cost of operating loans for businesses and individuals, as most of them are based on floating interest rates. The decision to reduce interest rates has also resulted in lower yields on treasury bonds, thus reducing the cost of servicing the public debt. In addition, the NBP started buying Treasury bonds and bonds guaranteed by the State Treasury in the secondary market. Such an action prevented an increase in the profitability of these securities, which could have occurred as a result of a significant increase in their supply by the Treasury, in this manner financing aid programs directed at entrepreneurs. On the other hand, the decisions taken by central banks have contributed to a reduction in the profitability of the banks’ operations, by reducing deposit interest margins to practically zero. It should be noted that banks have obtained relatively high income from deposit activity in the Polish banking sector. However, most of the central banks have exhausted the possibility of further reductions in interest rates set for transactions with commercial banks, and thus another use of this basic instrument of monetary policy. The reduction in key interest rates by major European central banks has led to a situation where some customers had to face negative deposit rates. A German financial product comparison portal, Biallo.de, analyzing the prices of products and services charged by 1,300 banks operating in the German banking sector, found that about 260 financial institutions charge some of their customers with negative interest (330 from corporate customers). Schick (2020) notes that banks do not usually use the phrase “negative” or “penalty interest” (Negativzins, Strafzins) but instead use the term “custody fee” (Verwahrentgelt). It is also common practice to impose charges on accounts that were previously free of charge. This means, in practice, a negative interest rate, although it is not charged directly. According to an analysis by the Bank of Slovenia (2020), certain customers would be willing to accept negative interest rates or custody fees, similarly to their acceptance of the negative effective interest rates or negative real interest rates that result from the combination of fees with very low positive interest rates and inflation, although it is difficult to determine the level of costs that they would be willing to accept. It should be noted, however, that central banks, by applying a negative interest rate policy, are also trying to achieve a market effect, the so-called forward guidance, which is an attempt to convince market participants that central banks are determined and will do everything to fight the results of the pandemic and

80  Policy response in the banking sector

stimulate the economy. Therefore, the idea is to build a strong monetary policy image, which plays a crucial role in cross-border capital investment markets. Supervision authorities have also taken a number of measures to mitigate the situation’s impact on the banking sector. ECB Banking Supervision made decisions on reducing capital and liquidity requirements. Banks were allowed to operate temporarily below the level of capital specified in Pillar 2 (P2G) guidelines, the capital conservation buffer (CCB), the countercyclical capital buffer and the liquidity coverage ratio (LCR). Also new guidance was introduced for the asset classification and the expected loss provisioning (Borio & Restoy, 2020). According to the ECB (2020a), “capital and liquidity buffers have been designed with a view to allowing banks to withstand stressed situations like the current one.” The ECB claims that these temporary measures will be strengthened by the appropriate relaxation of the countercyclical capital buffer (CCyB) by the national macroprudential authorities. In the ECB’s view, banks will also be allowed to partially use capital instruments that do not qualify as Common Equity Tier 1 (CET1) capital, for example, Additional Tier 1 or Tier 2 instruments, to meet the Pillar 2 Requirement (P2R). This brings forward a measure that was initially scheduled to come into effect in January 2021, as part of the latest revision of the Capital Requirements Directive (CRD V). The idea was also to leave the capital at the disposal of the banks so that they could use the funds thus used to increase their lending capacity and cover losses related to the pandemic. Moreover, the ECB (2020b) has benefited from supervisory flexibility under current legislation by: • • • •

announcing prudential treatment of loans backed by public guarantees; encouraging institutions to avoid excessive procyclical effects when applying International Financial Reporting Standards (IFRS 9); making temporary reductions in the qualitative market risk multiplier in response to extraordinary levels of market volatility; issuing a recommendation on dividend payouts to preserve capital resources in the banking system to enhance its ability to support the real economy.

ECB Banking Supervision put a series of measures to help banks cope with the situation; it has taken a pragmatic approach to implement its annual core activity – the Supervisory Review and Evaluation Process (SREP) – by introducing operational flexibility in terms of timing, deadlines, and supervisory procedures. At the same time, the ECB has indicated that it expects interaction between the launched support instruments, which should contribute to the synergy effect with the measures applied by the institution as part of its central bank monetary policy.

Policy response in the banking sector 81

The European Banking Authority (EBA) further strengthened measures in this area, in part by deciding to postpone exercising the 2021 EU-wide stress test. According to assumptions, this would allow banks to focus on and ensure continuity of their core operations, including support for their customers. The EBA also recommended that banks refrain from paying dividends and buying back their own shares, and defer payment on variable remuneration (EBA, 2020). The unprecedented impact of COVID-19 also prompted other supervisory institutions in countries outside the ECB’s jurisdiction to take swift and decisive action to ensure that commercial banks could continue to fulfill their essential role in financing the real economy. For example, the Bank of England suspended for at least 12 months the requirement for a countercyclical buffer to counteract threats to banks from UK borrowers (down to 0% from the current 1% of bank exposures and 2% of previously planned from December 2020). In Poland, the supervisory authority, the Polish Financial Supervision Authority (KNF), and the Ministry of Finance developed a special regulatory package that repealed the 3% systemic risk buffer to increase banks’ lending capacity. In addition, the rules for estimating losses on credit and banking risks were made more flexible. According to the KNF, the rescheduling of loans due to the pandemic for borrowers whose debt-servicing capacity has deteriorated solely on account of it, should not trigger the reclassification of receivables. More lenient requirements of IFRS 9 and the postponement of the need to comply with the MREL are intended to limit the impact of the crisis on banks’ cost of risk. The financial sector, particularly banks, is expected to play a key role in absorbing the shock by supplying much-needed funding. The actions of the banks themselves were directed at two parallel levels: debt restructuring, including credit holidays, which ensured that existing loans were serviced by the customers most affected by the pandemic; and guaranteeing the safety of employees and customers in banks’ facilities. One element of support was the creation, in many countries, of the possibility of deferring repayment of capital and interest installments or capital installments or interest installments, usually for 3 months, and automatically extending by the same period the total period of credit repayment subject to the extension of the period of validity of the security for credit repayment (socalled credit holidays). This support was addressed to economic entities and individual customers whose financial situation deteriorated due to the pandemic. This solution applied to bank customers who exhibited good financial credibility, documented credit history, and lack of arrears resulting from previously concluded contracts at the time of the declaration of the epidemic state. Banks additionally introduced special facilities for their customers, thus supporting systemic activities of the government and state institutions. One such facility was the additional extension of credit holidays by some banks over institutional proposals. Banks also offered to suspend the repayment of charges arising from credit card debts held by individual customers as well as businesses. In addition, banks modified their procedures for extending revolving

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facilities by introducing simplified rules. Furthermore, they did not charge fees or commissions for accepting and processing applications for credit holidays. For example, in Poland, according to the data of the Polish Bank Association (ZBP), this solution made it possible to suspend over 500,000 loans for individual customers and 45,000 loans for entrepreneurs (ZBP, 2020). In the interest of customer safety, banks have encouraged customers to make cashless payments. In some countries, the limits for contactless transactions, without the need for authorization, were also increased. According to the PwC Strategy (2020) report, the crisis has accelerated the gradual departure of consumers from cash payments. A  survey conducted in 12 European countries showed that only 36% of customers prefer cash payments. This constitutes a significant decrease compared to the results of the corresponding survey carried out in 2018, in which 43% of respondents favored this form of payment. It should be noted, however, that there are still substantial differences in payment methods across Europe. For example, in Sweden, only 15% of consumers prefer to pay by cash, compared to 57% in Austria and 56% in Germany. The most significant changes in customer mentality and change in their payment method habits were reported in Switzerland, Italy, and Poland. Banks have also taken a number of initiatives to ensure the operational continuity of their operations, including remote working for staff who do not have direct contact with customers and maintaining the functioning of most bank branches and facilities as far as possible, ensuring the safety of both staff and customers. However, this entailed limiting service hours in many branches. Customers were encouraged to reduce to the minimum face-to-face visits in banks. Restrictions were introduced on the number of people inside the premises and keeping a safe distance between customers; special screens were installed to separate customers from direct service personnel, supported by a unique system whereby customers were invited inside the building after another person had been served. It has become standard practice to provide hand disinfectant liquids, equip staff with gloves and protective masks, and regularly disinfect doorknobs, countertops, railings, handles, and other critical areas for virus transmission. Banks have introduced hours specifically dedicated to serving older people. In addition, measures were also implemented to create information campaigns with tips on how to use electronic channels by this segment of customers, who had not yet had much contact with the internet or online banking. The pandemic has contributed to a significant acceleration in the digitalization of products and services and the procedures used while encouraging customers to use remote communication channels: e-banking, mobile applications, telephone, chat, or video calls. This has resulted in a dynamic increase in mobile customer activity, including the sale of products and services. According to data by one of Poland’s largest banks, Bank Pekao SA, in April 2020 alone, the share of new personal accounts whose sales were initiated via digital channels (including account opening by sending necessary documents via electronic channels) increased significantly to 45% compared to January 2020, and 68%

Policy response in the banking sector 83

of cash loans were sold online. In addition, this bank’s service center handled around 15,000 phone calls per day (Pekao, 2020). Banks have accelerated the implementation of advanced digital solutions, digitalization, and automation of processes (e.g., accepting documents in electronic form) to enable remote customer service. The banks’ activities were not limited to business activity only. By making donations, they provided support to hospitals, medical institutions, and people working in the health care sector. Many banks, as part of their support for the Polish health service, donated funds for the purchase of modern medical equipment, SARS-CoV-2 tests, or the purchase of necessary personal protective equipment (protective masks, disposable gloves, disinfectants, etc.). In conclusion, there is no doubt that countries with more robust economic foundations and better responses to the pandemic by means of their swift and targeted economic policy measures will bear lower economic costs and return to economic growth more quickly. The extent of the recession and subsequent recovery will depend primarily on the duration and effectiveness of measures counteracting the spread of COVID-19 and the effectiveness of the instruments implemented by governments, central banks, supervision institutions, and banks themselves.

References Adamson, R. (1878). Franz Xaver von Baader. In: T.S. Baynes (ed.), Encyclopedia Britannica, Vol. 3, 9th ed. New York: Charles Scribner’s Sons, 173–175. Akerlof, G.A. (1984). An Economic Theorist’s Book of Tales: Essays That Entertain the Consequences of New Assumptions in Economic Theory. Cambridge: Cambridge University Press. Ames, G.J. (2016). Colbert, Mercantilism, and the French Quest for Asian Trade. New York: Cornell University Press. Andersen, L.C., & Jordan, J.L. (1968). Monetary and fiscal actions: A test of their relative importance in economic stabilization. Federal Reserve Bank of St. Louis Review, November, 11–24. Anderson, J., Bergamini, E., Brekelmans, S., Cameron, A., Darvas, Z., Domínguez Jíménez, M., Lenaerts, K., & Midões, C. (2020). The fiscal response to the economic fallout from the coronavirus. Bruegel Datasets. Retrieved from: www.bruegel.org/publications/ datasets/covid-national-dataset [17.01.2021]. Bank of Slovenia (2020). Bank of Slovenia Staff Analysis. Custody Fees and Negative Interest Rates for Household Deposits. Retrieved from: https://bankaslovenije.blob.core.win dows.net/publication-files/negativne_obrestne_mere_za_vloge_prebivalstva_eng-gb_02. pdf [18.01.2021] Barro, R.J. (1984). Macroeconomics. New York: Wiley. Borio, C., & Restoy, F. (2020). Reflections on regulatory responses to the Covid-19 pandemic. BIS. FSI Briefs, No. 1., 15 April 2020, 15. Retrieved May 16, 2020, from: www. bis.org/fsi/fsibriefs1.htm [16.05.2020]. Brunner, K. (1974). Monetary management, domestic inflation, and imported inflation. In: R.Z. Aliber (ed.), National Monetary Policies and the International Financial System. Chicago: University of Chicago Press. Buchanan, J.M., & Tullock, G. (1962). The Calculus of Consent: Logical Foundations of Constitutional Democracy. Ann Arbor: The University of Michigan Press.

84  Policy response in the banking sector Carey, H. (1840). Principles of Political Economy. Philadelphia: Carey, Lea & Blanchard. Commons, J.R. (1934). Institutional Economics. New York: Macmillan. EBA (2020). Statement on dividends distribution, share buybacks and variable remuneration. European Banking Authority. Retrieved from: https://eba.europa.eu/sites/default/documents/ files/document_library/News%20and%20Press/Press%20Room/Press%20Releases/2020/ EBA%20provides%20additional%20clar ity%20on%20measures%20to%20miti gate%20the%20impact%20of%20COVID-19%20on%20the%20EU%20banking%20 sector/Statement%20on%20dividends%20distribution%2C%20share%20buybacks%20 and%20variable%20remuneration.pdf [09.11.2020]. EC (2020). Recovery plan for Europe. Retrieved from: https://ec.europa.eu/info/strategy/ recovery-plan-europe_en [09.01.2021] ECB (2020a). ECB Banking Supervision provides temporary capital and operational relief in reaction to coronavirus. European Central Bank. Retrieved from: www.bankingsupervision. europa.eu/press/pr/date/2020/html/ssm.pr200312-43351ac3ac.en.html [19.01.2021] ECB (2020b). Opinia Europejskiego Banku Centralnego z dnia 20 maja 2020 r. w sprawie zmian ram ostrożnościowych Unii w odpowiedzi na pandemię Covid-19, CON/2020/16, (2020/C 180/04). Retrieved from: https://eur-lex.europa.eu/legal-content/PL/TXT/ HTML/?uri=CELEX:52020AB0016&from=ES [19.01.2021] Erhard, L. (1957). Wohlstand für Alle. Berlin: Econ Verlag. Fichte, J.G. (1800, 1964). The Closed Commercial State. Chicago: Aldine Publishing Company. Friedman, M. (1962). Capitalism and Freedom. Chicago: University of Chicago Press Galbraith, J.K. (1967). The New Industrial State. Boston: Houghton Mifflin Harcourt. GOV (2020). Tarcza antykryzysowa. Serwis Rzeczypospolitej Polskiej. Retrieved from: www. gov.pl/web/tarczaantykryzysowa/ [09.11.2020] Haberler, G. (1936). The Theory of International Trade. London: William Hodge. Keynes, J.M. (1936). The General Theory of Employment, Interest and Money. London: Palgrave Macmillan. Kydland, F.E., & Prescott, E. (1982). Time to build and aggregate fluctuations. Econometrica, 50(6), 1345–1370. Laffer, A. (1970). Trade credit and the money market. Journal of Political Economy, 78(2). List, F. (1841). The National System of Political Economy. London: Longmans, Green and Co. Lucas, R. (1981). Studies in Business-Cycle Theory. Cambridge: MIT Press. Machlup, F. (1962, 1972). The Production and Distribution of Knowledge in the United States. Princeton: Princeton University Press Malthus, T.R. (1798). An Essay on the Principle of Population. London: J. Johnson. Marshall, A. (1890). Principles of Economics. Vol. I. London: Macmillan. Marx, K. (1990, 1867). Capital. Vol. I. London: Penguin Books. Melman, S. (1985). The Permanent War Economy: American Capitalism in Decline. New York: Simon & Schuster. Meltzer, A.H. (1995). Money, Credit and Policy. London: Edward Elgar Publishing Ltd. Mill, J.S. (1863). Utilitarianism. London: Parker, Son, Bourn, West Strand. Müller, A.H. (1812). Die Theorie der Staatshaushaltung und ihre Forschritte in Deutschland und England seit Adam Smith. Vienna. Müller-Armack, A. (1946, 1976). Wirtschaftslenkung und Marktwirtschaft. In: A. MüllerArmack (ed.), Wirtschaftsordnung und Wirtschaftspolitik. Bern: Haupt. Okun, A.M. (1975). Equality and Efficiency: The Big Tradeoff. Washington, DC: Brookings Institution.

Policy response in the banking sector 85 Pekao (2020). Sprawozdanie z działalności Grupy Kapitałowej Banku Pekao S.A. w I półroczu 2020 roku. Bank Pekao SA. Retrieved from: www.pekao.com.pl/relacje-inwestorskie/ raporty-i-sprawozdania/raporty.html [09.11.2020] Pigou, A.C. (1920). The Economics of Welfare. 1st ed. London: MacMillan and Co., Ltd. PwC Strategy (2020). Payments  & open banking survey 2020. Retrieved from: www. strategyand.pwc.com/de/de/studien/2020/open-banking-and-payments-survey/openbanking-and-payments-survey.pdf [19.01.2021] Raymond, D. (1820). Thoughts on Political Economy. Baltimore: F. Lucas. Raymond, D. (1823). The Elements of Political Economy. Baltimore: Lucas jr. and E. J. Coale. Röpke, W. (1936). Crises and Cycles. London: William Hodge. Rusinowa, I. (1990). Alexander Hamilton. Wrocław: Ossolineum. Rüstow, A. (1925). Schutzzoll oder Freihandel? das Für u. d. Wider d. Schutzzollpolitik. Frankfurt a. M.: Frankfurter Societäts-Druckerei, Abt. Buchverlag. Sargent, T.J. (1987, 1979). Macroeconomic Theory. New York: Academic Press. Say, J.B. (1803, 2008). A Treatise on Political Economy. London: Routledge. Schick, S. (2020). Gut 330 Banken und Sparkassen berechnen Negativzinsen auf Guthaben. Retrieved from: www.biallo.de/geldanlage/ratgeber/so-vermeiden-sie-negativzinsen/ [18.01.2021] Schumpeter, J.A. (1934, 1983). The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle. New Brunswick, NJ: Transaction Books Smith, A. (1776). Wealth of Nations. London: W. Strahan and T. Cadell. Sprinkel, B. (1971). Money and Markets: A Monetarist View. Burr Ridge: R. D. Irwin. Stiglitz, J.E. (1989). The Economic Role of the State. Oxford, UK and Cambridge, MA: Wiley-Blackwell. Tobin, J. (1987). Essays in Economics. Vol. 1. Macroeconomics. Cambridge: MIT Press. von Hayek, F. (1931, 1935). Prices and Production. London: Routledge & Sons. von Mises, L. (1912). Theorie des Geldes und der Umlaufsmittel. Munchen und Leipzig: Verlag von Dunker und Humblot. ZBP (2020). Związek Banków Polskich. Retrieved from: https://zbp.pl/Aktualnosci/ Wydarzenia/Blisko-550-tys-wnioskow-o-zawieszenie-(odroczenie)-rat-kredytow [09.11.2020]

6 Changing the business model of banking operation

Response of different sectors of the economy to the extreme threat History clearly shows that fallouts of pandemics can be prolonged. However, such crises have spurred new systemic changes and improvements, contributing to the development of medicine, new technologies, and the expansion of several sectors of the economy. Hence, it is most questionable whether one has learned anything positive for society and the economy from previous health crises from the early 20th century onwards. The Spanish flu had a high mortality rate that killed between 50 million and 100 million people worldwide in 1918 and 1919 (Niall, 2006, 64–72). The epidemic was publicized in Spain, where 8 million people were infected. However, it should be recognized that it was called the “Spanish flu” because information about the killer flu and the induction of a general state of panic was distributed in particular by Spanish newspapers. The epidemic was noticed and appeared for the first time in Fort Riley, Kansas, United States, on 11 March 1918. A significant expansion of the epidemic occurred as a result of the demobilization of the army and the return of soldiers from the front to their places of residence. Thus, the epidemic spread to many countries and several continents simultaneously (Tuşa  & Vasilache, 2019). The Spanish flu epidemic led to intense work on flu vaccination, which was introduced on a mass scale, and which inspired the invention of the polio vaccine and the development of knowledge about HIV (Oldstone, 2020; Spinney, 2017). The need to accommodate the existing situation and to prevent it in the future has spurred innovative solutions. On the one hand, some of those solutions would never have been popularized, or even introduced at all, were it not for the harrowing experiences of a pandemic. On the other hand, the return of the situation surrounding the outbreak of COVID-19 shows that the human race is still unable to cope with the problem. The Spanish flu and coronavirus prove once again that we can never be sure of our safety and the environment in which we live. The health and psychological effects of epidemics lead to additional social and economic costs, adding to the question of public finances and altering the business models of economic players. The pandemic period, particularly the DOI: 10.4324/9781003351160-6

Changing the business model of banking operation 87

lockdown-related restrictions, affects the public’s psychological and emotional state. According to the Zunin and Myers model, the fifth phase of popular reaction to an extreme threat (disillusionment) is described as “pandemic fatigue.” The fourth, the “honeymoon” phase, is dominated by optimism and the wish to return as quickly as possible to the standard, pre-epidemic behavior. This phase is followed by disappointment and discouragement. Stress, anxiety about one’s life and health, and the sense of burnout lead to adverse consequences, such as depression, clinical phobias, social anxiety, abuse of medication and psychoactive substances such as alcohol and drugs, conflicts in the family, and domestic abuse. In the context of COVID-19-related insecurity, it is crucial to understand that this sense of disappointment is natural and can be expected. The past experiences of similar crises indicate it can be considered a normal cognitive reaction to a dynamic disturbance of the existing lifestyle (Lilleholt et al., 2020; WHO, 2020). People who used to be professionally and socially active suddenly experience a situation where their activity is limited to remote work, entertainment, and direct social contacts – to meetings with the closest family. All this may adversely affect their physical and psychological well-being and lead to pathological behavior, as well as to seeking other people’s help. This is why finding effective ways of coping with pandemic fatigue and reviving public activity has become an increasingly pressing challenge as the crisis continues (DeWolfe, 2000).

Change from traditional to nontraditional banking activity The behavior of banks’ clients will have changed in the wake of the COVID19 pandemic. According to Lally et al. (2010), the average modeled time when a new automatic behavior is established is 66 days, but the range is from 18 to 254 days. The crucial issue is whether the lockdown habits will prove permanent or whether the return to relative normality will reverse certain behaviors and reinstate the pre-pandemic lifestyle. People are accustomed to traditional ways and are stuck in their everyday habits and schemes. The research authors emphasize that “Interventions aiming to create habits may need to provide continued support to help individuals perform a behavior for long enough for it to be subsequently enacted with a high level of automaticity.” However, there is no doubt that the pandemic situation will contribute to the proliferation and acceptance of digital technologies. This will lead to permanent changes in how we work, study, shop, and access entertainment, culture, and art. The necessity to maintain social distance has forced adjustments to the activities formerly taking place in direct contact. Those adjustments include remote work and studying, videoconferences, online shopping, and digital and mobile banking. Early on, consumers noticed the advantages of such solutions, particularly in terms of time economy. Some of the phenomena observed during the pandemic are ephemeral; nevertheless, the most important ones are permanent and irreversible. The stress connected with health and financial and professional instability (the fear of losing a job and income) has impacted decisions concerning expenses

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and investment. People have become more cautious in making severe financial commitments, strategic investments, managing disposable income, and changing employment. According to the research commissioned by the European Parliament (2020), “a plurality of respondents (39%) declare that the Covid-19 crisis has already impacted their personal income. A further 27% expect such an impact in the future.” The analysis of responses indicates that Young people and families with children appear to be hit worst by the crisis: 64% of citizens between 16 and 34 years have experienced some form of financial difficulties, 27% of respondents with children have used their personal savings sooner than planned. A crisis similar to the present COVID-related one can hardly be prevented in the future. It will be crucial to draw correct conclusions and better prepare for similar threats. The current pandemic is too costly to let go to waste. The uncertainty about the time “normalcy” can be reinstated means that success in banking operation will depend on the banks’ ability to adapt to the existing and future conditions. The current budgets, financial plans, and long-term strategies require necessary reformatting for a changed economic reality. The aftermath of the pandemic and the changes in collective reactions and behavior of banks’ customers will cause permanent adjustments in the banks’ business model. They will be forced to operate at low interest rates, the quality of credit portfolios has deteriorated, and the demand for certain credits and loans has fallen. It can be expected that banks will be forced to adopt even more innovative and flexible principles of operation. Paradoxically, modern financial systems, despite up-to-date economic and financial management, management accounting, and control solutions, are more than ever vulnerable to crises in the global markets. At present, investors demand only positive information about their bank’s performance – permanently increasing profits, ever-growing performance indicators, rationalization of expenses, etc.  – which effectively contributes to growing share prices and higher dividends. Expectations concerning the invested capital change, and the time scale of the expected returns shorten. This is why banks will be forced to introduce new solutions and technologies even faster than they already have. Undoubtedly, from an economic point of view, more technology leads to cost savings and higher productivity, but in practice, the study of the banks’ performance may raise some questions. Dadoukis et al. (2021) examine the impact of adoption of information technology on bank performance during the COVID19 pandemic. Their study confirms that technology adoption promotes bank resilience by increasing financial stability. On the other hand, social distance habits have increased the time people spend on social networks to consult information. The COVID-19 pandemic disrupted personal banking operations and increased the physical threat to both retail banks and customers. As a result, the world has shifted towards online banking for settlement transactions and other banking operations. A  review of the literature on FinTech services reveals a range of opportunities and threats to bank operations. Murinde et  al. (2022)

Changing the business model of banking operation 89

reviewed key indicators of a changing banking sector in the FinTech era over the past 16 years. Their findings show that FinTech lenders are unlikely to replace banks, perhaps because banks are developing their own FinTech platforms or partnering with FinTech start-ups. It is useful to make some points to help us understand how recent developments have changed the business of financial intermediaries. Banks drive economic growth through two key functions: (i) the transformation of financial surpluses into loans and mortgages; and (ii) brokerage, or payment services. Regarding the first function, banks can effectively manage any potential mismatch between demand and supply of liquidity (Navaretti et  al., 2018). Banks’ ability to hold deposits makes them more trustworthy than nonbanks. Banks transform liquid short-term deposits into long-term loans, fulfilling their other function of providing liquidity. Deposits are usually made by a significant number of savers with different financial risk. Therefore, banks manage credit risk by diversifying funding sources (Murinde et al., 2022). In contrast, Navaretti et al. (2018) indicated that FinTech firms can pool funds so that customers can access and use them, but they cannot use these funds to make illiquid loans. The authors also argue that FinTech lending companies mainly act as brokers, providing services by matching counterparties and transferring the credit risk of loans directly to investors. Consequently, they have less diversified portfolios on the asset and liability side compared to banks. One of the fundamental challenges facing the banking sector is the environment of low interest rates. They result from the commonly adopted economic policy involving a rapid increase of public debt connected with government programs of support for the sectors most affected by the pandemic. Even after the end of the pandemic, when the economies of individual countries grow dynamically, zero interest rates are expected to persist for a few more years, as central banks use this strategy to support the servicing of public debt. Consequently, banks and their clients will need to learn to manage their assets in new conditions. It is widely acknowledged in finance studies that the diversification of investments/activities of financial institutions is beneficial for the financial system’s stability. However, the recent 2007–2009 financial crisis has shown that this form of investment can have costs: while diversification reduces the probability of an individual entity failing, it makes systemic crises more likely. In general, a bank fails when the value of its assets falls below its liability. Because bank assets generate specific risk, diversification reduces the probability that a bank’s portfolio value falls below its liability. On the one hand, this lowers the probability of bank failure, but it also makes the assets of individual banks more similar to each other and thus exposed to the same risks. Consequently, the costs of systemic crises resulting from over-diversification may outweigh its benefits. Despite the significant unification that characterizes the banking sector in Europe, the level of traditional activities based on interest income and nontraditional activity based on securities trading vary across European countries. Figure 6.1 shows how the banking sectors of selected European countries differ in their involvement in the diversification of financial results. However, Altavilla et  al. (2018) note, that banks relatively quickly adjust to the low-interest rate environment. They comment that “monetary policy

90  Changing the business model of banking operation

Figure 6.1 Structure of interest and noninterest income in banks’ total income in selected European sectors (average for the period 2015Q3–2020Q3) Sources: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021).

easing – a decrease in short-term interest rates and/or a flattening of the yield curve – is not associated with lower bank profits once we control for the endogeneity of the policy measures to expected macroeconomic and financial conditions.” They also indicate that the reduced income from interest on financial instruments, evaluated according to the amortized analysis, is compensated by income from fees and commissions on financial services provided by banks. Improving the price policy is essential as the persisting period of low interest rates may adversely affect profits. However, the authors emphasize that this materializes after a long period, usually followed by economic prosperity. Carletti et  al. (2020) also analyze the issue of compensating for the lost income from interest rates with banking fees and commissions. They emphasize that the low-interest-rate environment puts particular pressure on the banks running a traditional commercial operation. They play the role of an intermediary between individuals and institutions seeking sources of financing and the investors wishing to invest their savings. However, the authors observe, “the experience of countries such as Sweden suggests that negative rates are not necessarily detrimental to bank profitability if implemented in the context of sustained economic growth and efficient banking sector.” Brei et al. (2020) analyze the sample of 113 large international banks headquartered in 14 major advanced economies during 1994–2015. They confirm

Changing the business model of banking operation 91

that “persistent low-interest rates tend to reduce bank profits, mainly by depressing interest margins. They indicate that banks adjust their activities to offset that reduction, at least partially.” According to the authors, banks compensate for lost income with fees and commissions, and trading activities. Scientific research confirms, therefore, that in a low-interest-rate environment, banks re-orientate their income structure away from traditional management of assets and liabilities based on profiting from interest margins. Until recently, relying on the model of standard commercial banking, they made relatively high profits from their deposit operation, based on the difference between the interest on the deposits they offered and the market rates based on interbank rates. The current extraordinary situation has forced them to seek new sources of income by the principle that what matters is the created shareholder value and not whether it is achieved via operational, financial, or investment activity. Nevertheless, it is essential to remember that, despite attractive rates of return on capital in investment banking, it is not possible to quickly build a business model in which it would constitute the dominant segment of income. Furthermore, replacing the traditional banking model based on credits, loans, and deposits with investment banking generates problems connected with the irregularity of income coming from this source. Figure  6.2 shows changes in the share of interest and noninterest income in banks’ total income in the European sector from 2015Q1 to 2020Q3.

Figure 6.2 Changes in the share of interest and noninterest income in banks’ total income in the European sector from 2015Q1 to 2020Q3 Sources: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021).

92  Changing the business model of banking operation

The analysis evidenced that in the first quarter of the COVID-19 pandemic (2020Q1), banks achieved the highest level of noninterest income during the study period.

The impact of the COVID-19 pandemic on the performance of commercial banks in the European sectors The last decades and the time of the COVID-19 pandemic were a period of change in the financial markets, driven in an environment of globalization and deregulation by intense competition and the nature of financial institutions. The deregulation process lowered the barriers to market access and thus provided an opportunity for new competitive institutions to operate. The banks, losing their privileged position, started to fight for competitive advantage by developing new, often nontraditional income sources. To increase their income, banks began to operate on the market for off-balance-sheet assets on a massive scale. A common belief among bankers, regulators, and analysts alike is that income based on bank fees is more stable than that derived from loan interest. Underlying this thinking is the belief that margin income is less sensitive to changes in interest rates and economic downturns. Thus, increasing the proportion of noninterest businesses in the traditional banking portfolio reduces the overall earnings volatility and benefits from diversification effects. Therefore, this study examines whether the COVID-19 pandemic impacts the interest and noninterest performance of banks in sectors of selected European countries. This is an important issue for regulators responsible for maintaining the safety and soundness of commercial banks, for managers who hold significant financial and professional stakes in the banks, and for customers in the bank-borrower relationship who may be at risk from the effects of increased earnings volatility. To verify the impact of the COVID-19 pandemic and intra-bank factors on the interest and noninterest results of banks in Europe, we used the panel regression model OLS on quarterly data over the period 2020Q1–2021Q1. The study used data from a selection of 24 European countries, including 14 developed countries – France, Italy, Finland, Germany, Portugal, Austria, Belgium, Spain, Denmark, Netherlands, Cyprus, Ireland, Greece, and Malta – and 10 developing countries – Latvia, Serbia, Romania, Poland, Slovenia, Estonia, Croatia, Czech Republic, Bulgaria, and Slovakia. The data source is the European Central Bank statistics. The basic version of the model used in the study is presented by the following equation:  0 + β1 COVIDn,t + β2 LOANS_GRn,t BANK_INCOMEn,t= β + β3 LENDING_MARGINn,t + β4 NPLn,t + β5 LEVn,t + β6 TIME_DUMMYn,t + εn,t

Changing the business model of banking operation 93

The following indicators were used in the analysis:

BANK _ INCOMEn ,t – banking income ratio in n sector and t period, we consider two variables: INTEREST as net interest income as a share of total income and NONINTEREST as noninterest income (fee and commission as a share of total income); COVIDn,t – total confirmed deaths due to COVID-19 per million people in n country and t period; LOANS _ GRn,t – an annual growth rate of MFIs new loans to households and nonfinancial corporation in n sector and t period; LEVn,t – banking leverage ratio in n sector and t period; LENDING _ MARGINn,t – margin on outstanding loans to nonfinancial corporations and households in n sector and t period; NPL n,t – nonperforming loans in n sector and t period; TIME _ DUMMYn,t − time dummy variable; εn,t – random effect. Table 6.1 presents the descriptive statistics of the applied variables for the full sample in the period of 2020Q1–2021Q1. Interest income as a ratio of the total income of the banking sector in European countries is 65.45. In contrast, the noninterest result for the same period is 26.37, and compared with Figure 6.3, it is higher than the average value in the previous period 2015Q1–2019Q4. The average value for the loans’ growth rate is 6.18. Moreover, one can observe a lending margin, with an average level of 2.19. During the research period, one can also observe a higher value of 4.27 for nonperforming loans. Finally, the average value of the leverage ratio is 8.66. Table 6.2 represents the correlation degree of the individual variables employed in the study. In the next step, we estimate the influence of COVID-19 on the banks’ interest and noninterest income (see Tables 6.3 and 6.4, respectively). In model (1), we measure the impact of the COVID-19 pandemic on bank performance. This factor negatively affects both types of bank performance (INTEREST −0.889, vs NONINTEREST −0.22). In the second step, we take lending control variables to find the effect of credit policy (Model 2). The assumption for our study was that changes in the bank performance might be influenced by a lending Table 6.1  Descriptive statistics INTEREST NONINTEREST COVID LOANS_GR LENDING_MARGIN NPL LEV

Obs.

Mean

Median

SD

Min

Max

66 66 66 66 66 66 66

65.45 26.37 4.00 6.18 2.19 4.27 8.66

65.92 26.51 4.11 6.11 2.06 2.52 8.34

8.35 6.77 1.90 11.75 0.94 5.58 2.62

47.35 12.22 −0.14 −17.20 0.27 0.80 4.99

96.87 41.75 10.73 36.21 3.96 29.88 13.41

Source: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021).

94  Changing the business model of banking operation

Figure 6.3 Average changes of cost-to-income ratio in the European banking sectors in relation to ROA efficiency ratio Source: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 7 June 2021).

Table 6.2  Correlation matrix INTEREST INTEREST 1.00 NONIN0.14*** TEREST (0.00) COVID −0.25* (0.04) LOANS_GR −0.08* (0.01) LENDING_ 0.14*** MARGIN (0.00) NPL 0.18*** (0.00) LEV 0.07* (0.03)

NONCOVID INTEREST

LOANS_ LENDING_ NPL GR MARGIN

LEV

1.00 0.24 (0.05) 0.02 (0.52) −0.31*** (0.00) −0.32*** (0.00) –0.15*** (0.00)

1.00 0.03 (0.80) –0.40*** (0.00) –0.24 (0.05) –0.36** (0.00)

1.00 0.06* (0.02) –0.14*** (0.00) 0.08* (0.03)

1.00 0.42*** (0.00) 0.62*** (0.00)

1.00 0.22*** 1.00 (0.00)

Sources: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021). Note: P-values in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001

Changing the business model of banking operation 95 Table 6.3 COVID-19 and bank interest income in commercial banks in the European countries (full sample), over the period 2020Q1–2021Q1

COVID LOANS_GR

(Model 1) COVID

(Model 2) LENDING

(Model 3) RISK

(Model 4) FULL

−0.889** (0.419)

−0.731* (0.403) 0.169** (0.067) 3.061* (1.610)

69.152*** (2.241) 66 23 0.068 YES NO

60.754*** (4.529) 66 23 0.225 YES NO

−0.894** (0.402) 0.167** (0.065) 7.328*** (2.018) −0.641** (0.256) −1.471** (0.648) 67.478*** (5.072) 66 23 0.219 YES NO

0.407 (0.450) 0.178*** (0.056) 8.740*** (2.047) −0.720*** (0.260) −1.564** (0.640) 64.549*** (4.955) 66 23 0.512 YES YES

LENDING_MARGIN NPL LEV CONS OBSERVATIONS N_GROUP R2 FE TIME_DUMMY

Sources: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021). Standard errors are in parentheses *** p < .01, ** p < .05, * p < .1 Notes: This table shows how the bank’s interest income reacted to the COVID-19 crisis. In Model 1, only COVID reaction is included. COVID is the average COVID-19 death cases per 1000 people measured. Next, regressions include the bank’s lending policy (Model 2), risk-taking (Model 3), and time dummy (Model 4) control variables. The robust standard errors are reported under the coefficients. The symbols ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively.

Table 6.4 COVID-19 and bank noninterest income in commercial banks in the European countries (full sample), over the period 2020Q1–2021Q1

COVID LOANS_GR

(Model 1) COVID

(Model 2) LENDING

(Model 3) RISK

(Model 4) FULL

−0.220 (0.211)

–0.407** (0.198) 0.072** (0.033) −4.662*** (1.078)

27.206*** (1.566)

37.818*** (2.879)

–0.424** (0.201) 0.069** (0.033) −4.043*** (1.511) −0.211 (0.195) −0.046 (0.461) 37.816*** (3.570)

0.422** (0.188) 0.070*** (0.023) −2.336* (1.382) –0.349* (0.181) −0.588 (0.392) 38.783*** (3.139)

LENDING_ MARGIN NPL LEV CONS

(Continued )

96  Changing the business model of banking operation Table 6.4 (Continued)

OBSERVATIONS N_GROUP R2 FE TIME_DUMMY

(Model 1) COVID

(Model 2) LENDING

(Model 3) RISK

(Model 4) FULL

66 23 0.053 YES NO

66 23 0.172 YES NO

66 23 0.169 YES NO

66 23 0.650 YES YES

Sources: Authors’ compilation based on ECB database (https://sdw.ecb.europa.eu/, retrieved 5 June 2021). Standard errors are in parentheses *** p