(Dis)honesty in Management : Manifestations and Consequences 9781781906026, 9781781906019

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(DIS)HONESTY IN MANAGEMENT: MANIFESTATIONS AND CONSEQUENCES

ADVANCED SERIES IN MANAGEMENT

Previous Volumes: Relational Practices, Participative Organizing EDS. CHRIS STEYAERT AND BART VAN LOOY Autopoiesis in Organization Theory and Practice EDS. RODRIGO MAGALHAES AND RON SANCHEZ Organizations as Learning Systems ‘‘Living Composition’’ as an Enabling Infrastructure ED. MARJATTA MAULA Complex Systems and Evolutionary Perspectives on Organizations: The Application of Complexity Theory to Organizations ED. EVE MITLETON-KELLY Managing Imaginary Organizations: A New Perspective on Business EDS. BO HEDBERG, PHILIPPE BAUMARD AND A. YAKHLEF Systems Perspectives on Resources, Capabilities and Management Processes EDS. JOHN MORECROFT, RON SANCHEZ AND AIME´ HEENE Tracks and Frames: The Economy of Symbolic Forms in Organizations ED. K. SKOLDBERG Electronic HRM in Theory and Practice EDS. T. BONDAROUK , H. RUE¨L AND J.C. LOOISE Commercial Diplomacy and International Business: A Conceptual and Empirical Exploration ED. H. RUE¨L

(DIS)HONESTY IN MANAGEMENT: MANIFESTATIONS AND CONSEQUENCES

EDITED BY

TIIA VISSAK University of Tartu, Estonia

MAAJA VADI University of Tartu, Estonia

United Kingdom – North America – Japan India – Malaysia – China

Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2013 Copyright r 2013 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-78190-601-9 ISSN: 1877-6361 (Series)

ISOQAR certified Management System, awarded to Emerald for adherence to Environmental standard ISO 14001:2004. Certificate Number 1985 ISO 14001

Contents

List of Contributors

vii

Preface

ix

Introduction

xi

PART I: THE NATURE OF (DIS)HONESTY 1.

2.

3.

The Nature of (Dis)Honesty, Its Impact Factors and Consequences Maaja Vadi and Tiia Vissak

3

(Dis)Honesty in Organizations: Ethical Perspectives Eneli Kindsiko

19

Honesty and Trust: Integrating the Values of Individuals, Organizations, and the Society Anneli Kaasa and Eve Parts

37

PART II: (DIS)HONESTY IN PUBLIC SECTOR AND FINANCIAL MANAGEMENT 4.

5.

6.

The Banking Crisis in Iceland: Did the Government Pretend That Facts from Reality Were Other Than They Were? Hilmar –o´r Hilmarsson

61

Perceptions of Unreported Economic Activities in Baltic Firms: Individualistic and Non-individualistic Motives Jaanika Meriku¨ll, Tairi Ro˜o˜m and Karsten Staehr

85

Firm Bankruptcies and Violations of Law: An Analysis of Different Offences Oliver Lukason

127

vi 7.

Contents From Dishonesty to Disaster: The Reasons and Consequences of Rogue Traders’ Fraudulent Behavior Mark Kantsˇukov and Darja Medvedskaja

147

PART III: (DIS)HONESTY IN FIRM MANAGEMENT IN EUROPE AND AFRICA 8.

9.

10.

11.

The Drivers and Moderators for Dishonest Behavior in the Service Sector Krista Jaakson, Jaan Masso and Maaja Vadi

169

Human Resource Managers and Employees’ Rights: An ABC (Antecedents – Behavior – Consequences) Analysis of Ethical Dilemmas Dana Mesner Andolsˇek, Mateja Primozˇicˇ and Janez Sˇtebe

195

Honesty in Leadership: A Case of the Czech Republic Zuzana Dvorakova, Edward Shippen Bright and Jan Muehlfeit

227

Legitimizing Dishonesty in Organizations: A Survey of Managers in Four Sub-Sahara African Countries Martina L. Yanga and Isaac O. Amoako

243

PART IV: (DIS)HONESTY IN FIRM MANAGEMENT IN ASIA AND AMERICA 12.

13.

14.

15.

Evaluating ‘Honesty’ When Implementing Corporate Community Initiatives: A Developing Country Perspective Eshani Beddewela

271

Building Trust between American and Chinese Business Negotiators Maria Lai-Ling Lam

293

The Consequences of Dishonesty in International Partnerships: Three Chinese Cases Tiia Vissak and Xiaotian Zhang

313

From Dishonesty to Honesty: Is this Journey Path Dependent? Eneli Kindsiko, Maaja Vadi and Tiia Vissak

337

Authors’ Biographies

351

Author Index

357

Subject Index

371

List of Contributors Isaac O. Amoako

Centre for Enterprise and Economic Development Research, Middlesex University Business School, UK

Eshani Beddewela

Department of Strategy and Marketing, University of Huddersfield Business School, UK

Zuzana Dvorakova

Department of Human Resource Management, University of Economics, Prague, the Czech Republic

Hilmar –o´r Hilmarsson

School of Business and Science, University of Akureyri, Iceland

Krista Jaakson

Faculty of Economics and Business Administration, University of Tartu, Estonia

Anneli Kaasa

Faculty of Economics and Business Administration, University of Tartu, Estonia

Mark Kantsˇukov

Faculty of Economics and Business Administration, University of Tartu, Estonia

Eneli Kindsiko

Faculty of Economics and Business Administration, University of Tartu, Estonia

Maria Lai-Ling Lam

School of Business and leadership, Malone University, Canton, Ohio, USA

Oliver Lukason

Faculty of Economics and Business Administration, University of Tartu, Estonia

Jaan Masso

Faculty of Economics and Business Administration, University of Tartu, Estonia

Darja Medvedskaja

PricewaterhouseCoopers, Tallinn, Estonia

Jaanika Meriku¨ll

Eesti Pank (Bank of Estonia); Faculty of Economics and Business Administration, University of Tartu, Estonia

Dana Mesner Andolsˇek

Faculty of Social Sciences, University of Ljubljana, Slovenia

Jan Muehlfeit

Microsoft Corporation Europe, Prague, the Czech Republic

viii

List of Contributors

Eve Parts

Faculty of Economics and Business Administration, University of Tartu, Estonia

Mateja Primozˇicˇ

Faculty of Social Sciences, University of Ljubljana, Slovenia

Tairi Ro˜o˜m

Tallinn School of Economics and Business Administration, Tallinn University of Technology, Estonia; Eesti Pank (Bank of Estonia)

Edward Shippen Bright

Charles University and the University of Economics, Prague, the Czech Republic

Karsten Staehr

Tallinn School of Economics and Business Administration, Tallinn University of Technology, Estonia; Eesti Pank (Bank of Estonia)

Janez Sˇtebe

Faculty of Social Sciences, University of Ljubljana, Slovenia

Maaja Vadi

Faculty of Economics and Business Administration, University of Tartu, Estonia

Tiia Vissak

Faculty of Economics and Business Administration, University of Tartu, Estonia

Martina L. Yanga

Department of International Management and Innovation, Middlesex University Business School, UK

Xiaotian Zhang

Faculty of Economics and Business Administration, University of Tartu, Estonia; Department of Management and International Business, University of Oulu, Finland

Preface

Enron, Parmalat, BP, Wal-Mart, Monsanto, Halliburton, Nike, Merck, Google, y the list goes on and on. It is widely acknowledged that business organizations are among the most important drivers of the quality of life that our society enjoys in our day, but the well-publicized samples of dishonest behavior by high-profile organizations around the world create no small amount of skepticism and cynicism. On the other hand, there are many companies that try explicitly to be a positive force for society, that were founded not as a morally neutral entity, but as organizations intended to change the world for the best. Some might disagree with their methods or even with their intentions, but the fact remains that, among the foundational principles of many entrepreneurs, the goal of making a positive difference for society is among if not the most important. In spite of the cynicism that seems to prevail even in business media, honesty is an expectation of many societies with respect to businesses and their managers, but not an easy one to meet. To illustrate briefly, Google has adopted ‘‘You can make money without doing evil’’ as one of its ‘‘10 things’’ or ‘‘philosophy principles’’ (for lack of a better expression; for details, see: https://www.google.com/about/company/philosophy/). This company, ranked no.1 in Fortune magazine’s list of ‘‘Best Companies to Work For’’ in 2013 (http://money.cnn.com/magazines/fortune/best-companies/2013/ snapshots/1.html), is also one which has caused many to question its integrity after it was known to sell advertising in ways that would promote illegal imports into the United States (see http://www.forbes.com/sites/sap/2011/09/02/google-needs-to-dropits-do-no-evil-thing/) or infringe on privacy-related issues in different countries. Another, highly instructive company is Merck, the firm that earned praise and admiration around the world for making available a drug to prevent river blindness in many of the most impoverished places of the world. A short time later, it found itself at the center of a controversy for failing to react appropriately to studies dealing with Vioxx, one of its best-selling drugs to treat chronic or acute pain. These two firms exemplify how even organizations that are well regarded can also be charged as dishonest. Seasoned, reflecting managers and researchers trying to ‘‘do the right thing’’ know that simplistic solutions are not effective. The collection of chapters in this volume presents readers with analytical and conceptual tools that have the potential of shedding light in the nature of honesty and dishonesty in the managing of business, with practical applications in the widest variety of circumstances. They offer us the

x

Preface

‘‘mental tools’’ that can help us discern the best courses of action and they also offer the rich vocabulary that reflects and describes situations, processes, and consequences related to this imperative of ethics in management. Each of these chapters draws from decades of work in various scholarly traditions to help the professional management audiences make more rapid progress and with less effort — whether for practice or for further conceptual exploration and advancement. Readers in a multiplicity of situations will find this volume helpful and usable. Students wanting to increase their potential for ethical discernment in business are probably the audience that may benefit the most from these chapters. But researchers and other scholars in cross-cultural, strategic, trans-national, ethical, and many other fields of management are likely to find this collection worth-citing and extending in their own knowledge-generation efforts. Journalists, management historians, and other professionals will no doubt profit from several of the case studies in this volume, as they have been written from a local perspective that has a global audience in mind. As the introductory chapter describes, several of these sections include measures and tests of the theories while others provide rich analytical frameworks to facilitate readers’ understanding of (dis)honesty in management. The geographic diversity reflected in the issues analyzed, the samples utilized, and even in the mix of authors gives this volume a strength that is not easy to match. In editing this volume, Tiia Vissak and Maaja Vadi have made a very significant contribution that will help managers and researchers better analyze and understand the complex, multi-faceted nature of (dis)honesty in business. They have dedicated themselves to the gigantic and highly needed task of requesting, revising, and accepting chapters from some of the brightest minds that around the world are concerned with this topic. As editors for the Advanced Series in Management, we could not have asked for a finer, more professional addition to this growing set of tools aimed at making the world a better place. Miguel R. Olivas-Luja´n Tanya Bondarouk Series Editors

Introduction The economic life is often hindered by problems that can be successfully solved by tapping into concepts of social sciences. Herein, basic assumptions uniform people’s behavior but these may also create problems and thus, nowadays the economy meets the consequences of the so-called ‘‘soft issues’’ for various reasons. In this light, the aim of the volume is to show what kind of influences may turn out from honesty and dishonesty to management and the economy, in general. These effects generate an ensemble where factors could affect and be affected by each other in several ways. This volume concentrates on different forms of honesty and dishonesty in management and their consequences for managers, firms, and the society. These issues are related to values and behavior patterns and thus, the basis of the contemporary business. Honesty can be defined as the refusal to pretend that facts of reality are other than what they are while dishonesty — including lying, stealing, cheating, distortion, concealing of important information, failing to fulfill promises, and abruptly abandoning a business relationship (Das & Rahman, 2002; Griesinger, 1990; Jap & Anderson, 2003; Ntayi, Rooks, Eyaa & Qian 2010; Parkhe, 1993; Wathne & Heide, 2000; Williamson, 1987) — presents its opposite. Dishonesty can be blatant, massive, strong and active or subtle, minimal, weak, and passive (Luo, 2006; Malshe, Al-Khatib & Sailors, 2010; Parkhe, 1993; Wathne & Heide, 2000). The volume is divided into four main parts. The contributions of the first part concern the nature of (dis)honesty in management. In the second part, the main attention is paid to (dis)honesty in public sector management and finance. The third part focuses on (dis)honesty in firm management in Europe and Africa, while the last part presents evidence on (dis)honesty in management in Asia and America. The volume ends with a concluding chapter. The authors of the 15 chapters conclude that the understanding of (dis)honesty and (un)ethical behavior differs in different cultural, societal, and organizational contexts; moreover, it is not always easy to discover it. Dishonesty may lead to unfavorable consequences for the dishonest and, quite often, also for the honest party, but, sometimes dishonesty may pay off for the dishonest party in the short term. This volume provides new theoretical, managerial, and policy insights in the field of management research and it should interest scholars, managers, and policymakers, but also others studying or discussing these issues or having to decide if they should act dishonestly or not.

xii

Introduction

Part I starts with the chapter ‘‘The Nature of (Dis)Honesty, Its Impact Factors and Consequences’’ by the editors Maaja Vadi and Tiia Vissak. It explains the concepts of honesty and dishonesty in management and provides a general understanding why and how honesty and dishonesty may manifest in different ways. Based on the chapter, it can be concluded that it is not always possible to draw a line between honest and dishonest acts: many acts have some characteristics of both. Thus, there are ‘‘gray areas’’ between honesty and dishonesty, and they may differ in size. Moreover, the evaluation how honest or dishonest a certain act is, depends on societal and organizational factors but also on personal characteristics: both from the actor’s and the evaluator’s (manager’s, coworker’s) perspective. In addition, situational characteristics and the consequences of the act may affect the perception how honest or dishonest this act is. Although managers cannot change the perceptions of honesty and dishonesty in the society as a whole, they can shape organizational culture and through that, the actions of their employees; thus, they need to understand these issues. In the second chapter ‘‘(Dis)Honesty in Organizations: Ethical Perspectives’’ Eneli Kindsiko states that (dis)honesty should be assessed at different levels: its essence, consequences, and also the people who commit dishonest acts and the context where they perform these acts should be studied and different ethical viewpoints should be taken into account. She also concludes that the understanding of what is considered to be honest and what is understood to be dishonest depends on the cultural context (also in terms of organizational culture, not only a specific country’s cultural context); moreover, dishonesty can be contagious, especially if the firm’s managers or other employees also seem to act dishonestly or if the company provides ample opportunities for dishonest behavior, if the risk of getting caught and punished for dishonest acts is low, the possible punishment is not considerable enough from the employee’s viewpoint and the potential (financial) gain is very high. Thus, it is not easy to fight against dishonesty if it has already become widespread in the organization; it should be dealt with as early as possible. The third chapter ‘‘Honesty and Trust: Integrating the Values of Individuals, Organizations, and the Society’’ by Anneli Kaasa and Eve Parts assesses the levels of trust in 81 countries across the world and explores differences in the levels of trust among different respondent groups (classified by age, education, sex, religion, and other characteristics). The authors found statistically significant differences in trust levels between almost all explored population groups, but could not find clear differences between geographical regions and/or countries at different development levels. They showed that the level of trust among supervisors did not differ significantly from the overall level of trust in the society; consequently, it can be assumed that honesty and trust tend to be contagious. Thus, reaching higher trust levels in the society as a whole could be accomplished by increasing trust in organizations. This, in turn, depends on the honesty and trustworthiness of managers. The opposite also holds: higher general trust in the society promotes the formation of trust and cooperation in organizations. Thus, the quality and reliability of formal institutions is very important.

Introduction

xiii

Part II starts with the chapter ‘‘The Banking Crisis in Iceland: Did the Government Pretend That Facts from Reality Were Other Than They Were?’’ by Hilmar –o´r Hilmarsson. The author of this case study paper states that the banking crisis in Iceland in October 2008 was caused by too rapid cross border expansion and too aggressive risk taking of Iceland’s three largest banks — Glitnir, Kaupthing, and Landsbanki — and by the government’s negligence and inability to take credible actions. As the government generally supported the international expansion of its banks, it failed to take credible measures to protect the economy in case of a potential banking crisis. Some experts also ignored the early warning signals and assured that everything was fine, while the government did not pay sufficient attention to the few more critical reports. Instead of reacting to these signals, the key ministers concentrated on dealing with the image crisis through launching a PR campaign, and, to some extent, even distorting facts. Thus, they were dishonest in the case they distorted facts on purpose or incompetent in the case they did not understand the full reality of the situation. In the second chapter ‘‘Perceptions of Unreported Economic Activities in Baltic Firms. Individualistic and Non-Individualistic Motives,’’ Jaanika Meriku¨ll, Tairi Ro˜o˜m, and Karsten Staehr study tax evasion in Estonia, Latvia, and Lithuania based on survey data from 1627 firms. They state that both individualistic (the management is solely profit-oriented and self-interested) and nonindividualistic motives (government performance and perceptions of reciprocity toward the government) are important for the prevalence of leaving profits, employment, wages, and other data unreported. For instance, managers may decide not to report firms’ economic activities to evade taxes or government regulations and, through that, attain economic benefits. The authors also propose that stronger government performance could lead to a reduction in unreported activities; if management sees taxation as a reciprocal payment for government activities — for instance, in terms of entrepreneurship support — it may see tax obligations as necessary and fair. Thus, it is not enough to control firms’ activities (although this is also important as lack of control can also motivate dishonesty): it is also necessary to motivate managers to make their firms more honest. In the third chapter ‘‘Firm Bankruptcies and Violations of Law: An Analysis of Different Offences,’’ Oliver Lukason analyzes how frequently Estonian firms that went bankrupt in 2002–2009 engaged in three types of pre-insolvency violations of law — non-submission of annual reports, violations of net asset requirement, and elements of criminal offence — and which factors affected them. Based on the whole population of Estonian bankrupt firms from this period, the author of this research paper concludes that all these violations were relatively frequent among bankrupt firms. In the case of the first two violations, their frequency varied depending on insolvency years and types: for instance, non-submission of annual reports was especially common in the case of bankruptcy proceeding abatement while net asset requirement violations were most common during the pre-insolvency year. In the case of the elements of criminal offence, insolvency years and types, but also industries and firm sizes were not relevant. Also, O. Lukason states that financial variables cannot be used for predicting the firm’s potential engagement in criminal offence.

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In the fourth chapter ‘‘From Dishonesty to Disaster: The Reasons and Consequences of Rogue Traders’ Fraudulent Behavior,’’ Mark Kantsˇ ukov and Darja Medvedskaja analyze six cases of rogue trading: the cases when a financial trader breaches organizational risk or loss limits on financial transactions. They conclude that although it is not possible to identify a universal pattern of rogue trading schemes, the cases have some similarities: such behavior is often motivated by the trader’s wish to earn excess returns, gain more recognition and respect within his/her organization, and, in many cases, also to cover up the losses from prior trades. Moreover, the people willing to take considerable risks, those having the opportunity for rogue trading due to weak control from their organization, and those having the knowledge and skills necessary for this — for instance, the employees who have previously worked in the back or middle office as they know how to settle accounts – are more likely to commit such white-collar crimes. Although rogue trading can result in considerable losses — in some cases, even billions of U.S. dollars — some organizations are willing to tolerate such fraud, and sometimes, they even support and/or hide it. Part III starts with the chapter ‘‘The Drivers and Moderators for Dishonest Behavior in the Service Sector.’’ Krista Jaakson, Jaan Masso, and Maaja Vadi test the strength of three different drivers — financial gain, response to injustice, and escape from boredom —to engage in dishonest behavior at work. They also analyze how individual and organizational values affect the effect of these drivers. They conclude that while the financial and injustice drivers triggered several forms of dishonest behavior, the escape from boredom did not lead to dishonest behavior. Thus, owners and employers should pay the most attention to the first two drivers. The authors also state that the effect of individual values in reacting to the drivers is relatively weak and the role of organizational values is marginal. Moreover, they find that some forms of behavior — for example, shirking, undermining the company’s reputation, and misuse of the employer’s facilities — classified as dishonest in the literature were regarded almost normal by the studied service employees. Also, many employees regarded hiding relevant information from the firm’s customers as a sign of honesty and loyalty toward the firm. In the second chapter ‘‘Human Resource Managers and Employees’ Rights: An ABC (Antecedents — Behavior — Consequences) Analysis of Ethical Dilemmas,’’ Dana Mesner Andolsˇ ek, Mateja Primozˇicˇ, and Janez Sˇtebe explore the ethical conflicts Slovenian human resource (HR) managers have to face. Based on a survey of 73 HR managers (out of 598 members of the Slovenian HR association), they conclude that HR managers are often caught in a specific position — ‘‘between Scylla and Carbides’’ — in relation to senior management and employees: to please the firm’s owners and top managers, they often have to violate their employees’ rights — engage in unfair payments, extreme differences in rewards, not respecting employees’ rights, discrimination; using over excessive disciplinary power, not paying social contributions, and using manipulations, among others — even if they understand that they are behaving dishonestly toward their employees. The authors also state that HR managers need professional education to understand how to prioritize expectations and demands in their workplace and how to solve ethical issues and engage in ethical behavior.

Introduction

xv

In the third chapter ‘‘Honesty in Leadership: A Case of the Czech Republic,’’ Zuzana Dvorakova, Edward Shippen Bright, and Jan Muehlfeit discuss honesty in leadership on an example of the Czech Republic. Based on an interview with a Czech top manager, some statistics and observations, they conclude that the ‘soft side’ of leadership — emotion, integrity, communication, networking and serving others — has become more important in current business life than it was before. Honesty is nowadays a necessary characteristic of effective leaders. In the Czech culture, several values are associated with honesty and integrity, especially being generous, caring about relatives and social relations. On the other hand, Czechs tend to have low acceptance of formal structures and rules, they value informal communication more highly than formal, have a strong tendency to conflicts and take criticism very personally. Moreover, due to relatively high corruption in the Czech Republic, more attention should be paid to the reestablishment of traditional public administration values and ethics. In the fourth chapter ‘‘Legitimizing Dishonesty in Organizations: A Survey of Managers in Four Sub-Sahara African Countries,’’ Martina L. Yanga and Isaac O. Amoako analyze how managers from Ghana, Kenya, Tanzania, and Uganda feel toward gift giving, patronage, and non-meritocratic employment practices: if they consider them dishonest or not. They conclude that gift giving was widespread in the studied organizations, but the managers did not agree that gift giving could cause dishonesty in organizations. Also, they were not unanimous if the expectations of the society on individuals to pursue the interests of their constituent groups ‘‘glorify and endorse’’ dishonesty: this impact was felt in Ghana and Kenya, but not in Tanzania and Uganda. On the other hand, most of the surveyed managers agreed that non-meritocratic employment practices may lead to hiring incompetent workforce, and, as a result, reduce trust and loyalty in organizations. Thus, although African managers do not feel that hiring friends and relatives is automatically dishonest, they try to exercise caution (only hire qualified candidates) in order to minimize these impacts. Part IV starts with the chapter ‘‘Evaluating ‘Honesty’ When Implementing Corporate Community Initiatives: A Developing Country Perspective.’’ Eshani Beddewela analyzes if implementing corporate community initiatives (CCIs) in Sri Lanka is ‘‘honest’’ in terms of the companies’ real motives for implementing them and their outcomes to these initiatives’ stakeholders or not. Based on three cases and six evaluative criteria (the ‘‘primary’’ organizational motive, the type of stakeholder selected for engagement, the frequency of engagement with salient stakeholder, the type of the community project, its duration, and the ‘‘primary’’ outcome expected by the organization), she concludes that the motives of CCIs tend to have a multifaceted nature — they are not always driven entirely by altruistic motives as companies also consider their future reputational gains and potential increases in revenues and, through that, advance their shareholders’ long-term interests — but their outcomes tend to be socially progressive; thus, they also fulfill some social objectives. She also concludes that it is not always easy to determine the level of ‘‘honesty’’ of every project; moreover, sometimes, companies’ motives may change: for instance, become less altruistic due to shareholder pressure.

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In the second chapter ‘‘Building Trust between American and Chinese Business Negotiators,’’ Maria Lai-Ling Lam examines how 36 Chinese expatriates in the United States and 24 Chinese executives in Hong Kong established trust between the U.S. and Chinese negotiators. She explains that the U.S. negotiators come from an individualistic, low-context culture, goal-oriented with a well-established legal system and a mature market economy but the Chinese negotiators come from a collectivistic, high-context, power-driven, and relationship-oriented culture with an embryonic legal system and an emerging market economy. Thus, during negotiations, it is important to entwine affect-based trust (feeling) and cognitive-based trust (information) and know how to use affect-based trust to ask for reciprocity. Affect-based trust can be also used to defer dishonest behaviors in negotiations and projects: imposing rules on Chinese firms to safeguard against dishonesty is not always the best strategy as they may pretend to obey these rules to get what they want from the negotiation process, but later, the project will be implemented by other people who will disobey these rules if they do not agree with them. In the third chapter ‘‘The Consequences of Dishonesty in International Partnerships: Three Chinese Cases,’’ Tiia Vissak and Xiaotian Zhang analyze how dishonest behavior toward their international partners affected three dishonest/opportunistic small Chinese firms and what caused their dishonesty. They conclude that although these firms benefited from relationships with their foreign partners in terms of knowledge, connections, market access, reputation, and financial returns, they engaged in dishonest behavior as they wished to earn higher profits. Thus, they started selling the products copied from their partners in China and/or abroad without informing them. Their dishonesty became possible because their partners were abroad, thus it was not easy for them to discover the dishonest activities of the Chinese firms fast. After the foreign partners discovered what their Chinese partners were doing, the partnerships were ended. Still, although one dishonest firm went bankrupt, for the two other dishonest firms, the overall effect was positive: they managed to grow fast in China and abroad after the partnerships were ended and both also became more innovative. Thus, for them, dishonesty paid off. In the last chapter ‘‘From Dishonesty to Honesty: Is This Journey Path Dependent?’’ Eneli Kindsiko, Maaja Vadi, and Tiia Vissak discuss the results of the chapters published in this book, but also some other management studies. They argue that the perception of the ‘‘level of honesty’’ of a certain act may depend on several factors. First, they emphasize that today’s acts depend on past events: in other words, they are past dependent. This dependency manifests itself in differences in culture, trust toward employees, managers or business partners; societal, political, and economic factors, but also organizational and group values. Second, they explain how complex (dis)honesty is and how hard it is to draw a clear line between honest and dishonest acts because of ‘‘gray areas’’ in between. Dishonesty may sometimes lead to positive outcomes and honesty to negative consequences. Moreover, sometimes the same act may be perceived as honest and sometimes as dishonest. This is especially the case in international and cross-cultural management. Third, as both honesty and dishonesty can be contagious, managers have to become good role models to achieve organizational goals as ‘‘one bad apple can ruin the whole barrel.’’

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We hope that the important topics covered in the 15 chapters of this volume will provide intellectually stimulating and enjoyable reading and will have an impact on the future management research and business practice. Tiia Vissak Maaja Vadi Volume Editors

References Das, T. K., & Rahman, N. (2002). Opportunism dynamics in strategic alliances. In F. J. Contractor, P. Lornage & P. N. Ghauri (Eds.), Cooperative strategies and alliances (pp. 89–118). Amsterdam: Pergamon. Griesinger, D. W. (1990). The human side of economic organization. Academy of Management Review, 15(3), 478–499. Jap, S. D., & Anderson, E. (2003). Safeguarding interorganizational performance and continuity under ex post opportunism. Management Science, 49(12), 1684–1701. Luo, Y. (2006). Opportunism in inter-firm exchanges in emerging markets. Management & Organization Review, 2(1), 121–147. Malshe, A., Al-Khatib, J. A., & Sailors, J. J. (2010). Business-to-business negotiations: The role of relativism, deceit, and opportunism. Journal of Business-to-Business Marketing, 17(2), 173–207. Ntayi, M. J., Rooks, G., Eyaa, S., & Qian, C. (2010). Perceived project value, opportunistic behavior, interorganizational cooperation and contractor performance. Journal of African Business, 11(1), 124–141. Parkhe, A. (1993). Strategic alliance structuring: A game theoretic and transaction cost examination of interfirm cooperation. Academy of Management Journal, 36(4), 794–829. Wathne, K. H., & Heide, J. B. (2000). Opportunism in interfirm relationships: Forms, outcomes, and solutions. Journal of Marketing, 64(4), 36–51. Williamson, O. E. (1987). The economic institutions of capitalism: Firms, markets, relational contracting. New York, NY: Free Press.

PART I THE NATURE OF (DIS)HONESTY

Chapter 1

The Nature of (Dis)Honesty, Its Impact Factors and Consequences Maaja Vadi and Tiia Vissak

Abstract Purpose — The aim of this chapter is to explain the concepts of honesty and dishonesty in management and provide a general understanding why and how honesty and dishonesty may manifest in different ways. Design/methodology/approach — This conceptual chapter discusses what (dis)honesty is, which factors affect it and which consequences result from it. It is illustrated with several short examples. Findings — (Dis)honesty is a complex concept. It is not always possible to classify a certain act as honest or dishonest: sometimes, it is in the ‘grey area’. Moreover, the understanding what is honest and what is not depends on the cultural context. Thus, the term (dis)honesty may be sometimes more appropriate. Originality/value — The complexity of (dis)honesty in management (encompassing its nature, impact factors and consequences) has received relatively little research attention. Keywords: Honesty; dishonesty; management

Introduction Studying honesty implies dealing with dishonesty and vice versa. Both concepts are important and widely used in management literature and other social sciences research but many scholars have admitted that they are not very well defined. For

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 3–18 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010005

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example, Scott and Jehn (1999, p. 298) stated: ‘One of the reasons why there is not a common definition of dishonesty is that dishonesty is not simply defined.’ If definitions are different, this may also lead to contradictory results: for instance, when the reasons for or consequences of dishonesty are studied. Thus, before studying the impact factors or manifestations of dishonesty, it is necessary to understand its nature, and also the nature of its opposite — honesty. Moreover, it is important to discuss the ‘grey areas’ in between these two opposites. We use the term ‘grey area’ to indicate that many acts have some characteristics of honesty and some of dishonesty. As there are many crossroads where honesty meets dishonesty, the definition of these categories is a challenging task. This topic is especially important nowadays. For instance, van Gigch (2006, p. 9) claimed: ‘There is rampant dishonesty in management, lying and fraud are the order of the day. The ‘‘ENRONS’’ and other frauds make the daily news.’ Crittenden, Hanna, and Peterson (2009, p. 338) agreed: ‘Cheating is certainly not a new phenomenon. Yet, the difference between today’s environment and that of yesteryear is that cheating behavior is now considered commonplace rather than an exception to the norm.’ Thus, for managers, it is necessary to understand what dishonesty is: not only because they are usually expected by the society, employees and other stakeholders to act honestly (with some exceptions), but also as they have to shape the organisational culture so that their employees will also act more honestly. Moreover, they need to understand the nature of ‘grey areas’ in between. The aim of this chapter is to explain the concepts of honesty and dishonesty in management and provide a general understanding why and how honesty and dishonesty may manifest in different ways. The chapter focuses on both honesty and dishonesty and, due to ‘grey areas’ in between, it also uses the term ‘(dis)honesty’. It also explains why these areas are sometimes very big. As, according to Scott and Jehn (1999, p. 320): ‘there is no difference between the definition of dishonesty in business and the definition of dishonesty outside of business — that is, something that is dishonest within an organization is dishonest outside of the organization’, we also integrate knowledge from other areas besides management. The chapter starts from definitions and forms of honesty and dishonesty. It continues with the reasons of (dis)honesty (societal, organisational and individual characteristics). The consequences of dishonesty are integrated within the text. The chapter ends with managerial and research implications.

The Definitions of Honesty and Dishonesty This section concentrates on different understandings of what honesty is (we agree with the definition by Becker (1998, p.158): ‘Honesty is the refusal to pretend that facts of reality are other than what they are.’) and how to define its opposite dishonesty. Defining dishonesty through lack of honesty is not uncommon. For instance, Ashton, Lee, and Son (2000, p. 361) stated: ‘the terms defining the positive pole of the Honesty factor (e.g. honest, fair, trustworthy) suggest a reluctance to

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exploit others, whereas the terms at the negative pole of the factor (e.g. sly, greedy, haughty) suggest an inclination or a willingness to exploit others.’ It has to be noted that from the perspective of organisational life, it would be useful to differentiate between honesty and integrity, and it is the latter that contributes more directly to ethical behaviour. Integrity is ‘closer’ to ethical behaviour than honesty, but it involves honesty. For instance, according to Namagembe and Ntayi (2012, p. 57), ‘high moral standards of integrity are taken to be measures that are used to prevent the misconduct of y staff through creating an awareness of the unethical and ethical issues’, while Petrick (2011, p. 652) has stated: ‘integrity capacity is the alignment of individual and collective moral awareness, deliberation, character and conduct on a sustained basis.’ Some authors have defined dishonesty through committing certain acts. For example, according to Skillern (1978–1979, p. 339): ‘the word dishonesty implies an intent to commit a wrongful act’ and (p. 344) the intent may be ‘to obtain financial benefit (other than benefits earned in the normal course of employment) (a) for the employee or (b) for any other person or organization intended by the employee to receive such benefit’. This may seem easily understandable, but (p. 341): ‘the key question is really: what intent is required, the intent to commit the act, or the intent to do something wrong?’ Scott and Jehn (2003) identified more dishonest acts but also explained what makes defining dishonesty difficult. They (p. 238) stated: ‘Researchers have included many types of behavior that are not clear-cut lies in definitions of the construct dishonesty. These other behaviors include such things as cheating, stealing, and shirking. The disparities among these behaviors have made it difficult to establish a clear set of necessary and sufficient conditions for defining dishonesty. This has led researchers to suggest that the construct of dishonesty in organizations is multidimensional.’ In their earlier article, Scott and Jehn (1999) were more specific in defining dishonesty. They (p. 296) developed the following definition: ‘Dishonesty occurs when a responsible actor voluntarily and intentionally violates some convention of the transfer of information or of property, and, in so doing, potentially harms a valued being.’ The various characteristics and forms of dishonesty are presented in Table 1. Honesty and dishonesty can seem to be each other’s opposites or polar by their nature, but they can be actually interrelated. For instance, Frankel (2006, p. 4) stated: ‘There are gray areas between y absolutely honest and truthful communication and clear deceit. Within these areas, one can move in small steps, one at a time, from honesty to dishonesty.’ Scott and Jehn (2003, p. 239) reached a similar conclusion: ‘We propose that people categorize behaviors as dishonest insofar as they contain some or all of the components of a prototypical lie — or come close to the components of a prototypical lie. As with the category lie, we argue that people make gradient judgments about what belongs in the category. Behaviors very clearly belong in the category dishonesty when they match the prototype most closely, but as they move away from the prototype, they become ‘‘kind of’’ or ‘‘a little’’ dishonest.’

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Table 1: Dishonesty: characteristics, forms, reasons and impact factors. Characteristics of dishonesty



  





Forms of dishonesty













Reasons for dishonesty

  

Impact factors of determining the perceived level of honesty of an act

 



  

An act violates conventions of transferring information or property The actor has acted voluntarily The person engaging in the action can be deemed responsible It affects (or has the potential to affect) how a person is being valued by society The actor must intend to violate the conventions of transfer of information or of property The act has the potential to harm some valued being Property theft: thefts of assets of customers, coworkers and suppliers Production theft: the voluntary, intentional taking of unearned money from an organisation (for instance, taking long breaks, padding expense accounts, or taking sick days when well) Lying about beliefs: misrepresenting the speaker’s knowledge (presenting information that the speaker believes to be untrue) Lying about intentions: stating the intention to perform or to refrain from performing some action without any actual intention to do so Lying about emotions: intentionally misrepresenting the feelings of the speaker (encouraging the hearer to believe that the speaker either has an emotion that the speaker does not have, or does not have an emotion that the speaker does have) Concealment: intentionally withholding information under conditions designed to encourage the recipient that all relevant information has been revealed (the deceiver is silent about a particular belief, intention or emotion in a manner intended to lead the target to believe something untrue) Altruism Self-enrichment (self-interest) Revenge The evaluator’s previous actions and experiences The evaluator’s moral development, ability to trust and other characteristics The evaluator’s ability to identify with the victim or the beneficiary The motives of dishonesty (altruism, self-interest, revenge) The level of the actor’s control in a given situation Culture

Source: Compiled by the authors based on Frank (1989, p. 28), Scott and Jehn (1999, pp. 300, 306–315) and Scott and Jehn (2003, pp. 243–246).

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Thus, the real issue is not whether but to what extent and in what ways honesty and dishonesty can be differentiated. We admit that it is not easy to draw a line between those categories and therefore the term ‘grey area’ can be introduced for encompassing this undefined sphere. We combine this idea with knowledge that individuals, organisations, and societies are actors on the playground of an economy. Figure 1 shows that on the society level the ‘grey area’ is not as big as on the individual level because persons are influenced not only by the legal system, shared values, and norms in the society, but also by the values and norms in the organisation where they work, and these may influence them more directly. The individuals’ own norms and values influence them the most. Still, we agree with Romar (2004, p. 670) that ‘human beings exist in society and are defined by the social context, social roles, and the behavior expected in the situation, where the situation is defined by role, rules y and the conditions facing the individual at the moment.’ Moreover, we agree with Choo and Tan (2007, pp. 209–210) that ‘a corporate environment that is preoccupied with monetary success, and that implicitly or explicitly allows corporate executives to exploit/disregard regulatory controls, also provides justification/ rationalization for success by any means such as Fraud’. There is room for interpretation of ‘grey areas’ and knowledge about social behaviour helps to understand their preconditions, essence and consequences. Dose (1997) mentions that the degree of social consensus regarding the importance or desirability of a particular value is a forming unit of the work values framework model. She further says that greater social consensus may lead to a greater attempt to influence individuals towards accepting the majority view. In the moral range, there is likely to be a social influence informing individuals of the standards of what is ‘right’ (p. 229). Organisations have to find ways for avoiding significant losses and this is why employers and governments are naturally concerned about honesty. Yet, we believe that knowledge of the factors that trigger the importance of honesty and those that lead to dishonesty may help to identify some preconditions for ethical behaviour at the workplace.

Absolute dishonesty (societal)

grey area

Absolute dishonesty (organizational)

grey area

Absolute dishonesty (individual)

grey area

Absolute honesty (societal) Absolute honesty (organizational) Absolute honesty (individual)

Figure 1: Absolute dishonesty and honesty opposed to the grey areas. Source: Compiled by the authors.

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Societal and Organisatonal Factors Influencing Manifestations of Honesty and Dishonesty A person’s behaviour depends on circumstances. When a person is born, he or she cannot be evaluated as being honest or dishonest; however, this is deeply acquired knowledge because the person starts to learn from early childhood and understand which acts are right or wrong, honest or dishonest. Frank (1989, p. 28) explains this in the following way: ‘Attitudes and values are not etched with great specificity at birth. On the contrary, their development is, as noted, largely the task of culture.’ In this light we argue that it is necessary to study the factors that affect manifestations of honesty and dishonesty. In this section the focus is on societal and organisational factors, while individual factors are examined in the following section. The society frames the understanding whether the acts or consequences are in accordance with moral values including honesty and therefore the context is always an important factor that influences this assessment. Still, this is not the only factor: besides societal reasons and factors, organisational, personal and some socio-demographic characteristics also affect the manifestation of honesty and dishonesty (see Figure 2).

Manifestations (acts) and consequences

Dishonesty

Honesty

Organizational (i.e. management) factors

Sociodemographic characteristics

Personal values

Society

Figure 2: Factors

influencing manifestations of honesty Source: Compiled by the authors.

and

dishonesty.

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The following short example presents a vivid picture about one important factor for the manifestation of honesty or dishonesty. During the Soviet era, people were divided into two separate types: ‘radish-type’ people represented the red ideology surface, while being ‘white’ inside, but ‘tomato-type’ people were ‘red’ all over. The ‘radish type’ was the most common among Soviet citizens at least in one of the former Soviet Bloc countries — Estonia. Such duality was mirrored also at the organisational level, because on the one hand organisations employing these people were stateowned or -controlled, thus they represented the state, but on the other hand, socialisation with colleagues was based on openness and sincerity. Honesty was a mixed moral value for Soviet people: relationships with the state and government and also with their representatives were characterised by hypocrisy and double standards, whereas on an interpersonal level honesty was considered a cornerstone for associating with others and it played an essential role in fostering good relationships with colleagues. This example illustrates an important aspect of honesty in organisations. Nowadays, in many former Soviet Bloc countries the strict rules imposed by the ideology are gone; people feel that there is a lot of freedom but they are not always prepared to cope with it. In a similar vein, Snavely, Miassoedov, and McNeilly (1998) underlined that the Russian entrepreneurs’ understanding of meaning of honesty may differ from their Western partners’ traditions and thus the internal networks are very important in order to gain trust in business. Honesty still has an ambiguous role in Russia. Radaev (2003, p. 18) expressed it as follows: ‘By and large, honesty may not pay in free market relationships while it starts paying within closed business networks.’ The role of honesty among former socialist systems is ambiguous, because previous experiences could be combined with certain cultural issues. One potential explanation derives from the cultural dimension individualism–collectivism and namely, collectivists desire to maintain group solidarity and thus prefer norms of equality to equity (Leung & Bond, 1984). Accordingly, this disposition may create serious dissonance when staying on the position or presenting things as these are. This is one important reason why the scope and scale of ‘grey areas’ vary along cultures significantly. Here it is suitable to mention a notion by Hayek (1973) ‘The more complex a society became the more it had to replace innate responses with new rules, which were perceived and learned from outside the group. The instincts themselves no longer led to a beneficial life, but instead it was their gradual suppression combined with their replacement by new rules of conduct that brought about a new order thoughts about the morality of property and honesty, which, in an extended order, ensures cooperation.’ It means that the understanding and knowledge reflecting how others see what honesty is may facilitate copying with the new realities what societies have met in the global and rapidly changing environment. As noted in the Introduction, Scott and Jehn (1999, p. 320) argued that ‘there is no difference between the definition of dishonesty in business and the definition of dishonesty outside of business y something that is dishonest within an organization is dishonest outside of the organization’. Still, the organisational context affects economic activities and employees considerably. Here the management’s role and

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activities are very important. We follow the understanding offered by Zeitz, Mittal, and McAulay (1999) according to which management practices are techniques and behaviours to plan, lead, and control people in an organisation. This view covers provisionally all the management functions. Modern managers of the companies with Soviet history have admitted that the biggest challenge in their managerial career has been changing their employees’ attitudes towards stealing the company’s assets. However, the stealing incident is only a part of the problem; the real issue has been to facilitate the culture that the thief would be turned in by his/her colleagues. Still, the situation in the former Soviet Bloc countries is far from unique in respect with ethical behaviour: for example, van Gigch (2006, p. 9) claimed about USA: ‘The meaning of ethics has vanished and the inner controls and motivation to do good are non-existent. y Frauds and lack of ethics in business transactions are at a record high’1 while Giacomino, Akers, and Fujita (1999) concluded that for Japanese business managers, honesty was among the less important values. On the other hand, Cileli and Tezer (1998) found that in Turkey, honesty ranked as one of the most important instrumental values and Akers and Giacomino (2000) argued that honesty was ranked among the five top values regardless of the socio-demographic characteristics when they investigated audit and tax professionals in Milwaukee, United States. It is also important to mention that the role of ethical issues is currently increasing because new technologies involve the areas where the employees’ ethical decisions play a crucial role. For example, information technology has become a very important channel of communication and therefore the role of direct communication has decreased. Consequently, the traditional kinds of social control executed in direct communication have got less importance than they had years ago. Organisations have to find ways for avoiding significant losses and this is why employers are naturally concerned about honesty of their work force. A finding by Kujala (2004) confirms that there are certainly national differences in respect with the importance of honesty. She refers a Finnish manager who had said that Finnish business people experience problems when they deal with some foreign business people because they are too honest compared to others. Here the context of the Soviet Union can be also presented and it provides many examples about the role of honesty. Honesty had different meanings in the USSR compared to the Western society. It could be illustrated by Grossman (1977) who brings forth that in the USSR the distinction was between two stealing forms — stealing from the state and stealing from private owners. While the former was practised by virtually everyone, the latter was generally condemned. When shared understandings are analysed in organisations, then organisational culture is often mentioned as an important factor (see e.g. Peterson & Smith, 2000; 1

KPMG’s Fraudster Survey (2011) showed that loss per fraud is substantial in some high-growth and BRIC economies as well as in some established economies. There are no signs of amendment in this respect because in 2007–2011 the time needed for detection of fraud increased from an average 2.9 years to 3.4, respectively (Who is the typical fraudster? 2011, pp. 15–16).

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Trice & Beyer, 1993). Organisational culture is a complex of several elements, involving unconscious parts of organisational life and it covers all functions of an organisation (Schein, 1992). On the one hand, organisational culture depends on the sector and sphere of activity as well as on the economic environment in which organisations operate. On the other hand, it creates the atmosphere where some values are strongly supported and others are suppressed. For example, Dufresne (2004) relates the implementation of academic honour codes and other ethics codes to the enacting organisational culture while Christensen and Kohls (2003) discuss ethical decision making in times of organisational crisis and consider organisational culture as important factor of the process and outcome (see Figure 3). It is impossible to ‘touch’ or fully ‘measure’ honesty and dishonesty because they are always intangible by their nature. Therefore, it is necessary to find out what are the manifestations of these abstract phenomena. For perceiving and evaluating whether a person has been honest rather than dishonest, her/his acts have to be evaluated. In the light, the acts can be evaluated as being right or wrong, but as the evaluators’ values differ and some acts can have some ‘right’ and ‘wrong’ characteristics, some acts also belong to the ‘grey area’. For instance, Scott and Jehn (2003, p. 246) stated: ‘the more the judge identifies with the actor and the beneficiary, the less dishonest the event will be judged to be, and the more the judge identifies with the victim, the more dishonest the event will be judged to be’. Again, even honesty-oriented management and organisational culture do not guarantee that the outcome of an organisation or its individual member would always be the right act.

management

dishonesty ACTS

INDIVIDUAL

A RIGHT ACT

A WRONG ACT

CONSEQUENCES

Organizational culture honesty

MANIFESTATIONS

THE RIGHT ACT

THE WRONG ACT

Figure 3: The role of management in forming manifestations and consequences of honesty and dishonesty. Source: Compiled by the authors.

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Individual Factors Influencing Manifestations of Honesty and Dishonesty In this section, individual factors are divided into two categories to differentiate between values and other (mainly generic) characteristics. Personal values form patterns of values and individuals may vary significantly in terms of combinations of values. On the other hand, they are not the only individual factors that lead to honesty or dishonesty. The portrait of a typical fraudster illustrates one possible set of characteristics which can be considered as example of individual factors. KPMG (Who is the typical fraudster? 2011) presents a profile of a typical fraudster based on 348 actual fraud investigations in 69 countries. According to their findings (p. 1), a typical fraudster:       

is male; is 36–45 years old; commits fraud against his own employer; works in the finance function or in a finance-related role; holds a senior management position; has been employed by the company for more than 10 years; and works in collusion with another perpetrator.

Indeed, it would be a stereotypical approach if we think that all persons having these characteristics can be considered as the potential unethical employees because here, motivation plays a determining role. The KPMG study shows that the motivation for fraud is personal greed, followed by pressures on individuals to reach tough profit and budget targets. For an explanation, we can construe the following path. The pressure (material/economic, social and moral) pushes a person to become a fraudster or a cheater, possibilities for acting dishonestly (for instance, weak control, unclear organisation of work and suitable technological means) facilitate and enable the (most) wrong or a wrong act, whereas a threshold question comes from a person’s value system: can he or she justify this act to himself/herself? The wrong or a wrong act happens then, and only then, when the person can justify it even for a while. Self-justification is based on values because these play a significant role in decision making, standards of evaluation and ideals (Rokeach, 1973) and here values serve the function of a mirror and substance for solving dissonance. The importance of the value honesty is illustrated by Rokeach (1973) on the basis of returning borrowed pencils. Upon completing a questionnaire, 39% of the subjects returned the scoring pencils that had been distributed to them, while 61% did not. The investigators found four values that significantly distinguished those returning from those not returning the pencils. Those who returned the pencils gave a median rank of 2.0 to honesty, whereas the non-returners ranked honesty much lower: a median of 4.38. There was also the paradoxical result that the pencil returners placed a significantly lower value on being helpful. This account suggests that there may indeed be a linkage between the individual value honesty and ethical behaviour, if we

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consider the act of pencil returning to be ethical in its nature. The role of the value helpful suggests that the social aspect of returning of pencils has to be considered as well. Several researchers have agreed that the decision to behave honestly or dishonestly may depend on the person’s nature. For example, Frank (1989, p. 26) claimed: ‘When an opportunistic person is exhorted to behave morally, his immediate, if unspoken question is, ‘‘What’s in it for me?’’’ Moreover, Choo and Tan (2007, p. 209) stated that striving for monetary success ‘has provided the motivational dynamic for greed, corporate Fraud, unethical behavior, and illegal act’. On the other hand, Frank (1989, p. 22) also claimed that some people are honest even if it is not in their self-interest (at least when evaluated by an opportunistic person): ‘Consider, too, a person who ‘‘feels bad’’ when he cheats. These feelings can accomplish for him what a rational assessment of self-interest cannot — namely, they can cause him to behave honestly even when he knows he could get away with cheating.’ We propose that if honesty is important for a person, he/she has a disposition towards ethical behaviour but in this respect it is important to mention that the results of empirical studies show contradictory tendencies. On the one hand, Finegan (1994) and Mudrack (1994) found that the value honesty was the only value among others which was a significant predictor of ethical judgements but on the other hand, Shafer, Morris, and Ketchand (2001) demonstrated that personal value preferences — including the instrumental value honesty — did not influence ethical decision-making. Even if a person understands what is honest and what is not, it will not guarantee that he/she will prefer to behave ethically. For example, according to Gino, Schweitzer, Mead, and Ariely (2011, p. 200), ‘resisting unethical behavior consumes self-regulatory resources. This finding suggests that good conduct that involves refraining from unethical behavior may result in subsequent cheating. If new opportunities to engage in unethical behavior arise, depleted self-regulatory resources may make otherwise ethical individuals particularly vulnerable.’ On the other hand ‘Some individuals, even when they are depleted, are better equipped to resist unethical behavior.’ An evaluation what is honest and what is not or what belongs to the ‘grey area’ also depends on the possible consequences of the act. For instance, Scott and Jehn (2003, p. 242) concluded: ‘The potential consequences of the event will moderate judgments of dishonesty, such that events y will be seen as less dishonest if they are beneficial and more dishonest if they are harmful.’ Thus, if the consequences of dishonesty may seem beneficial, a person is more likely to engage in it. It also matters who will benefit from the potential dishonest act. For example, Wiltermuth (2011, p. 157) stated: ‘people may be more likely to behave dishonestly for their own benefit if they can point to benefiting others as a mitigating factor for their unethical behavior’ and explained (p. 166): ‘because people see cheating as greedier and less ethical when the cheater alone benefits than when others also benefit, splitting the spoils of cheating can make people more likely to cheat’. The consequences of dishonesty do not always manifest in achieving certain results, but also in not being to achieve certain results. For example,

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Stokke (2013, p. 348–359) explained: ‘(part of) the moral wrongness of lies comes from the fact that lies block certain choices that otherwise would have been available. Sometimes, probably most often, this is due to misinformation generated by a deceptive lie. But sometimes it is due to reasons of protocol, custom, etiquette, or law, which disallow particular actions in the presence of certain statements having been made, or not made.’ A decision to act honestly or dishonestly also depends on a person’s ability to rationalise it. For instance, Gellerman (1986, p. 88) stated: ‘we can delineate four commonly held rationalizations that can lead to misconduct:    

A belief that the activity is within reasonable ethical and legal limits — that is, that it is not ‘‘really’’ illegal or immoral. A belief that the activity is in the individual’s or the corporation’s best interests — that the individual would somehow be expected to undertake the activity. A belief that the activity is ‘‘safe’’ because it will never be found out or publicised; the classic crime-and-punishment issue of discovery. A belief that because the activity helps the company the company will condone it and even protect the person who engages in it.’2

Expectations towards other people’s activities also affect a person’s decision how to behave. For instance, according to Frank (1989, p. 28): ‘Someone who expects always to be cheated has little motive to behave honestly.’ Crittenden et al. (2009, p. 338) even defined a cheating culture as a culture ‘in which people: (1) are tolerant of cheating behavior, (2) believe in the need for cheating to achieve a goal, and (3) perceive that everyone around them is cheating in order to succeed’. There is one sensitive theme related to right and wrong acts and it touches workforce diversity. The latter concept notifies that all socio-demographic characteristics must be treated with caution and it obliges us to guardedly raise the question: Are there any gender, age or other differences with respect to the importance of honesty among workforce? The results of empirical studies vary. Glover, Bumpus, Sharp, and Munchus (2002) and Kamat and Kanekar (2001) compared female and male respondents’ reactions to several dealings of ethical nature, concluding that women were more likely to make ethical choices than men. A sizeable analysis by Ones and Viswesvaran (1998) additionally revealed that women scored higher than men on overt integrity tests and there were very small differences between the groups of those under 40 and those over 40 and older. On the contrary, findings by Vadi and Jaakson (2011) tell that gender, age (or age-category) and position were not significant in predicting how honesty was ranked among the individual values, it means whether it was considered to be very important or unimportant. Although KPMG (Who is the typical fraudster? 2011, p. 1) provided a portrait of a typical 2

Wiltermuth (2011, p. 166) agreed with this statement: ‘‘an individual employee may be likely to act fraudulently when the doing so would benefit not only that individual employee but the company’s other stakeholders. This may be the case even if the other stakeholders would have advised the employee against acting fraudulently if they were involved in the decision.’’

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fraudster, we cannot say that a persons’ characteristics fully predict her or his intents and acts because of the impacts from the society, organisation and its management. This wide and ambiguous statement can be grounded with a quotation from Scott and Jehn (1999, pp. 300–301): ‘Individuals may differ vastly in their determinations about the intent or harm of a given action. Their views of the intent or harm of a given action may be affected by their own previous actions or previous experiences. They may have differing dispositions that affect their assessments of how much control an actor has in a given situation. They may have different levels of moral development that affect their abilities to analyze situations. These individual differences result in different understandings of whether an action is dishonest and are extremely important to a complete understanding of the topic of dishonesty in organizations.’

Conclusions and Implications Honesty and dishonesty have been studied by many authors from management and other research fields, but not all of them have defined these concepts. Thus, future research should pay more attention to them, but also to ‘grey areas’ in between of them, as otherwise it would be hard to compare the results of different studies; moreover, classifying all acts only into honest or dishonest may limit the understanding of the nature of these acts: they may have both ‘honest’ and ‘dishonest’ characteristics. Managers also have to understand what is honest and what is dishonest; moreover, they need to understand that the evaluation of a certain act should not be either ‘black’ or ‘white’, but there are ‘grey areas’ in between. Moreover, the evaluation also depends on the particular society (as organisational culture is partly shaped by societal values), organisational culture, a situation; the consequences of the act for the organisation and its stakeholders and the values of the evaluator. We can conclude that the understanding of what is honest and what is not also depends on the cultural context: what is considered honest (acceptable) in some cultures may be considered dishonest (unacceptable) in others, while some may be more neutral in their evaluations. Thus, studies should be conducted in many countries and regions to find out these differences and similarities, and also concentrate on the factors that could have caused them. In addition to the impact from the societal level, a person’s decision to behave honestly or dishonestly depends on the organisational culture of the firm (or other organisation) where he/she works. Managers can shape the organisational culture to some extent (although making considerable and lasting changes can sometimes be time-consuming). Future studies are needed on how to achieve that the organisation and its individual employees will become more honest: to what extent reaching this goal depends on managers, employees and the society, in general, but also on a specific situation: for instance, an economic crisis.

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Besides organisational characteristics, personal characteristics should be studied in more detail: why some people act honestly even if it is not always in their self-interest and if they know that their dishonesty will never be discovered and that their managers may even approve some dishonest acts, and why some other people tend to behave more opportunistically even if they can expect that they would be caught and punished and that this could harm their future career as their managers do not approve such acts. Moreover, it is important to understand how different situations affect persons’ decisions to act honestly or dishonestly: for instance, if an honest person may sometimes decide to behave dishonesty because of altruistic motives or if a dishonest person may sometimes prefer to appear honest in order to gain a reputation of being honest to behave dishonestly again in the future.

Acknowledgements The research was financed by the Estonian Science Foundation’s Grant No. 8546 and target financing of the Estonian Ministry of Education and Research No. 0180037s08. This research has also received support from the European Community 7th Framework Programme (FP7/2010-2.2-1) under grant agreement no. 266834 (SEARCH).

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Frank, R. H. (1989). How passion pays: Finding opportunities in honesty. Business & Society Review, 70, 20–28. Frankel, T. (2006). Trust and honesty: America’s business culture at a crossroad? Oxford: Oxford University Press. Gellerman, S. (1986). Why ‘good’ managers make bad ethical choices. Harvard Business Review, 64(July–August), 85–90. Giacomino, D. E., Akers, M. D., & Fujita, A. (1999). Personal values of Japanese business managers. Business Forum, 24(1/2), 9–14. Gino, F., Schweitzer, M. E., Mead, N. L., & Ariely, D. (2011). Unable to resist temptation: How self-control depletion promotes unethical behavior. Organizational Behavior and Human Decision Processes, 115(2), 191–203. Glover, S. H., Bumpus, M. A., Sharp, G. F., & Munchus, G. A. (2002). Gender differences in ethical decision making. Women in Management Review, 17(5), 217–227. Grossman, G. (1977). The ‘‘second economy’’ of the USSR. Problems of Communism, 26, 25–40. Hayek, F. A. (1973). Law, legislation, and liberty, Volume 1: Rules and order. Chicago, IL: University of Chicago Press. Kamat, S. S., & Kanekar, S. (2001). Prediction of and recommendation for honest behavior. The Journal of Social Psychology, 130(5), 597–607. Kujala, J. (2004). Managers’ moral perceptions: Change in Finland during the 1990s. Business Ethics: A European Review, 13(2/3), 143–166. Leung, K., & Bond, M. H. (1984). The impact of cultural collectivism on reward allocation. Journal of Personality and Social Psychology, 47(4), 793–804. Mudrack, P. (1994). Are the elderly really machiavellian? A reinterpretation of an unexpected finding. Journal of Business Ethics, 13(9), 757–758. Namagembe, S., & Ntayi, J. M. (2012). Ethical sensitivity, academic dishonesty and career growth of academic staff in institutions of higher learning in Uganda. International Journal of Economics and Management Sciences, 1(8), 56–63. Ones, D. S., & Viswesvaran, C. (1998). Gender, age, and race differences on overt integrity tests: Results across four large-state job data sets. Journal of Applied Psychology, 83(1), 35–43. Peterson, M. F., & Smith, P. B. (2000). Sources of meaning, organizations, and culture: Making sense of organizational events. In N. A. Ashkanasy, C. P. M. Wilderom & M. F. Peterson (Eds.), Handbook of organizational culture & climate (p. 629). Thousand Oaks, CA: Sage. Petrick, J. A. (2011). Sustaining governance integrity capacity: A strategic opportunity for China-US public administration. Journal of US-China Public Administration, 8(6), 650–663. Radaev, V. (2003). Russian entrepreneurship and violence in the late 1990s. Alternatives: Global, Local, Political, 28(4), 459–471. Rokeach, M. (1973). The nature of human values. New York, NY: Free Press. Romar, E. J. (2004). Globalization, ethics, and opportunism: A Confucian view of business relationships. Business Ethics Quarterly, 14(4), 663–678. Schein, E. H. (1992). Organizational culture and leadership (2nd ed.). San Francisco, CA: Jossey Bass Publishers. Scott, E. D., & Jehn, K. A. (1999). Ranking rank behaviors: A comprehensive situation-based definition of dishonesty. Business & Society, 38(3), 296–325. Scott, E. D., & Jehn, K. A. (2003). Multiple stakeholder judgments of employee behaviors: A contingent prototype model of dishonesty. Journal of Business Ethics, 46(3), 235–250. Shafer, W. E., Morris, R. E., & Ketchand, A. A. (2001). Effects of personal values on auditors’ ethical decisions. Accounting, Auditing & Accountability Journal, 14(3), 254–277.

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Skillern, F. L., Jr. (1978–1979). The new definition of dishonesty in financial institution bonds. The Forum, 14, 339–351. Snavely, W. B., Miassoedov, S., & McNeilly, K. (1998). Cross-cultural peculiarities of the Russian entrepreneur: Adapting to the new Russians. Business Horizons, 41(2), 8–14. Stokke, A. (2013). Lying, deceiving, and misleading. Philosophy Compass, 8(4), 348–359. Trice, H. M., & Beyer, J. M. (1993). The cultures of work organizations. Englewood Cliffs, NJ: Prentice Hall. Vadi, M., & Jaakson, K. (2011). The dual value of honesty among Russians in selected former Soviet countries. Cross Cultural Management: An International Journal, 18(1), 55–70. van Gigch, J. P. (2006). Progress achieving C. West Churchman’s epistemiological program: The implementation of science of science and of science of ethics. In J. P. van Gigch & J. McIntyre-Mills (Eds.), Wisdom, knowledge, and management: A critique and analysis of Churchman’s systems approach (pp. 1–13). New York, NY: Springer. Who is the typical fraudster? (2011). KPMG analysis of global patterns of fraud. Retrieved from http://www.kpmg.com/US/en/IssuesAndInsights/ArticlesPublications/Documents/who-isthe-typical-fraudster.PDF. Accessed on 27 November 2012. Wiltermuth, S. S. (2011). Cheating more when the spoils are split. Organizational Behavior and Human Decision Processes, 115(2), 157–168. Zeitz, G., Mittal, V., & McAulay, B. (1999). Distinguishing adoption and entrenchment of management practices: A framework for analysis. Organization Studies, 20(5), 741–776.

Chapter 2

(Dis)Honesty in Organizations: Ethical Perspectives Eneli Kindsiko

Abstract Purpose — (Dis)honesty as a quality of our actions can be assessed at different levels. Often these levels have not been differentiated. Semantically we cannot talk about a dishonest society or dishonest organizations — dishonesty can only be attributed to individual actions. We can approach a dishonest act through its essence (deontology), consequences (utilitarianism), and also through the person committing the act (virtue ethics), but most often organizational spheres are too complex objects of study to face ethical dilemmas without the influences that their context can bring. Therefore, the purpose of the chapter is to look at dishonesty as an unethical act through the lenses of behavioral ethics, since behavioral ethics is able to grasp the framing effects of ethical situations while combining the main elements of the previously mentioned traditional ethical theories. Design/methodology/approach — In the current chapter it will be differentiated between traditional ethical theories and acknowledged that depending on the level of analysis (individual, organization, or the society level) with their distinctly different ontological backgrounds, we will have different groundings for making any kind of axiological statements about the dishonesty of an action. Findings — In order to give ethical statements about (dis)honesty in organizations, we cannot neglect the influences brought by context. Organizations with endless social interactions both locally and globally usually have no universal basis for making axiological statements. Originality/value — The originality of this chapter is twofold: firstly to cover the importance of making sense of what ethical approaches we take as a grounding when we make ethical judgments in organizational context, and secondly to analyze

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 19–35 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010006

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whether and how the question of dishonesty differs when we switch between the most traditional ethical approaches. The chapter proposes a new framework how ethical decision-making should be assessed depending on the level of social interactions and how dishonesty is associated with gaining social approval. Keywords: Management; utilitarianism; deontology; behavior ethics; virtue ethics

Introduction Ethics is about what we do and what we say, but even more importantly, ethics is about what we leave undone or unsaid. Ethics is a study of giving value to acts we make as individuals, as members of organizations and furthermore, as managers. Arthur (1984, p. 320) has stressed the importance of ethics in business organizations: The fact of the matter is that business relies much more frequently upon applied ethics and ethical practices than does the average individual. The explanation of this is easy. It is primarily because businesses have more relationships (‘‘transactions,’’ if you will) than is ever likely for the average individual. It is not just that one firm is dealing with other firms or individuals; the firm is also the framework within which employers deal with employees, salesmen with customers, bosses with subordinates.

From the above-stated quote one should easily grasp how complex issue ethics in an organizational context can be — it means endless interactions between people at different levels and with different intensity. Taking dishonesty as one of the deviant phenomena in the eyes of ethics, the complexity of making ethical judgments in organizations stems from endless sources. As Scott and Jehn (2003, p. 235) have stated: The judgment that dishonesty has occurred is one of the most complex judgments made in organizational life, because there are information asymmetries, because there are competing interests, and because the goal of dishonesty is to appear honest. Various organizational stakeholders, observing from their own perspectives, make different judgments as to whether the same behavior is or is not dishonest, based on their own interpretations of the information they have available.

It is a complex issue to draw a line between a dishonest and an honest act, especially when we are not dealing with extreme cases like Enron or Tyco. Would a secretary taking a pencil home from the office qualify as a dishonest person or how would we judge a secretary who had a strong urge to take free pencils home from office, but managed to restrain her wants? Trying to define dishonesty in a global context will go even beyond complexity. Just to bring an example, mixing family and company business by hiring relatives would be noted as nepotism in some countries and considered as a dishonest act, yet in other places not helping one’s own relatives will be judged as deviant behavior. As stated, the mentioned fact is strongly dependent on sociocultural structure and

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behaviors, which in some parts of the world like Arab countries make obligatory to prefer relatives over nonrelatives (Abdalla, Maghrabi, & Raggad, 1995). This is also the reason why many authors (for instance, Heine, Lehman, Peng & Greenholtz, 2002; Hofstede, 1980; House, Hanges, Javidan, Dorfman, & Gupta, 2004) have started to bring up the notion of societal culture, which can be considered as a contextual characteristic that enables to create reasonable expectations of acceptable or unacceptable behavior in a given situation (Resick et al., 2011). No act in itself can be deviant; the people give value assessments. Depending on the social system people belong to, these assessments about the degree of dishonesty may vary to a great extent. In the following sections, firstly as dishonesty is a matter for ethics, I will give etymological insight into the origin of ethics and morals, since often in literature they seem to be used without differentiating one from another; secondly, it will be focused on the many possible ethical theories we might take as our roadmap for assessing the dishonesty of an act within a social system. Then, I will primarily concentrate on behavioral ethics, since it manages to cover the complexity of ethical issues at group and organizational levels, behavioral ethics ‘‘primarily concerned with explaining individual behavior that occurs in the context of larger social prescriptions’’ (Trevin˜o, Weaver, & Reynolds, 2006, p. 952).

Etyomology of Ethics and Morals In order to bring out the function of ethics one should firstly return to the origins of the notion of ethics. As often ethics is seen somehow associated with morals, and sometimes they are even used as synonyms, it is necessary to bring out the historical development of meaning and usage of ethics and morals. The notion of ethics dates back to the ancient Greek philosopher Aristotle, who modified the noun eˆthos (custom) with an adjective which stressed the importance of areteˆ (excellence, virtue). It resulted in forming eˆthikeˆ areteˆ (ethical excellence, ethical virtue), and by time, the first part, eˆthikeˆ was popularized and taken into the practice independently as eˆthikos. The notion of morals originated from Latin (moralis) through the works of Cicero some 300 years after Aristotle’s eˆthikeˆ areteˆ, and was needed for creating a synonym for the Greek notion eˆthos. Ethics, having rooted in the ancient Greek literature, was striving to discover the way of being as oneself and the way of being as oneself among the others — ultimately resulting in questioning how we should treat our parents and children, friends and enemies, our government, and the God. For Aristotle, it is the ultimate task of the human being through his/her activities to create and mold one-self so that the perfection in ethical excellence (eˆthikeˆ areteˆ) could be achieved. (Lill, 1997; Sauve´ Mayer, 2008; Williams, 2009) By perfection Aristotle proposed choosing the middle way between the extremes of possible actions. Aristotle managed to link ethics with practice instead of making it a too idealistic and unreachable field to human beings. According to Aristotle, human behavior should take notice of the gradations of all possible actions and choose the most reasonable one. In this light, lack of bravery would be cowardice and too

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much bravery would refer to daredevilry (Lill, 1997, p. 511). In this sense bravery can only have meaning in ethics through its practical application in real-life situations — how a person would actually behave when faced with a specific threat situation (Lill, 1997, p. 516). Returning to the comparison of ethics and morals, as ethics emerged from the thoughts of Aristotle, who saw ethics as strongly earthly, the principles of ethics and ethical behavior should be governed by the reason and weighted calculations, the notion of morals was shaped by religious (mostly Christian) minds dominating during the Middle Age (Lill, 1997). In the center of ethics is a human being and his/her free will to choose between a spectrum of actions, while in the center of morals are ideals above the individual human being so that human beings could be judged based on the above without taking into an account the context that situations bring on them. In this sense, morals mean dos and don’ts and a person is a mere follower of moral rules (a moral disciple) and behavior patterns expected from him/her. Compared to a society and an individual level, the investigation of organizations through the ethical lens is a new phenomenon, which by modest estimates dates back to the end of the 18th century, when organizations started to become an everyday part of human activities. Nowadays it is impossible to grasp how strongly an individual is connected and influenced by so many organizations through the roles of a student, customer, member, and so on. It is the impact brought by the big scandals in organizations ranging from business to athletic teams, not mentioning the political and religious organizations that have brought out the widespread interest in ethics in organizations (Trevin˜o et al., 2006, p. 951). Following the original function of ethics as brought out by Aristotle, ethics is for and about choosing the balance between the possible spectrum of available actions in a certain situation and environment (i.e., the organization). Already in ancient Greece great minds could notice that ethics is about social phenomena. Without other people around us what use could ethics have? Hence, ethics is for choosing the suitable action within the existing social environment (family, group, organization, society, and so forth). It is very frequently thought that corporate scandals occur because of desperation or greed (Leonard & Elkind, 2005), yet the reality can prove a wider range of reasons. Accepting dishonesty as deviant behavior or as a violation of established norms in a specific environment, Markova and Folger (2012) have further stressed how an act in order to qualify as deviant is dependent not solely on behavior, but also on what is the reaction from others to this behavior. Hence, dishonest behavior always needs a social phenomenon as a yard-stick for its existence. In this case, the perception of our role in social surrounding will come down to morals and the concept of the ‘‘moral self’’ has to be seen as the ‘‘social moral self,’’ which means that whether an individual behaves right or wrong is highly dependent on the actions of those around them (Gino & Galinsky, 2012). Morality with its strong influences from the spheres of religion stresses the importance of following the rules and being a good student, having a suitable character for the social system. Hence, developing a social moral self means following certain pre-set rules of a specific environment or of a group. For example, dishonesty in an organizational context could be defined as deviant behavior (most often lying, shirking, cheating, or

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stealing; see Williamson, 1987) by the employee or a member of an organization that results in a loss for the mentioned organization and to its members, which means that the above-mentioned subjects are not acting up to the expectations that their role demands. Just to repeat an example of nepotism mentioned earlier — morality of and act like hiring one’s own relatives would rely on the social system surrounding the act. Moral codes are about ‘‘acceptable’’ and ‘‘appropriate’’ behavior within a certain environment. Ethics is about the application of morals and its function is to sustain and maintain the social system, morals is about shaping the individual character so that it would best fit the social system. Inevitably the two notions are strongly connected, yet not with same meaning.

Switching Between the Levels of Ethical Reasoning Looking at dishonesty from an organizational context, it should be noted how and to what extent it is possible to base our ethical judgments on traditional ethical approaches. Since the beginning of time, great thinkers have tried to develop the most adequate and accurate tool for systematizing our (ethical) thinking. The idea of making moral questioning as accurate as the accountancy has been the aim of many ethicists throughout the history (Coddington, 1976). Traditionally, ethics tries to answer the question ‘‘how should we act.’’ For this, for centuries ethicists have tried to develop some kind of maxims that could be guiding in our ethical decision-making. In the chapter I will concentrate on utilitarianism, deontology, and virtue ethics as one of the oldest ones that are still widely in use. Utilitarianism is the most dominating form of consequentialism, deontology distances itself from the consequentialist approach by stressing our moral obligation and duty to notice the intrinsic and static quality of actions (e.g., lying is always bad and telling truth should be preferred), whereas virtue ethics concentrates on the subject and her character, not on the agentneutral actions. During last decades the notion of ethics has become popular both in management practice and in scholarly literature, yet not many scholars have approached ethics systematically and through the lens of its philosophical heritance. Albrecht, Thompson, Hoopes, and Rodrigo (2010) have further stressed how, although business ethics has emerged as an academic discipline during the last few decades, still many scholars have noted the great lack of a common definition or a common approach for business ethics. Furthermore, as an addition to the incommensurability of definitions in business ethics, I would also bring out the intense fragmentation in ethical analyses. Organizations as artificially created social realities have endless social interactions, and being prone to the possibility of complex ethical dilemmas, the need for adequate and appropriate use of ethical theories should be acknowledged. As for centuries, ethics has been systematically approached mostly in philosophy and by philosophers, any attempt to transfer ethics into business and management should make notice of aspects that are the basis of any ethical judgment — whether they be the person making the act (his/her character), the consequences of an act, the act

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itself, or all combined. Merely looking at ethics as an abstract and universal notion would make any kind of judgment arbitrary and not valid. For centuries, philosophy of ethics has been focusing on developing a systematic framework for ethical analyses, giving an excellent tool for any specialized field that is interested in the application of ethics in practice. One of the most known streams of ethics bases its assessments on the consequences of actions — utilitarianism. Although by these days ethicists have developed many forms of utilitarianism, still utilitarianism by its original essence proposes a rather simple maxim: one should act so that the act would bring the best consequences possible. The development on an idea of utilitarianism is most strongly attributed to English philosophers John Stuart Mill (1806–1873) and Jeremy Bentham (1748–1832), who proposed to measure the quality of consequences by seeing whether an action maximizes pleasure or pain. Coddington (1976, p. 216) has captured the most authentic and classical version of utilitarianism, which he calls as ‘‘old’’ utilitarianism. According to Coddington, old utilitarianism is based on the reconciliation of two principles: the first one is psychological and the second one is ethical:  

each individual firstly and mostly pursues her/his own happiness; instead of this, individuals ought to pursue the general happiness.

The maxim that utilitarianism proposes is manifested in the second principle. When faced with an ethical dilemma, utilitarianism should choose the action that would bring the greatest good for the greatest number of people. Therefore, utilitarianism assesses actions through looking at the consequences they bring — it is the nature of the consequences that determines whether an action is right or wrong (Coddington, 1976, p. 215). For example, traces of utilitarianism can be often seen in official laws. In fact, Mill and Bentham back in the beginning of the 19th century were mostly showing concern over the downgrading of social practices and nonefficient laws. According to them, laws and practices that do not hold up the system and foster happiness and pleasure of their members should be changed. Deontology rejects utilitarian principle that the moral good is to be maximized (Brook, 1991) and that the foreseeable consequences are the main basis in decisionmaking. Deontological ethics, mostly popularized through the works of a German philosopher Immanuel Kant (1724–1804), is synonymously called duty-based ethics, which bases itself on the notion of duty, takes the moral act as a starting point by stating that an act itself has some intrinsic qualities that make it ‘‘right’’ or ‘‘wrong.’’ Kant event went to find a categorical imperative, which would allow the universalization of the moral law (Froese, 2008). Hence, it would be reasonable to question not even the context that surrounded the mentioned act, nor the agent performing the act. Kant set out for the people themselves to assess, whether their intentions could be imagined to become as a universal law for everyone. Just to illustrate, if I were to consider whether to leave my organization’s taxes unpaid in order to survive the next months financially, I should hypothetically consider whether it would be good if everybody started avoiding taxes if they were in the same state as I am.

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Utilitarian and deontological conceptualizations derive most of their core beliefs at the level of the society — based on the rules and the norms of the society or aiming at bringing effects benefiting largest audience. Virtue-based ethics focuses on the qualities of one’s character, stressing idealistic features that would characterize a truly moral character. Compared to utilitarianism, which strives for the greatest good for the greatest number of people, while giving no absolute intrinsic quality neither to the agent performing the act nor the act itself, and deontology with its teleological essence focusing solely on the act itself, virtue-based ethics takes the individual as its target of any moral assessment — it stresses the development of good character traits as virtues (Arjoon, 2000). Virtue-based ethics sees the person strongly connected to the value of the acts, making him- or herself thereby to me a more or less virtuous character. One might see its maxim to be ‘‘You shall tell me how you act and I will tell how virtuous of a person you are .’’ Yet again, by making the connection between the quality of the individual character and the ethical value of an act so strongly connected, virtue-based ethics loses its ability to give explanations why in some context people behave differently than in others. Compared to rather abstract-level ethical theories like utilitarian, deontological, and virtue-based ethics, behavioral ethics tries to account for the framing effects that surround our moral decision-making. Behavioral ethics acknowledges moral statements to have truth values, yet these values are considered to be valid only for the specific social group involved, thus metaphorically, treating ethics similar to linguistics, where grammaticality and correct usage are important and analytically tractable, yet unique to a specific society of speakers (Gintis, 2009). Behavioral ethicists want to know how individuals actually behave in ethical dilemmas, furthermore, how situational and social forces influence it, and how the decisions behind moral actions could be directed into more ethical direction (Bazerman & Gino, 2012, p. 10). Although the levels of ethical reasoning might seem too strict as categorizations, it should be still acknowledged that they are not absolute. This kind of reasoning shown in Table 1 is most of all needed for structuring the main ethical approaches. Furthermore, in practice it can be often witnessed how intertwined ethical concepts might be. Van Staveren (2007, p. 23) has proved how in an economy, organizations can also function ‘‘only when certain normative requirements are fulfilled,’’ both at formal and nonformal levels (the notions of ‘‘rights,’’ ‘‘dignity,’’ ‘‘equality,’’ and so forth). As an example, the right of female employees to equal wages for equal work implies one’s duty not to discriminate on the basis of gender (van Staveren, 2007, p. 23). Moreover, it is not reasonable to reduce the wages of all employees by 5% instead of firing 5% of employees to save costs, since firing 5% of employees would surely bring greatest good for the greatest number of people as 95% of employees would continue working without salary cuts. The first example belongs to the realms of deontological and the latter to the utilitarian approach. Behavioral ethics might be useful especially in the case of explaining organizational phenomena because it acknowledges the strong social influences of specific groups we belong into. Both ethical decision-making and behavior are never in isolation from framing effects — they have strong influences from the surrounding environment.

y To maximize the utility or happiness. Being agent-neutral, utilitarianism gives everyone`s happiness same count J. S. Mill (1998/1861), J. Bentham (1907), A. Smith (1759/2007)

Source: Composed by the author.

Some of the authors

The end result to be achieved is y

y Produces the most good

Consequences or the effects of an act y Consequences produced

Object of analysis

Morality of an act will be judged on the basis of y Morally right action is the action that y

The greatest good for the greatest number of people

Utilitarian

Deontological

I. Kant (1785, 1788, 1797), T. Nagel (1970), T. Scanlon (2003)

y Some good state of affairs

Aristotle, 350 B.C.E, G.E.M. Anscombe (1958), A. MacIntyre (1985)

M. H. Bazerman and A. E. Tenbrunsel (2011)

y The best result in given situation

y Embraces the virtues of our individual characters y Moral character

y Virtues or the morality of the character

y Produces best results in this situation

y Context

Morality of actions is based on virtuous character

We can only learn about morality when we look how people actually behave in moral context Depends on the context

The moral character

Virtue based

Individual level

Behavioral

Organizational level

Level of ethical reasoning

Morality as a duty or universal rule that ought to be followed no matter what The act itself and the will of the subject y Motives and rules and the reason expressed through human will y Follows the duty and obligation

Society level

Core statement

Aspect of ethical reasoning

Table 1: Three levels of ethical reasoning.

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Coyne and Bartram (2000, p. 44) have also stressed how dishonest behavior is not solely the result of individual characteristics, it is more likely ‘‘a function of both individual differences and organizational factors.’’ Secondly, as utilitarianism and deontology might often seem too distant for the uniqueness of an organization with its specific environment, and virtue ethic strives to set the focus only on individuals, making it therefore hard to notice the complexity of social phenomena, behavioral ethics manages to close the gap in between. In order to make ethical analyses more applicable and closer to organizational realities, in the current chapter the benefits of behavioral ethics will be placed on such an epitome of unethical behavior as dishonesty. Jones (1991), Trevin˜o et al. (2006), Trevin˜o, Weaver, and Reynolds (2007), and Kaptein (2010) have defined unethical behavior as a behavior that violates generally accepted moral norms of behavior. Following this definition, dishonesty as the violation of generally accepted moral norms of behavior can bring severe consequences in the form of not only financial loss, but also losses at the social level — dishonest behavior patterns can ruin the work environment. There are many studies that have shown how an honest person who moves to a dishonest environment would soon also start showing dishonest patterns of behavior. Bazerman and Gino (2012, p. 93) have brought out how it is in fact the environment in which the people operate that activates ‘‘explicit or implicit norms that, in turn, influence the tendency to cross the ethical line.’’ Analyzing dishonesty at an organizational level strongly reflects that dishonesty can therefore manifest in a specific environment, usually referred to as the work environment. It has been proven that the tendency to engage in dishonest acts is deeply associated with situational constraints, whether the participants can rationalize their dishonest behavior or not. As Gino and Ariely (2012) have stated, one could easily reason that other people would also choose dishonesty under the same circumstances or that in rational terms, little cheating would not hurt anyone. Inevitably, surrounded by other people, one might start to mirror other people’s values and perceptions of right and wrong. Gino, Ayal, and Ariely (2009) refer to three possible ways how our unethical behavior can be a result of a mirror effect of other people’s behavior. Firstly, if dishonesty and cheating are witnessed rather often, an individual might change his or her estimate of likelihood of being caught by cheating (see also Provan & Skinner, 1989). Secondly, when observing an act of dishonesty, a person might reflect on his or her value systems and take deeper attention to generally accepted moral standards in the society. Instead, as a result, a risk of turning to activities of dishonesty might decrease. Thirdly, the influence from observing dishonest acts in a certain context can easily change a person’s understanding of social norms, also referred to as social learning. Social learning is especially relevant in the cases when we face situations with a great degree of ambiguity about the acceptable ways of behaving, making it therefore easy to understand why people would look to others and reflect on their behavior in order to understand the prevailing norms (Gino & Galinsky, 2012). As an illustrative example, Gino et al. (2009) refer to an experiment done by Cialdini, Reno, and Kallgren (1990), where they artificially asked some people to litter in front of others in a public space and observed how this influenced the behavior of other

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people. As a result, individuals who saw the place littered started themselves to litter remarkably more. Psychologists Hartshorne and May (1928, p. 411) have proved through a series of experiments and tests that honesty and dishonesty are not unique character traits, but rather ‘‘specific functions of life situations.’’ Thus it is clear that the influence brought by the need for social approval will depend on networks around an individual. When dishonest behavior is accepted by informal group norms, then it has been shown to be promoting stealing by restaurant workers (Hawkins, 1984) and nurses (Dabney, 1995), but furthermore, feelings of unfairness and job dissatisfaction have been proven to relate to an increase in absenteeism in fast food restaurant employees (Hollinger, Slora, & Terris, 1992) and theft in factory employees (Greenberg, 1990). Individuals strive for social approval starting from the smallest to the broadest spheres of belonging. It will also mean that our ethical reasoning will also widen to a more abstract level as we move toward the society level. Hence, ethical reasoning behind our acts has to accommodate to the expectations of the social group we belong to. Similarly, in business, applied ethics takes up certain patterns of business conduct ‘‘that are accepted as good within the particular environment where they are applied’’ (Arthur, 1984, p. 322). Saks and Krupat (1988) have stressed how our interactions with other individuals or groups help us to learn which attitudes and beliefs are to be followed. Moreover, they stated that if a conflict occurs as a result of acting contrarily to the widely expected behavior, then it can lead to the need for self-correction to regain social approval (Sims, 2007, p. 40). The need for self-correction has its roots in cognitive dissonance or cognitive disharmony, which is the state of holding conflicting cognitions, and results in discomfort or tension that brings intense need for an alternation in one of the conflicting cognitions. Just to systematize the impact of social inflation and the need for social approval somehow, Cialdini (2007) managed to show two kinds of social norms that make us to reach for the social approval from the people around us. Firstly, injunctive social norms refer to one’s perception of what the others believe to be a morally relevant behavior in the given situation, and secondly, descriptive social norms refer to one’s perception of what others actually do in a given situation. The first of these social norms relies on moral evaluation, while the second on observation and social information. Injunctive social norms, which make us to evaluate given situations in the light of morally right and wrong, can be interpreted as an individual’s cost– benefit calculation, where he or she will assess whether the costs (most of all the possible costs regarding the loss in reputation) from deviant behavior would make up the gains. Descriptive social norms will give the individual assuring social information either to proceed or not with the deviant behavior — ‘‘if others do it, why should not I do it?’’ The most evident example of this would be deviant behaviors conducted by groups of people — individuals who would not engage in the dishonest acts by themselves are often willing to do so as a part of the group (Kahan, 1997). Cialdini (2007, p. 264) stresses how too often people tend to underestimate the great extent to which their actions in a given situation in fact are determined by the similar actions of others. Acknowledging the existence of this kind of a social control in organizational informal control mechanisms can say a lot about the nature and emergence of deviant

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behaviors like dishonesty. In fact, individuals usually do not go for deviant behavior isolation — for example, individuals are much more likely to commit dishonest acts more freely when they perceive that others also do it, or when dishonest acting is widespread (Kahan, 1997).

A Cost–Benefit Analysis: Internal and External Benchmarks The environment or the context which surrounds our ethical decision-making often combines the nature of the act itself (deontology), the foreseeable consequences of an act (utilitarianism), and the person committing the act (virtue ethics), making a person a decision-maker to be oriented on the cost–benefit analysis. In its essence, already Thomas Hobbes and Adam Smith have stressed the standard economic model of rational and selfish human behavior, which is ultimately based on the idea that people carry out dishonest acts consciously by making trade-offs between the expected external benefits and the costs of the dishonest act (Allingham & Sandmo, 1972; Becker, 1968; Mazar, Amir, & Ariely, 2008). As an illustration, a person may consider three aspects before engaging into a dishonest act like tax evasion: the expected financial reward, the probability of getting caught, and the perception of the punishment if caught. Mazar et al. (2008) have stressed how in the case of deciding whether to act dishonestly, we face at least two kinds of inputs — external and internal. External inputs refer to the inputs that maximize individual interests. For example, in the case of potential financial gains, a person has to decide whether it is more useful to cheat and gain financially or if the costs of cheating (for instance, fines, criminal punishment, and so forth) are proportionally higher than in the case of behaving honestly. Internal inputs are constituted as a part of the socialization process where norms and values of the specific society or the group are internalized by a person, serving as ‘‘an internal benchmark’’ against which the person evaluates his or her behavior (Mazar et al., 2008). Here socialization could be defined as ‘‘an ongoing process by which people come to adopt the attitudes, behaviors, and ways of seeing the world that are held by the groups to which they belong and relate’’ (Saks & Krupat, 1988, p. 125) (Figure 1). Cressey (1973) developed three elements of the fraud triangle, which can also be easily broadened to a larger scale of unethical acts like dishonesty: pressure, rationalization, and opportunity. The pressure or the motivation for a dishonest act can come from different sources. One of the most obvious of them would be greed. The rationalization of dishonest acts precedes deviant behavior. Just to bring a reallife illustration, Wang and Kleiner (2005, p. 17) have brought out some of the most common examples of employee rationale behind theft:    

I am underpaid and I am taking only what I deserve. Everybody does it; besides, they can write it off. The company makes a large profit, and I deserve some of it. The company angered me and I got back at it.

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Informal norms and values of the society and groups

Formal norms and values of the society and groups

Internal inputs or benchmarks

External inputs or benchmarks

The cost-benefit calculation over the potential gains and losses of dishonest acts at the social and the individual level

The cost-benefit calculation over the potential gains and losses of dishonest acts at the rational and the objective level

For example, is hiring your underqualified nephew instead of a qualified outsider perceived as ethical or not in a group or a society?

For instance, legal punishment, the probability of being caught versus the potential financial rewards

Figure 1: Decision-making behind (dis)honest acts. Source: Composed by the author.

Furthermore, Beck and Willis (1993, p. 52) held a survey of 277 face-to-face interviews with employees from electrical retail stores in UK. The results showed that the most common reason why people steal from their employer is having an opportunity (see Figure 2). The most worrying fact behind employee stealing is that their main motivator for stealing is having opportunities for, and not the financial need; furthermore, the management is seen as setting an example that stealing is a normal activity in a working environment (Wang & Kleiner, 2005). One of the elements benefiting the occurrence of deception and dishonesty while analyzing the element of opportunity is the asymmetry of information. In fact, deception will happen only when work behavior is unmonitored (Grover, 1993, p. 487). Hence people who are more intensively monitored have less opportunity to deceit. But as Grover (1993, p. 488) has brought out, most of the monitoring is done at lower hierarchies of power, leaving managers and professionals rarely to be observed directly. Then again, biggest scandals in media usually emerge among employees with a higher status. It may be useful here to reflect to a notion of social control, which in social groups is supposed to inhibit deviant behavior (Sykes & Matza, 1957). These findings are further backed by Vadi and Jaakson (2011) in their study about the dual value of honesty among Russians living in selected former Soviet countries. These authors found that societal influence prevails over cultural influence when assessing the importance of honesty, and furthermore, as their study showed, the value ‘‘honesty’’ is socially constructed, making it therefore easily manipulated by the surrounding (social) environment. In this case, when employees feel strong social connections to

(Dis)Honesty in Organizations: Ethical Perspectives 10.3

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Temptation/opportunity (94)

1.8 2.2

Need money (73)

3.3

34.6

Greed (46)

4.1

Pressure from others (11) Poor pay (9) Thrill of excitement (5) 16.9

Get back at the company Other (28) 26.8

Figure 2: Estimates of why the firm’s staff steals, per cent (the numbers of responses are in brackets). Source: Based on Beck and Willis (1993, p. 52). the organizations they belong to, there might be less probability of acting dishonestly. As seen from the retail store example, employees clearly have declared the mentality and reality of ‘‘us’’ versus ‘‘them’’ (the managers), hence distracting themselves from the organization. As a result, the need for social approval at the organizational level is brought to a minimum. Therefore, the working environment and the membership to the organization can be among the triggers that influence our moral judgments and possible deviant behavior. Axiological judgments that help to differentiate an honest act from a dishonest one are under the influence of many aspects. Mostly, moral judgments have been associated with age and education level (Rest, Thoma, Moon, & Getz, 1986), but more importantly it is the working environment that strongly manages to shape our moral judgments (Lampe & Finn, 1992). Just to bring some examples, Ponemon (1989) found that the power hierarchy in organizations can give strong deviance in moral judgments — he proved that managers and partners in public accounting firms tend to get lower moral reasoning scores compared to those at the lower organizational levels in the firm. But more generally, Weber (1990) has brought out how moral reasoning and judgments tend to be lower when individuals are to face work-related dilemmas compared to nonwork-related dilemmas. This is strongly associated with the rationalization of one’s behavior when caught in unethical behavior — the same act in a nonwork environment could be judged differently when in the working environment.

Discussion and Conclusions The function of ethics is to maintain the social system. The function of morals is to shape the individual character so that it would fit the social system in the most

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appropriate way. For example, the notion of business ethics gives us a rather broad understanding what kind of behaviors are acceptable and needed for maintaining the spheres of business, while morals and moral codes furthermore focus on molding individual characters so that they would be acceptable within the business world. A number of important conclusions can be drawn from this chapter. First, methodologically, despite the fact that ethics is becoming a more and more relevant research object at an organizational level, a large amount of studies have been published mostly without differentiating between the ontological standpoints of ethical approaches taken as baselines when assessing ethical judgments. Inevitably, assessing organizations at an individual or society level, one can result making errors in ethical judgments. Much of the prior work has focused on certain ethical phenomena in organizations (for instance, sexual harassment, discrimination, or corruption) without creating the levels of ethical approaches that lie under our ethical judgments. By specifying between the ethical approaches, one can see how complex environment organizational arrangements are for ethical analyses. It makes a great difference what kind of ethical theory we take as our basis for making judgments in the organizational context. All widely used ethical theories come with their distinct ontological assumptions, hence making strong implications on any kind of axiological assessment. From the three most widely used ethical theories, utilitarianism focuses on the effects or impacts of the actions, deontological ethics on the actions and behaviour of the agents, and virtue ethics on who the agents are (Kaptein, 2010, p. 602). Secondly, in the case of organizational spheres, we often cannot make clear distinctions of the mentioned approaches, which is the reason why ethicists studying organizations have started to develop behavioral ethics. Behavioral ethics manages to bring in the contextual influences and combine the effects of an act, the act itself, and the person behind the act. Also, when investigating dishonesty in organizations, we should be aware what exactly and when we are judging — is it the harmful consequences of a dishonest act, the act itself, or the person committing the act, and would our judgments change when the context changes. Compared to traditional ethical theories, behavioral ethics has been attractive especially because of its applicability and ability to reach the complexity of the social interactions within organizations. Thirdly, as dishonesty can be defined as a deviant behavior in a social system (organization), we should make notice of the triggers of why people cross the ethical line accepted in this system. According to Bazerman and Gino (2012), it is the norms activated by the surrounding environment that usually result in the tendency to cross the ethical line. In many ways, organizations are like human societies, adopting normative behavioral patterns and acknowledging sanctions following deviant behaviors, where appropriate conduct will be introduced through both formal and informal mechanisms (Markova & Folger, 2012). Especially for the practitioners, the current chapter managed to imply the strong social pressure that the working environment can bring and our ‘‘moral self’’ inside the organizational context might transfer itself to the ‘‘social moral self.’’ For a manager it would be beneficial to understand to what extent their employees define themselves in terms of their

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relationships to others (Brewer & Gardner, 1996) so that the first traces of acting dishonestly inside the organizations would not have a snowball effect on fellow employees.

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Nagel, T. (1970). The possibility of altruism. Oxford: Oxford University Press. Ponemon, L. (1989). Ethical judgments in accounting: A cognitive-developmental perspective. Critical Perspectives on Accounting, 1, 191–215. Provan, K. G., & Skinner, S. J. (1989). Interorganizational dependence and control as predictors of opportunism in dealer-supplier relations. The Academy of Management Journal, 32, 202–212. Resick, C. J., Martin, G. S., Keating, M. A., Dickson, M. W., Kwan, H. K., & Peng, C. (2011). What ethical leadership means to me: Asian, American, and European perspectives. Journal of Business Ethics, 101, 435–457. Rest, J., Thoma, S. J., Moon, Y. L., & Getz, I. (1986). Different cultures, sexes, and religions. In J. Rest (Ed.), Moral development: Advances in research and theory (pp. 89–132). New York, NY: Praeger. Saks, M. J., & Krupat, E. (1988). Social psychology and its applications. New York, NY: Harper & Row. Sauve´ Mayer, S. (2008). Ancient ethics: A critical introduction. New York, NY: Routledge. Scanlon, T. M. (2003). The difficulty of tolerance: Essays in political philosophy. Cambridge: Cambridge University Press. Scott, E. D., & Jehn, K. A. (2003). Multiple stakeholder judgments of employee behaviors: A contingent prototype model of dishonesty. Journal of Business Ethics, 46, 235–250. Sims, R. L. (2007). Collective versus individualist national cultures: Comparing Taiwan and U.S. employee attitudes toward unethical business practices. Business Society, 48, 39–59. Smith, A. (2007/1759). The theory of moral sentiments. New York, NY: Cosimo Inc. (Original work published in 1759). Sykes, G. M., & Matza, D. (1957). Techniques of neutralization: A theory of delinquency. American Sociological Review, 22, 664–670. Trevin˜o, L. K., Weaver, G. R., & Reynolds, S. J. (2006). Behavioral ethics in organizations: A review. Journal of Management, 32, 951–990. Trevin˜o, L. K., Weaver, G. R., & Reynolds, S. J. (2007). Behavioral ethics: A review. Journal of Management, 32, 951–990. Vadi, M., & Jaakson, K. (2011). The dual value of honesty among Russians in selected former Soviet countries. Cross Cultural Management: An International Journal, 18, 55–70. van Staveren, I. (2007). Beyond utilitarianism and deontology: Ethics in economics. Review of Political Economy, 19, 21–35. Wang, Y., & Kleiner, B. H. (2005). Defining employee dishonesty. Management Research News, 28, 11–22. Weber, J. (1990). Managers’ moral reasoning: Assessing their responses to three moral dilemmas. Human Relations, 43, 687–702. Williams, J. D. (2009). An introduction to classical rhetoric: Essential readings. Chichester: Blackwell Publishing. Williamson, O. E. (1987). The economic institutions of capitalism: Firms, markets, relational contracting. New York, NY: Free Press.

Chapter 3

Honesty and Trust: Integrating the Values of Individuals, Organizations, and the Society Anneli Kaasa and Eve Parts

Abstract Purpose — The purpose of this chapter is to assess empirically the levels of trust across the world and to explore possible differences in the levels of trust among different groups of respondents. Design/methodology/approach — We analyze the individual-level data from 81 countries around the world using latest available European Values Study (EVS) and World Values Survey (WVS) datasets (most data refer to the year 2008). Methodologically, we compose three trust indicators using confirmatory factor analysis and then compare the level of trust in different groups. After that we calculate country-level means of trust indicators and use these as inputs in cluster analysis. Findings — The results of our empirical analysis show that the level of trust among supervisors do not differ significantly from the overall level of trust in a society, supporting the hypothesis that honesty and trust tend to be contagious. Still, there are statistically significant differences in trust levels between almost all explored population groups which were composed on the basis of previous theoretical and empirical literature. Limitations — Our analysis covered only selected socio-economic determinants of trust. It would be reasonable to add some contextual or systemic factors at the level of nation (like GDP per capita, quality of formal institutions, society’s polarization, or others) into further analysis.

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 37–58 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010007

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Originality/value — Our analysis distinguishes between three different types of trust which are studied both at individual and national level. Also, differences between age groups and educational groups, men and women, religious and non-religious persons are examined. Finally, we compare the levels of trust of those supervising someone with the average trust levels in the society as a whole. Keywords: Honesty; general trust; institutional trust; trustworthiness

Introduction Honesty and integrity are among the key values in management and leadership. In everyday business, both honesty and integrity are necessary ingredients for developing trust, which in turn can be considered as a key element in establishing credibility (Clemmer, 2001). Credibility is strongly related to one’s ability to influence others and provide strong leadership. In more general terms, trust is the basis for all successful relationships the manager or leader sustains, including those with customers, employees, community and stockholders (Heathfield, 2012). When trust exists in an organization or in the society as a whole, almost everything else is easier to achieve because of lower transaction costs. Scholarly interest in the study of honesty and trust in organizations has grown remarkably since the beginning of the 1990s along with expanding research on social capital. Since then but, to some extent, also much earlier, several authors have described different forms of trust along with types of benefits of trust at the level of individuals (for instance, Hardin, 1993; Uslaner, 2002), organizations (for example, Adler & Kwon, 2002; Kramer, 1999; Kramer & Tyler, 1996; Leana & Van Buren, 1999) and society (for instance, Cook, 2001; Fukuyama, 1995, 2000; Misztal, 1996). When studying values, one serious problem is related to their measurement. How can we measure honesty or trust? As people tend to be reluctant to report that they could act dishonestly or that they approve dishonest behavior, more indirect measurement methods need to be implemented. In the related literature, different measures of trust are often used as proxies for the value ‘‘honesty.’’ This is to say that in order to explore the ‘true’ level of honesty and integrity, one should look at how much people trust others, or how trustworthy they expect others to be. The logic behind this approach is well explained by Clemmer (2001): Since we see the world as we are, any feelings that people are basically dishonest and can’t be trusted may be revealing more about me than them. One of the hazards of lying is not just that people wouldn’t believe us, it’s also that we can’t believe anyone else.

The purpose of the current chapter is to assess empirically the levels of trust across the world and to explore possible differences in the levels of trust among different population groups. It starts from a literature overview on studies about trust and honesty at the level of individuals, organizations, and societies. It first highlights the importance of trust and honesty in the performance of organizations, then describes

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the benefits and bases of trust within organizations, and finally presents a broader overview of different types of trust and their possible sources in the context of social capital literature. Our empirical analysis is based on the trust data which are available in the most recent datasets of the World Values Survey (WVS, 2009) and European Values Study (see EVS, 2010). When measuring trust, we distinguish between general trust, institutional trust, and trustworthiness. Individual-level comparisons of the levels of trust between different population groups — men and women, younger and older people, more and less educated, and others — give information about the possible sociodemographic determinants of trust. Also, we compare the levels of trust of those supervising someone with the average trust levels in the society as a whole, in order to test a theoretical hypothesis that both trust and honesty tend to be contagious, so higher level of trust in the society as a whole is expected to associate with higher trust in organizations, and also vice versa.

Theoretical Background The importance of honesty and trust in management is straightforward and theoretically well explained through traditional principal-agent problem. In the interaction between firms and employees, both parties have potential joint gains from delegating certain actions by trusting the agent. In particular, the firm has an interest in high-productivity workforce with little shirking and low monitoring costs (Rigdon, 2009, p. 94). Therefore, honesty and trustworthiness are among the fundamental values that employers seek in the employees whom they hire. At the same time, there is a natural tendency of agents to reciprocate trusting behavior of principals. Such mutual benefits from trust are widely discussed in the context of organizational social capital, the concept which can be defined as ‘‘a resource that reflects the character of social relations within the organization’’ (Leana & Van Buren, 1999, p. 538). This resource is realized through collective goal orientation and shared trust, which create value by facilitating successful collective action. More specifically, Kramer (1999, p. 582) generalizes on the basis of social capital literature that the benefits of trust include ‘‘its constructive effects on reducing transaction costs within organizations, increasing spontaneous sociability among organizational members, and facilitating appropriate forms of deference to organizational authorities.’’ Given that there are important benefits of trust within organizations (for more detailed overview, see Kramer, 1999, pp. 582–586), an important issue is how to create trust. The existing literature focuses on the design of reciprocity norms, procedures, and stability employment practices as primary mechanisms by which trust is fostered or discouraged within organizations. More recently, the concept of ethical leadership has emerged that emphasizes the importance of moral management which aims to influence the behavior of others by explicitly setting ethical standards and keeping employees accountable for these standards using rewards and discipline (Brown, Trevin˜o, & Harrison, 2005; Pastoriza & Arin˜o, forthcoming). As an example,

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Pastoriza, Arin˜o, & Ricart (2008) have explored the impact of ethical managerial behavior on the development of employees’ associability and identification-based trust with the firm. They suggest that a manager’s behavior should be based on three principles: following exemplary behavior, helping the employees to value the consequences of their actions in other persons, and not betraying their employees’ trust (p. 329). Further, not top managers but also bottom-level managers (that is, supervisors) are believed more likely to serve as ethical role models who influence employee behaviors because they occupy a more visible position and work more closely with bottom-level employees (Brown et al., 2005; Walumbwa et al., 2011). Next we take a broader look at the concept of trust in order to create a comprehensive knowledge of its essence and influencers. The concept of trust1 is nowadays most widely explored in the social capital literature. The earlier researchers of social capital (see, for instance, Bourdieu, 1980; Coleman, 1988; Putnam, Leonardi, & Nanetti, 1993) mostly used a general term ‘interpersonal trust’, which refers to the trust between two or more persons and is not directly related to the notions of generalized trust, which became later the basis of social capital. In subsequent literature, numerous definitions and typologies of trust have been developed. The wider explanatory basis for trust is the need in a complex society for individuals to rely on rules that are accepted by many people and that guide both interpersonal and impersonal exchanges — the institutions. Sociologists have explained trust as the foundation of conventions, expectations, and shared values that enable societies to renew themselves across generations (Streeten, 2002, p. 10). Yamagishi and Yamagishi (1994) refer to trust as ‘‘assurance,’’ an expectation of benign behavior derived from knowledge of the incentive structure facing one’s trading partner. In a similar way, Zaheer, McEvily, and Perrone (1998) frame the concept of trust as an expectation of a partner’s reliability with regard to his/her obligations, predictability of behavior, and fairness in actions and negotiations while faced with the possibility to behave opportunistically. As it can be seen from different definitions, it is not clear at all that people mean the same thing when talking about trust. The literature distinguishes between at least five types of trust which differ in relation to what trust is, how it can be generated, and to which extent it expands to include various circles of people. Figure 1 summarizes different types of trust along the trust continuum, starting from narrow personal trust (on the right-hand side) up to abstract moral trust (on the lefthand side). The vertical dimension of the figure distinguishes between trust in persons and informal groups (the upper part) and trust in informal institution and their representatives (the lower part of the figure). Personalized trust or strategic trust varies according to the person, situation, conditions, and arena. It is important to know personally the person who is trusted. This approach relies on a rational perspective — trust is a calculation of future cooperation (Hardin, 1993, Williamson, 1993). It does not remove the element of uncertainty from cooperation, implying the importance of contract and assurance.

1

For more detailed overview of the trust literature, see, for example, Nooteboom (2002).

Honesty and Trust Generalized trust

Moral trust

Knowledgebased trust

Assurance, particularized trust

Personalized or strategic trust

Total faith in others (Infant trust, blind trust)

Trust in social system

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General institutional trust

Trust in public officials

Total certainty about others (Perfectly enforceable contracts)

Figure 1: The trust continuum. Source: Based on r Stolle, 2004 and Misztal, 1996.

Particularized trust is based mainly on identification and categorization (Tajfel, 1974; Tajfel & Turner, 1979). People trust those to whom they feel close: for instance, in terms of behavioral similarity, socio-economic status, geographical proximity, frequency of interaction, or common fate (Brewer, 1981; Kramer & Tyler, 1996). This is similar to the concept of knowledge-based trust which refers to the fact that the behavior of the other person is predictable because one knows the other either from his/her own experience or through reputation effects arising in networks (Beugelsdijk & Schaik, 2005). Moral trust is based on underlying values that people share and its development depends heavily on parental upbringing. As such, trust is a stable trait which exists generally regardless of the context, of the other person, and even regardless of prior experiences (Uslaner, 2002). Similar with moral trust is generalized trust or social trust which also assumes abstract trust to unknown members of the society. It is all-inclusive like moral trust, but contrasts the former in two aspects: it is context dependent and influenced by personal and collective experiences (Levi, 1996, 1999). Generalized trust indicates the potential readiness of citizens to cooperate with each other and the abstract preparedness to engage in civic endeavors with each other (Rothstein & Stolle, 2002). At the society level, generalized trust is based on the society’s ethical habits and the moral norm of reciprocity (Fukuyama, 2001). Generalized trust is often opposed to special trust or institutional trust. These types of trust are also called horizontal and vertical trust, respectively. Institutional trust includes trust in social system (Hayoz & Sergeyev, 2003; Luhmann, 1988) and toward public institutions, positions and officers (Hardin, 1998). Rothstein and Stolle (2003) have developed an institutional theory of generalized trust, which states that citizens draw distinctions between various institutions along at least two dimensions: they expect representatives of political, legal, and social institutions to function as their agents, and they expect impartiality and an unbiased approach from order institutions (see Figure 2). Based on these assumptions, the authors distinguish between the confidence in the institutions on the representational (parties, parliament,

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Anneli Kaasa and Eve Parts Structure of everyday bureaucracies

Effectiveness

Fairness and bias

Determines the effectiveness of state institutions to punish those who violate rules

Determines whether institutions function in an impartial way or not

Trust in institutions Trust in institutional effectiveness

Experiences of safety or insecurity with others

Attitudinal extensions to everyone else

Trust in institutional fairness

Actual behavioral influence on fellow citizens

Actual experience of discrimination or fair treatment

Generalized trust in other people

Figure 2: Causal mechanisms between institutions, institutional trust, and generalized trust. Source: Based on r Rothstein & Stolle, 2002, p. 29.

cabinets) side and implementation side of the political system, the latter being especially important in generating institutional trust (Rothstein & Stolle, 2003, pp. 142, 143). Figure 2 also specifies four causal mechanisms from impartial, unbiased, and uncorrupt institutions to generalized trust. Taken together, trust in institutions determines how citizens experience feelings of safety and protection, how citizens make inferences from the system and public officials to other citizens, how citizens observe the behavior of fellow citizens, and how they experience discrimination against themselves or close others (Rothstein & Stolle, 2002, p. 27). Based on the above explanations, we can divide the determinants of trust into two broad categories: 



The psychological and socio-economic characteristics of individuals such as personal income and education, family and social status, values and personal experiences, which determine the incentive of individuals to invest in social capital Contextual or systemic factors at the level of the community/nation, such as the overall level of development, quality and fairness of formal institutions, distribution of resources and society’s polarization, and prior patterns of cooperation and trust

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When coming back to the level of organizations and firms, there is strong support to the argument that trust is contagious, meaning that higher level of trust in the society as a whole associates with a higher level of trust among all categories of citizens, including managers and employees. As such, we can use the above, more general knowledge about trust also as a basis for the following empirical analysis which aims to assess the differences in the level of trust both among groups of individuals and countries.

Data and Methodology Data were drawn from the European Values Study (EVS, 2010) (45 countries), which were complemented with the data about 36 countries obtained from the World Values Survey (WVS, 2009). Altogether data from 81 countries around the world were analyzed. These two surveys are very closely connected and stand on very similar methodological grounds. Many questions asked in these surveys coincide and that enabled to integrate the data from these two databases. Both surveys are multicountry surveys that are repeated every nine years and cover an increasing number of countries. Here, the data from the latest waves were used: for most countries the indicators pertain to the year 2008. It should be pointed out that in the WVS dataset data were given for Great Britain and Northern Ireland separately, instead of the United Kingdom. However, as the population of Northern Ireland is only about 3 per cent of the population of the United Kingdom, here, for technical reasons, the data of Great Britain were used at the country level as a proxy for the data of the United Kingdom. About 1500 respondents were interviewed in every country (in some countries this number was also smaller or larger: for countries analyzed here the number of respondents ranged from 808 for Iceland to 3051 for Egypt). Data from the WVS and the EVS datasets were integrated into one file in order to perform individual-level analysis (including, in total, 125,118 observations at the individual level). In order to describe the concept of trust in a way which reflects its relations with the value ‘‘honesty,’’ three types of trust were distinguished. First, general trust was described by the statement that people can be trusted (survey question ‘‘Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?’’; answers on scale 1 ¼ ‘‘most people can be trusted’’, 2 ¼ ‘‘cannot be too careful’’). Second, institutional trust was described by four variables describing confidence in the following institutions: the government, parliament, justice system, and political parties. The selection of institutions was based on the theoretical assumption that the fairness and impartiality of political and legal institutions are especially important in generating institutional trust (Rothstein & Stolle, 2003). Third, the acceptance of social norms was covered by four indicators that reflected how much the respondent justifies the following actions: claiming state benefits, accepting a bribe, cheating on taxes, and avoiding a fare on public transport

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(measurement scale: 1 ¼ ‘‘never justifiable y 10 ¼ ‘‘always justifiable’’). As explained in the theoretical part of the chapter, indicators of norm acceptance can be interpreted as a proxy for the trustworthiness of the respondent. The selected four statements describe best the expected behavior of the respondent in the situations where dishonest behavior would pay off in terms of economic benefits. For institutional trust and trustworthiness, in order to capture the information of initial indicators into variables of institutional trust and trustworthiness, a confirmatory factor analysis (the principal components method) was performed in both cases. As there were some missing values in the dataset, here and hereafter, the cases were excluded pairwise, not listwise, in order to utilize all the information available. The results of the factor analysis are presented in Tables 1 and 2. The percentages of total variance explained by the factors indicate good explanation power and Kaiser-Meyer-Olkin (KMO) measures indicate the appropriateness of the factor models (values of the KMO measure larger than 0.5 are usually considered as acceptable). All factor loadings are equal to or above 0.74. Next, the factor scores of latent variables were saved as variables for use in the further analysis. Additionally, the indicator of trustworthiness was inverted to get trustworthiness and not the opposite. The factors obtained from the factor analysis are standardized (mean value equal to 0 and standard deviation equal to 1).

Table 1: Results of the confirmatory factor analysis of institutional trust. Indicator

Factor loadings

Confidence in: parliament Confidence in: the government Confidence in: the political parties Confidence in: justice system Variance explained (%) KMO measure of sampling adequacy

0.86 0.85 0.82 0.75 67.27 0.81

Source: Authors’ calculations.

Table 2: Results of the confirmatory factor analysis of trustworthiness. Indicator Justifiable: cheating on taxes Justifiable: avoiding a fare on public transport Justifiable: claiming state benefits Justifiable: someone accepting a bribe Variance explained (%) KMO measure of sampling adequacy Source: Authors’ calculations.

Factor loadings 0.80 0.75 0.75 0.74 57.49 0.77

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In order to provide better comparability, the indicator of general trust was also standardized. As a result, in case of all indicators of trust higher values refer to higher level of trust.

Discussion of the Results In the first part of the empirical analysis, the possible differences in trust levels between different socio-demographic groups were examined. Based on the overview of the theoretical and empirical literature about the determinants of trust at the individual level, the respondents were divided into separate groups by age, gender, education, and religiosity. As our data were measured on an ordinal scale, the Kruskall–Wallis Test was used as a nonparametric test equivalent to the one-way ANOVA and an extension of the Mann–Whitney Test to allow the comparison of more than two independent groups. Table 3 presents the mean values of general trust, institutional trust, and trustworthiness for different groups and concludes the results of the Kruskall–Wallis test. From Table 3 it can be seen that in case of general trust and trustworthiness, there are statistically significant differences between all sub-groups. However, institutional trust is not influenced by educational levels. Regarding the effect of age on institutional trust, there are differences only between people younger and older than 50 but not between younger are groups themselves. In general, men have more general trust and higher trustworthiness as compared to women, but the opposite holds in the case of institutional trust. Higher education and lower religiosity associate also with higher trust levels, while the relations between trust and age are quite mixed and probably non-linear. In order to compare the trust levels of people in managerial positions with overall trust in the society, all respondents were additionally divided into two groups: those who supervise someone and those who do not.2 Unfortunately, the question about supervising was not asked in Uruguay, Colombia, New Zealand, Iraq, Guatemala, and Hong Kong, so these countries were omitted from the respective parts of the analysis. Results presented in the end of Table 3 reveal that supervisors have a significantly higher level of general trust but at the same time a lower level of institutional trust compared to those who do not supervise anyone. Trustworthiness of the supervisors is also higher as compared to the reference group, but this difference is not statistically significant. The results support the assumption that trusting and trustworthy persons are more likely good managers or supervisors (that is, they have probably gained their position because of these traits). 2

WVS (2009) contains also a question about the profession/job of the respondent that distinguishes between 18 categories of jobs, including employers and managers of the establishments with different number of employed. Unfortunately, these data were available only for very few countries and could be not used in the current analysis. However, dividing respondents in a more detailed way along their profession and managerial or supervisory tasks could give very interesting information for the country-level analysis (in case of countries for which these data are available).

Source: Authors’ calculations. a Here and hereafter significance means p-value under 0.05.

Supervising someone

Religious person

Not a religious person Religious person Kruskall–Wallis test: Not supervising Supervising Kruskall–Wallis test:

Women Men Kruskall–Wallis test: Below tertiary education With tertiary education Kruskall–Wallis test:

Sex

Tertiary education

Age group 15–29 Age group 30–49 Age group 50 and more Kruskall–Wallis test:

Age

0.161 0.064 Significant difference 0.015 0.136 Significant difference

0.009 0.010 Significant difference 0.065 0.238 Significant difference

0.087 0.004 0.063 Significanta differences between all three age groups

General trust 0.015 0.008 0.020 Two younger age groups do not differ significantly from each other (p-value 0.82), but both differ significantly from the oldest age group 0.008 0.009 Significant difference 0.007 0.022 No significant difference (p-value 0.17) .042 .025 Significant difference 0.008 0.026 Significant difference

Institutional trust

Table 3: Mean values and the results of the Kruskall–Wallis test concerning different groups.

.157 .055 Significant difference 0.013 0.024 No significant difference (p-value 0.21)

0.026 0.031 Significant difference 0.006 0.026 Significant difference

0.109 0.034 0.093 Significant differences between all three age groups

Trustworthiness

46 Anneli Kaasa and Eve Parts

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Next, the country-level trust indicators were obtained by aggregating individuallevel data using the database-provided weights in order to ensure that the data would be representative of the demographic structure of a country. Data for all respondents as well as those who supervise someone were aggregated. Mean levels of standardized indicators of general trust, institutional trust, and trustworthiness (norms) for all countries (both for all respondents and for supervising respondents) are presented in Appendix 1. In Figures 3–5, the mean levels of trust of supervisors (vertical axes) are compared with trust levels of all respondents (horizontal axes). The following conclusions can be drawn based on Figures 3–5. First, there are no remarkable differences between trust levels of supervisors as compared to trust levels of all respondents. Still, it seems that average levels of general trust are slightly higher among supervisors, so aggregate data confirm our similar earlier finding at individual level. At the same time, supervisors tend to have a slightly lower level of trustworthiness, and this result is an opposite to what we found at the individual level. When summarizing the above results one can suggest that in most countries the level of trust of supervisors is more or less similar with the overall level of trust in the society. This result can again be interpreted as a contagiousness of trust — there could be certain transmission mechanisms that guarantee the spread of trust from the aggregate level to the organizational and individual level — and/or vice versa. This suggestion is supported by the results of national-level correlation analysis which are

Figure 3: Comparison of the levels of general trust between supervisors and all respondents. Source: Compiled by the authors.

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Figure 4: Comparison of the levels of institutional trust between supervisors and all respondents. Source: Compiled by the authors. presented in Table 4. The practical value of this outcome is the possibility to use country mean data for describing the level of trust among managers when the latter is not directly measured. Next, cluster analysis was used in order to identify groups of countries that could have similar patterns of trust. However, as the distribution of countries in Figures 3–5 was rather mixed, no very clear or easily interpretable results were expected. Cluster analysis was performed separately with average trust levels of supervisors and all respondents in each country. In both cases, we obtained three clusters which were quite similar regarding the average trust levels and country composition (see Table 5). Countries belonging to Cluster 1 are characterized by the highest general trust, and below average (but not the lowest) levels of institutional trust and trustworthiness. This cluster included initially 16 countries — mainly highly developed Western European and North American countries, but also some countries from Asia and Oceania (Australia, Thailand, Indonesia) and from the Caucasus and Eastern Europe (Azerbaijan, Belarus). Cluster 2 contains countries with the highest institutional trust but the lowest level of trustworthiness, combined with a below average level of general trust. This cluster is most populous (43 countries from the total sample and 46 countries from the sample of supervisors) and includes the majority of the Central and Eastern European transition countries, Southern American countries, and also

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Figure 5: Comparison of the levels of trustworthiness between supervisors and all respondents. Source: Compiled by the authors.

some African countries. Trust pattern in this cluster could be possibly related to the remains of transition and/or former communist legacy. Finally, Cluster 3 is characterized by close to average levels of all trust indicators (general and institutional trust are slightly above the average and trustworthiness is slightly below the average). Despite its smallness (16 versus 12 countries, respectively), the heterogeneity of this cluster is the most difficult to explain, concerning the size and location as well as the development level of the countries. From Table 5 we can see that most countries group into the same cluster independently on whether we use the sub-sample of supervisors or that of all respondents. However, there are some exceptions from this general pattern. When looking at clusters based only on the respondents who are supervising, the following changes can be noticed compared to the initial clusters based on the total sample: 



The United States and Japan have moved from Cluster 1 to Cluster 2, indicating that in these countries the level of general trust is relatively lower among supervisors. Germany, the United Kingdom, and Belgium have moved from Cluster 2 to Cluster 1, meaning that in these countries the level of general trust is relatively higher among supervisors.

General trust Institutional trust Trust worthiness General trust Institutional trust Trust worthiness

Notes: Country level data, N ¼ 75. Source: Authors’ calculations. * Correlation is significant at the 0.05 level (two-tailed). ** Correlation is significant at the 0.01 level (two-tailed).

Based on respondents supervising

Based on all respondents

1.00

General trust

Trust worthiness 0.05 0.05 1.00

Institutional trust 0.33** 1.00

Based on all respondents

Table 4: Correlations between average trust levels of supervisors and all respondents.

0.98** .29* 0.05 1.00

General trust

0.38** .97** 0.00 0.35** 1.00

Institutional trust

0.09 0.04 0.95** 0.11 0.02 1.00

Trust worthiness

Based on respondents supervising

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Table 5: Results of the cluster analysis. Trust indicator General trust Institutional trust Trustworthiness Number of countries

Based on all respondents

Based on respondents supervising

Cluster 1 Cluster 2 Cluster 3 0.523 0.140 0.124 16

0.180 0.300 0.638 43

0.149 0.070 0.128 16

Cluster 1

Cluster 2

Cluster 3

0.621 0.108 0.066 17

0.166 0.255 0.754 46

0.163 0.008 0.140 12

List of countries in the initial clusters (based on all respondents): 

Cluster 1: United Statesa, Canada, Japana, Australia, Thailand, Indonesia, Denmark, Finland, Iceland, Ireland, Netherlands, Norway, Sweden, Switzerland, Azerbaijan, Belarus



Cluster 2: Mexico, Argentina, South Korea, Brazil, Chile, Taiwan, Peru, Iran, Bulgaria, Trinidad and Tobago, Burkina Faso, Ethiopia, Rwanda, Zambia, Croatia, Czech Republic, Estonia, France, Georgia, Germanyb, Greece, Hungary, Italy, Latvia, Lithuania, Moldova, Montenegro, Poland, Portugal, Romania, Russia, Serbia, Slovak Republic, Slovenia, Spain, Ukraine, Macedonia, United Kingdomb, Albania, Austria, Armenia, Belgiumb, Bosnia Herzegovina



Cluster 3: India, China, South Africac, Ghana, Vietnam, Egypt, Moroccoc, Jordan, Andorra, Malaysia, Mali, Cyprus, Luxembourg, Maltac, Turkeyc, Kosovo

Notes: Clusters based on respondents supervising differ from initial clusters in the following: a

United States and Japan have moved from Cluster 1 to Cluster 2.

b

Germany, United Kingdom, and Belgium have moved from Cluster 2 to Cluster 1.

c

Malta, Morocco, Turkey, and South Africa have moved from Cluster 3 to Cluster 2.

Source: Authors’ calculations.



Malta, Morocco, Turkey, and South Africa have moved from Cluster 3 to Cluster 2, which could be interpreted that supervisors in these countries are on average less trusting and less trustworthy compared to the overall population.

When summarizing the results of the cluster analysis, we can see that supervisors are rather similar to the overall population in terms of trust. On the other hand, the distribution of countries into different clusters is quite confusing and needs future investigation, incorporating possible national-level economic, political, and cultural determinants of trust into the analysis.

Conclusions and Future Research Suggestions This chapter focused on the values ‘‘honesty’’ and ‘‘trust,’’ their essence and importance in the society in general and in organizational studies particularly. In theory, the most widely recognized benefits of trust associate with increasing cooperation and lower transaction costs. Among different types of trust, generalized trust is considered to be the most important for realizing mutual benefits for individuals, organizations, and societies.

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The main purpose of the chapter was to empirically explore the levels of trust across the world and to assess possible differences in the levels of trust among different population groups — men and women, older and younger persons, those with higher education and others, religious and non-religious persons, respondents who supervise someone and those who do not. We analyzed the individual-level data from 81 countries around the world using latest available EVS and WVS datasets (most data refer to the year 2008). When measuring trust, we distinguished between general trust, institutional trust, and trustworthiness, the latter reflecting acceptance of common norms in the society. Methodologically, we composed three trust indicators using confirmatory factor analysis and then compared the level of trust in different groups. Also, country-level means of trust indicators were calculated and used as inputs in the cluster analysis. The results of the empirical analysis showed that there were statistically significant differences in trust levels between almost all explored population groups which were composed on the basis of previous theoretical and empirical literature. At the same time, the level of trust among supervisors did not differ significantly from the overall level of trust in the society, supporting the hypothesis that honesty and trust tend to be contagious. Consequently, increasing trust in organizations could result in higher trust levels in the society as a whole. Generating trust in organizations, in turn, depends on the honesty and trustworthiness of managers. The opposite holds also — one could expect that higher general trust and especially institutional trust in the society promotes the formation of trust and cooperation in organizations. In this respect, the quality and reliability of formal institutions has utmost importance. The main limitation of the chapter was that only selected socio-economic determinants of trust were analyzed, which did not explain all differences between countries and population groups. Regarding the further research, it would be reasonable to supplement the analysis with additional national-level factors of trust, such as the overall level of development, quality and fairness of formal institutions, distribution of resources and the society’s polarization, and prior patterns of cooperation and trust.

Acknowledgments This work was supported by the Estonian Ministry of Education (target funding No. SF0180037s08) and the European Community’s Seventh Framework Programme (grant agreement No. 266834).

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1534 1003 1002 1500 1505 1421 1510 1500 1509 1512 1500 1500 1534 2164 1000 2015 3025 1525 1821 1000 1507 3051

All 54 374 176 190 146 850 333 259 328 75 214 172 180 436 254 309 n.a. 255 282 190 460 307

Supervising

Number of respondents

0.38 0.16 0.24 0.16 0.39 0.46 0.20 0.38 0.16 0.02 0.41 0.22 0.29 0.32 0.34 0.55 0.29 0.18 0.06 0.41 1.08 0.21

All 0.26 0.12 0.28 0.12 0.24 0.51 0.30 0.38 0.30 0.23 0.42 0.15 0.34 0.50 0.32 0.73 n.a. 0.04 0.09 0.49 1.18 0.29

Supervising

Trust

0.41 n.a. 0.62 0.11 0.71 0.01 0.18 0.29 0.11 0.39 0.27 0.89 0.03 0.06 0.33 1.30 0.28 0.72 0.48 0.36 0.58 n.a.

All 0.05 n.a. 0.74 0.09 0.41 0.01 0.17 0.34 0.04 0.50 0.40 0.96 0.06 0.02 0.29 1.23 n.a. 0.65 0.56 0.28 0.62 n.a.

Supervising

Institutional trust

0.32 0.11 0.48 0.06 0.35 0.08 0.01 0.73 0.19 0.24 0.23 0.15 0.12 0.04 0.29 0.03 n.a. 0.01 0.39 0.00 0.18 0.24

All

0.57 0.18 0.53 0.00 0.16 0.07 0.03 0.52 0.19 0.19 0.13 0.27 0.23 0.02 0.22 0.10 n.a. 0.15 0.31 0.22 0.16 0.35

Supervising

Trustworthiness

Mean values of trust, institutional trust, and trustworthiness by countries (all and those who supervise someone).

Albania Andorra Argentina Armenia Azerbaijan Australia Austria Belarus Belgium Bosnia Herzegovina Brazil Bulgaria Burkina Faso Canada Chile China Colombia Croatia Czech Republic Cyprus Denmark Egypt

Country

Table A.1:

Appendix 1

Honesty and Trust 55

Estonia Ethiopia Finland France Georgia Germany Ghana Greece Guatemala Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Italy Japan Jordan Kosovo Latvia Lithuania Luxembourg

Country

Table A.1: (Continued )

1518 1500 1134 1501 1500 2075 1534 1500 1000 1252 1513 808 2001 2015 2667 2701 1013 1519 1096 1200 1601 1506 1500 1610

All 276 281 131 499 199 504 315 135 n.a. n.a. 277 249 591 440 352 n.a. 142 258 491 360 106 299 182 363

Supervising

Number of respondents

0.11 0.07 0.83 0.01 0.13 0.25 0.43 0.14 0.27 0.30 0.15 0.53 0.10 0.33 0.38 0.29 0.25 0.07 0.26 0.08 0.37 0.05 0.05 0.08

All 0.18 0.09 0.92 0.02 0.14 0.36 0.39 0.00 n.a. n.a. 0.06 0.57 0.07 0.39 0.31 n.a. 0.40 0.28 0.21 0.09 0.34 0.06 0.05 0.15

Supervising

Trust

0.22 0.20 0.03 0.08 0.14 0.22 0.58 0.32 n.a. n.a. 0.52 0.04 0.65 0.16 0.19 n.a. 0.04 0.34 0.05 0.86 0.66 0.47 0.43 0.47

All 0.22 0.18 0.05 0.09 0.26 0.13 0.67 0.36 n.a. n.a. 0.58 0.02 0.80 0.11 0.08 n.a. 0.04 0.28 0.07 0.71 0.39 0.56 0.43 0.47

Supervising

Institutional trust

0.16 0.12 0.07 0.25 0.27 0.16 0.05 0.16 0.11 0.29 0.15 0.05 0.01 0.31 0.07 n.a. 0.18 0.03 0.15 0.55 0.50 0.34 0.49 0.00

All

0.26 0.06 0.02 0.23 0.28 0.03 0.09 0.07 n.a. n.a. 0.14 0.12 0.02 0.27 0.05 n.a. 0.27 0.15 0.12 0.56 0.54 0.23 0.42 0.06

Supervising

Trustworthiness

56 Anneli Kaasa and Eve Parts

Macedonia Malaysia Mali Malta Mexico Moldova Montenegro Morocco Netherlands New Zealand Norway Peru Poland Portugal Romania Russia Rwanda Serbia Slovak Republic Slovenia South Africa South Korea Spain Sweden Switzerland Taiwan Thailand Trinidad and Tobago Turkey Ukraine

1500 1201 1534 1500 1560 1551 1516 1200 1554 954 1090 1500 1510 1553 1489 1504 1507 1512 1509 1366 2988 1200 1500 1187 1272 1227 1534 1002 2384 1507

164 299 201 238 310 161 242 209 479 n.a. 334 285 159 167 151 241 181 205 196 293 544 288 173 147 403 361 993 195 85 284 0.17 0.42 0.23 0.13 0.27 0.34 0.06 0.33 0.76 0.53 1.06 0.47 0.00 0.23 0.22 0.05 0.51 0.35 0.34 0.08 0.23 0.06 0.15 0.96 0.62 0.08 0.31 0.53 0.37 0.03

0.28 0.37 0.24 0.02 0.06 0.37 0.03 0.32 0.89 n.a. 1.13 0.41 0.05 0.24 0.27 0.13 0.54 0.23 0.27 0.03 0.20 0.01 0.25 1.16 0.70 0.05 0.41 0.54 0.33 0.03

0.03 0.79 0.51 0.25 0.28 0.18 0.19 0.24 0.13 0.06 0.38 0.86 0.47 0.25 0.39 0.00 n.a. 0.71 0.00 0.02 0.51 0.07 0.10 0.28 0.38 0.47 0.17 0.36 0.32 0.73

0.05 0.67 0.45 0.17 0.26 0.20 0.20 0.22 0.20 n.a. 0.42 0.83 0.43 0.13 0.35 0.02 n.a. 0.78 0.12 0.01 0.10 0.15 0.11 0.45 0.46 0.52 0.20 0.39 0.08 0.71 0.38 0.79 0.23 0.36 0.02 0.01 0.17 0.29 0.03 0.09 0.19 n.a. 0.28 0.07 0.02 0.07 0.60 0.26 0.45 0.05 0.09 0.18 0.03 0.17 0.24 0.16 1.46 0.09 0.39 0.11

0.47 0.95 0.16 0.21 0.10 0.04 0.27 0.14 0.06 n.a. 0.12 n.a. 0.18 0.04 0.13 0.03 0.48 0.18 0.52 0.07 0.01 0.22 0.04 0.37 0.24 0.12 1.39 0.23 0.36 0.15

Honesty and Trust 57

Source: Authors’ calculations.

United Kingdom Uruguay United States Vietnam Zambia

Country

Table A.1: (Continued )

1561 1000 1249 1495 1500

All 381 n.a. 276 234 208

Supervising

Number of respondents

0.28 0.02 0.27 0.55 0.36

All 0.49 n.a. 0.33 0.55 0.35

Supervising

Trust

0.33 0.17 0.06 1.90 0.08

All 0.23 n.a. 0.09 1.87 0.23

Supervising

Institutional trust

0.11 0.14 0.13 0.32 0.47

All

0.01 n.a. 0.08 0.35 0.13

Supervising

Trustworthiness

58 Anneli Kaasa and Eve Parts

PART II (DIS)HONESTY IN PUBLIC SECTOR AND FINANCIAL MANAGEMENT

Chapter 4

The Banking Crisis in Iceland: Did the Government Pretend That Facts from Reality Were Other Than They Were? Hilmar –o´r Hilmarsson

Abstract Purpose — Analyze and assess the actions taken by the government of Iceland prior to a banking crisis that resulted in the collapse of Iceland’s largest banks in October 2008. Was the government’s behavior prior to the crisis dishonest in the sense that it deliberately tried to fake reality or was the government honest but incompetent in the sense that it did not see the problem coming, and was therefore not trustworthy? Design/methodology/approach — Review of the existing literature, analysis, and assessment of this literature. Case study of Iceland. Findings — The government showed negligence and made mistakes by not taking credible actions to manage risks following a rapid cross-border expansion of Iceland’s largest banks. This had severe consequences and resulted in the collapse of the largest banks in October 2008. Instead of addressing the problems in the economy the government launched a PR campaign and the analysis of various scholars may have helped to justify inaction. According to the Special Investigation Commission (SIC),1 the government did not address an obvious problem and could perhaps on that basis be charged with dishonesty, including faking reality with PR campaigns. As some

1

The Special Investigation Commission (SIC) delivered its report to Althingi (the Icelandic Parliament) on April 12, 2010. The SIC was established by Act No. 142/2008 by Althingi in December 2008 to investigate and analyze the processes leading to the collapse of the three main banks in Iceland. Members of the Commission were Supreme Court Judge, Mr. Pa´ll Hreinsson, Parliamentary Ombudsman of Iceland, Mr. Tryggvi Gunnarsson, and Mrs. Sigrı´ jur Benediktsdo´ttir, Ph.D., lecturer and associate chair at Yale University, USA.

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 61–84 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010008

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scholars put it, the authorities gambled for resurrection, and failed. The analysis carried out by a number of other scholars who downplayed the problem may have confused the government and it may have been honest in its inaction. In that situation one can argue that the government was honest but incompetent and not trustworthy, as according to the SIC and several international scholars the problem was obvious. Research limitations/implications — This is a case study. The study does not present results that can be evaluated on the basis of statistical significance and generalized. Some of the lessons, however, can have a wider relevance than for Iceland only. This is especially true for small countries with a large banking sector, using its own currency, and with limited fiscal space to support the banks during a crisis. Practical implications — The combination of a risk seeking behavior of businesses, in this case in the banking sector, and inactive or negligent governments can result in the collapse of a country’s economy. The Icelandic government should encourage and enforce more risk mitigation via regulations, monitoring, and supervision of the private sector’s cross-border activities. This does not only apply to the banking sector but also to other sectors such as the energy sector. Social implications — Less risk seeking behavior and more risk mitigating actions can stabilize Iceland´s economic growth in the medium and long term, and reduce the risk of an economic collapse that typically has severe social consequences. Originality/value — The so-called Viking spirit of Icelandic business people accompanied with aggressive risk taking and bold business behavior can be very detrimental for a small economy especially when global economic and financial crisis hit. Keywords: Economic and financial crisis; economic policy; international expansion of firms; risk management; honesty

Introduction According to Wade (2009, p. 6), ‘‘in 2007 average income in Iceland was almost $70,000, 1.6 times that in the United States.’’ The global crisis that started in the fall 2008 hit the Icelandic economy hard. During this crisis its three largest banks (Glitnir (formerly Islandsbanki), Kaupthing (formerly Bunadarbanki), and Landsbanki)2 all collapsed with severe consequences for the economy and the people: in 2008 the Krona declined nearly 51 per cent against the dollar while the OMX 15 Iceland stock

2 The three banks accounted for about 85 per cent of Iceland’s financial system. According to Wade (2009, p. 6), their assets ‘‘had risen to almost nine times GDP’’ while Jackson (2010, p. 101) stated that they had ‘‘total assets of more than $168 billion, or 14 times Iceland’s GDP.’’

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index dropped by 93 per cent compared to its highest value in 2007 (White, 2011) and ‘‘general government debt increased from 28 per cent of GDP in 2007 to over 96 per cent of GDP in 2010’’ (Thorhallsson & Kirby, 2012, p. 805). In February 2009, Iceland’s GDP per capita was only 80 per cent of the level of the United States (Wade, 2009). According to Sigurjonsson and Mixa (2011, p. 2010), ‘‘Iceland experienced the worst financial collapse of any Western country.’’ Prior to the crisis Iceland had experienced strong economic growth and unprecedented expansion in cross-border investments and activities, especially in the financial sector; thus, this was a considerable shock for the country. During a crisis of this magnitude the government has an important role to play, including taking actions to interfere with developments that can be dangerous for the stability in the economy and an imminent threat for the welfare of the nation. This includes taking actions if developments in a particular sector, such as the financial sector, make the economy extremely vulnerable. This chapter will focus on the behavior of top government officials while an aggressive cross-border banking expansion was ongoing. It aims at replying the following questions3:    

Did the government take appropriate action when the banks expanded with investments and operations overseas? Was inaction a problem? Can the government’s behavior in any way be classified as dishonest? Is it possible that the government was honest but incompetent and therefore not trustworthy?

In this chapter, the main focus is on government officials — the cabinet ministers responsible for the banking system including the prime minister, the minister of finance, and the minister of business affairs. The role of the president of Iceland, who traditionally has been a symbolic and a ceremonial figure in the government, is also discussed. Other officials are also mentioned including the governors of the Central Bank of Iceland as well the director of the Financial Supervisory Authority. All those officials are mentioned in the report of the Special Investigation Commission (SIC) of the Parliament. After this brief introduction the chapter will be organized into the following sections: (i) methodology, (ii) definitions and some theoretical considerations, (iii) the expansion of the banking sector in Iceland, (iv) what did experts say about the health of the Icelandic banks before and after their collapse in October 2008 (where the banks solvent after all?), (v) how did the government react to concerns and criticism about the banking system prior to the crisis, (vi) the SIC and its report to the Parliament, (vii) the president of Iceland and the expansion of the Icelandic banks, (viii) discussions, and (ix) conclusions.

3

As Russell (2012) has already discussed in detail, the arguments of Iceland, United Kingdom, and the Netherlands on compensation after the collapse of Icesave, this topic will not be discussed in this chapter.

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Methodology The methodology used in the chapter is the case study method. Compared to other research methods, a case study enables the researcher to study complex phenomena and examine the issues at hand more in-depth (Eisenhardt, 1989). According to Yin (2009, pp. 101, 102), there are six sources of evidence that are most commonly used in conducting case studies. Those are documentation, archival records, interviews, direct observations, participant-observation, and physical artifacts. Each of these sources has advantages and disadvantages and according to Yin one should ‘‘note that no single source has a complete advantage over all the others. In fact, the various sources are highly complementary, and a good case study will therefore want to use as many sources as possible’’ (Yin, 2009, p. 101). Among the sources of evidence used for the analysis in this chapter are documentation/secondary data, including reports and scholarly literature, articles, and books. The author also exchanged e-mails with various scholars in the field of economics, political science, public administration, and philosophy/ethics. These communications when referred to are documented in footnotes. Direct observation also plays a role in this chapter as the author draws on his experience and observations prior to and during the crisis. However, preference was given to using well-documented evidence that is publicly available and listed in the references. In addition to scholarly articles the study refers to reports prepared by recognized Icelandic and international scholars. It is likely that more scholarly journal articles will appear on this topic in the future than are currently available, but this remains to be seen. This case study does not present results that can be evaluated on the basis of statistical significance and one should be careful in generalizing findings of one case study on another case or situation. However, some lessons from the study can have a wider relevance than for Iceland only. This is especially true for small countries with a large banking sector, using their own currency, and with limited fiscal space to support the banks during a crisis.

Definitions, Some Theoretical Considerations, and Research Questions The word ‘‘honesty’’ is sometimes mentioned in the economics, political science, and public administration literature, but the author has so far not found a definition of what exactly is meant by honesty in these fields. Contact was made with economists, public administration specialists, political scientists, and lawyers without finding a definition of what honesty means in those professions. A literature review in these fields also did not yield a definition. Several reports and scholarly articles reviewed mentioned the term ‘‘honesty,’’ but without providing a definition. For example, a key report on the sources of sustained economic growth — the ‘‘Growth Report — Strategies for Sustained Growth and Inclusive Development’’ — mentions honesty as important in the public sector and one can find sentences like ‘‘A culture of honest

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public service must be fostered and maintained’’ and ‘‘But stable, honest, and effective government is critical in the long run’’ (International Bank for Reconstruction and Development/The World Bank, 2008, pp. 4, 5). Still, there is no definition what honesty is, and in fact, the commission that included two Nobel Prize winning economists as well as many other internationally recognized scholars and policy makers never defined what honesty is.4 This seems to be a common problem that the word ‘‘honesty’’ is used without specifying its exact meaning. The Report of the Special Investigation Commission (SIC) established by the Icelandic Parliament to investigate and analyze the processes leading to the collapse of the three main banks in Iceland mentions honesty. One can, for example, find a quote like ‘‘honesty is the best policy,’’ but honesty is never defined. Furthermore, the working group on ethics under the SIC did not make any judgment as to whether or not government officials showed dishonesty in their work prior to the banking crisis.5 In this chapter honesty6 is defined with Ayn Rand’s discussion of honesty in mind. Rand’s honesty is the refusal to pretend that facts from reality are other than they are. According to Rand, one should not fake reality for others or oneself. Rand states that the virtue of honesty is that ‘‘one must never attempt to fake reality in any manner’’ (Rand, 1961). Honesty ‘‘is the recognition of the fact that you cannot fake existence’’ and ‘‘is the recognition of the fact that the unreal is unreal and can have no value’’ (Rand, n.d.). In other words what is not so is not so. Things must be understood for what they are. Tara Smith devotes a chapter on honesty in her outstanding book Ayn Rand’s Normative Ethics — The Virtuous Egoist. According to Professor Smith, faking ‘‘refers to familiar forms of pretending that things are other than they are, such as deliberately omitting pertinent information about a subject, covering something up, or twisting one’s account of a situation to foster misleading impressions’’7 (Smith, 2006, p. 76). And she goes on to note: ‘‘Misrepresenting facts does not change them. However successful one might fool another person, faking is ultimately futile’’ (Smith, 2006, p. 105). Pretending that things are other than they are does not make them other than they are. As Tara Smith notes, ‘‘Dishonesty can sometimes fool other people, but it cannot fool reality’’ (Smith, 2006, p. 81). ‘‘Facing reality is in a person’s 4

According to an e-mail from Professor Danny Lepziger, Commission Vice Chair, sent to the author of this chapter received on August 13, 2012. 5 According to an e-mail from Professor Vilhja´lmur A´rnasson to the author of this chapter received on July 27, 2012. Professor A´rnasson was the leader of a special three-person working group on ethics that was mandated in the Special Investigation Commission legislation by Al“ingi. 6 When searching for a definition of honesty the author of this chapter was in contact with Professor Tara A. Smith who recommended Ayn Rand’s discussion of honesty in Galt’s speech, as well as in her essay ‘‘The Objectivist Ethics,’’ which is in The Virtue of Selfishness. For fuller elaboration, see Leonard Peikoff’s discussion of honesty in Objectivism: The Philosophy of Ayn Rand, pages 267–276. Professor Smith also devotes a chapter to honesty in her book Ayn Rand’s Normative Ethics: The Virtuous Egoist. E-mail received from Professor Smith on September 17, 2012. 7 Tara Smith (2006, p. 77) also refers to Peikoff’s Objectivism when he explains that ‘‘If rationality, as we may say, is the commitment to reality, then honesty is its obverse: it is the rejection of unreality. The exponent of the first acknowledges that existence exists; of the second, that only existence exists’’ (Peikoff, 1991, p. 268).

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interest, even when certain aspects of reality are threatening, because it allows him to proceed rationally — realistically — and thus with the change of overcoming threatsy.’’ (Smith, 2006, p. 105). In addition to Rand’s definition of honesty, and Smith’s discussion, the following statement from Susan Rose-Ackerman is also used in this chapter: ‘‘Honesty is an important substantive value with close connection to trust. Honesty implies both truth-telling and responsible behavior that seeks to abide by the rules. One may trust another person to behave honestly, but honesty is not identical to trustworthiness. A person may be honest but incompetent and so not worth of trust’’ (Rose-Ackerman, 2001, p. 526). Ayn Rand’s definition and Rose-Ackerman’s observation triggered the following research questions: 



Was the behavior of top government officials prior to the crisis in Iceland dishonest in the sense that they pretended that facts from reality where other than they were? Did they try to convince the nation and the international community that Icelandic economy was not facing imminent danger even if they knew that a collapse of the banking system was likely? If they were honest and thought that the banking system would survive, was it because they were incompetent and did not see the danger? Were they honest but incompetent and thus not trustworthy?

The Extraordinary Expansion of the Banking Sector Prior to the Crisis Prior to the global economic and financial crisis that started in October 2008, the Icelandic banks had grown extraordinarily. According to the IMF the consolidated assets of the three main Icelandic banks increased from 100 per cent of GDP in 2004 to 923 per cent at the end 2007, reflecting expansion overseas. By the end of 2007, almost 50 per cent of the three banks’ assets were held abroad (IMF, 2008, p. 11) Such growth was consistent with the country’s global focus; moreover, banks expanded to Europe, Asia, and America to serve their Icelandic customers whose businesses had expanded abroad (Centonze, 2011) and low taxes also quickened their foreign expansion (Benediktsdottir, Danielsson, & Zoega, 2011; Centonze, 2011). Benediktsdottir et al. (2011, p. 224) also stated: ‘‘The banking system of Iceland was sold to political cronies at the turn of the century and the authorities subsequently changed the laws and regulations to facilitate the rapid expansion of the banks.’’ The access to global debt finance markets was among the key driving forces behind this growth. The big three banks also enjoyed high credit ratings inherited from Iceland’s sovereign debt rating at that time. According to the SIC, these banks issued around 14 billion EUR in foreign debt securities markets, during 2005, a little over the GDP of Iceland that year. Most of the funding matured in only 3–5 years. Refinancing risk was thus imminent (SIC, 2010a).

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In the beginning of 2006, during the so called ‘‘mini crisis,’’8 international debt funding dried up temporarily. Once the liquidity crisis started in 2007, foreign deposits and short-term securitized funding became the main source of funding for the three banks. Such short-term funding was sensitive to market conditions and thus risky (SIC, 2010a). According to the SIC, other countries with relatively large financial systems manage to avoid disastrous banking outcomes, since, unlike Iceland, those nations have long experience and proven ability to supervise large, international banks. Their accumulated reputation for careful prudential supervision therefore offsets their inability to provide fully reliable lender of last resort protection, at least to some extent. But in Iceland the Financial Supervisory Authority (FME)9 was in general understaffed and lacked experience,10 the Central Bank of Iceland’s (CBI) foreign currency reserve was low, and the deposit insurance fund was underfunded (SIC, 2010a). How could the above happen in a high-income developed country like Iceland? How could Iceland move from privatization of state-owned banks to exploding banking sector and then to a collapse?

What did the Experts Say about the Viability of the Icelandic Banking Sector before and after their Collapse? A number of experts, local and international, commented on the viability of the Icelandic banking system as well as on the soundness of the government’s macroeconomic policies both prior to the banks’ collapse (including after the so-called mini crisis in 2006) as well as after their collapse in October 2008 (see, for example, Aliber, 2008; Buiter & Sibert, 2008a, 2008b; Danielsson & Zoega, 2009; Danske Bank, 2006; Eggertsson & Herbertsson, 2009; Flannery, 2009; Herbertsson & Mishkin, 2006; Ja¨nna¨ri, 2009; Portes, 2008; Portes & Baldursson, 2007). It is especially interesting to recall the remarks made prior to the collapse as they may have influenced government action, or inaction. It is also interesting to review some comments made after the collapse to see what lessons may have been learned from this catastrophic event. The next two sections will focus on some of the analysis done and statements made.

Opinions Prior to the Collapse of the Banks in October 2008 Danske Bank issued a critical report in 2006 highlighting some of the macroeconomic imbalances in Iceland. ‘‘Based on the macro data alone, we think the economy is heading for a recession in 2006–7. GDP could probably dip 5–10 per cent in the 8

See Bergsman (2011). The Financial Supervisory Authority in Iceland is a regulatory organization charged with the task of supervising financial enterprises, referred to as regulated entities (see further http://en.fme.is/about-fme/). 10 Benediktsdottir et al. (2011) also stressed this problem. 9

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next 2 years, and inflation is likely to spike above 10 per cent as the ISK depreciates markedly’’ and ‘‘we see a substantial risk of a financial crisis developing as an integral part of an Icelandic recession in 2006–7.’’ (Danske Bank, 2006). Iceland is a former colony of Denmark and large investments had recently been made there by Icelandic companies and any negative comments from Copenhagen were likely to be taken with some suspicion in Reykjavı´ k. Talking about a possible financial crisis during a time period that many people experienced as a boom was not likely to be taken too seriously in Iceland. Nevertheless Icelandic business interests and cabinet ministers responded with assistance from individuals in the academia. An international PR campaign was launched to present a favorable view of the Icelandic banks and point to a strong government that balanced its fiscal budget and carried only small debts on its books. The Iceland Chamber of Commerce commissioned well-known and respected Icelandic economists who joined forces with distinguished and internationally known foreign colleagues who together painted a favorable picture of Iceland’s banking system and its economy. In 2006 Herbertsson and Mishkin issued a report titled ‘‘Financial Stability in Iceland’’ (Herbertsson & Mishkin, 2006) and in 2007 Portes and Baldursson issued a report titled ‘‘The Internationalization of Iceland’s Financial Sector’’ (Portes & Baldursson, 2007). The title of the Herbertsson and Mishkin report is especially ironic given what happened in 2008, and in fact Mishkin was accused in the famous movie Inside Job11 to have changed the title of the paper on his CV into Financial Instability in Iceland, a label more in line with what subsequently happened. The Herbertsson and Mishkin report painted a picture of a stable and strong financial system in Iceland. According to the report, Iceland was ‘‘an advanced country with excellent institutions (low corruption, rule of law, high education, and freedom of the press). In addition, its financial regulation and supervision is considered to be of high quality. Iceland also has a strong fiscal position that is far superior to what is seen in the United States, Japan, and Europe’’ (Herbertsson & Mishkin, 2006, p. 8). According to the report there are three traditional routes to financial instability that have manifested themselves in recent financial crises: (1) financial liberalization with weak prudential regulation and supervision,12 (2) severe fiscal imbalances,13 and (3) imprudent monetary policy. None of these routes were said to describe the current situation in Iceland (Herbertsson & Mishkin, 2006, p. 8). So politicians and business leaders in Iceland did not have much to worry about according to the report and the government could well use these results to justify inaction during a time when it should have taken drastic measures to insist on downsizing the banking sector and stabilize the economy, including a very large current account deficit. The Portes and Baldursson report came out in 2007 and again a nice picture was painted of the state of affairs in Iceland. According to the report, ‘‘Icelandic banks come out well in a comparison 11

In the movie Inside Job, Mishkin is said to have received US$124,000 for his contribution to the report; see http://www.youtube.com/watch?v=5msVl3oZl4U. 12 Benediktsdottir et al. (2011), Centonze (2011), Jackson (2010), and Vaiman, Sigurjonsson, and Davı´ dsson (2011) also stressed this aspect. 13 Pe´tursson and O´lafsson (2010) also pointed to this problem.

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with their Nordic peers — and their overall and core profitability is higher’’ (Portes & Baldursson, 2007, p. 3). Furthermore, according to the report, ‘‘Overall, the internationalisation of the Icelandic financial sector is a remarkable success story that the markets should better acknowledge’’ (Portes & Baldursson, 2007, p. 3). Here Icelandic banks outperform other Nordic banks so Icelanders have every reason to be proud of large banking system that is unlikely to turn into a violent monster and the markets should do a better job in appreciating this ‘‘remarkable success story.’’ At that time, this idea seemed to occupy the minds of many politicians who seemed to think that foreign critics were insufficiently informed about the Icelandic way and needed more education to understand the realities in Iceland. In fact, according to Portes and Baldursson, ‘‘The ‘mini-crisis’ of 2006 was an informational crisis, arising from external criticisms of the banks’ reliance on market funding with short maturities, questions of earnings quality, cross ownership, and lack of transparency, as well as perceived macroeconomic imbalances in the Icelandic economy’’ (Portes & Baldursson, 2007, p. 1). According to these two authors, Danske bank and other critics where thus misinformed and unappreciative of the Icelandic success. Not every report was positive and well-known economists pointed out weaknesses in the financial system and the Icelandic economy. Warnings did thus not only come from Danske Bank in 2006. Among the scholars who expressed concern was Robert Z. Aliber of the University of Chicago Business School who presented a paper at the University of Iceland in May 2008 (Aliber, 2008). Anne Sibert of Birkbeck College and Willem Buiter of the London School of Economics, who were commissioned by the Landsbanki to write a report about the Icelandic banking system in early 2008 (Buiter & Sibert, 2008b), also expressed concern about the situation in Iceland. Aliber was very critical of the Bank’s expansion as well as the overall economic situation in Iceland. Icelandic bankers were still at the time of Aliber’s visit seen as national heroes in Iceland and often linked to the Vikings and their golden age. Aliber could not help joking in his lecture: ‘‘And the Icelandic banks may have a compensating advantage in the form of the ‘Viking spirit’, although it is not clear how this plays out in the Norway and Denmark and Sweden’’ (Aliber, 2008, p. 22). According to Aliber, ‘‘The increase in asset prices and household wealth in Iceland between 2002 and 2007 was larger in percentage terms than the comparable increases in most other countries. The likelihood that Iceland is likely to remain immune from the market forces that are leading to declines in the price of real estate and increases in the costs of capital in the United States, Britain, and other countries seems low’’ (Aliber, 2008, p. 23). In a meeting with the then prime minister, Aliber urged the government to split each of the Icelandic banks into separate domestic retail banks and foreign investment banks (Rannso´knarnefnd Al“ingis, 2010, p. 226). After the meeting the prime minister commented, ‘‘He (Aliber) did not talk the whole thing down as he did in his lecture, he was just a nice, old man on a visit.’’14 The prime minister did not take an international expert like Aliber seriously and preferred to

14

‘‘[H]ann var ekkert aj tala “etta allt nijur eins og hann gerji svo ı´ ræju sinni, hann var bara huggulegur, gamall kall sem var aj koma “arna.’’ (Rannso´knarsky´rsla Al“ingis, 2010, bindi 8, p. 226).

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chat about common friends at Brandeis University where Aliber had taught and from where the prime minister had graduated. In the beginning of 2008 Buiter and Sibert were asked by one of the three big banks, Landsbanki, to write a paper on the causes of the financial problems faced by Iceland and its banks, and on the available policy options for the banks and the Icelandic authorities (Buiter & Sibert, 2008a). In April 2008 they submitted a paper titled ‘‘The Icelandic Banking Crisis and What to Do about It: The Lender of Last Resort Theory of Optimal Currency Areas.’’ In July 2008, they presented a slightly updated version of the paper in Reykjavı´ k before an audience of economists from the central bank, the ministry of finance, the private sector and the academic community. In April and July 2008, the ‘‘Icelandic interlocutors considered our paper to be too market-sensitive to be put in the public domain and we agreed to keep it confidential’’ (Buiter & Sibert, 2008a). This chapter was made public only after the collapse of the three large banks in Iceland (see Buiter & Sibert, 2008b). Buiter and Sibert’s analysis focused on the banks’ liquidity problems caused by the absence of a credible lender of last resort. According to them: The main message of our paper is, however, that it was not the drama and mismanagement of the last three months that brought down Iceland’s banks. Instead it was absolutely obvious, as soon as we began, during January 2008, to study Iceland’s problems, that its banking model was not viable. The fundamental reason was that Iceland was the most extreme example in the world of a very small country, with its own currency, and with an internationally active and internationally exposed financial sector that is very large relative to its GDP and relative to its fiscal capacity (Buiter & Sibert, 2008a).

Furthermore, according to Buiter and Sibert: The only way for a small country like Iceland to have a large internationally active banking sector that is immune to the risk of insolvency triggered by illiquidity caused by either traditional or modern bank runs, is for Iceland to join the EU and become a full member of the euro area. If Iceland had a global reserve currency as its national currency, and with the full liquidity facilities of the Eurosystem at its disposal, no Icelandic bank could be brought down by illiquidity alone. If Iceland was unwilling to take that step, it should not have grown a massive on-shore internationally exposed banking sector (Buiter & Sibert, 2008a).

Pe´tursson and O´lafsson (2010, p. 24) also stated that ‘‘the large banking collapse in Iceland could have been contained to some extent had Iceland been a member of EMU’’ (European Monetary Union). According to Buiter and Sibert it ought to have been clear to everyone (including presumably Icelandic politicians) that the banks’ business model was not viable long before the global economic and financial crisis hit in the fall of 2008. This was clear in July 2008, as it was in April 2008 and in January 2008 when we first considered these issues. We are pretty sure this ought to have been clear in 2006, 2004, or 2000. The Icelandic banks’ business model and Iceland’s global banking ambitions were incompatible with its tiny size and minor-league currency, even if the banks did not have any fundamental insolvency problems (Buiter & Sibert, 2008a).

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The Collapse of the Banks in October 2008 The collapse of the Icelandic banks in the beginning of October 2008 was a shock to the Icelandic nation as well as to many international interest groups and experts. If fact, it can be said that this was the first time that financial events in a tiny country like Iceland sent shockwaves through the international financial markets. As before the collapse, experts continued to express their views including Portes who had painted a favorable picture of the situation in Iceland in a report in November 2007. In his Financial Times column of October 13, 2008, Portes argued: ‘‘Like fellow Icelandic banks Landsbanki and Kaupthing, Glitnir was solvent. All posted good first-half results, all had healthy capital adequacy ratios, and their dependence on market funding was no greater than their peers’. None held any toxic securities. These banks had been managed well since their ‘mini-crisis’ in early 2006’’ (Portes, 2008). Portes thus still maintained after the collapse that the banks were solvent, but how could he know with any certainty the quality and value of the banks’ assets? Buiter and Sibert pointed out that the only parties likely to have substantive knowledge of the quality of a bank’s assets are its management, for whom truth telling may not be a dominant strategy and, possibly, the regulator/ supervisor. In this recent crisis, however, regulators and supervisors have tended to be uninformed and out of their depth. We doubt Iceland is an exception to this rule. The quality of the balance sheet of the three Icelandic banks has to be viewed by outsiders as unknown (Buiter & Sibert, 2008a).

We now know that the Financial Supervisory Authority in Iceland in charge of the task of supervising financial enterprises was understaffed and lacked experience. According to Wade (2009, p. 20), it ‘‘was captured by the banks and began to act more like a member of the bankers’ team than a regulator. [y] it did not do genuine tests of the accuracy of the balance sheets of the banks and the private equity companies they financed.’’ Kaarlo Ja¨nna¨ri15 — a retired director general of the Finnish Financial Supervision Authority who prepared a report on the banking regulation and supervision in Iceland after the collapse of the banks — concluded: ‘‘There might — just might — have been a possibility for the Icelandic banks to survive if the almost total freezing of the international financial markets had not taken place and confidence in Iceland had not been lost. Even in that case, they probably would have needed government support to maintain their solvency, as credit losses would have risen due to the deterioration of their loan portfolios’’ (Ja¨nna¨ri, 2009, p. 37).

15 In November 2008, as part of its Stand-By Arrangement with the International Monetary Fund, the Icelandic government undertook to invite an experienced bank supervisor to assess the regulatory framework and supervisory practices in Iceland and to propose needed changes. Kaarlo Ja¨nna¨ri, retired director general of the Finnish Financial Supervision Authority, was invited to carry out the assessment and prepared a report titled ‘‘Report on Banking Regulation and Supervision in Iceland: Past, Present and future.’’Retrieved from http://eng.forsaetisraduneyti.is/media/frettir/KaarloJannari__2009.pdf

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Mark J. Flannery16 who prepared a report for the Icelandic Special Investigation Commission just after the bank’s collapse stated: In the end, we cannot establish definitively whether one or all of the banks was in fact insolvent during that first week of October. However, their increasing loan delinquencies after March 2008 and the low recovery values implied by the FME’s ultimate settlement with the Old (receivership) banks imply that insolvency was a good possibility even before the banks encountered their terminal funding crises. One is left with the strong suspicion that some or all of the banks were insolvent — and hence that the market’s unwillingness to lend was rational (Flannery, 2009, p. 106).

Weaknesses in EU banking regulations, insufficient supervision, and inappropriate policy responses in Iceland, as well as the global financial crisis all contributed to the storm in October 2008. As risk aversion replaced financial mania in the international financial markets community, the Icelandic banks were doomed. Only a concerted international rescue effort could have saved the banks in October 2008. At this point the government of Iceland was isolated and could not assemble assistance. The outrageous bullying behavior of the British government also did not help.17 After the collapse of the three largest banks the only way forward seemed to be trying to regain some international credibility by entering into negotiations with the IMF and agree on a program to stabilize the troubled economy. In October 2008, the government of Iceland was left with no other choice.

How did the Government of Iceland React to Concerns and Criticism? Prior to the crisis and the collapse of the Icelandic banks the government had great ambitions regarding the potential for growth of the banking sector and in fact proposed that Iceland should become an international financial center (Benediktsdottir et al., 2011; Invest in Iceland, 2006). In fact a report was published on the issue by a committee appointed by the prime minister (Nefnd forsætisra´jherra um al“jo´jlega fja´rma´lastarfsemi, 2006). The chairman of the committee was Sigurdur Einarsson, at that time the chairman of the Board of Directors, Kaupthing Bank, one of the three big banks. According to the Invest in Iceland Agency, ‘‘Iceland’s positive business environment, low tax rates and efficient infrastructure make the country an ideal candidate for an international finance center according to a new report compiled for the Prime Minister by a team of experts’’ (Invest in Iceland, 2006). Furthermore, ‘‘Iceland does not have a long history as a financial center and is much better known for competitively priced sustainable energy and quality seafood. But extensive reforms, including liberalization and privatization, has changed the 16 Mark J. Flannery — professor of finance at the University of Florida — prepared a report for the Icelandic Special Investigation Commission just after the banks’ collapse, titled ‘‘Iceland’s Failed Banks: A Post-Mortem.’’ Retrieved from http://sic.althingi.is/pdf/RNAvefVidauki3Enska.pdf 17 UK authorities invoked the 2001 Anti-Terrorism, Crime and Security Act, passed after the September 11, 2001 terrorist attacks in the United States to justify the freezing of the UK assets of the of Landsbanki and Kaupthing (Me´ndez-Pinedo, 2011; Thorhallsson & Kirby, 2012).

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business environment dramatically during the last decade and Iceland is now recognized as one of Europe’s most competitive economies’’ (Invest in Iceland, 2006). The government thus saw a great growth opportunity in the banking sector. Liberalization of the financial markets and privatization of the state-owned banks were ‘‘good music’’ internationally at this time and such efforts were supported globally by institutions such as the IMF and the World Bank. As it turned out, the supervision of the banks in Iceland was weak and many people still question how the privatization of the state-owned banks was implemented with a few politically influential groups taking control and involving managers with little experience in international banking. As Ja¨nna¨ri pointed out, ‘‘For the most part, the new owners and the people behind them were not traditional commercial bankers, instead they had the rather innovative and somewhat adventurous mindset of investment bankers, which favoured a strategy of rapid growth and highly leveraged, aggressive deals’’ (Ja¨nna¨ri, 2009, p. 14). How could this happen in a developed OECD country like Iceland? How could Iceland move from the privatization of state-owned banks to ideas to create a financial center and from an exploding banking sector to a collapse? As Eggertsson and Herbertsson point out in a paper titled ‘‘System Failure in Iceland and the 2008 Global Financial Crisis,’’ ‘‘the prime minister talked about turning Iceland into a fullscale center of international finance. Scholars have documented how communities that are caught in extreme price bubbles become virtually manic and throw caution in the wind. Iceland is no exception, although, as always, there were early critics and skeptics’’ (Eggertsson & Herbertsson, 2009, pp. 28, 29). And further on, ‘‘Modern capitalism has had its fair share of financial manias, panics, and crises, but the global financial exuberance and the subsequent crash in the first decade of the 21st century stands out as exceptional and has been compared to the events leading to Great Depression’’ (Eggertsson & Herbertsson, 2009, p. 11). As discussed in the above, respected international experts issued warnings to the government about the expansion to the Icelandic financial sector well before the collapse in 2008. This included, for example, the Danske Bank report in 2006 and Aliber’s lecture in 2008 as well as the Buiter and Sibert report in 2008. Lower credit ratings issued by rating agencies were additional warning signals. The refusal from the Bank of England, the European Central Bank, and the Federal Reserve to increase the Icelandic Central Bank’s foreign exchange reserves should have also been a warning to the government and trigger immediate response from the key ministers involved.18 However, in Iceland, the response to negative reports and lower credit ratings was generally one of shock and anger over what was seen as unfair and unsubstantiated criticism. According to Sigurjonsson and Mixa (2011, p. 221), ‘‘The foreign criticism from financial institutions, rating agencies, and foreign media in 2006 did not manage to influence the general discussion in the Icelandic media in such a way that the international expansion of the Icelandic banks was scaled down.

18

The responsibility for money, banking, and finance in Iceland was divided between three ministries, those of the prime minister, minister of finance, and minister of business affairs.

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On the contrary, the growth only escalated.’’ Business people and cabinet ministers, aided by experts from some Icelandic universities, initiated a public relations campaign and painted a positive picture of the situation: for example, by emphasizing the excellent standing of the government that was virtually debt free and balanced its budget. Given the numerous warnings mentioned above, this can be interpreted as an attempt to convince others that facts from reality were other than they were, and thus, classified as dishonest behavior. Kaarlo Ja¨nna¨ri claims that foreign supervisors and central banks with which he was in contact when he was preparing his report on banking regulation and supervision in Iceland generally commented favorably on the cooperative and friendly attitude of the Icelandic authorities; however, he also comments Some disappointment has also been expressed about the willingness of the CBI and the FME to share the concerns they had about the Icelandic banks with their EU counterparts before the crisis exploded. There are feelings that the Icelandic authorities were protective of the banks and tried to tone down the worries expressed by their foreign counterparts. This has undermined the credibility of the FME and the CBI in the eyes of their colleagues. The FME and the CBI consider these criticisms to be unfair and unjustified (Ja¨nna¨ri, 2009, p. 12).

This again can be taken as an attempt from the government to fake the facts of reality. Furthermore, he comments: The supervisors were too timid and lacked legal authority in their efforts to intervene in these developments, but the overall national pride in the success of the banks would probably have made it futile even to try while the going was good and success followed success. By the time the tide turned, it was too late, and there was too little that could be done to avoid catastrophe (Ja¨nna¨ri, 2009, p. 37).

The same may have applied to the Icelandic cabinet of ministers. They may have lacked the courage to intervene and simply decided on a hands-off policy and hoped for the best and did not to prepare for the worst. As Danielsson and Zoega say in a recent paper, ‘‘By not addressing the pending failure of the banking system, perhaps in the hope that the instability would disappear, we cannot escape the feeling that the Icelandic authorities gambled for resurrection, and failed’’ (Danielsson & Zoega, 2009, p. 14). But, could the banks have been saved even if the cabinet would have interfered at full force? Eggertsson and Herbertsson have expressed their opinion as to whether it was still possible to restructure the banking system in 2006, following the early warning signs and criticisms from abroad. They ‘‘believe that even then, had they desired, the banks could have either downsized or split and moved their headquarters for foreign operations abroad’’ (Eggertsson & Herbertsson, 2009, p. 28). But in their view ‘‘only the prime minister and the cabinet could have made the critical political decision to reverse the spectacular growth of the country’s banking system or relocate most of it overseas’’ (Eggertsson & Herbertsson, 2009, p. 28). Sigurjonsson and Mixa (2011, p. 209) also agreed that ‘‘the financial crisis in 2008 could have been partially avoided by Iceland through observing the warning signs,’’ but the cabinet did not take action after the mini-crisis in 2006 and decided to defend the banks instead of downsizing or move their headquarters overseas. The cabinet chose to be

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inactive during a critical time in Iceland’s history. Their hopes for resurrection did not materialize. They seem to have refused to face reality. The consequences were dire.

The SIC and its Report to Al“ingi An SIC delivered its report to the Icelandic Parliament, Al“ingi, on April 12, 2010. The Commission was established by Act No. 142/2008 by Al“ingi in December 2008 to investigate and analyze the processes leading to the collapse of the three main banks (Glitnir, Kaupthing, and Landsbanki) in Iceland. The following section gives a flavor of the failure of leadership and coordination at the top government level in Iceland before the crisis hit with disastrous consequences. In fact, the SIC named ministers and high-level government officials in its report who were thought to have shown negligence. The report that accounts for nine volumes is quite extensive and only a few points can be highlighted in this section. According to the SIC the balance sheets and lending portfolios of the Icelandic banks expanded beyond the capacity of their own infrastructure. The growth had been especially rapid during the end of 2007. According to the SIC, the banks’ rapid lending growth had the effect that their asset portfolios became fraught with high risk. In the SIC’s opinion such a large-scale and high-risk growth was not compatible with the long-term interests of solid banks19 (SIC, 2010b, p. 1). Access to international financial markets was, for the banks, the principal premise for their extensive growth. According to the SIC, ‘‘there were mainly two reasons why international financial markets opened their doors to the banks, firstly, because of their good credit rating. This was to some extent inherited from the Treasury. Secondly, they had access to European markets, on the basis of the EEA Agreement’’ (SIC, 2010b, p. 1). The banks that had operated as state-owned banks for decades before their privatization had earned a reputation for being rather conservative and reliable and economic integration in Europe via the EEA agreement opened doors for the Icelandic banks to European financial markets. The SIC made strong comments on the lack of government response during a critical time prior to the crisis: When the banking system had become far too big, relative to the size of the Icelandic economy, the governmental authorities needed to respond. No later than 2006 it would have been necessary to take action, if there was to be any chance of preventing the collapse of the banks, without severely impacting upon the value of their assets. Neither that year nor the next did the authorities try, in a decisive way, to have the banks reduce the size of their balance sheets (SIC, 2010b, p. 2).

In addition to this the policy of the government was that the banks’ headquarters remain in Iceland, which meant that Iceland was responsible for their supervision. 19

Benediktsdottir et al. (2011, p. 224) also stressed another risk factor: the banks’ growth was ‘‘based on gearing up of equity that was in large part lent from within the system.’’

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The SIC was also very critical on the government’s macroeconomic policies during the period when the banks expanded: The authorities decided to lower taxes during an economic expansion period. This was done despite expert advice and even against the better judgment of policy makers who made the decision. This decision was highly reproachable. The changes made to the lending guidelines at the Housing Financing Fund in 2004 also fuelled expansion. The changes in the lending guidelines were one of the biggest mistakes in monetary and fiscal management made in the period leading up to the banks’ collapse. That mistake was made with full knowledge of the likely consequences. The repercussions were quick to emerge and the consequences were even greater under the global low interest rate environment at the time. These decisions in fiscal and monetary management and others named in the report exacerbated the imbalance in the economy. They were a factor in forcing an adjustment of the imbalances, which ended with a very hard landing (SIC, 2010b, p. 5).

According to SIC it was mostly left to the Central Bank of Iceland (CBI) to counteract the effects of the expansion by raising interest rates. According to the SIC: From November 2007 onwards the Board of Governors of the CBI became increasingly concerned about the situation that was developing in the operational environment of the banks. The Board of Governors described these concerns either directly to the Prime Minister and a small group of ministers, or within the platform of the government consultative group. In spite of these concerns there is no evidence that the Board of Governors of the CBI made available to the government formal propositions for necessary measures (SIC, 2010b, p. 8).

Also, key cabinet ministers failed to report the problems to the others in the government, as the SIC states: Nothing suggests, either from the government’s minutes or the accounts of those who reported to the SIC, that the ministers of the Icelandic government responsible for economic affairs (the Prime Minister), banking affairs (the Minister of Business Affairs) or the state’s finances (the Minister of Finance) submitted to the government a specific report on the problems of the banks or its possible impact on the state’s economy and finance when the banks started to face constraints in their operations and until the banking system collapsed in October 2008 (SIC 2010b, p. 10).

Again this shows a failure of coordination and the cabinet as a whole seemed not to have been informed formally. Nor was the cabinet activated to share responsibility or discuss possible government actions. According to the SIC: In 2008 the Prime Minister had quite a few meetings with the Chairman of the CBI Board of Governors and the CEOs of the banks. During the period from February until May 2008 Board of Governors had at least five meetings with the Prime Minister, Minister of Finance and the Minister for Foreign Affairs. Banking affairs came under the domain of the ministry of Mr. Bjo¨rgvin G. Sigurjsson, Minister for Business Affairs. He was not summoned to attend any of these meetings, in spite of the fact that the problems the banks were facing and the liquidity crisis were being discussed there (SIC, 2010b, p. 10).

This shows a grave coordination failure within the government, and as the SIC emphasizes: ‘‘As the leader of the government, the Prime Minister had the

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responsibility to inform the Minister of Business Affairs of the aforementioned meetings so that he could attend to his duties’’ (SIC, 2010b, p. 10). As stated earlier in this chapter, the ministers considered the outside criticism on the banks unjustified, unfair, and due to a lack of information. Foreign critics needed education, and efforts were mostly spent on improving the image of the banks. As the SIC states: It is the assessment of the SIC that the government’s actions concerning matters relating to the banks were unfocused when the situation became more dire in the beginning of 2008. The ministers focused too much on the image crisis facing the financial institutions rather than the obvious problem, that the Icelandic financial system was far too large in relation to the Icelandic economy. When the ministers intended to improve the image of the banking system by partaking in public discussions, mainly abroad, it was done without any assessment of the financial capability of the state to come to the banks’ assistance and without information being available on the cost of a possible financial shock’’ (SIC, 2010b, p. 10).

From the above it seems that the SIC is of the opinion that the government was faking reality and focusing on the image crisis instead of dealing with the obvious problem. When one looks at the analysis presented by the SIC, the powerlessness of the government and the authorities, when it came to reducing the size of the financial system in time before the financial shock hit, becomes evident. As the SIC states: ‘‘It appears that both the parliament and the government lacked both the power and the courage to set reasonable limits to the financial system. All the energy seems to have been directed at keeping the financial system going. It had grown so large, that it was impossible to risk that even one part of it would collapse’’ (SIC, 2010b, p. 17). Thus, the government hoped for the best but it did not prepare for the worst. Unfortunately, the worst scenario materialized when the government finally was forced to face reality. And in its conclusions the SIC names ministers and high-level officials and accuses them of negligence. The SIC’s assessment, pursuant to Article 1(1) of Act no. 142/2008, was mainly aimed at the activities of public bodies and those who might be responsible for mistakes or negligence within the meaning of those terms, as defined in the Act. Although the SIC was entrusted with investigating whether weaknesses in the operations of the banks and their policies had played a part in their collapse, the Commission was not expected to address possible criminal conduct of the directors of the banks in their operations. On the basis of events and viewpoints that are described in more detail in individual chapters of this report, the SIC is of the opinion that Mr. Geir H. Haarde, then Prime Minister, Mr. A´rni M. Mathiesen, then Minister of Finance, and Mr. Bjo¨rgvin G. Sigurjsson, then Minister of Business Affairs, showed negligence, within the meaning of Article 1(1) of Act No 142/2008, during the time leading up to the collapse of the Icelandic banks, by omitting to respond in an appropriate fashion to the impending danger for the Icelandic economy that was caused by the deteriorating situation of the banks. The SIC is also of the opinion that Mr. Jo´nas Fr. Jo´nsson, then Director General of the FME, and Mr. Davı´ j Oddsson, Mr. Eirı´ kur Gujnason and Mr. Ingimundur Frijriksson, then Governors of the CBI, showed negligence, within the meaning of Article 1(1) of Act No 142/2008, in the course of particular work during the administration of laws and rules on financial activities, and monitoring thereof (SIC, 2010b, p. 18).

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In April 2012, the former prime minister, Geir H. Haarde, was found guilty before a special court, Landsdo´mur, for not holding cabinet meetings when things turned critical in the period leading up to the crisis in 2008.20 His response to the media was: ‘‘I always found that charge to be even more ridiculous than the others. I still hold that view. It is therefore my opinion that the Court has made a grave error in reaching this conclusion and I therefore plan to take this case to the European Court of Human Rights as soon as I can’’ (XD, 2012). It would probably be beneficial for the international community to hear from the European Court of Human Rights as soon as possible.

The President’s Role Prior to the Crisis In the Icelandic political system the president remains largely a ceremonial figure. However, O´lafur Ragnar Grı´ msson who took office in August 1996 (and has been re-elected in 2000, 2004, 2008, and 2012) is influential both locally and internationally and he has been very active in promoting Icelandic business interests abroad. As stated in the above, according the SIC: ‘‘No later than 2006 it would have been necessary to take action, if there was to be any chance of preventing the collapse of the banks, without severely impacting upon the value of their assets. Neither that year nor the next did the authorities try, in a decisive way, to have the banks reduce the size of their balance sheets’’ (SIC, 2010b, p. 2). What did the president say about the Icelandic banking sector in 2006? In a speech at ‘‘The Kaupthing Seminar’’ in Helsinki in May 2006, the president said: Yes, the future does indeed offer fascinating opportunities — and the growing strength of the Icelandic banking sector will, as before, play a crucial role, both in itself and by providing valuable connections to the international banking community. The three leading Icelandic banks — Kaupthing, Landsbanki and Glitnir — are amongst the fastest growing banks in the world. And the largest of the three, Kaupthing, has already established a pivotal position in Northern European banking. It has been both a privilege and an education for me to follow the growth of their activities and witness the praise that the Icelandic banks have received from their foreign clients — to confirm how the Icelandic banks have become key players in international financing for prominent European and American companies (Grı´ msson, 2006, p. 5).

20

The trail and the verdict drew attention in the international media; see examples below: CNN World: http://articles.cnn.com/2012-04-23/world/world_europe_iceland-haarde-verdict_1_landsbankiicesave-haarde?_s=PM:EUROPE Financial Times: http://www.ft.com/intl/cms/s/0/13c2552a-6eb3-11e1-acf0-00144feab49a.html#axzz1zrlEtSUi Bloomberg: http://www.businessweek.com/printer/articles/51940?type=bloomberg The Guardian: http://www.guardian.co.uk/world/2012/mar/05/iceland-pm-charged-crisis The Telegraph: http://www.telegraph.co.uk/finance/financialcrisis/9221480/Ex-Iceland-PM-Geir-Haarde-toescape-punishment-despite-guilty-verdict-over-banking-collapse.html BBC: http://www.bbc.co.uk/news/world-europe-17817174

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Like the government, the president is concerned about the image of the banks. The outside world needs to be informed and educated about the Icelandic banking sector. At ‘‘The Kaupthing Seminar’’ the president made his view on this very clear when he stated: We have, however, been reminded of valuable lessons. One is that if you are a player in the global financial system, it is of paramount importance to keep foreign confidence in your financial institutions. Another is that reporting or misreporting by others can play a role. It is worth noting that in the avalanche of reporting and evaluation to which we have been submitted in recent weeks, there is a prevailing characteristic: The greater the knowledge of Iceland and the longer the experts have followed the Icelandic voyage, the more positive, informed and optimistic the conclusions have been. We have to admit, however, that we could be more active in explaining our case; but then you have to remember that we Icelanders make up the nation that discovered America 1000 years ago but did not tell anyone about it. We only wrote the story down in books for ourselves, in texts we alone could understand. Consequently, Christopher Columbus got all the glory when he stumbled upon America 500 years later. Now we have to do better: to build on the tradition of storytelling, aimed currently not only at ourselves but also at others. It is important to further the extensive knowledge and detailed understanding of the Icelandic experience; to be both transparent and open — willing to engage in dialogue with others. (Grı´ msson, 2006, p. 7).

At the Walbrook Club in London, May 3, 2005, the president offered a list of a dozen or so elements that he believed had been crucial to Iceland’s ‘‘success story.’’ One was that ‘‘Icelanders are risk takers. They are daring and aggressive.’’ (Grı´ msson, 2005, p. 4) The president of Iceland can hardly be blamed for the collapse of the banks in the fall 2008, but he did also not urge the bankers to show caution during a time when it was most critical. On the contrary, he encouraged further risk taking and expansion. Currently, he also encourages cross-border expansion of Iceland’s energy sector that would involve large and long-term investments, with long repayment periods. Such investments in emerging markets can be risky, especially for the companies from small countries (see, for example, Hilmarsson, 2008, 2010,2012). The president is a highly educated man with extensive experience. He should have known what dangers the banks could face with further expansion, risk taking, and aggressiveness. He should not have fueled excessive risk seeking behavior and he should have listened more to the critics. He should also know the risks energy companies may face when investing in emerging market economies.

Discussion According to the SIC, but also Vaiman et al. (2011),21 particular government officials showed negligence and made mistakes by not taking credible actions to manage risks 21

They stated, ‘‘the Icelandic circumstances tend to involve systemic negligence, ignorance, and confusion’’ (Vaiman et al., 2011, p. 270).

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following a rapid cross-border expansion of Iceland’s largest banks. As, according to Benediktsdottir et al. (2011, p. 224), ‘‘the banks were affiliated with one or more political parties,’’ this was not very surprising. The negligence and mistakes had severe consequences and resulted in the banks’ collapse in October 2008. Instead of addressing the problems in the economy, the government launched a PR campaign and according to the SIC the ministers focused too much on the image crisis facing the financial institutions rather than the obvious problem: in other words, the SIC claims that the government did not address an obvious problem, and this is a sign of dishonesty. The president of Iceland O´lafur Ragnar Grı´ msson supported the ministers in their efforts aggressively in speeches overseas. With that in mind the ministers and the president could be charged with attempting to fake reality and thus showing dishonesty according to Rand’s definition of the term. Also as some scholars put it, the authorities gambled for resurrection, and failed (Danielsson & Zoega, 2009). Nevertheless, one needs to keep in mind that the analysis carried out by a number of scholars who downplayed the problem may have confused the government and it may claim that it was honest in its inaction (Herbertsson & Mishkin, 2006; Portes & Baldursson, 2007). In that situation one can speculate if the government was honest but incompetent22 or not trustworthy. Some scholars presenting favorable assessment for the Icelandic banks were paid for their analysis and this was definitely the case with Mishkin. This undermines the credibility of the Herbertsson and Mishkin report. Other scholars warned the government strongly prior to the crisis but were ignored. These include Danske Bank (2006), Aliber (2008), and Buiter and Sibert (2008a). In fact, Buiter and Sibert claimed that the end of a non-viable business model was obvious from the beginning, years before the crisis. Also the fact that the Icelandic government had prepared Emergency Act (No. 125/2008) prior to the collapse of the Icelandic banks shows that the government was aware of the fact that things could go seriously wrong and result in severe consequences.

Conclusions It seems clear that by promoting the idea that Iceland should become an international financial center the government did express strong faith in the banking sector and encouraged its expansion. The President of Iceland also was a strong supporter of the expansion of the three largest banks as can be seen from the speeches he made overseas. The government generally welcomed the expansion of the banks and did not take credible measures to protect the economy in the event of a banking crisis. Private

22 Benediktsdottir et al. (2011, p. 186) partially agreed with this view: they stated that ‘‘government ministries and the political class were out of their depth when it came to managing an economy based on an international financial system.’’

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interests via the Iceland Chamber of Commerce aided by academics, including internationally recognized scholars, also published reports that could be used to justify government inaction. This was done by arguing that the realities did not call for any drastic measures. The government — including the key cabinet ministers responsible for the banking sector in Iceland — did not take international critics seriously and according to the SIC the ministers focused too much on the image crisis facing the bank rather than the obvious problem. They seem to have thought that foreigners needed more information to understand that the Icelandic banks were built on solid ground and therefore launched a cross-border PR campaign. The president also supported this campaign in his speeches overseas. If the ministers knew that the economy was facing an imminent danger, but decided to fake reality and pretended that facts from reality were other than they were, this behavior could be classified as dishonesty according to Rand’s definition. However, there is a possibility that they honestly thought that a PR campaign could stabilize the situation and decided to take that risk, gamble for resurrection. If so, and in the light of the SIC commission conclusions, one can ask if they were then honest but incompetent and thus not trustworthy. However, if they thought all was well, why then would they have prepared the Emergency Act prior to the collapse of the Icelandic banks? It is difficult to reach a final judgment as whether or not the ministers responsible for the banking sector in Iceland can be charged with dishonesty in the sense that they sought to fake reality. However, the SIC states that the problem was obvious and the fact that the ministers had prepared emergency law prior to the crisis confirms that they knew that things could go wrong but only took action at the last minute. Furthermore, in its conclusions the SIC was of the opinion that the prime minister, the minister of finance, and the minister of business affairs showed negligence during the time leading up to the collapse of the Icelandic banks by omitting to respond in an appropriate fashion to the impending danger for the Icelandic economy that was caused by the deteriorating situation of the banks. Also, the SIC was of the opinion that the director general of the FME, and the three governors of the CBI, showed negligence in the course of particular work during the administration of laws and rules on financial activities, and monitoring thereof. Future research needs to be conducted on the importance of honesty in the public administration/management and economics literature. Honesty is sometimes mentioned in these fields as being important, but the meaning of the word ‘‘honesty’’ is generally not defined or discussed at all. Moreover, (dis)honesty in public sector management — especially during crises — needs further research attention.

References Aliber, R. Z. (2008). Monetary turbulence and the Icelandic economy. Lecture at the University of Iceland, May 5. Retrieved from http://www.hi.is/files/skjol/icelandlecutre-May-2008.pdf

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Benediktsdottir, S., Danielsson, J., & Zoega, G. (2011). Lessons from a collapse of a financial system. Economic Policy, 26(66), 183–231. Bergsman, S. (2011). Iceland’s meltdown. Mortgage Banking, 72(1), 74–81. Buiter, W., & Sibert, A. (2008a). The collapse of Iceland’s banks: The predictable end of a nonviable business model. Retrieved from http://voxeu.org/article/iceland-s-banking-collapsepredicable-end-and-lessons-other-vulnerable-nations Buiter, W., & Sibert, A. (2008b). The Icelandic banking crisis and what to do about it: The lender of last resort theory of optimal currency areas. CEPR Policy Insight No. 26. Retrieved from http://www.cepr.org/pubs/PolicyInsights/CEPR_Policy_Insight_026.asp Centonze, A. L. (2011). Iceland’s financial meltdown. Journal of Financial Education, 37(1/2), 131–166. Danielsson, J., & Zoega, G. (2009). Collapse of a country (2nd ed.). Retrieved from http:// www.riskresearch.org/files/e.pdf Danske Bank. (2006). Iceland: Geyser crisis. Research. Retrieved from http://www.mbl.is/ media/98/398.pdf Eggertsson, T., & Herbertsson, T. T. (2009). System failure in Iceland and the 2008 global financial crisis. Paper presented at the 13th Annual Conference of ISNIE. Retrieved from http://papers.isnie.org/paper/373.html Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Flannery, M. J. (2009). Iceland’s failed banks: A post-mortem. Prepared for the Icelandic Special Investigation Commission. Retrieved from http://sic.althingi.is/pdf/RNAvefVidau ki3Enska.pdf Grı´ msson, O´. R. (2005). How to succeed in modern business: Lessons from the Icelandic voyage. A speech at the Walbrook Club London, May 3. Retrieved from http://www. forseti.is/media/files/%2005.05.03.Walbrook.Club.pdf Grı´ msson, O´. R. (2006). Icelandic ventures: Can the success continue? A speech at the Kaupthing Seminar in Helsinki, May 24, 2006. Retrieved from http://www.forseti.is/media/ files/06.05.24.Helsinki.Conference.pdf Herbertsson, T. T., & Mishkin, F. S. (2006). Financial stability in Iceland. Iceland Chamber of Commerce. Retrieved from http://www.vi.is/files/%20555877819Financial%20Stability%20 in%20Iceland%20Screen%20Version.pdf Hilmarsson, H. T. (2008). Private sector investments from small states in emerging markets: Can international financial institutions help handle the risks? Stjo´rnma´l og stjo´rnsy´sla, veftı´ marit Stofnunar stjo´rnsy´slufræja og stjo´rnma´la, fræjigreinar 4. a´rgangur 2. tbl., bls. 113–132. Retrieved from http://skemman.is/is/stream/get/1946/8972/23944/1/a.2008.4.2.1.pdf Hilmarsson, H. T. (2010). Public-private partnerships and energy sector investments in emerging market economies: Can the risk mitigation instruments offered by international financial institutions help private investors from small states? Bridges Scientific Journal, 2(51), 33–43. Retrieved from http://www.ku.lt/leidykla/leidiniai/tiltai/ tiltai_2010_2% 2851%29.pdf Hilmarsson, H. T. (2012). Small states and large private sector investments in emerging market economies in partnership with international financial institutions. In E. G. Carayannis, U. Varblane & T. Roolaht (Eds.), Innovation systems in small catching-up economies: New perspectives on practice and policy (Vol. 15, Part 2, pp. 139–158). New York, NY: Springer. Retrieved from http://link.springer.com/book/10.1007/978-1-4614-1548-0/ page/1 IMF. (2008). Iceland: Financial system stability assessment — Update. Retrieved from http:// www.imf.org/external/pubs/ft/scr/2008/cr08368.pdf

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International Bank for Reconstruction and Development/The World Bank. (2008). Growth report — Strategies for sustained growth and inclusive development. Retrieved from http:// cgd.s3.amazonaws.com/GrowthReportComplete.pdf Invest in Iceland. (2006, November). Iceland to become an international financial centre. Retrieved from http://www.invest.is/news/5/default.aspx Jackson, J. K. (2010). Iceland’s financial crisis. Current Politics & Economics of Europe, 21(1), 99–106. Ja¨nna¨ri, K. (2009). Report on banking regulation and supervision in Iceland: Past, present and future. Retrieved from http://eng.forsaetisraduneyti.is/media/frettir/%20KaarloJannari__ 2009.pdf Me´ndez-Pinedo, M. E. (2011). Iceland and the EU: Bitter lessons after the bank collapse and the Icesave dispute. Contemporary Legal & Economic Issues, III, 9–42. Nefnd forsætisra´jherra um al“jo´jlega fja´rma´lastarfsemi. (2006). Al“jo´jleg fja´rma´lastarfsemi a´ I´slandi. Retrieved from http://www.forsaetisraduneyti.is/media/frettir/Skyrsla.pdf Peikoff, L. (1991). Objectivism: The philosophy of Ayn Rand. New York, NY: Penguin. Pe´tursson, T. G, & O´lafsson, T. T. (2010).Weathering the financial storm: The importance of fundamentals and flexibility. Economics Working Paper 2010–17, Aarhus University School of Economics and Management. Retrieved from http://www.econ.au.dk/fileadmin/%20site_ files/filer_oekonomi/Working_Papers/Economics/2010/wp10_17.pdf Portes, R. (2008). The shocking errors of Iceland’s meltdown. Financial Times. Retrieved from http://www.ft.com/intl/cms/s/0/80f767e4-9882-11dd-ace3-000077b07658.html#axzz1yd 3SisEB Portes, R., & Baldursson, F. M. (2007). The internationalisation of Iceland’s financial sector. Iceland Chamber of Commerce. Retrieved from http://www.vi.is/files/15921776Vid4WEB.pdf Rand, A. (n.d.). John Galt speech. Retrieved from http://amberandchaos.com/?page_id=106 Rand, A. (1961). The objectivist ethics. Paper delivered by Ayn Rand at the University of Wisconsin Symposium on ‘‘Ethics in Our Time’’ in Madison, Wisconsin. Retrieved from http://www.aynrand.org/site/PageServer?pagename=ari_ayn_rand_the_objectivist_ethics Rannso´knarnefnd Al“ingis. (2010). Ajdragandi og orsakir falls ı´ slensku bankanna 2008 og tengdir atburjir. Bindi 8. Retrieved from http://www.rannsoknarnefnd.is/ Rose-Ackerman, S. (2001). Trust, honesty and corruption: Reflection on the state-building process. European Journal of Sociology, 42(3), 526–570. Russell, J. (2012). Ethical crises in the international political economy.Journal of Socioeconomics. Retrieved from http://dx.doi.org/10.1016/j.socec.2012.08.001 SIC (Special Investigation Commission). (2010a). Press Conference 2012. Retrieved from http://sic.althingi.is/ SIC (Special Investigation Commission). (2010b). Report of the Special Investigation Commission, 1(2).Retrieved from http://sic.althingi.is/pdf/RNAvefKafli2Enska.pdf Sigurjonsson, T. O., & Mixa, M. W. (2011). Learning from the ‘‘worst behaved’’: Iceland’s financial crisis and the Nordic comparison. Thunderbird International Business Review, 53(2), 209–223. Smith, T. (2006). Ayn Rand’s normative ethics: The virtuous egoist. Cambridge: Cambridge University Press. Thorhallsson, B., & Kirby, P. (2012). Financial crises in Iceland and Ireland: Does European Union and Euro membership matter? Journal of Common Market Studies, 50(5), 801–818. Vaiman, V., Sigurjonsson, T., & Davı´ dsson, P. (2011). Weak business culture as an antecedent of economic crisis: The case of Iceland. Journal of Business Ethics, 98(2), 259–272. Wade, R. (2009). Iceland as Icarus. Challenge, 52(3), 5–33.

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White, R. S. G. (2011). Bank structure and reevaluating the case for risk: The Icelandic banking crisis. Journal of International Finance and Economics, 11(2). Retrieved from http://www. highbeam.com/doc/1G1-272616556.html XD. (2012). Mr. Geir H. Haarde, former Prime Minister. His statement on the verdict delivered by Landsdo´mur. Retrieved from http://www.xd.is/i-brennidepli/frettir/nr/1768 Yin, R. K. (2009). Case study research: Design and methods (4th ed., Vol. 5). Thousand Oaks, CA: Sage.

Chapter 5

Perceptions of Unreported Economic Activities in Baltic Firms: Individualistic and Non-individualistic Motives Jaanika Meriku¨ll, Tairi Ro˜o˜m and Karsten Staehr

Abstract Purpose — The chapter assesses the linkages between unreported economic activities and different individualistic and non-individualistic motives as perceived by firm management. Design/methodology/approach — The empirical research is based on a survey of the management of firms operating in the Baltic States. The survey contains information on the perceived extent of unreported activities and on a large number of firm-, sector-, and country-specific factors. A principal component analysis identifies clusters of motives for unreported activity. Regression analyses ascertain the importance of motives individually and as principal components on the extent of unreported activities. Findings — Both individualistic and non-individualistic motives are important for the prevalence of unreported activities. The individualist motives refer to the management being solely profit-oriented and self-interested. Among possible non-individualist motives, measures of government performance and perceptions of reciprocity towards the government appear to play important roles for the extent of unreported activities, but broader societal norms may also play a role. Research limitations/implications — The study considers the perceptions that managers have of unreported activities and other features. These perceptions are subjective and subject to substantial uncertainty. All results should be interpreted in light of the subjective nature of the survey answers.

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 85–125 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010009

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Social implications — Taken literally, the results suggest that stronger government performance is associated with a reduction in unreported activities, at least as perceived by the management. Broader societal developments may also be of importance. Originality/value — The inclusion of variables capturing individualistic as well as non-individualistic motives gives a comprehensive picture of factors behind unreported activities. We employ principal component analysis which allows us to cluster individual survey answers and to produce composite measures of different explanatory factors. Keywords: Unreported economic activity; tax evasion; tax morale; norms; governance; social coherence; Baltic States How selfish soever man may be supposed, there are evidently some principles in his nature, which interest him in the fortune of others, and render their happiness necessary to him, though he derives nothing from it except the pleasure of seeing it. – Adam Smith (1767, p.1)

Introduction This chapter considers a specific manifestation of dishonest behaviour in management: namely, unreported economic activities. The management of firms can choose to conceal employment, salary payments or profit data from the authorities in order to evade taxation or elude regulation. Such behaviour may lead to distortion of competition, misallocation of resources, lower tax revenues, and ineffectiveness of government regulation. It is thus important to improve the understanding of this form of dishonesty — both from the perspective of businesses management and that of the society as a whole. The management practice of leaving economic activities unreported is chiefly motivated by a wish to reduce the cost of taxation, staff salaries, supplies or regulatory compliance (see the following section). Economic theory posits that the extent of unreported activities is determined by the direct pecuniary benefits and costs of such behaviour being traded off. The baseline model of rational individualistic choice assumes that the costs are related to the possibility of being caught and the resulting pecuniary punishment. The decision is subject to many sources of uncertainty which makes the decision-making complex. The baseline model of rational individualistic choice has traditionally dominated research on tax evasion and other forms of unreported economic activity. The assumption of purely individualistic behaviour as the only explanation of unreported activities has recently been questioned. The costs of unreported economic activities may also be affected by non-pecuniary factors related to moral convictions and perceptions of fairness in the society (Alm, Martinez-Vazquez, & Targlter, 2010).

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Dishonesty in the form of tax evasion may thus be traced back to the tax morale or, even broader, societal morale in the society, that is, a multitude of non-individualistic preferences reflecting different cultural, governmental, and societal contexts. Numerous empirical studies have sought to ascertain the importance of both individualistic and non-individualistic factors on tax evasion and other forms of unreported economic activities. Most studies find at least indirect support for individualistic factors playing an important role. Various firm characteristics such as the size, age, and sector of the firm are of importance for the extent of unreported activity, presumably because they are related with the economic benefits and costs associated with unreported activities (Kirchler et al., 2010). Other studies find that non-individualistic factors also play a role: in particular, the satisfaction with government policies and perceptions of the social acceptability of tax evasion and corruption. Most studies on the importance of non-individualistic factors on unreported activities are undertaken using data on advanced economies in Western Europe or the United States. Few studies deal with the former transition countries in Central and Eastern Europe and even fewer with the Baltic States. Putnins and Sauka (2011) report results using the SSE Riga dataset and conclude that managers working in recently established firms or in the construction sector generally perceive unreported activities to be very prevalent in the Baltic States. Moreover, managers perceive tax evasion to be more common when they are unhappy about tax levels and government performance, when tax evasion is perceived to be socially acceptable and when firms have economic problems. McGee, Alver, and Alver (2008) surveyed university students in Estonia and found that tax evasion was deemed more acceptable if the tax system is seen to be unjust, if tax rates are excessively high, if the government is corrupt or wasteful, or if the taxpayer faces economic hardship. The Baltic States constitute an interesting region for empirical research on economic activities left unreported by management. These three countries emerged from the Soviet Union in 1991 and integrated with Western European institutions in the following two decades. The unique background of the countries and the rapid transition have resulted in specific economic structures, and arguably also in distinctive views on the role of government and the role individuals and firms play in the society at large. This chapter considers the prevalence and determinants of different types of economic activity not reported to the authorities by the management of firms operating in Estonia, Latvia, and Lithuania. The main focus is on the linkages between the extent of unreported activities and the prevalence of individualistic and non-individualistic behaviour by the management. The individualistic behaviour relates to narrow rational behaviour as typically associated with homo economicus. Non-individualistic behaviour may stem from absolutist views on honesty, satisfaction with the government, and various forms of societal norms. The analysis is based on a survey that was compiled in 2010 by researchers at the Stockholm School of Economics in Riga (Sauka & Putnins, 2011). The SSE Riga survey is distinctive in the way information on unreported activities was collected. The survey asked managers of firms in the three Baltic States to state what they

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perceive to be the extent of unreported activities by firms operating in the same industry as their own firm. Targeting the perceived unreported activities in the industry rather than in the responding firm itself reduces the risk of the respondent understating the extent of unreported activities.1 The analysis in this chapter sheds light on managerial dishonesty in the form of unreported economic activities and links the behaviour of management to broader societal characteristics. The chapter contributes to the literature by being one of the first detailed studies linking behaviour based on rational choice as well as societal morale to unreported economic activities as perceived by the management. The study differentiates between different sources or reasons for unreported activities and investigates their separate impact on unreported activities. At the methodological level, the use of principal component clustering is novel in this context. Different questions from the SSE Riga survey on societal characteristics are mapped into different clusters of non-individualistic factors and these group measures are interpreted as composite indicators of different sources of managerial preferences. The rest of the chapter is organized as follows. The following section contains a review of the theoretical and empirical literature on the extent and determinants of unreported activities. Thereafter, background information is presented on the three Baltic societies in order to facilitate the interpretation of the empirical results. The chapter continues with a section presenting the dataset used in the empirical analysis. Thereafter, descriptive statistics on the perceived extent of unreported activities and some of the possible explanatory factors are presented. The following section contains econometric analysis seeking to establish linkages between measures of tax morale and unreported activities. The final section summarizes the chapter.

Unreported Economic Activity in Theory and in Empirical Studies The management of firms may choose not to report employment, turnover or profits to the authorities for a number of reasons. Arguably, the most important argument for not fully disclosing economic activities is to evade taxation, including value-added tax, social security contributions, labour income taxes and corporate income taxes. Other reasons may be that the activity is itself illegal, that the firm seeks to circumvent regulation of occupational health and safety conditions or that the required administrative and reporting procedures are considered excessive (Kirchga¨ssner, 2011). In all cases, there is an economic incentive to leave economic activities unreported. We will generally not distinguish between these two reasons for unreported activities and typically use the terms ‘unreported activity’ and ‘tax evasion’ interchangeably.

1 Beyond arguably more precise estimates of tax evasion, the measures of perceived unreported activities may also reveal possible self-reinforcing dynamics as tax morale in the society is likely to be dependent on perceived tax evasion (Frey & Torgler, 2007; Torgler & Schneider, 2005).

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Theories of Tax Evasion Individualistic preferences. The starting point is the theory of tax evasion as a model of individualistic rational choice. The theory, or at least the mathematical formalization of such a theory, dates back to Allingham and Sandmo (1972) and Yitzhaki (1974). The object of analysis is an economic entity that is legally entitled to report economic activities such as sales, value added, wage payments or profit to the authorities.2 It is assumed that the decision-maker, for instance, the firm’s management, acts as homo economicus, a rational and egoistic actor who makes decisions based only on monetary flows or stocks, and decides how much of an economic activity to report to the authorities. The model of unreported activities or tax evasion implies a decision under uncertainty for which the possible benefit from evasion is weighed against the cost in utility terms (Sandmo, 2005). The benefit is the reduced tax payment, which depends on the tax rate, minus the direct cost of the evasion, for example, from using cash instead of bank transfer. The expected cost relates mainly to the disutility stemming from the possibility of being caught and subsequently punished, which depends on factors such as the intensity of auditing and the punishment following detection. The baseline rational choice model assumes that the firm is risk neutral, in which case the expected cost of evasion is simply the probability of detection times the pecuniary cost incurred following detection. To the extent that tax rates, the direct cost of evasion, auditing intensities, fines and other factors are similar across different firms, the degree of tax evasion could also be expected to be relatively similar across the firms. It is conceivable, however, that the direct evasion costs, auditing intensities and possibly also fines will vary across different sectors, firm sizes and other firm characteristics, in which case such factors may end up affecting the evasion decision. The assumption of risk neutrality can be relaxed. In this case the expected cost of evasion will also depend on the degree of risk aversion of the firm, presumably the risk aversion of the owners, top management or the managers responsible for reporting to the authorities. More risk aversion entails a higher expected cost of evasion and therefore more truthful reporting of economic activity. Risk preferences may be seen as reflecting inherently individualistic preferences among the firm’s owners or management, but they may also reflect non-individualistic features such as the performance of the firm. As an example of the latter, moral hazard3 may emerge in underperforming firms with a high probability of default in the immediate future; the management may in this situation engage in tax evasion to increase the probability of the firm surviving. The extent of tax evasion varies substantially across countries that share many common features. This observation has given rise to a theoretical literature stressing 2

The model considers the decision-making of one entity. Some cases of tax evasion, such as undeclared wages, entail the involvement of two parties, the firm paying out, and the employee receiving the wages. The interaction and possible conflicting interests between the two parties are typically not modeled in theoretical models. 3 For an explanation of the term, see Rowell & Connelly (2012).

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the possibility of multiple equilibria (Cule & Fulton, 2009; Myles & Naylor, 1996). The probability of auditing and hence the probability of being caught evading tax is likely to be a decreasing function of the extent of tax evasion in the society. Similarly, the social stigma of being caught may be a decreasing function of the prevalence of tax evasion. This implies that the incentive to leave taxes unreported is positively related to the size of the unreported economy and this makes possible multiple equilibria. If tax evasion is limited, there is little incentive to evade taxes, whereas if it is pervasive, the risk from evading taxes is small. Such models suggest that path dependence may be important; a country can experience relatively little tax evasion or alternatively be caught in a ‘high evasion trap’. A particular form of tax evasion emerges when it is possible for the management or owners of firms to influence the probability of their being audited, the effectiveness of the audit, the fines or other factors affecting the expected disutility from evasion. This may, for instance, be the case when firms can use bribes or political influence— peddling to interfere in the work of tax authorities and courts. This suggests that tax evasion and political and bureaucratic corruption may coexist and in some cases even reinforce each other (Escobari, forthcoming). The models discussed so far assume a strictly rational approach to choices under uncertainty. Research within behavioural economics and economic psychology posit, however, that economic agents such as members of management may not make fully rational decisions when subject to a choice under uncertainty, but instead may make decisions based on rationality that is bounded in different ways (Hashimzade, Myles, & Tran-Nam, forthcoming, Section 3; Webley et al., 1991, Chapter 4). The decision under uncertainty might depend on the framing of the problem at hand. The prospect theory of Kahneman and Tversky (1979) is one prominent theory of bounded rationality, building on the importance of the framing of the choice problem. The management may, for instance, make different decisions for problems entailing the same pay-offs depending on whether the adverse outcome is framed as a loss or just a reduced gain. Framing is typically seen to be of particular importance when the decision problem is complex and includes uncertain factors for which no objective expectations are available. In such situations, economic agents may give up solving the problem under uncertainty and instead resort to ‘rule of thumb’ decisions. One example of such bounded rationality is inertial decision-making according to which the choice or behaviour from earlier periods is repeated (Webley et al., 1991, Chapter 4). Non-individualistic preferences and tax morale. It has generally been assumed that benefits and costs stem entirely from pecuniary flows. It is possible, however, that the expected costs of being caught evading tax also include non-pecuniary costs that relate to non-individualistic preferences. This suggests that the extent of reporting to the authorities may depend on broader societal norms and attitudes (Kirchga¨ssner, 2011). One example is the cost from embarrassment, loss of reputation or social stigmatization when taxpayers are caught having left economic activities unreported. Such costs are likely to depend on the specific context: for example, whether

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information is disseminated on evaders who have been discovered and how tax evaders are looked upon in the society. Even if there is no chance — or only a remote chance — of detection and subsequent punishment in the form of fines or stigmatization, firm management may still abstain from tax evasion. As the management chooses to forsake essentially riskfree ways of improving profits or other performance measures, such behavior implies that evasion is thought to be associated with a large disutility irrespective of the probability of auditing and detection. A number of factors could affect this psychic utility cost of tax evasion. One factor is predicated on religious or moral convictions that laws and other requirements set out by government authorities should be followed in all cases, simply because it is ‘the right thing to do’. In this case tax evasion is associated with extreme psychic disutility and, hence, is unacceptable for firm management in all circumstances. This is an extreme or absolutist case of tax morality stemming from strict adherence to authority or belief systems (Kirchga¨ssner, 2011; McGee et al., 2008). Another factor that may enhance tax compliance is the perception by taxpayers of reciprocity towards government. The government delivers services and income transfers, and the taxpayer sees taxation as the ‘price’ paid for these government activities. If the government delivers the desired services and transfers, the taxpayer perceives an obligation of repayment in the form of tax payments and this may enhance tax compliance (Kirchga¨ssner, 2011). In this view tax compliance is invoked by reciprocal behavior and tax morale becomes intertwined with the performance of government. Schnellenbach (2010) uses the term vertical reciprocity to capture the reciprocity between the taxpayer and the government. Another factor which may enhance tax compliance is the possibility that the individual taxpayer believes that other taxpayers abstain from evasion. The taxpayer may discern the existence of a social contract according to which all or most taxpayers act non-individualistically (Vihanto, 2003). In this context, tax morale is a result of a social contract based on a high degree of generalized trust across the society. Schnellenbach (2010) uses the term horizontal reciprocity to capture this perception of a social contract between individuals and firms in the society. A closely related motive for non-individualistic behavior is that taxpayers believe that the economic system and the tax system provide fair outcomes. This may be of particular importance for personal income taxes, which typically entail redistribution. Tax compliance might suffer if individuals see the income distribution and the tax system as providing unfair outcomes. In this situation, individuals with low pre-tax income may see tax evasion as a means of reaching a more equitable — and presumably fairer — post-tax income distribution (Webley et al., 1991, Chapter 3). Empirical studies. The theoretical literature provides numerous reasons for the management to engage in (dis)honest behavior in reporting their activities to the authorities. The reasons can conveniently be divided into two strands. The first strand assumes individualistic behavior, in which case honesty is entirely the result of self-interest. The behavior takes into account direct pecuniary benefits and costs: for instance, tax rates, auditing schemes and fines, and also the characteristics of

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management such as risk preferences and bounded rationality. The second strand assumes that management decisions may reflect non-individualistic preferences, in which case honesty may be the result of various components of tax morale. The tax morale may stem from absolutist values, reciprocity towards the government or perceptions of fairness in the society. The empirical literature can be divided into two parts. One part provides estimates of the extent of unreported activities: for instance in the form of production, employment or wages concealed from the authorities. Another part seeks to assess how different factors affect the prevalence of unreported activities. Space limitations demand that we focus only on the latter. Studies generally find that a range of firm-specific variables, such as sector, firm size and performance, have substantial explanatory power. The extent of unreported activities is typically larger in sectors such as construction and services than in other industries. Different proxies of management’s risk aversion similarly exhibit explanatory power in many studies (Schneider & Enste, 2000). Meriku¨ll and Staehr (2010) find for the Baltic States that firm characteristics are correlated with the prevalence of unreported employment. Unreported employment is more prevalent in the construction sector, in small firms and in firms with growing employment. Changes in sectoral composition and firm size can, however, only explain a small part of the developments in unreported employment across time, which may suggest that changes in tax morale and broader societal developments may also be relevant. Kriz et al. (2008) show that company characteristics have substantial explanatory power for different forms of unreported activities in Estonia. Moreover, relatively disenfranchised individuals are the most likely to receive undeclared wages. Such results lend support to the individualistic choice model, but it is clear that other factors must also be of importance. First, the extent of unreported economic activities varies substantially across countries that are in many other respects similar. Second, since the probabilities of audit and the levels of fines are low in practice and taxpayers are typically found to be only moderately risk averse, the individualistic rational choice model would predict much more tax evasion than is typically observed (Hashimzade et al., forthcoming). The literature survey in Kirchga¨ssner (2011, Section 6) concludes that empirical studies have generally shown that tax morale is an important determinant of tax evasion. Religious observance, democratic rights, confidence in the government and many other factors may help to explain tax morale. It is underscored in the survey that it can be difficult to identify the exact channel through which a given factor affects tax evasion. A high auditing rate, for instance, will affect the expected cost of evasion, but it may also influence the reputational cost of being caught and the perception of a social contract. Alm and Torgler (2006) observe that tax morale or the willingness to pay taxes differs substantially between the United States and many West European countries and attribute this to cultural differences. Torgler and Schneider (2006) use the data from the World Value Survey to ascertain the factors that shape tax morale in a number of European countries. They conclude that religion, culture, trust in the government, national pride and democratic orientation help to explain tax morale.

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However, the relative importance of these factors varies substantially across the countries surveyed. In a survey in Sweden, taxpayers stated the perceived evasion of different taxes and their trust in other taxpayers and the government as influential factors (Hammar, Jagers, & Nordblom, 2009). The perceived tax evasion was negatively related to both types of trust, but trust in the government was the most important. Turning to the post-communist countries, Torgler (2003) uses data from World Value Surveys undertaken immediately after communism was abandoned (1990–1993) and again five years later (1995–1997). The tax morale was higher in Central and Eastern European countries than in the countries emerging from the Soviet Union and this difference increased during the five-year span. The tax morale depends inter alia on the trust in the legal system and in government in general. Hanousek and Palda (2004) analyze surveys of individuals in Central European countries and find evidence that their willingness to pay taxes depends in large part on the perceived quality of government services. They conclude that reciprocity is important for tax compliance. The paper by Uslaner (2010) is based on the 2002 and 2005 BEEPS surveys of businesses in a large number of transition countries and has substantial affinity to this chapter.4 Managers are interviewed and asked what share of sales the typical firm in their area of business reports for tax purposes. The results for the impact of auditing and control are ambiguous, possibly because such measures also lead to increased corruption, which facilitates tax evasion. The efficient provision of government services seems to be a very important factor for the tax compliance decisions of firms in transition countries. Theory and Empirical Studies in Review. The starting point of the theories explaining unreported economic activities is the assumption that the decision-maker of a firm — the management — trades off benefits and uncertain costs. There are two main strands of theories; see Figure 1. The first strand consists of theories which generally

Individualistic preferences

Rational choice

Behavioral choice

Non-individualistic preferences

Absolutist values

Reciprocity towards the government

Social contract

Unreported economic activity

Figure 1: The determinants of unreported economic activity (compiled by the authors).

4

The BEEPS refers to the Business Environment and Enterprise Performance Survey administered by the World Bank.

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assume that the decision-maker acts as homo economicus, that is, the decision-maker is strictly individualistic and rational, and all benefits and costs are purely pecuniary. In some cases the decision-making problem may be very complex and entail uncertainty that is difficult to determine, and this may lead to a behavioural choice that is not strictly rational. The second strand of theories posits that non-individualistic factors play a role in whether the management chooses to leave economic activities unreported. We distinguish between three different underlying reasons. First, the management might have absolutist values that affect the psychic costs of tax evasion or other unreported activities. Second, the management might see taxation as a reciprocal payment for government activities and therefore see its tax obligations as necessary and fair. Third, the management might see tax payments as stemming from a social contract under which everybody is obliged to contribute to the society and to follow the rules of the society. The three explanations of non-individualistic preferences may together be seen to produce a tax morale under which decisions on tax evasion or other unreported activities are not driven only by narrow motives of self-interest. Most empirical studies consider the theories of individualistic choice as an explanation for tax evasion, often somewhat indirectly. It is typically found that a number of firm characteristics such as industry, size, and business performance are important explanatory factors, presumably because these factors determine the benefits and costs of unreported activities. Studies also suggest that factors depicting non-individualistic preferences are of importance, but there appears to be substantial heterogeneity across different countries, time periods and study methodologies. Overall, the theoretical and empirical literature makes it reasonable to hypothesize that both individualistic and non-individualistic factors play an important role in the prevalence of unreported activities in the Baltic States.

The Baltic States: Tax Systems, Values and Unreported Activity The Baltic States constitute an interesting region for empirical research of unreported activities. The three countries regained their independence from the Soviet Union in 1991 and share much of their economic and institutional background. To facilitate the interpretation of the empirical results, this section presents key information on the three Baltic countries with special focus on the economy, the tax system, government effectiveness and trust in society. In 2010, GDP per capita adjusted for differences in purchasing power reached 58.3 per cent of the EU15 average in Estonia, 52.0 per cent in Lithuania and 46.4 per cent in Latvia (Eurostat, 2012, code: nama_aux_gph). The countries faced very deep recessions in connection with the global financial crisis, leading to corporate bankruptcies and rapidly increasing unemployment. In 2009, GDP fell by 14 per cent or more in each of the countries; in 2010, the survey year, GDP growth was 2.3 per cent in Estonia, 1.4 per cent in Lithuania and 0.3 per cent — a decline — in Latvia (Eurostat, 2012, code: nama_gdp_k).

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The Baltic States established in 1990–1992 tax systems whose basic components resembled those of Western Europe. Reforms of the tax systems have subsequently introduced a number of features that are not typically seen in Western Europe. The rates of social security contributions are high, but part of the contribution is transferred to individualized pension accounts. The countries have flat personal income taxes with relatively low tax rates and modest tax-free minimums. The corporate income tax rates are equal to the personal income tax rates in Estonia and Lithuania, but not in Latvia; see below. Value-added taxation and excise duties are important contributors to the budget. Although the tax systems have many similarities, there is an important difference regarding corporate income taxation. In Estonia, unlike in Lithuania and Latvia, the corporate income tax is applied only to dividend payments, thus retained profits are not taxed. Consequently, Estonia applies a relatively high tax rate on corporate income but a narrow tax base. The flat statutory tax rate on corporate profits is 21 per cent in Estonia, but 15 per cent in Latvia and Lithuania.5 In 2010, the reference year for the empirical analysis, the total tax intake, including social security contributions, was 34 per cent of GDP in Estonia and 27 per cent of GDP in Latvia and Lithuania (European Commission, 2012, p. 180). The higher tax intake for Estonia is due to the fiscal consolidation initiated in 2009 and continued in 2010, whereas Latvia and Lithuania resorted to less austerity after the global financial crisis (Staehr, 2010). The economic structures are relatively similar across the Baltic States. In 2010, the rank correlation coefficients between NACE 2008 two-digit level industry shares were 0.94 between Latvia and Lithuania; 0.91 between Estonia and Lithuania; and 0.90 between Estonia and Latvia (based on employment shares across 33 industries; Eurostat, 2012, code: nama_nace38_e). At the same time the rank correlation coefficients with the EU15 industrial structure were around 0.79–0.80 for all three Baltic States. Administrative and governance structures show substantial differences across the countries. The World Bank assessment shows that Estonia has better governance than Latvia and Lithuania within a range of indicators such as governance effectiveness, regulatory quality, the rule of law and control of corruption. The World Bank (2012) reports data for 2010 and for the global sample and the indices range from 2.5 to 2.5, indicating low and high quality of governance respectively. In 2010 the score for the effectiveness of governance was 1.22 for Estonia, 0.72 for Lithuania and 0.70 for Latvia. The score for the quality of government regulation was 1.45 for Estonia, 0.97 for Lithuania and 0.98 for Latvia. Fabrizio and Mody (2008) reach similar conclusions regarding the quality of fiscal institutions in the three countries. The assessments of government quality by the World Bank are in correspondence with the findings in the European Social Survey, 2008, which is based on fieldwork done in the Baltic States during late 2008 and early 2009 (European Social Survey,

5

In Estonia, Latvia and Lithuania, the tax bases to GDP are 24, 29 and 34 per cent, respectively (European Commission 2012, p. 39).

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2011). A question on the efficiency of the tax authorities in tasks like handling queries on time, avoiding mistakes and preventing fraud resulted in scores of 5.6, 4.8 and 4.8 for Estonia, Lithuania and Latvia respectively. The scores were allowed to range from 0 to 10, where the highest value 10 captured the opinion that the authorities were ‘extremely efficient’. According to the same survey, social trust was also higher in Estonia than in the other Baltic States. On a scale from 0 (‘You cannot be too careful’) to 10 (‘Most people can be trusted’), the average score for social trust was 5.4 in Estonia, 4.1 in Latvia and 4.4 in Lithuania. McGee (2008) documents the attitude towards tax evasion among individuals in the Baltic States and other post-communist countries around 1990 and 2000 using data from the Human Beliefs and Values Surveys. The main finding is that the tolerance of tax evasion in the Baltic States is broadly comparable to the levels observed in other transition countries. Surprisingly, while tax evasion becomes more acceptable in Estonia and Lithuania during the first decade of transition, this is not the case in Latvia. The attitude towards cheating on taxes among individuals can be inferred from the World Values Survey, but unfortunately detailed questions for the Baltic States are only available from 1999. Latvia was the country with the lowest rate of acceptance of tax evasion; on a scale between never justified (1) and always justified (10), the mean score was 3.15 for Estonia, 2.36 for Latvia and 3.77 for Lithuania. Only Latvians found tax evasion less justified than the EU25 average (score 2.57), while Lithuanians were the most tolerant of tax evasion in the whole of EU25 (World Values Survey, 1999). Torgler (2012) uses data from the European Values Survey of 1999 and 2008 and concludes that the tax morale of individuals has decreased in most of the 10 CEE countries between the two survey periods. Within the Baltic States, the tax morale has increased in Lithuania and decreased in Estonia and Latvia. Unlike the study by McGee (2008), this study shows that tax morale is lower in the Baltic States than in other CEE countries, while Latvia still has the highest tax morale in the Baltic States. Only a few studies seek to estimate the prevalence of unreported economic activities in the Baltic States, although in some cases the three countries are included in broader cross-country studies. There is no consensus about the size of the unreported or ‘shadow’ economy. Schneider (2010) uses the indirect MIMIC method, which combines a number of observable indicator variables to produce estimates of the size of the unreported economy.6 It is relatively stable over the period 2003–2010 and in 2010 amounts to 29.9 per cent of reported GDP in Estonia, 27.3 per cent in Latvia and 30.0 per cent in Lithuania. These values are substantially above the average for the 27 EU countries which is estimated to be 20.0 per cent of reported GDP. Tafenau, Herwartz, and Schneider (2010) also use the MIMIC methodology but find much lower shares for 2004 of 16.6 per cent for Estonia, 20.4 per cent for Latvia and 22.4 per cent for Lithuania. Putnins and Sauka (2011, Table 1) estimate the size

6

The methodology is discussed in detail in Schneider (2005).

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of the unreported economy using the SSE Riga dataset of perceived unreported economic activities and find that unreported GDP amounts to 19.4 per cent of total of reported and unreported GDP in Estonia, 38.1 per cent in Latvia and 18.8 per cent in Lithuania. The upshot is that the size of the unreported economy in the Baltic States is relatively large, but the exact size and even the ranking within the three countries are difficult to determine. Williams (2008, 2009) compares the prevalence of undeclared wages in the Baltic States with their occurrence in other European countries using data from a Eurobarometer survey conducted in 2007 (European Commission, 2007). In total 7 per cent of the respondents in Estonia, 11 per cent in Latvia and 17 per cent in Lithuania stated that they had received undeclared wages within the preceding year. In comparison, the share receiving undeclared wages averaged 11 per cent in the 10 CEE countries, but only 3 per cent in the 15 ‘old’ Western European EU countries (unweighted averages). The relatively low share of recipients of undeclared wages should be seen in the context of data being self-reported.

The SSE Riga Dataset The analysis in this chapter draws on the SSE Riga survey, which is a micro-level dataset that was compiled by the Stockholm School of Economics in Riga, Latvia. It is based on surveys of company managers conducted in the three Baltic States of Latvia, Lithuania, and Estonia. The survey fieldwork was carried out in March and April 2011. Firms were chosen by random sampling from among all active firms in the Baltic States listed in the Orbis database managed by the Bureau van Dijk. For each country, five size groups were formed using the book value of assets and an equal number of contacts were randomly drawn for each size group. Since the response rates were unequal across these firm size groups, we use sample weights based on the data for the total population of firms. The final sample sizes were 591 firms in Latvia, 536 in Lithuania and 500 in Estonia. The comparisons of the extent of the shadow economy across countries and sectors are based on weighted averages. The weights measure the inverse probability that a firm from the given size and industry group will appear in the database. Weights are calculated by dividing the number of firms in the population by the number of firms in the database in a given country, sector and firm size group. For this purpose we use six sectors (manufacturing, wholesale trade, retail trade, construction, services, and other) and six size groups which are based on the number of employees (1–9, 10–19, 20–49, 50–99, 100–249, and over 249).7 The survey questionnaire consisted of five main blocks of questions (see Sauka & Putnins, 2011). The first, introductory, block gathered information from managers on their satisfaction with various aspects of governance as well as their assessment of the 7

The number of firms in the population is based on data provided by the national statistical offices of the three Baltic States.

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tolerance of tax avoidance and bribery in their country. The second block was targeted at tax evasion. The size of the shadow economy was measured in three dimensions. Firms were asked about the perceived share of net profits, employees and salaries that are not reported to tax authorities. The third block covered various aspects of managerial orientation (risk aversion, innovativeness, and other characteristics). The fourth block collected information on the characteristics of the business (including sector, sales turnover, age, and the number of employees) and the manager who was answering the questions (his/her level of education and years of business management experience). In the fifth and final part of the survey the managers were asked to express their opinions about a variety of statements related to possible reasons why firms evade taxes. The primary purpose of the survey was to collect information on tax evasion. Given the sensitivity of this topic, surveys asking managers directly about the size of unreported activities in their companies usually yield downward-biased estimates. In order to minimize the understatements of the true extent of the shadow economy, the related questions were formulated in an indirect manner. Instead of giving information on their own companies, managers were asked to assess the size of the shadow economy in the industry in which their firm operates. In addition, in order to increase the response rate and to ‘melt the ice’, the survey started with a block of questions which covered a more neutral topic — the quality of governance. This type of indirect and gradual approach should provide more truthful answers (see, for example, Flexman, 1997 and Sauka & Putnins, 2011). It should be noted that the indirect method of measuring the shadow economy used in the SSE Riga survey is also prone to measurement errors, insofar as the assessments of firm managers about the extent of the shadow economy in their sector do not coincide with its actual size. Although measuring economic variables with errors decreases the precision of the estimates, measurement errors do not cause biases in the estimation if they are not systematic. We are not aware of any studies which try to assess the extent of erroneous reporting and potential biases caused by non-randomness of this type of measurement error. In particular, it is not known whether asking about the degree of unreported economic activity in the industry where the firm is operating rather than in the firm itself will still provide estimates which are downward biased and whether the extent of honest reporting will vary from country to country. So, although we provide many comparisons between Latvia, Lithuania and Estonia in the following sections, they are all based on an implicit assumption that biases caused by misreporting do not differ systematically between the three countries. If firms’ assessments of others’ behavior are influenced by their own actions, we should observe that firm-specific factors customarily explaining firm-level tax evasion can explain a firm’s estimation about the industry’s tax evasion. This is an indirect way of testing whether managers have their own company in mind or if they are really talking about the industry as asked by the questionnaire. We can also interpret these results as an indicator of data quality. Biases in the perceived extent of shadow economy may be caused by a non-random refusal to answer to the related questions. Approximately one fifth (22 per cent) of

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respondents do not provide answers to the tax-evasion-related questions in the survey (questions 7, 9 and 11). This share is similar across the three Baltic States: it is 21 per cent for Estonia, 24 per cent for Lithuania and 21 per cent for Latvia.8 So, even when the biases mentioned above exist, we can assume that non-random refusals do not cause distortions in cross-country comparisons. The respondents were asked to assess the extent of shadow economy in the two years preceding the survey: in 2009 and 2010. In this chapter we only use the information provided for 2010. Since this time period is assessed with a shorter lag, it can be assumed that the data referring to 2010 are more precise and up-to-date. However, the differences in assessments are relatively small between the two years surveyed (Sauka & Putnins, 2011).

Descriptive Statistics An Overview of the Sample Variables In this section we provide descriptive statistics of the SSE Riga shadow economy survey (see Table A.1). The descriptive statistics use sample weights but the data collectors do not use weights in their report about the shadow economy in the Baltic States (see Sauka & Putnins, 2011). However, the sample coverage differs substantially across countries: for example, small firms are significantly overrepresented in Estonia. After the application of weights, the cross-country differences in unconditional estimations (presented in Figures 2 and 3) become lower than reported by Sauka and Putnins (2011). The survey estimates imply that the shadow economy is quite substantial. Figure 2 presents the weighted average estimates of the perceived extent of unreported activities in the three Baltic States together with 95 per cent confidence intervals. Firm managers believe that around one fifth to one fourth of company profits remain unreported to tax authorities (about 19, 20 and 26 per cent in Estonia, Lithuania and Latvia respectively). This amount is larger in Latvia than in the two other Baltic States, but the difference is not statistically significant. According to the managers’ assessment, the share of employees who do not have formal employment contracts is around 15 per cent and does not vary much across Estonia, Lithuania and Latvia. The perceived share of undeclared wages is significantly larger in Latvia than in Estonia and Lithuania; the point estimates of the weighted average shares are 34, 24 and 22 per cent, accordingly. The confidence intervals tend to be the largest for Latvia and the smallest for Estonia, implying that the answers of Estonian managers have the lowest variation, followed by those from Lithuania and then from Latvia. Latvian managers have the most varying views about the size of the shadow economy in their country. 8

The cases when a respondent has answered ‘‘0’’ to all three questions about the shadow economy (the extent of unreported profits, employees and salaries) are also treated as non-responses.

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LT Profits

LV

EE

LT Employees

LV

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LT

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Salaries

Figure 2: Share of perceived unreported activity in Estonia (EE), Lithuania (LT) and Latvia (LV) (compiled by the authors). Note: The figure depicts weighted average percentages of profits, employees and salaries not reported to every country’s tax authorities. Weighted means and 95 per cent confidence intervals are shown. Interestingly, this regularity holds for other blocks of the survey questions as well: Latvian answers tend to have the largest and Estonian answers the lowest variation. Figure 3 presents the share of perceived undeclared activity in the same three dimensions (profits, employees and salaries) across six sectors: manufacturing, wholesale sales, retail sales, services, construction and other private activities. Previous empirical studies typically show that tax evasion is more prevalent in construction and services than in manufacturing (Meriku¨ll & Staehr, 2010; Schneider & Enste, 2000). The estimates based on the SSE Riga survey do not follow this pattern. Although the point estimates for the weighted shares of unreported profits and salaries are somewhat lower than the average for manufacturing, these differences tend to be not statistically significant. The estimated shares of unreported profits and employees are higher in construction than in all other sectors, but these differences are also not statistically significant. Overall, our survey estimates imply little variation in the extent of shadow economy across sectors. The first two figures presented in this section illustrated the perceived level of unreported activity. Next we will give an overview of the statistics for the variables which are later used in the regression analysis and shown to be related to the perceived extent of unreported activity. The first group of variables consists of managers’ perceptions of various aspects of government performance in their country and their attitudes to how the quality of governance affects tax evasion (see Figure 4). As was described in the literature review, tax compliance may be influenced by the quality of government services because firm managers behave reciprocally: If the government services are of high quality, taxpayers feel obliged to repay

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50 45 40 35 30 25 20 15 10 5

Profits

Employees

Other

Construction

Retail

Services

Wholesale

Other

Manufacturing

Construction

Retail

Services

Wholesale

Other

Manufacturing

Construction

Retail

Services

Wholesale

Manufacturing

0

Salaries

Figure 3: Share of perceived unreported activity across sectors in the Baltic States (compiled by the authors). Note: The figure depicts weighted average percentages of profits, employees and salaries not reported to tax authorities. Weighted means and 95 per cent confidence intervals are shown.

this favour in the form of tax payments and this may enhance tax compliance (Kirchga¨ssner, 2011). The survey estimates suggest that the level of satisfaction with government services is significantly higher in Estonia than in Lithuania and Latvia (see Figure 4). This result holds for all four variables measuring good governance practices. Across the three Baltic States, Latvian managers tend to be the least satisfied. Although the answers of the Latvian and Lithuanian managers are closer to each other, they are still significantly different for two out of four variables. The shares of managers satisfied with the government’s tax policy and the quality of business legislation are significantly lower in Latvia than in Lithuania. Only about 4 per cent of Latvian business managers approve of the tax policy and 10 per cent are satisfied with the quality of business legislation in their country. The same shares are about 50 and 51 per cent in Estonia and 16 and 19 per cent in Lithuania respectively. The estimates presented in Figure 4 imply that Estonian managers are significantly more likely to agree with the statement that ‘Entrepreneurs believe that their tax money is spent appropriately’ and significantly less likely to agree with the statement that ‘Tax evasion is the response to a lack of government support’ than their Baltic neighbours. The comparison of the country-level shares of managers agreeing with different statements presented in Figure 3 gives support to the explanation proposed above that tax evasion is at least partly driven by reciprocity towards government. We find that Estonian managers have the highest perception of the quality of government

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Performance of State Revenue Service

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Government's tax policy

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Quality of business legislation

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Government's support to enterpreneurs

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Enterpreneurs believe their tax money is spent appropriately

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Tax evasion is the response to lack of government support

Figure 4: Satisfaction with government services and reciprocity towards government (compiled by the authors). Note: For the four measures of government quality, the figure presents weighted average percentages of firm managers stating that they are satisfied or very satisfied with a particular aspect of governance. For the two measures of reciprocity, the figure presents weighted average percentages of firm managers who gave 7 or 6 points on a 1–7 point scale, where 1 means ‘completely disagree’ and 7 means ‘completely agree’. Weighted means and 95 per cent confidence intervals are shown.

services and at the same time are also the least likely to state that taxes are evaded in response to lack of government support. Conversely, Latvian managers have the lowest opinion of the quality of governance and are the most likely to support this statement. The second group of variables, which are later used in the regression analysis and shown to be correlated with perceptions of tax evasion, tries to capture the influence of the perceived social contract on unreported activities. As described in the literature review, besides the direct cost-benefit analysis embedded in rational agent models, the decisions of whether and to what extent to leave activities unreported may be influenced by prevailing views in the society regarding business ethics and by the general tolerance of corruption and illegal activities. The SSE Riga survey includes two questions which make it possible to evaluate the extent to which tax avoidance and bribery are tolerated. The related statistics are presented in Figure 5. Company managers were asked whether they agree that illegal activities — tax avoidance and bribery — are tolerated in their country. Figure 5 depicts the weighted average shares of company managers in Estonia, Lithuania and Latvia who either disagreed or completely disagreed with these statements. We see a lot of variation across countries. The shares are significantly lower in Lithuania than in Latvia and Estonia, meaning that the level of tolerance of the two illegal activities seems to be

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1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 EE

LT Tax avoidance

LV

EE

LT

LV

Bribery

Figure 5: The share of company managers disagreeing with the statement: ‘Tax avoidance/bribery is tolerated behavior in your country’ (compiled by the authors). Note: The figure presents weighted average percentages of firm managers stating that they disagree or completely disagree with either statement. Weighted means and 95 per cent confidence intervals are shown.

higher in Lithuania than in the other two Baltic States. The shares of managers disagreeing with either statement are the highest in Latvia, although they are not significantly different from the Estonian shares.9 The aim of the last group of the variables presented in this section is to capture explanations for tax evasion that stem from rational choice. In the following regression analysis, we aim to assess whether the perceptions about tax evasion can be explained by commonly used models of rational agents, where it is assumed that the decisionmaker, usually the owners or the top management, acts as homo economicus — a rational and egoistic actor who makes decisions only based on individualistic and pecuniary motives. Figure 6 gives an overview of the extent to which firm managers agree with statements that can be linked to causes of unreported activity based on rational behavior. The first two variables depicted in Figure 6 capture whether company managers agree with the notion of tax evasion as rational optimizing behavior, which all firms use regardless of the economic necessity and the quality of the government’s performance. The last two variables focus on the notion that unreported activities are related to economic hardship: firms are more likely to evade taxes when this is necessitated by low profits or a threat to survival. This concept can also be linked to rational choice since it is likely that during economic difficulties and especially 9

The estimates of the SSE Riga survey correspond to the results of the World Values Survey (see McGee, 2008) and the European Values Survey (see Torgler, 2012) in the sense that Latvia holds the highest tax morale in Baltic States. The order of Lithuania and Estonia varies across the surveys.

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EE

LT

LV

Firms always evade taxes Firms always evade taxes Taxes are evaded more in to reduce costs, regardless to reduce costs, regardless difficult times of firm performance of government

EE

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Evading taxes is the only way to survive

Figure 6: Reasons for tax evasion related to the rational choice model (compiled by the authors). Note: The figure presents weighted average percentages of firm managers who gave 7 or 6 points on a 1–7 point scale, where 1 means ‘completely disagree’ and 7 means ‘completely agree’. Weighted means and 95 per cent confidence intervals are shown.

when a firm is facing bankruptcy, the expected economic benefits of tax evasion outweigh the expected costs, the latter stemming from the possibility of being caught and subsequently punished. It should be noted that agreement with the statements depicted by the last two variables presented in Figure 6 indicates that an answer is inclining towards rational choice-based arguments of tax evasion. On the other hand, when a respondent disagrees with these statements, he/she is supportive of the social contract-based views outlined in the literature review of this chapter, since when taxes are paid on the basis of the belief that it is part of the social contract, this would imply that the willingness to pay taxes and to support the society is stronger during economically difficult times: thus, the opposite of what the statements presented in Figure 5 indicate. The summary statistics presented in Figure 6 show that only a minority — about 10 per cent of the firm managers — support the entirely rationalistic view that firms should evade taxes whenever possible because this reduces the costs of running the business. It is also interesting to note that the shares of firm managers agreeing with the first two statements presented in Figure 6 are almost identical in the three Baltic States. There are no significant differences across the three Baltic States for the proportion of managers agreeing with the statement that taxes are more likely to be evaded in difficult times, although the point estimate for the average proportion is much higher in Latvia than in Estonia and Lithuania. The perceived sensitivity of profits to tax evasion is stronger in Latvia and Lithuania than in Estonia: firm managers in the two former countries are significantly more likely to agree that company profits are strongly affected by tax evasion.

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Principal Component Analysis In light of the literature review, one might seek to relate each explanatory variable that we presented in the above figures to a particular theory of tax evasion or unreported activities. The variables reported in Figure 4 capture the theory of reciprocity, that is, the notion that firms that are satisfied with government institutions are also willing to contribute taxes for the public goods provided. The tolerance of tax evasion and bribery depicted in Figure 5 proxy the perceptions about the social norms and can therefore be linked with the social contract or tax moralebased explanations of tax evasion. The statements presented in Figure 6 capture the justifications for tax evasion based on the models stemming from rational behavior. We have tested whether the explanatory variables do indeed group to indicators related to the three different theories of tax evasion described above using principal component analysis based on eigenvalue decomposition of the data covariance matrix. Principal component analysis is often used by social scientists for the purpose of data reduction. Originating from the correlation matrix of the included variables, this technique also enables us to learn more about the underlying relations between variables. Table 1: Grouping of explanatory variables into three groups by principal component analysis. Variable

PC1

PC2

PC3

Satisfaction with the State Revenue Servicea Satisfaction with the government’s tax policya Satisfaction with business legislationa Satisfaction with the government’s support to entrepreneursa (5) Entrepreneurs in my country believe that their tax money is spent appropriatelyb (6) Tax evasion is the response to a lack of government supportb (7) Tax avoidance is tolerated behaviora (8) Bribery is tolerated behaviora (9) Taxes are evaded more in difficult timesb (10) Evading taxes is the only way to surviveb (11) Firms always evade taxes to reduce costs, regardless of firm performanceb (12) Firms always evade taxes to reduce costs, regardless of government performanceb

0.287 0.413 0.368 0.382

0.156 0.231 0.258 0.215

0.026 0.154 0.006 0.033

0.322

0.151

0.069

0.307

0.012

0.128

0.175 0.146 0.230 0.300 0.209

0.017 0.089 0.357 0.320 0.506

0.622 0.654 0.212 0.220 0.134

0.174

0.542

0.167

(1) (2) (3) (4)

Note: Sample weights not applied. Source: Compiled by the authors. a Questions are assessed on a five-point scale: from 1 ¼ ‘very unsatisfied’ to 5 ¼ ‘very satisfied’. b Questions are assessed on a seven-point scale: from 1 ¼ ‘completely disagree’ to 7 ¼ ‘completely agree’.

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Table 1 reports the factor loadings of different variables under the assumption of three principal components. We do not apply sample weights in the principal component analysis (and econometric regressions performed later) since the correlations between managers’ agreements about different statements and assessments of tax evasion should not depend on firm size. In addition, our conditional estimations control for firm size. The principal component analysis suggests clearly that our proposed grouping of variables is reasonable. As we expected, the first six variables have the largest factor loadings related to the first principal component (PC1) and therefore can be grouped together. It is noticeable that all these variables capture satisfaction with government institutions or firms’ reciprocal behavior dependent on the quality of government institutions as a possible explanation leaving activities unreported. The last four variables also form a related group of variables (PC2) since they all share a common feature of having the largest factor loadings associated with the second principal component. All these variables are related to rational choice-based reasons for tax avoidance. Finally, the two variables measuring tolerance of tax evasion and bribery can be assigned into a third group (PC3) since they have the largest factor loadings in the third principal component.

The Econometric Analysis Perceived Tax Evasion and Various Firm Characteristics The aim of the analysis presented here is to shed light on the effect of traditional firmlevel explanatory variables on tax evasion. For each specification, we run three regressions using the managers’ perceived shares of unreported profits, employees and salaries as dependent variables. The regressions include various firm characteristics (size, sector, sales turnover, age and average wage) and the tenure and education of the manager who is responding to the survey as explanatory variables. We employ OLS regressions with heteroscedasticity-robust standard errors. The estimation results are reported in Appendix 2. Since the dependent variables are limited continuous variables that vary from 0 to 100 and many observations are clustered on round numbers (5, 10, 15 and so forth), we also experimented with an alternative estimation method as a robustness check. We created categorical variables from the original tax evasion measures allowing them to take values from 1 (for zero tax evasion) to 5 (when tax evasion exceeded 30 per cent). Thereafter we ran ordered probit regressions where we used the categorical variables of tax evasion as the dependent variables. The implications from these regressions were very similar to the OLS regressions and are therefore not reported. We run two regression specifications for each dependent variable. In the first specification all coefficient estimates are constrained to be the same across the three Baltic States. The regression results for this specification are reported in Table B.1.

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In the second we allow the estimated effects for firm size and sector to vary across the countries by interacting country dummies with sector- and size-related variables.10 The results for the second specification are reported in Table B.2. The interaction terms also control for the cross-country differences in the sample composition (different company sizes, fields of activity and other differences). The estimations for country dummies are statistically significant and substantial in magnitude for the share of unreported profits and salaries, whereas the estimated coefficients of other explanatory variables tend to be insignificant with only a few exceptions. The regression estimates for sectoral effects are mostly insignificant and no clear pattern emerges from them. This result does not correspond with the usual finding from the empirical literature that tax evasion is more prevalent in construction and services. Another traditionally important explanatory variable in tax evasion studies, firm size, also fails to become statistically significant. The only explanatory variable that has a statistically significant effect in all regression specifications is the experience of the manager who is responding to the survey. The managers’ experience measured in years is negatively related to perceived tax evasion. The lack of explanatory power of the usual firm characteristics is a strong indication that the company managers interviewed for the survey are not describing their own firm, but are actually reporting their perception of tax evasion for the sector as a whole. We also experimented with including in the regressions various variables that capture the extent of risk aversion. We were able to assess the relative risk aversion from the management practices of individual firms. According to the models of tax evasion based on behavioural choices, risk aversion is potentially an important driver of tax evasion or other forms of unreported economic activity. The regression results indicated that the level of risk aversion in a given company was not related with the perceived levels of unreported activity and the related estimates are therefore not reported. We interpret this result as yet another indication that the respondents were not describing their own company in their answers, even implicitly, but had in mind the overall level of tax evasion in the industries where their firms operated.

Perceived Unreported Activities and Reciprocity Next, we employ regression analysis for evaluating the extent to which company managers’ assessments of the scope of unreported economic activities can be explained by their perceptions of the quality of government services and reciprocal behavior towards government. For this purpose, we add the variables describing satisfaction with various aspects of governance and reciprocity to the benchmark 10

The second regression specification is the benchmark specification to which additional control variables are added in the analysis described in the following subsections. We also carried out regressions where all the included variables were interacted with country dummies. Since the coefficients of these interacted variables (besides sector and size) were insignificant and the inclusion of additional interactive variables did not alter the other estimated coefficients substantially, the results are not reported.

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regressions presented in Table B.2.11 The variables are added one-by-one as they are generally highly correlated. The estimated coefficients are reported in Table 2; the coefficients of other control variables are not reported. The negative relationship between the quality of government services and perceived tax evasion would appear to confirm the relevance of the theory of reciprocity for unreported activities in the Baltic States. The estimations imply that the perceived quality of government services is indeed negatively related with the perceived level of unreported activity. In other words, the company managers who have a more favourable opinion of government services also tend to believe that unreported activities are less prevalent. The estimated coefficients of the last two variables presented in Table 2 also indicate that reciprocity is an important factor influencing the perceptions of unreported activities in the Baltic States. The estimated slope coefficients can be interpreted as a percentage point change of one point in the perceived share of unreported activity associated with an increase in the level of satisfaction on the scale discussed above (that is, from 1 to 2, 2 to 3 and so forth). For example, it follows from Table 2 that in comparison to the firm managers who are unsatisfied with the performance of the State Revenue Service, those who have a neutral opinion believe that the average unreported share of profits is 1.4 percentage points (pp) lower, ceteris paribus. Some aspects of governance are more relevant for entrepreneurs’ reciprocal behavior than others. The estimated slope coefficients are negative and statistically significant for the following variables: performance of the State Revenue Service, quality of business legislation and the statement that tax evasion is the response to a lack of government support. These results are almost uniformly significant for all three aspects of unreported activities, that is, unreported profits, unreported employees and unreported salaries. The estimated effects are mostly insignificant for the remaining measures of the quality of governance: government tax policy, support to entrepreneurs and the entrepreneurs’ belief that their tax money is spent appropriately. The theoretical and empirical survey in previous sections highlighted that tax evasion is reciprocal to a large extent: firms are more likely to evade taxes when the public sector is less efficient and the government does not support entrepreneurial activity. The estimation results presented in Table 2 provide a similar picture for the three Baltic States. Satisfaction with government matters is negatively associated with the perceived extent of unreported activity. Moreover, firm managers agreeing with the statement that ‘Tax evasion is the response to a lack of government support’ also tend to perceive higher levels of unreported activity. The results are the strongest both in statistical and economic terms for governance matters such as revenue services and business legislation and also government effectiveness, while satisfaction with the tax policy seems to be of lesser importance.

11

We also estimated the relationships between the quality of government services and perceived tax evasion separately for the three Baltic States. The country-by-country regression results yield the same implications as the pooled regressions. The links are the weakest for Latvia, where most of the estimated effects are insignificant.

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Table 2: The extent of perceived tax evasion and satisfaction with government activities. Dependent variable Satisfaction with the state revenue servicea R2 Number of observations Satisfaction with tax policya R2 Number of observations Satisfaction with business legislationa R2 Number of observations Satisfaction with support to entrepreneursa R2 Number of observations Entrepreneurs in my country believe their tax money is spent appropriatelyb 2 R Number of observations Tax evasion is the response to the lack of government supportb 2 R Number of observations

Profits

Employees

Salaries

1.358* (0.761) 0.122 859 0.489 (0.691) 0.120 863 1.945** (0.798) 0.132 860 0.005 (0.668) 0.120 844 0.583 (0.407) 0.121 862 1.389*** (0.364) 0.134 857

1.377** (0.692) 0.080 860 0.224 (0.636) 0.076 864 2.015*** (0.639) 0.086 861 1.010 (0.651) 0.083 845 0.539 (0.346) 0.078 863 0.925*** (0.316) 0.085 858

1.409 (0.863) 0.114 857 0.976 (0.741) 0.112 861 3.331*** (0.767) 0.131 858 2.204*** (0.715) 0.122 842 1.189*** (0.445) 0.118 860 1.176*** (0.387) 0.118 855

Note: The table presents OLS regressions where the dependent variable is the perceived average percentage of profits, employees or salaries unreported to the tax authorities in the industry of a given firm. Heteroscedasticity-robust standard errors are reported in parentheses below the estimated coefficients. ***, ** , and * denote significance at 1, 5, and 10 per cent respectively. Source: Compiled by the authors. a For satisfaction questions, the scale is from 1 ¼ ‘very unsatisfied’ to 5 ¼ ‘very satisfied’. b For agreement questions, the scale is from 1 ¼ ‘completely agree’ to 7 ¼ ‘completely disagree’.

Perceived Unreported Activity and the Social Contract The extent of tax evasion depends on the prevailing norms in the society regarding what is considered to be acceptable business conduct. As indicated in the literature overview in the beginning of this chapter, various forms of unreported activities are less common in societies where they are less tolerated. It may therefore be expected that managers’ perceptions of unreported activity would be positively related with their assessment of how acceptable this behavior and other forms of illegal activity are. The SSE Riga survey asked the respondents to evaluate the level of

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tolerance of tax avoidance and bribery in their country. We used regression analysis to estimate the relationship between either of these two variables and the perceived extent of unreported activity. The regression results are presented in Table 3.12 The results confirm our expectations: all estimated slope coefficients are positive and statistically significant. This implies that the managers who answered that the perceived level of unreported profits, salaries or number of employees is larger were also more likely to agree that tax avoidance and/or bribery are tolerated. These findings indicate that managers’ assessments regarding a social contract are related to their evaluations of unreported activity. This yields relevance to the theory of the social contract as an explanation for tax evasion in the Baltic countries.

Perceived Unreported Activity and Rational Choice Tax compliance may also depend on the economic conditions facing the firms. Economic hardship may lead firms into a fight for survival in which it is beneficial for them to take more risks. Tax evasion can be a rational choice if the probabilityweighted expected cost of being caught evading taxes and subsequently punished is smaller than the expected benefit associated with tax evasion. Four questions in the SSE Riga survey allow us to assess the extent to which the perceived tax evasion can be explained by rational choices. The first two of these questions (presented as

Table 3: The extent of perceived tax evasion and absolutist values. Dependent variable Tolerance of tax avoidance R2 Number of observations Tolerance of bribery R2 Number of observations

Profits

Employees

Salaries

2.242*** (0.631) 0.134 859 1.306** (0.639) 0.119 854

1.218** (0.559) 0.082 861 1.218** (0.549) 0.082 855

2.434*** (0.649) 0.127 858 1.431** (0.666) 0.113 852

Note: See the note for Table 2 for the description of regressions. Source: Compiled by the authors.

12

We also performed the same analysis separately for each of the three Baltic States. This indicates that the positive relationship between the perceived level of tax avoidance and tolerance of illegal activities is present for Estonia and Lithuania, whereas almost all estimated coefficients are insignificant in the case of Latvia.

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explanatory variables in Table 4) relate tax evasion to economic hardship, assessing managers’ degree of agreement with statements that tax evasion is justified in cases of economic hardship or threat to survival. The last two of the questions identify rational choice as the reason for tax avoidance in absolute terms, regardless of firm or government performance. Table 4 shows the regression results where the four variables described above are added to the benchmark regressions (presented in Table B.2) one-by-one. The estimated effects are positive and statistically significant for all regression specifications. This implies that managers who think that taxes are evaded more in difficult times; who agree that evading taxes is the only way to survive; and who believe that taxes are evaded since this reduces business costs are also more likely to perceive that tax evasion is widespread. Interestingly, for all the variables reported the effect is the strongest on taxes evaded on salaries. This indicates that the rational choice-based reasons have the strongest impact for this form of tax evasion and that under economic hardship taxes on salaries are the first to become unreported.

What Explains the Cross-Country Differences in Perceived Unreported Activity? The regression estimations (presented in Appendix 2) imply that there are significant differences between the three Baltic States in the perceived level of unreported Table 4: The extent of perceived tax evasion and rational choice. Dependent variable Taxes are evaded more in difficult times R2 Number of observations Evading taxes is the only way to survive R2 Number of observations Firms always evade taxes to reduce costs, regardless of firm performance R2 Number of observations Firms always evade taxes to reduce costs, regardless of government performance R2 Number of observations

Profits

Employees

Salaries

1.152*** (0.359) 0.130 860 1.622*** (0.347) 0.141 861 0.648*

1.391*** (0.325) 0.096 861 1.291*** (0.319) 0.094 862 0.804**

2.175*** (0.389) 0.144 858 2.279*** (0.376) 0.148 859 1.677***

0.122 856 0.833**

0.082 857 0.767**

0.128 854 1.808***

0.125 857

0.082 858

0.130 855

Note: See the note for Table 2 for the description of regressions. Source: Compiled by the authors.

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activity. The estimated effects for country dummies are significantly negative for both Estonia and Lithuania in regressions of unreported profits and salaries and insignificant in the third regression (unreported employees). This indicates that the perceived share of unreported activity tends to be larger in Latvia than in the other two Baltic States for profits and salaries, but not for the reported number of employees. The purpose of this section is to see whether the cross-country differences in perceived tax evasion persist after controlling for the traditional firm-level control variables in regressions. Thereafter we test the impact of including additional control variables in the regressions, which capture various reasons for tax evasion: reciprocity towards government, social norms regarding illegal activities, and variables capturing rational choice-based reasons for tax evasion. We also assess which of these three groups of variables can explain more of the tax evasion in Baltic countries by including in the regressions factor scores arrived at from the principal component analysis presented in the previous section. Table 5 gives an overview of the cross-country differences in tax evasion after the inclusion of various controls. We present the coefficients of Estonian and Lithuanian country dummies while holding Latvia as a control group. The first section of the table shows the estimated effects for regressions which include country dummies as the only control variables. The results show that compared to the situation in Latvia, Estonian and Lithuanian unreported activity is lower for profits and salaries, while for employees only Lithuania differs statistically significantly from Latvia. The perceived level of unreported profits is about 10 percentage points lower in Estonia and Lithuania than in Latvia. This difference is approximately 9 pp for Estonia and 13 pp for Lithuania for salaries. Looking at the unreported share of employees, there is no significant difference between Estonia and Latvia, whereas the share of unreported employment is about 4 pp lower in Lithuania than in Latvia. The second section of Table 5 presents results that also include firm and respondent characteristics and interactive terms as controls (control variables are similar to the benchmark regressions with interactive terms, see Table B.2 for the full set of control variables). The results imply that in comparison to the situation in Latvia, the perceived share of unreported profits is 20 pp lower in Estonia and 9 pp lower in Lithuania. For salaries, the estimated share is 15 pp lower in Estonia and 13 pp lower in Lithuania than in Latvia. The results imply that the country-level differences remain present after controlling for differences in sampled business characteristics and respondent characteristics. When we include the factor scores depicting reciprocity towards the government, social norms and rational choice into the regression, only two out of six country dummies remain statistically significant. Controlling for tax morale explains differences between Estonia and Latvia in the shares of unreported employees and salaries, while the coefficient of the country dummy for Estonia remains significantly negative for unreported profits. The latter can be assigned to Estonia’s generous corporate income tax system that, unlike the systems in the other two Baltic States, does not tax retained earnings. However, in principle this generous aspect should be

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Table 5: Cross-country differences in perceived tax evasion. Dependent variable

Profits

Country dummies only (Control group: Latvia) Estonia 9.792*** (1.483) Lithuania 9.630*** (1.359)

Employees

Salaries

0.127 (1.302) 3.584*** (1.142)

8.482*** (1.531) 12.784*** (1.356)

R2

0.051

0.009

0.065

Number of observations

1233

1239

1241

Baseline estimation from Table B.2 (with country interaction terms) Estonia 19.803*** 6.935 (6.281) (5.296) Lithuania 8.612* 2.685 (5.203) (4.661) R2 Number of observations

14.667** (5.715) 12.774*** (4.562)

0.119

0.076

0.110

865

866

863

Baseline estimation from Table B.2 (with country interaction terms) and tax morale PC1: reciprocity towards government 1.826*** 1.798*** 3.324*** (0.466) (0.399) (0.467) PC2: rational choice 0.919 1.123** 2.187*** (0.570) (0.550) (0.610) PC3: social norms 0.672 0.064 0.528 (0.742) (0.653) (0.786) Estonia 14.888** 1.242 2.750 (6.333) (5.556) (6.152) Lithuania 7.747 0.961 9.436* (5.561) (4.948) (4.954) 2 R 0.140 0.107 0.176 Number of observations

809

811

808

Note: See the note for Table 2 for the description of regressions. Source: Compiled by the authors.

captured by the reciprocity towards the government component. The differences between Lithuania and Latvia remain statistically significant only for unreported salaries. In addition, the difference in unreported profits remains sizeable, although statistically significant. In conclusion, the inclusion of various explanatory variables which are correlated with tax evasion helps to explain the cross-country differences between the three Baltic States regarding tax evasion but does not render all the estimated coefficients of the country dummies insignificant. This indicates that there may be other possible

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explanations for cross-country differences in tax evasion that we could not capture in the current analysis. A comparison of the importance of the three factor scores formed from of the principal components analysis suggests that the first and the second scores are statistically significantly related to unreported activity, whereas the estimated coefficients of the third score are small in magnitude and insignificant. This means that reciprocity towards governance quality and various rationality-based arguments are relevant for explaining unreported activities in the Baltic States. Surprisingly, the impact of social norms, which we assess on the basis of tolerance of tax avoidance and bribery, has but little explanatory power.

Conclusions and Implications This chapter considered managerial (dis)honesty in the form of economic activity not reported to the authorities. Management may decide to act in a dishonest way and leave profits, employment, wages, and other data unreported in order to evade taxes or government regulation and in this way attain economic benefits. Evidently, such dishonesty has important implications for government operations and for the society at large. There are two main strands of theories explaining unreported economic activity. The first strand consists of theories that assume that the decision-maker behaves as homo economicus. The decision-maker is strictly individualistic, rational and only concerned about pecuniary measures. Some of these theories recognize that the decision-making problem may be very complex and entail uncertainty that is difficult to determine, and this may lead to a behavioural choice that is not strictly rational. The second strand of theories posits that non-individualistic factors play a role in the decision of the management to leave economic activities unreported. It is possible to distinguish between three, arguably related, reasons. First, the management might have absolutist values that affect the psychic costs of tax evasion. Second, the management might see taxation as a reciprocal payment for government activities and therefore see tax obligations as necessary and fair. Third, the management might see tax payments as relating to a social contract according to which everybody has to contribute to the society. The three explanations of nonindividualistic preferences may together be seen to encapsulate a tax morale or, more broadly, societal morale according to which decisions regarding tax evasion or other unreported activities are not driven entirely by narrow motives of selfinterest. The theory of tax evasion makes it reasonable to hypothesize that individualist as well as non-individualistic motives are of importance for the extent of unreported activity. This chapter investigated the linkages between unreported economic activities by firms operating in the Baltic States and different explanatory factors related to individualistic and non-individualistic motives. The analysis was based on the SSE Riga survey from 2010, which covers firms operating in Estonia, Latvia and

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Lithuania (Sauka & Putnins, 2011). In the survey the managers interviewed were asked to assess the prevalence of unreported profits, employment and wages in their industry and to give their view on a range of questions relating to their firm, sector or country. The three Baltic States share many features. They have seen rapid, although unstable, economic growth since 1991, but were in 2010 still among the countries in the European Union with lowest per capita income. They were strongly affected by the initial phase of the global financial crisis, but 2010 was a year of stabilization. The industrial structures of the economies are broadly comparable. The tax systems are quite similar although the Estonian corporate tax system differs from those in the other two countries by only taxing distributed profits. The formal framework of regulation and governance is shared among the countries as they are all members of the European Union, but administration and governance are typically rated to be more effective in Estonia than in Lithuania and Latvia. According to the SSE Riga survey, Latvia generally stands out as having the highest prevalence of perceived unreported activity in 2010, although the differences are not substantial across the three Baltic States. The shares of unreported profits were around 20 per cent of total profits in Estonia and Lithuania and 26 per cent in Latvia. The extent of unreported employment is relatively similar across the Baltic States at around 14–17 per cent of total employment. Finally, the share of undeclared wages in total wages was the smallest in Lithuania at 22 per cent, slightly larger in Estonia at 24 per cent and the largest in Latvia at 31 per cent. These sample-weighted percentage shares are based on the perceptions of managers and are, evidently, estimated with substantial uncertainty. The empirical analysis evolved in three stages. The first stage was a clustering or principal component analysis in which the different explanatory variables were mapped into three different clusters. The first group assigned the largest weights to the set of variables which are related to perceptions of reciprocity towards the government. The second group gave the largest weights to a group of variables that can be linked to rational-choice motives for unreported activities. Finally, the third group assigned the largest weights to variables capturing social norms and tolerance of various illegal activities such as tax evasion and bribery. The principal component analysis confirmed the interpretation of the different explanatory variables in the dataset and also brought down the dimensionality of the set of explanatory variables. The second stage of the empirical analysis was conducting regression analyses in which the unreported activities perceived by the management interviewed were explained by various variables reflecting different motives for unreported economic activity. The analysis showed that a number of variables reflecting firm and management characteristics exhibit only little explanatory power as regards the perceived extent of unreported activity. This is an indication that the respondents in the SSE Riga survey were indeed reporting their perception of unreported activity in the industry, not the unreported activity in their own firms. In the end, firm and management characteristics were included as control variables without any particular interpretation.

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In general, the regression results were supportive of all the theories of unreported activity which we were able to test given the data limitations. We found that the quality of various forms of government service was negatively related with the perceived extent of unreported activity. The importance of reciprocity towards the government services was also confirmed by the regression analysis. Four questions in the SSE Riga survey allowed us to assess the extent to which the perceived unreported activity stems from rational choice motives. The estimations indicated that the variables capturing rational choice motives were positively related to the perceived extent of unreported activity.13 Finally, the social norms or the perception of a social contract also seems to be of importance. In particular, the managers’ assessments of the prevalence of (negative) social norms, such as tolerance of tax evasion or bribery, were positively related to the perceived level of unreported activity. The third stage of the empirical analysis sought to assess the relative importance of the different motives for unreported activity in each of the three Baltic States. The analysis employed the factor scores formed from the principal component analysis in order to reduce the ‘curse of dimensionality’ in the estimations. In particular, we used the scores of the principal component analysis since the answers to the individual survey questions tended to be strongly correlated and the survey included a relatively low number of observation points for each country. The reasons linked to reciprocity towards the government turned out to be the most relevant for explaining cross-country differences in perceived unreported activity, which is an expected result given that the assessment of the quality of government services differs quite substantially across the three Baltic countries. Also relevant, although to a lesser extent, appeared to be the set of variables reflecting individualistic rational behavior. The group of variables capturing social norms had no explanatory power in the regressions. Overall the results highlight a complex interaction between unreported economic activity and individualistic and non-individualistic motives. The main result in this survey of perceptions by managers in the Baltic States is a close correlation between the extent of unreported activity and the role of the government. The relevance of individualistic or profit-motivated behavior is also supported by our analysis. Given the data limitations, we were not able to analyze which set of explanatory factors managers consider more important — whether they put more emphasis on individualistic or non-individualistic motives for tax evasion and unreported activity. The assessment of the relative importance of motives for different theories of tax evasion would be an interesting avenue for the future research.

13

It is noticeable that the support for rational choice as a reason for tax evasion unconditionally from firm or government performance is very low among Baltic firm managers: only about 10 per cent of them supported the view of tax evasion as a purely rational choice in absolute terms. This yields support for other non-individualistic reasons for tax compliance.

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Acknowledgements The authors would like to thank Katrin Humal, Maaja Vadi and Tiia Vissak for useful comments to an earlier version of the paper. Karsten Staehr acknowledges support from Estonian Base Financing grant no. B617A and Estonian Target Financing grant no. SF0140059s12. Jaanika Meriku¨ll acknowledges financial support from the Estonian Science Foundation grant no. 8311. The views expressed are those of the authors and not necessarily those of Eesti Pank (Bank of Estonia).

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Torgler, B., & Schneider, F. (2006). What shapes attitudes toward paying taxes? Evidence from multicultural European countries. IZA Discussion Paper, 2117. Retrieved from http:// ftp.iza.org/dp2117.pdf Uslaner, E. M. (2010). Tax evasion, corruption, and the social contract in transition. In J. Alm, J. Martinez-Vazquez & B. Torgler (Eds.), Developing alternative frameworks for explaining tax compliance (pp. 206–225). New York, NY: Routledge. Vihanto, M. (2003). Tax evasion in a transition from socialism to capitalism: The psychology of the social contract. Journal of Socio-Economics, 32(2), 111–125. Webley, P., Robben, H., Elffers, H., & Hessing, D. (1991). Tax evasion: An experimental approach. Cambridge: Cambridge University Press. Williams, C. (2008). Envelope wages in Central and Eastern Europe and the EU. PostCommunist Economies, 20(3), 363–376. Williams, C. (2009). The prevalence of envelope wages in the Baltic Sea region. Baltic Journal of Management, 4(3), 288–300. World Bank. (2012). Worldwide governance indicators. Retrieved from http://info.worldbank. org/governance/wgi/index.asp World Values Survey. (1999). Online Data Analysis 19992004, Estonia [1999], Latvia [1999], Lithuania [1999]. Retrieved from http://www.worldvaluessurvey.org/ Yitzhaki, S. (1974). A note on income tax evasion: A theoretical analysis. Journal of Public Economics, 3(2), 201–202.

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Appendix 1 Table A.1:

Descriptive statistics of the key indicators of the econometric analysis. Estonia Mean

S.D.

Lithuania Mean

Share of profits, employment and wages evaded, in per cent Unreported profits 19.6 19.9 20.2 Unreported employment 15.9 18.4 14.0 Unreported wages 24.2 21.0 21.8 Reciprocity towards government: Perception of government 3.69 0.82 Satisfaction with the State Revenue Servicea Satisfaction with the government’s tax 3.35 1.01 policya Satisfaction with business legislationa 3.43 0.88 Satisfaction with the government’s 2.99 1.03 support for entrepreneursa Entrepreneurs in my country believe 3.77 1.89 that their tax money is spent appropriatelyb 3.72 2.01 Tax evasion is the response to a lack of government supportb

S.D.

Mean

S.D.

17.2 15.0 17.8

25.8 17.4 30.5

21.0 19.5 22.1

performance 3.33 0.94

2.81

1.17

2.34

1.06

2.02

0.83

2.56 2.03

1.02 1.07

2.70 2.15

0.80 1.09

2.15

1.65

1.81

1.23

4.61

2.01

5.03

1.91

3.39 3.75

1.27 1.28

2.21 1.74

1.21 1.00

2.09

3.95

1.89

4.51

2.00

2.13

3.96

2.08

4.71

2.02

3.17

1.81

3.64

1.75

3.34

1.73

3.35

1.82

3.34

1.73

3.12

1.69

Social norms: Tolerance of tax avoidance and bribery Tax avoidance is tolerated behaviora 2.55 1.15 2.16 1.15 Bribing is tolerated behaviora Rational choice: Rational reasons for tax evasion 4.04 Taxes are evaded more in difficult timesb Evading taxes is the only way to 3.48 surviveb Regardless of how the company performs, evading taxes is the way to decrease business costsb Regardless of government’s entrepreneurship policy, evading taxes is the way to decrease business costsb

Latvia

Note: S.D. indicates the standard deviation. Means and standard deviations are calculated using sample weights. Source: compiled by the authors. a Questions are assessed on a five-point scale: from 1 ¼ ‘very unsatisfied’ to 5 ¼ ‘very satisfied’. b Questions are assessed on a seven-point scale: from 1 ¼ ‘completely disagree’ to 7 ¼ ‘completely agree’.

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Appendix 2 Table B.1:

The perceived share of undeclared activity and firm characteristics. Profits

Employees

Salaries

12.781*** (2.005) 6.264*** (1.743)

2.337 (1.753) 2.226 (1.470)

9.515*** (2.022) 10.619*** (1.786)

Sector (Reference group: manufacturing) Wholesale 1.602 (2.280) Retail 2.052 (2.680) Services 0.966 (2.079) Construction 2.450 (2.685) Other 3.289 (2.486)

4.468** (2.073) 4.213* (2.340) 3.945** (1.889) 0.819 (2.422) 4.345* (2.612)

3.563 (2.494) 3.466 (2.648) 0.288 (2.213) 3.078 (2.835) 0.990 (3.233)

Firm size (Reference group: number of employees W 100) 1–5 employees 2.896 (3.417) 6–9 employees 1.472 (3.330) 10–19 employees 3.216 (3.043) 20–49 employees 5.327* (2.838) 50–99 employees 3.228 (3.242)

2.858 (3.393) 3.767 (3.103) 0.169 (2.668) 0.641 (2.405) 3.358 (2.449)

0.486 (3.621) 1.174 (3.644) 4.556 (3.285) 4.356 (2.995) 4.347 (3.266)

Country (Reference group: Latvia) Estonia Lithuania

Sales turnover (Reference group: 0–35,000) 35,000–130,000 5.754* 0.448 (3.106) (2.865) 130,001–600,000 4.874 2.759 (3.306) (2.841) 600,001–2,500,000 1.925 1.994 (3.740) (3.027) More than 2,500,000 0.144 1.893 (4.066) (3.622) The manager’s level of education (Reference group: less than secondary) Secondary 1.790 0.058 (3.228) (2.635) BA/engineering degree 1.494 0.154 (2.191) (2.133)

0.954 (3.093) 0.923 (3.146) 2.127 (3.536) 0.019 (3.977) 0.924 (3.348) 0.669 (2.279)

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Table B.1: (Continued )

Masters/doctoral degree The manager’s experience (years) Log (firm average wage) Log (firm age) R2 Number of observations

Profits

Employees

Salaries

4.385* (2.494) 0.242** (0.098) 0.230 (1.306) 0.546 (1.563)

1.373 (2.401) 0.205** (0.089) 0.078 (0.748) 1.350 (1.487)

0.447 (2.708) 0.258** (0.101) 0.185 (1.148) 2.909** (1.429)

0.097

0.054

0.091

865

866

863

Note: See the note for Table 2 for the description of regressions. Source: Compiled by the authors.

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Table B.2: The perceived share of undeclared activity and firm characteristics interacted with country dummies.

Country (Reference group: Latvia) Estonia Lithuania

Profits

Employees

Salaries

19.803*** (6.281) 8.612* (5.203)

6.935 (5.296) 2.685 (4.661)

14.667** (5.715) 12.774*** (4.562)

2.014 (3.833) 0.885 (4.293) 1.148 (3.329) 5.458 (5.852) 11.492*** (2.972)

3.563 (2.494) 3.466 (2.648) 0.288 (2.213) 3.078 (2.835) 0.990 (3.233)

Sector (Reference group: manufacturing) Wholesale 2.411 (4.081) Retail 5.569 (4.094) Services 5.363 (3.587) Construction 8.960 (6.133) Other 5.709 (4.444)

Firm size (Reference group: number of employees W 100) 1–5 employees 1.604 1.275 (4.742) (4.799) 6–9 employees 1.828 0.072 (4.821) (4.203) 10–19 employees 8.547* 3.432 (4.619) (4.005) 20–49 employees 13.098*** 4.359 (4.291) (3.666) 50–99 employees 4.733 3.045 (4.981) (4.250) Sales turnover (Reference group: 0–35,000) 35,000–130,000 6.251* (3.199) 130,001–600,000 5.674 (3.476) 600,001–2,500,000 2.517 (3.836) More than 2,500,000 0.545 (4.213)

0.098 (2.906) 3.128 (2.963) 2.076 (3.126) 2.071 (3.733)

2.756 (4.931) 4.608 (5.076) 11.093** (4.755) 10.858** (4.424) 8.677* (5.157) 1.239 (3.105) 1.147 (3.267) 2.304 (3.654) 0.440 (4.179)

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Table B.2: (Continued ) Profits

Employees

The manager’s level of education (Reference group: less than secondary) Secondary 2.402 0.711 (3.290) (2.671) BA/engineering degree 1.201 0.214 (2.228) (2.145) Masters/doctoral degree 3.872 1.024 (2.548) (2.390) The manager’s experience 0.247** 0.212** (years) (0.099) (0.090) Log (firm average wage) 0.134 0.200 (1.315) (0.784) Log (firm age) 0.723 1.548 (1.605) (1.536) Interacted dummies Estonia  wholesale Estonia  retail Estonia  services Estonia  construction Estonia  other Estonia  1–5 employees Estonia  6–9 employees Estonia  10–19 employees Estonia  20–49 employees Estonia  50–99 employees Lithuania  wholesale Lithuania  retail Lithuania  services

3.330 (6.067) 2.851 (6.705) 7.305 (5.064) 10.024 (7.451) 2.975 (6.302) 12.038* (6.289) 12.281* (6.612) 11.800* (6.590) 19.605** (7.750) 0.658 (7.316) 9.418* (5.250) 9.133 (6.396) 6.234 (5.197)

2.579 (5.884) 3.674 (6.636) 3.868 (4.884) 6.643 (7.094) 11.179** (5.601) 5.909 (5.363) 11.041* (5.678) 4.906 (5.202) 12.298** (5.655) 0.717 (5.874) 4.833 (4.676) 7.533 (5.063) 4.858 (4.508)

Salaries 1.299 (3.423) 0.343 (2.299) 0.050 (2.727) 0.238** (0.102) 0.208 (1.189) 3.161** (1.453) 7.608 (6.982) 8.562 (7.869) 8.384 (5.634) 6.404 (7.212) 1.220 (8.020) 10.283* (5.683) 14.442** (6.600) 10.427 (6.789) 14.788** (7.034) 10.122 (10.469) 12.634** (5.472) 9.942* (5.403) 9.960** (4.787)

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Table B.2: (Continued )

Lithuania  construction Lithuania  other Lithuania  1–5 employees Lithuania  6–9 employees Lithuania  10–19 employees Lithuania  20–49 employees Lithuania  50–99 employees R2 Number of observations

Profits

Employees

Salaries

7.124 (7.543) 0.524 (5.910) 9.187 (6.588) 1.021 (6.152) 11.757** (5.874) 13.656** (5.362) 6.616 (7.069)

4.306 (6.993) 5.656 (5.832) 2.012 (5.852) 1.466 (5.464) 8.540* (4.835) 5.112 (4.710) 1.709 (5.349)

2.435 (8.206) 2.663 (7.655) 4.003 (6.164) 8.540 (6.623) 15.526*** (5.518) 12.393** (5.355) 9.095 (6.974)

0.119

0.076

0.110

865

866

863

Note: See the note for Table 2 for the description of regressions. Source: Compiled by the authors.

Chapter 6

Firm Bankruptcies and Violations of Law: An Analysis of Different Offences Oliver Lukason

Abstract Purpose — The main aim of the paper is to study the occurrence and connections of different pre-insolvency violations of law on the example of Estonian firms. Design/methodology/approach — The study is based on the whole population financial data of Estonian bankrupt firms and all publicly available court judgments about firm insolvencies from the period 2002–2009. Three types of violations have been considered: non-submission of annual reports, violations of net asset requirement and elements of criminal offence. Findings — The paper shows that non-submission of annual reports is common for insolvent firms but its occurrence varies through insolvency years and types. A similar finding can be attributed to net asset requirement violations. Elements of criminal offence are also frequent, but their occurrence is not different through insolvency years, industries and firm size groups. Elements of criminal offence and net asset requirement violations are not likely to exist together. Although medians of several pre-insolvency financial variables are significantly different in case of firms where criminal offence elements were found, they are not useful for offence prediction. Research limitations/implications — Statistical analysis limitations of the current study are mainly associated with the content of the data, because the dataset itself covers the whole population of publicly available information. The application of some results in different countries might be limited because of differences in legislation and its implementation. The study outlines novel information about and connections of different pre-insolvency violations which could be applied for relevant theory-building or more elaborate empirical research in the future.

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 127–146 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010010

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Practical implications — The study can be used by managers, owners, creditors and other stakeholders of firms to improve detection of possible pre-insolvency violations. Social implications — Regulators and regulation implementers can make use of the study when considering a change in legal framework or in its practice. Originality/value — The paper shows the presence of selected pre-insolvency violations on an extensive dataset. Previous studies have mainly been theoretical, qualitative or using small datasets. Keywords: Bankruptcies; offences; violations of law

Introduction Dishonest behavior has always accompanied business, as people often consider self-interest more important than accounting with other parties. Numerous academic studies have been published on the topic, but still large-scale empirical evidence cannot be found about several sub-topics. In the corporate context different forms of dishonesty can be found: for example, domains like unethical behavior, lying, nondisclosure of information, theft, and criminal offences have been elaborated in literature. Each of those domains can encompass various violations: for instance, according to Ostas (2007, p. 571) fraud can take various forms, like ‘‘the submitting of false claims, tampering with scales and measures, false bookkeeping, tax evasion, and intentionally lying in contractual negotiations.’’ Drawing the line between different forms of dishonesty — for example, discriminating between criminal and unethical behavior — is often not unambiguous (Pontani, 2004). Such an issue can emerge from several reasons, among them from different theories of punishment (see, e.g., Goldman, 1982) and variance in the setup of legal systems and/or their implementation (see, for instance, Rajak, 2011). There is a multitude of evidence that firm insolvencies are often associated with various types of dishonesty, especially violations of law (see, e.g., Anderson, 1997; Bollen, Mertens, Meuwissen, Schelleman, & Van Raak, 2005). From one standpoint it is logical, as agency conflicts can arise in a collapsing or a collapsed firm, as managers and owners try to satisfy their own interests and creditors try to prove the mismanagement of firm for achieving higher satisfaction rate for their claims. On the other hand, different forms of dishonesty are often not studied in non-failed firms, which can bring to serious underestimations of faulty behavior for a given set of firms. For an empirical analysis of corporate violations of law, Estonia is an interesting research object. Although being a member of the European Union (EU), Estonia can be considered less developed than older EU countries, being therefore categorized as a post-transition (Masso & Vahter, 2008) or a catching-up economy (Masso, Roolaht, & Varblane, 2012). Such a classification is mostly based on the comparison of welfare indicators, but also on a short time being in a market economy system. It

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has been suggested that in less developed countries different violations of law could be more common (Lotspeich, 1995). From another point of view, Estonian business, insolvency and penal legislations are relatively similar to highly developed European Union countries — for example, Germany and Finland — which makes the results of an empirical analysis comparable. Of course a separate question lies in the regulation implementation efficiency. Also, databases to detect different forms of violations are rather advanced in Estonia and large-scale datasets can be easily acquired for the analysis. Events during the past few years at world financial markets shook Estonian economy considerably, the drop in GDP between years 2008 and 2009 being around 15% and even in 2011 Estonia had not yet recovered to the GDP level of 2008. This has caused the number of firm insolvencies to rise sharply and the ratio of insolvencies to the total number of companies (all registered, not only active firms) peaked at 0.9% in 2009. This, in turn, enables to involve both the economic growth and downsizing periods in the analysis. Derived from the above discussion, the objective of this paper is to study the occurrence and connections of different pre-insolvency violations of law on the example of Estonian firms. For achieving it, the paper is divided to following sections. Introduction is followed by a short literature review which clarifies the taxonomy of violations and extracts some important findings from available studies. After that empirical analysis will be conducted, which starts with the clarification of datasets and variables for analysis, but also offers more detailed insight to the Estonian legal system and its implementation. Thereafter, descriptive statistics of different violations will be outlined and tests conducted to study whether the occurrence of violations varies in time and through different firm types. Also, connections between different violations are studied and finally it will be detected whether the financial data of firms where these violations occurred systematically differ from those where they did not. The study is finalized with conclusive remarks.

Firm Insolvencies and Violations of Law in Previous Studies The literature offers several classifications about law violations associated with firm insolvencies. For instance, it is possible to use classifiers like time, affected parties (victims), criminality, domain, legal origin, intent or beneficiary for establishing the taxonomy of violations. Time refers to whether the violation has been committed before insolvency has been officially declared (i.e., the firm goes bankrupt) or if it occurs during insolvency proceeding. For determining affected parties, the following categories could be used (Anderson, 1997): investors, creditors, banks and other financial institutions, central or local government and financial markets. Criminality refers to the fact whether the violations have been penalized in the laws of the specific country. The domain of violation points to which functional field is abused: for example, accounting, finance, production, or personnel management. In broader terms the violation can be directed to the abuse of general or specific management

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responsibilities. The legal origin means what is the specific law the violation conflicts with. Intent refers to whether the violation was performed deliberately or not. The beneficiaries of the violation can be the firm’s employees (including management), owners, both of them or third parties. The previous description shows a variety of possibilities for classifying violations and now, examples of their use in empirical studies will be discussed. The non-submission of or manipulation with accounting information has not only been viewed as commonly coinciding with failed firms, but also as an important predictor of firm failure (Argenti, 1976; Keasey & Watson, 1987, 1988). Reporting delays are very common in insolvent firms (Lawrence, 1983; Whittred & Zimmer, 1984). Misstatement of accounting information can take various forms, like improper revenue recognition, overstatement of assets, understatement of expenses, misappropriation of assets, inappropriate disclosure, whereas given forms can be disguised through related party transactions (Beasley, Carcello, Hermanson, & Neal, 2010). In the context of failing or insolvent firms earnings manipulation has been especially emphasized (see, for instance, Rosner, 2003). There has been a lot of academic discussion about the auditors’ role in detecting management fraud (see, e.g., Caplan, 1999; Newman & Noel, 1989; Shibano, 1990), but this mostly concerns larger firms, as in several countries (including in the European Union) the performance criteria making auditing compulsory for firms are rather high. A distinct category of firms has been outlined, which are founded not for economic activities, but instead to implement some fraud, referred to as firms serving other interests in the study by Crutzen (2009). Crutzen divided such firms to those serving the purpose of enriching the entrepreneur, sheltering the interests of some other organizations or firms with fraudulent activities. As a development of the above, it would probably be reasonable to make a distinction between those firms which have been founded to serve other interests, and firms, which start it at some point of their life-cycle. An important connection between high leverage and firm failure has been detected (Opler & Titman, 1994). The literature reviews of Dimitras, Zanakis, and Zopounidis (1996) and Bellovary, Giacomino, and Akers (2007) have indicated that high debt to assets and low equity to assets ratios of failing firms in comparison of surviving firms have been common even during several years before permanent insolvency. Numerous studies would suggest that equity becomes negative or at least very low before the failure (see, e.g., Altman, 1968; Ohlson, 1980). This is at least partially supported by the fact that in most bankruptcy proceedings, creditors’ claims are not fully satisfied (see The World Bank, doing business database). As regulations of most countries do not allow equity to be negative (at least for a lengthy time), then based on the above it could be assumed that violations of the given requirement are common to insolvent firms. Of course, in cases the creditors are secured and they acknowledge the risk of possible failure (i.e., they include it to their lending practices) such an action might not even have ethical issues. On the other hand, borrowing from unsecured creditors in the case of negative equity and knowing that future failure is likely, at the same time also not disclosing the firm’s financial situation, is surely not ethical, but also criminalized in many countries.

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Besides the violations mentioned in the above, there are numerous violations specific to certain legal environments: for example, company duplication issue referred by Rotem (2011).

An Empirical Analysis of Insolvent Firms’ Law Violations in Estonia Data and Methodology For the current analysis two different datasets have been used, namely the Estonian Commercial Register (ECR) database and the Estonian Court Information System (ECIS) database. Information is retrieved from the databases for the period of 2002–2009. ECR data includes firms’ financial information and other general data of firms. More specifically, the empirical analysis applies the following data from ECR, whereas most important data limitations have also been outlined: 1. Information whether firms have submitted annual reports or not. The analysis does not consider the fact whether firms have violated the submission date set in law and information is just retrieved whether the annual report is present in the register or not. In addition, the content of the reports will not be studied — for instance, if there are any violations of accounting regulations — and just the presence of the document will be considered. 2. Financial data from annual reports, namely from the balance sheet and profit statement. As with all studies of small- and medium-sized enterprises (especially from transformation societies), the annual reports might not be punctual about the financial situation, as there can be undeclared events, accounting errors, intentional manipulation of accounts and other reasons. Still, the information must be treated as it is and the list of specific variables applied will be outlined below. 3. Firms’ main industries determined in the annual reports. The issue concerning industries is the fact that firms might be active in several sectors or the main industry reported does not generate the largest sales revenue when compared to other fields the firm is active in. Still, there were no digital data available about different fields the firm was active in, so information about the main industry has to be treated as it is. 4. Number of employees. The given data are available as a continuous variable, but for the analysis purposes size groups will be formed. This is achieved by using the division based on the European Commission regulation 96/280/EC, which recommends using the following groups according to the number of employees: (1) 1–9, (2) 10–49, (3) 50–249 and (4) 250–499. 5. Firm’s insolvency type according to the Estonian Bankruptcy Act (EBA). EBA outlines two different insolvency procedures which are also common to some other countries. If a firm does not have enough resources left in the bankruptcy estate to finance the bankruptcy proceeding, the court supervised process will be discontinued and the firm will be deleted from ECR (referred to as an abatement of

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bankruptcy proceeding). In this case the creditors’ claims are satisfied at a rate of 0%. The other option is when bankruptcy is declared (the case where there are enough resources to conduct the proceeding), although even in this situation it might emerge after some time that there are no resources for continuing the proceeding, and abatement will arise after the bankruptcy declaration. As post-bankruptcy declaration abatement of proceeding is rather uncommon according to statistics, those cases will not be outlined separately. There are several reasons why to study those two groups of insolvencies separately. First, as in the case of proceeding abatements there are no resources to study previous events thoroughly, such cases get less attention than declarations and therefore some violations might remain undetected. Second, pre-insolvency exhaustion of all assets can probably point to a higher likelihood of bad management practices. In the current study bankruptcy declarations and bankruptcy proceeding abatements together will be referred to as insolvencies and in the case their distinction is necessary, then the two given terms will be applied. In order the empirical analysis to be profound, as financial data the majority of available balance sheet and profit statement variables have been applied. Excluded are those variables in case of which there is a lot of missing information, partly because a large proportion of firms just do not use those accounts in their reporting. Information from cash flow statements is not applied, as that data are missing for six years out of ten in the analysis. From balance sheets the following variables have been used (with abbreviations in brackets): assets (ASSETS), liabilities (LIABIL), equity (EQUITY), current assets (CASSETS), cash and cash equivalents (CASH), accounts receivables (RECEIV), current liabilities (CLIABIL), current financial liabilities (CFLIABIL), accounts payables (APAYABL), retained earnings (RETEARN) and net income (or net profit, NI). From profit statements the following variables have been used: sales revenue (SALES), operating costs (OCOST), operating profit (OPROFIT), the sum of operating costs, financial income and financial cost (COST) and profit before taxation (BTPROFIT). Financial ratios have been chosen for the analysis based on their previous application in studies (see, e.g., Dimitras et al., 1996). Several ratios which provide ambiguous results have been excluded from the analysis. The following financial ratios have been used in the analysis: two solvency ratios (CASSETS/CLIABIL, i.e., CA/CL; CASH/CLIABIL , i.e., C/CL), three profitability ratios (NI/SALES, i.e., NI/S; OPROFIT/SALES, i.e., OP/S; BTPROFIT/SALES, i.e., BP/S) and two other ratios (EQUITY/LIABIL measuring capital structure, i.e., E/L; CASSETS/ASSETS measuring liquidity, i.e., CA/A). Also two additional solvency variables, that is, balance sheet test or net assets (Net assets ¼ ASSETS LIABIL, i.e., NETASSET) and net working capital (CASSETS–CLIABIL ¼ Net working capital, i.e., NWC) have been applied. Besides using values of financial variables and financial ratios, their changes have also been calculated to capture the dynamics of failure process (see, e.g., Laitinen, 1993). The change will be calculated as (ValuenValuem) divided by absolute value

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of Valuem, where n ¼ {1,2} and m ¼ {2,3} and the numbers indicate years before insolvency years. The application of absolute value in the denominator is needed, as some financial data can have negative values. In total three different changes will be calculated: that is, between the 1st and 2nd pre-insolvency year, the 2nd and 3rd pre-insolvency year, the 1st and 3rd pre-insolvency year. The specific change in the value will be notified in the text as a subscript nm. Besides a well-known statistical tool Cramer’s V association test, a nonparametric test — independent samples median test (i.e., ISMT) — will be applied to test whether financial information differs between groups of firms. This is needed because the assumption of normality for parametric tests is violated in financial data. The ISMT views whether there is at least one sample among k samples that has a different median than others (i.e., H0: Y0 ¼ Y1 ¼ Y2 ¼ y ¼ Yk; while H1: the median of at least one population is different). H1 will be accepted when asymptotic significance of the test is equal to or lower than 0.05. Based on the literature and the available information, three types of violations will be considered in the analysis, namely non-submission of an annual report, nonaccordance of net assets with requirements and pre-insolvency elements of criminal offence (the list of relevant variables is in Table 1). Two of them, the presence of annual reports in the register and accordance with the net asset requirement set in law, are calculated based on ECR data. According to the Estonian Commercial Code (ECC), a firm must submit its annual report half a year after its business year ends: that is, if its business year ends on the 31st of December, then the last day to present it is the 30th June. An exception to this rule is applied if a firm’s life-cycle from its foundation to the end of its business year is less than a half a year, in this case it can sum it up with the annual report for the forthcoming full business year. There are of course occasions (e.g., in the case of an acceptable reason), when the submission could be postponed. According to the Estonian penal code the non-submission has been criminalized, but court statistics show that criminal proceedings for that have been instituted on rare occasions (Kuritegevus Eestis, 2010[2009]). The more frequent procedure for non-submission is imposing a penalty by ECR at first and the deletion from the register after the penalty has proven to be ineffective. In the case the firm goes bankrupt, the obligation to submit annual reports is shifted from its management to the trustee, but those reports are submitted quite rarely because trustees want to save as much resources as possible from bankruptcy estate for claim satisfaction and not to use them for purposes that are not vital. ECR also does not monitor the submission of post-bankruptcy reports. The non-submission by the management in the current analysis will be detected taking into account the criteria outlined above. As for financial variables, the non-submission as a dummy variable will be viewed for all three pre-insolvency years separately (respectively SUBM1, SUMB2, SUMB3, all having values {0,1}, where 0 means the fulfillment of the submission obligation and 1 means violating it) and also those cases will be detected, where there has been non-submission for two consecutive years (SUBM2yrs, having values {0,1}, where 0 means not violating the submission obligation for two consecutive years and 1 means violating it).

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Table 1: Variables explaining violations and insolvencies in the analysis. Variable

Values and explanations

SUBM1

{0,1}, where 0 means the fulfillment of the submission obligation and 1 means a violation of the submission obligation {0,1}, where 0 means the fulfillment of the submission obligation and 1 means a violation of the submission obligation {0,1}, where 0 means the fulfillment of the submission obligation and 1 means a violation of the submission obligation {0,1}, where 0 means a non-violation of the submission obligation for two consecutive years and 1 means a violation of the given obligation {0,1}, where 0 means the fulfillment of the net asset requirement and 1 means a violation of the given requirement {0,1}, where 0 means the fulfillment of the net asset requirement and 1 means a violation of the given requirement {0,1}, where 0 means the fulfillment of the net asset requirement and 1 means a violation of the given requirement {0,1}, where 0 means a non-violation of the net asset requirement on two consecutive years and 1 means a violation of the given requirement {0,1}, where 0 means a non-violation of the net asset requirement on three consecutive years and 1 means a violation of the given requirement {0,1}, where 0 means that elements of criminal offence have not been suspected by the trustee and 1 means that at least one element of criminal offence has been suspected {2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009}, year when the bankruptcy was declared or the abatement of bankruptcy proceeding occurred {0,1}, where 0 means bankruptcy proceeding abatement and 1 means bankruptcy declaration

SUMB2 SUMB3 SUBM2yrs

NA1 NA2 NA3 NA2yrs NA3yrs

CRIME

BYEAR

BTYPE

Source: Compiled by the author.

The second aspect to be considered based on annual reports is the accordance of net assets with regulations. EBA y1 states that a debtor is considered to be insolvent in the case it is not able to satisfy the creditor’s claims and this situation is not temporary derived from the economic circumstances of the debtor. A legal person is considered to be insolvent also in the case its assets are less than liabilities and that situation is not temporary. The limit for the relationship between assets and liabilities has also been given in ECC, which states that net assets (= equity=assetsliabilities) cannot be (permanently) less than a half of the share/stock capital or the legal minimum limit for a private/public limited company. For private limited companies the minimum was about 2557 EUR until the end of 2010 and starting from 2011 is 2500 EUR, although a

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firm can be founded without capital input and the minimal share capital requirement is applied only in the case the firm’s financial situation demands it. For public limited companies the minimum was about 25,565 EUR until the end of 2010 and starting from 2011 it was lowered to 25,000 EUR. The above information shows that the net asset requirement given in ECC is stricter compared to that given in EBA. The European Union’s policy for small- and medium-sized firms is directed at lowering capital requirements (see, e.g., the Small Business Act, 2011), which has resulted in the elimination of or reduction of capital requirements for start-up firms. The given logic is supported by several researchers, who find that initial capital requirements do not guarantee the protection of creditors (see, for instance, Petrosˇ evicˇiene, 2010). The current analysis applies the regulation from ECC to construct dummy variables showing whether the net asset criteria were violated or not for all three pre-insolvency years (respectively NA1, NA2, NA3, all having values {0,1}, where 0 means fulfillment of the net asset requirement and 1 means violating it). In addition, two dummy variables will be constructed to show whether the violation has lasted for two or three consecutive years (respectively NA2yrs, NA3yrs, all having values {0,1}, where 0 means a nonviolation of the net asset requirement on two or three consecutive years and 1 means violating it). An option would also be to count the cases when net assets are negative, but as this is not the actual criterion being checked by the ECR, this approach is abandoned. The non-responsiveness to the non-accordance of net assets with requirements has also been criminalized in Estonia, but similarly to the nonsubmission of annual reports, the practice of instituting proceedings and convicting entrepreneurs is rare. The second dataset includes the country’s court judgments about firm insolvencies. EBA outlines information that must be presented in court judgments, which among others also includes the fact whether elements of criminal offence where detected. Court judgments can include various different suspicions about possible crime, which will not be treated separately in the current analysis and instead one variable CRIME will be applied (it has values {0,1}, where 0 means that elements of criminal offence have not been detected by the trustee and 1 that at least one from the list given below has been suspected). The possible criminal offence categories are the following (all derived from the Estonian Penal Code): 1. Embezzlement of the firm’s resources, which can include various forms of criminal activity. For instance taking cash from the firm for personal purposes, the usage of fake invoices to transfer money, purchases with abnormal price are common examples of pre-insolvency resource embezzlement. 2. Absence of accounting documents, which means that in case the (temporary) trustee needs to check previous transactions, no accounting information is available. 3. The firm is active in some criminal activity: for instance in tax fraud through drawing up fake bills, not declaring taxes, involvement in some scam. 4. Insolvency has occurred a long time ago, which means that during bankruptcy proceedings it is detected that the firm has been insolvent for several years

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(in terms of an absence of business activities), but bankruptcy petition has not been submitted by the management (which in many cases is already consisting of so-called shadow board members, being individuals offering the service of acting as board members in insolvent firms). The following description outlines some aspects about Estonian legislation that have to be addressed in order to create a better overview of the requirements and their violations. EBA y28 states that a temporary trustee must notify the prosecutors’ office and the police if any elements of criminal offence have been found. The court must be also notified of grave errors in management. Both previous notification conditions also apply for trustees. Criminal offence or management errors can result in claims against the management or owners of firm. Still it is not unambiguously clear, what is a grave error in management. The General Part of the Civil Code Act y35–37 clarifies the responsibilities and liabilities of the firm’s management (and owners). According to it, the management must act with care commonly expected from the management, submit bankruptcy petition if firm is permanently insolvent and are solidarily liable for the losses caused for the firm. ECC is more specific about the liability for losses in the case the firm becomes insolvent and it states in y180 that bankruptcy petition must be submitted no later than 20 days after the emergence of a permanent insolvency. The management has the responsibility to compensate all payments made after that date, which exceed the commonly expected care from the management. The practice of making management responsible for grave management errors that are not criminal ones is weak. This is partly because of difficulties determining the exact permanent insolvency moment. Several of the mismanagement issues have been included in the Estonian Penal Code, including not submitting a bankruptcy petition when the firm has become insolvent, causing a bankruptcy intentionally, not maintaining the required accounting, not reacting to a net asset value decrease below the legal minimum limit and others. Still, according to the statistics of commenced criminal proceedings (Kuritegevus Eestis, 2010[2009]), which do not encompass criminal convictions, the practice of filing or proceeding such crimes has not been common in previous years. The above trends have also found support in the study of Vutt (2008b). Still, according to the ECR the prohibition on business due to different pre-insolvency violations is not uncommon in Estonia (also addressed by Vutt (2009)). Vutt (2008a) has also addressed the issue that in the case bankruptcy proceeding abatement occurs, the management has been asked to finance the proceeding and the sum paid by them to the bankruptcy estate has been equaled with the losses caused by their mismanagement. The above is of course not methodologically grounded. In the light of the above, the Estonian situation differs from some countries where clear and stricter rules have been established (also supported by the accompanying practice) to make management liable for their faults (see, e.g., the Austrian Business Reorganization Law from 1997 — Unternehmensreorganisationsgesetz (URG)).

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Descriptive Statistics and Statistical Tests This section outlines the most important descriptive statistics and the results of the conducted statistical tests. First of all, it is important to clarify the sizes of datasets available for the analysis, as for different parts of the study a varying amount of cases is available. Table 2 shows that in total there were 4086 insolvencies in the viewed period, out of which for 3656 cases the applied database included the firm’s foundation date. The foundation date is an important variable, as the discussion in the previous section showed that it determines when a firm must submit its annual report. Through insolvency years there was different amount of annual reports in the ECR database and there were 999 cases for which all three pre-insolvency annual reports were present. From ECIS, 1281 county court judgments were available with insolvency reasons disclosed (among them the information whether any elements of criminal offence were detected). The missing data will probably have no remarkable effect on the validity results, as the current dataset can be considered highly representative according to the requirements of the statistical analysis. The analysis continues with studying the violation of submitting annual reports (see Table 3). For analyzing annual reports, there are four variables as described earlier (SUBM1, SUMB2, SUMB3, SUBM2yrs). A relatively large amount of firms is characterized by the absence of annual reports, whereas lengthy absence (i.e., for two consecutive years) is present for about 15.1% of firms. The amount of occasional nonsubmissions (at least for some specific pre-insolvency years) is remarkably more common than the previously stated frequencies. This coincides with propositions in the literature (Argenti, 1976; Keasey & Watson, 1987, 1988) that non-submission of such data often precedes bankruptcy. It can be seen that during the economic crisis years the non-submission has been more frequent in absolute figures, but this can be obviously associated with the quick growth in the number of insolvencies. The most frequent is the non-submission for the second pre-insolvency year, but this evidently is associated to the fact, that from the middle of the insolvency year the submission responsibility is shifted from the management to the trustee, which reduces the preinsolvency year’s non-submission frequency. Cramer’s V test is conducted to analyze whether for different insolvency years (BYEAR) and different insolvency types (BTYPE) the submission and non-submission are similar. For insolvency year the test shows significant differences except for the nonsubmission of annual reports in the pre-insolvency year, while for insolvency type the test shows significant differences for all non-submission variables (the non-submission being more frequent in the cases of proceeding abatement). This can in some sense be logical, as there might not be resources to conduct book-keeping, but it needs to be investigated more specifically, as there is also a threat that accounts are not submitted to shadow transactions that have left the firm without assets. Table 4 allows concluding that the practice of non-submitting annual reports about pre-insolvency year is equally common and it is not depending of the insolvency year (economic cycle). The analysis is followed by studying the violation of the net asset requirement by insolvent firms. Two sets of data will be analyzed, including only cases which have

1281

Total

Source: Compiled by the author.

60 145 132 133 182 168 232 229

Court judgments

2002 2003 2004 2005 2006 2007 2008 2009

Insolvency year

3656

402 439 383 357 323 285 431 1036

Firm’s foundation time available

999

122 121 105 64 79 71 117 320

Reports for all three years present

1283

154 150 123 90 95 90 165 416

the 1st year’s report present

2602

294 303 269 218 213 185 309 811

the 2nd year’s report present

Table 2: The number of cases for the analysis depending of their information content.

2653

301 318 291 237 223 208 285 790

the 3rd year’s report present

4086

463 509 442 416 359 318 476 1103

The total number of insolvencies

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Table 3: The frequencies for annual report non-submission through different insolvency years. BYEAR

SUMB3 ¼ 1

SUMB2 ¼ 1

SUBM1 ¼ 1

SUBM2yrs ¼ 1

2002 2003 2004 2005 2006 2007 2008 2009

60 83 57 85 63 37 58 66

103 126 108 129 103 83 96 173

90 96 84 90 77 64 104 235

67 86 73 94 76 50 72 100

Total

509

921

840

618

Source: Compiled by the author.

Table 4: Cramer’s V test results to study the association between insolvency years, insolvency types and non-submission types. Tested variables BYEAR*SUMB3 BYEAR*SUMB2 BYEAR*SUBM1 BYEAR*SUBM2yrs BTYPE*SUMB3 BTYPE*SUMB2 BTYPE*SUBM1 BTYPE*SUBM2yrs

Cramer’s V

Approx. Sig.

0.163 0.147 0.024 0.143 0.140 0.101 0.039 0.140

0.000 0.000 0.949 0.000 0.000 0.000 0.018 0.000

Source: Compiled by the author.

information about all three pre-insolvency years and all cases which have information about the specific variable studied. Such a setting is necessary as it allows following the violation on a firms’ whole population level, but also enables to capture the dynamics of the violation for the cases where sufficient time-series is available. Tables 5 and 6 outline that the violation of the net asset requirement is highly common for the pre-insolvency year, accounting for up to 78% of all insolvency cases. The violation figures for the second and the third pre-insolvency year are also relatively high. Statistics also show that lengthy violation (i.e., for two or three consecutive years) of the requirement is also relatively common. The conducted Cramer’s V test shows that the violation of the net asset requirement is significantly different for the viewed years, this applies for both

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Table 5: Violations of the net asset requirement for those firms which have annual reports for the three pre-insolvency years present. NA1 ¼ 1

NA2 ¼ 1

NA3 ¼ 1

NA2yrs ¼ 1

NA3yrs=1

Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share

87 71% 78 64% 78 74% 49 77% 60 76% 50 70% 81 69% 186 58%

57 47% 64 53% 41 39% 23 36% 33 42% 25 35% 51 44% 75 23%

49 40% 46 38% 38 36% 21 33% 24 30% 15 21% 34 29% 60 19%

55 45% 59 49% 39 37% 23 36% 31 39% 24 34% 49 42% 70 22%

34 28% 41 34% 25 24% 15 23% 16 20% 10 14% 28 24% 37 12%

Cases Share

669 67%

369 37%

287 29%

350 35%

206 21%

Year 2002 2003 2004 2005 2006 2007 2008 2009 Total

Source: Compiled by the author.

datasets used (see Table 7). As a positive tendency, the recent years show a drop in the share of violations, which could be associated to the fact that ECR has launched a digital register where the violation can automatically be detected and the firm’s management notified. Still, another possible explanation could be the overvaluation of assets during the economic boom and not correcting the estimates during the crisis. Also, the number of insolvencies increased considerably in 2009, which can have an influence on the share of net assets non-accordance cases. It was also tested whether the violation of the net asset requirement is significantly different for the bankruptcy declaration and bankruptcy proceeding abatement cases, as it could be hypothesized that for abatements the problems have advanced relatively more. The differences find confirmation with Cramer’s V test (see Table 7) and the study of frequencies indicates that in abatement cases, the violation of the net assets requirement is more common. The third violation in the analysis is the presence of elements of criminal offence in the court judgments studied. Table 8 shows the frequencies of the elements of criminal offence in the studied 1281 cases. Cramer’s V test does not indicate that there would be significant differences through the analyzed years. Cramer’s V test was also conducted using firm size categories and industries outlined previously, but in case of them the analysis also does not outline significant differences through groups. So it

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Table 6: Violations of the net asset requirement for all cases for three pre-insolvency years. NA1 ¼ 1

NA2 ¼ 1

NA3 ¼ 1

NA2yrs ¼ 1

NA3yrs ¼ 1

Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share Cases Share

112 73% 96 64% 91 74% 70 78% 70 74% 61 68% 113 68% 262 63%

155 53% 156 51% 122 45% 103 47% 92 43% 70 38% 124 40% 221 27%

137 46% 128 40% 122 42% 86 36% 76 34% 62 30% 76 27% 152 19%

111 31% 119 30% 86 24% 64 19% 62 21% 47 17% 85 21% 133 13%

34 9% 41 10% 25 7% 16 5% 16 5% 10 4% 28 7% 38 4%

Cases Share

875 68%

1043 40%

839 32%

707 21%

208 6%

Year 2002 2003 2004 2005 2006 2007 2008 2009 Total

Source: Compiled by the author.

Table 7: Cramer’s V test results to study the association between insolvency years, insolvency types and the net asset requirement violation. All cases

Only the cases where three pre-insolvency annual reports are available

Tested variables

Cramer’s V

Approx. sig.

Cramer’s V

Approx. sig.

BYEAR* NA1 BYEAR*NA2 BYEAR*NA3 BYEAR*NA2yrs BYEAR*NA3yrs BTYPE*NA1 BTYPE*NA2 BTYPE*NA3 BTYPE*NA2yrs BTYPE*NA3yrs

0.108 0.197 0.208 0.155 0.100 0.196 0.182 0.186 0.117 0.070

0.037 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.146 0.216 0.184 0.208 0.191 0.198 0.159 0.170 0.159 0.163

0.003 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Source: Compiled by the author.

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Table 8: Frequencies of elements of criminal offence in the Estonian court judgments. Year

CRIME ¼ 0

CRIME ¼ 1

Total

2002 2003 2004 2005 2006 2007 2008 2009

50 120 112 115 161 146 197 203

10 25 20 18 21 22 35 26

60 145 132 133 182 168 232 229

Total

1104

177

1281

Source: Compiled by the author.

Table 9: Cramer’s V test results to study the association between the net asset requirement violation and elements of criminal offence. Tested variables

Cramer’s V

Approx. sig.

CRIME*NA1 CRIME*NA2 CRIME*NA3 CRIME*NA2yrs CRIME*NA3yrs

0.125 0.062 0.057 0.108 0.076

0.008 0.059 0.076 0.000 0.006

Source: Compiled by the author.

could be summarized that suspected criminal activities in insolvent firms do not occur differently during economic growth or recession times, are not industry specific and do not change with the size of firm. It was also tested whether there is an association between suspected criminal activities and non-accordance with the net asset requirement. The results are given in Table 9, which shows that the pre-insolvency year net asset requirement violation and also violations on several consecutive years have statistically significant association with CRIME at 0.1 level, although some (e.g., CRIME*NA2 and CRIME*NA3 indicate very low Cramer’s V values). The study of frequencies shows that CRIME=1 has a larger share for cases, where there is no net asset requirement violation, which allows to hypothesize that different violations are more likely not to exist together. Lastly, it will be tested whether and how the presence of the elements of criminal offence is signaled through firms’ pre-insolvency financial data. Table 10 shows the results of conducted ISMT, namely variables that are significantly different between

Source: Compiled by the author.

0.08

Total

OCOST23

CRIME

0.06 0.42

312

Total

0 1

848 114

RETEARN1 (EUR)

0 1

CRIME

0.07

0.04 0.41

COST23

1358

1611 82

OPROFIT2 (EUR)

0.36

0.42 0.72

0.00

0.01 0.10 0.11

0.17 0.12

CASH23

0.06

0.06 0.12

C/CL3

CASSETS23

OPROFIT23

0.01

0.02 0.14

ASSETS23

0.63

0.70 0.07

NI/S23

0.15

0.14 0.29

CLIABIL23

0.52

0.55 0.41

OP/S23

0.08

0.04 0.35

RECEIV23

0.63

0.69 0.07

BP/S23

0.04

0.01 0.24

SALES23

Table 10: Median values of financial variables, ratios and their changes significantly different for cases where elements of criminal offence have been detected or not (in % if not noted otherwise).

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two groups of firms. It can be seen that only three values (two variables and one ratio) are significantly different through two groups of firms. Concerning the dynamics of failure processes, there are more differences, totaling at 12 changes (8 variable changes and 4 ratio changes). All significantly different changes occur between the second and third pre-bankruptcy year. The cases where elements of criminal offence have been detected show systematically better tendencies for the financial data and their changes than for the cases where it was not detected. This will allow proposing that forthcoming criminal violations are difficult to detect through firms’ annual reports. The given statement was also analyzed with logistic regression analysis and when applied with variables given in Table 10, no model could be constructed were some of the variables would be significant in discriminating between the two groups of firms.

Conclusions The paper focused on a specific domain of dishonesty, namely on different violations of law occurring before a firm becomes bankrupt. The literature would suggest that a firm would engage in various violations of law before the insolvency situation, which depending on a country’s legal system can also be criminalized. Based on the literature review and the data available for the analysis, three violation types were selected for the analysis: non-submission of annual reports, violations of the net asset requirement and suspected elements of criminal offence. The analysis was conducted based on the whole population of Estonian insolvent firms in the period 2002–2009, but due to several reasons mentioned in previous sections the dataset was limited in different analysis phases. The paper confirmed several propositions made in the current literature. The study showed that pre-insolvency non-submission of annual reports is common (also for two subsequent years) among Estonian firms and that the occurrence of nonsubmission practice varies through different insolvency years and types. In the case of bankruptcy proceeding abatement, the non-submission is more frequent, which could mean that if a firm ends up without assets the management is more motivated to hide information. Net asset requirement violations are also common, whereas the highest frequency is for the pre-insolvency year. All the studied net asset violation types are differently associated with insolvency years and types. The presence of criminal offence elements as the third violation studied in this paper is not significantly different through insolvency years, industries and firm size groups. The study of net asset requirement violations and elements of criminal offence shows that different violations are more likely not to exist together. It was also shown that although medians of several pre-insolvency financial variables are significantly different in the case of firms where criminal offence elements were found, they are not useful for offence prediction. The study could be developed in several ways: for instance, in terms of a more elaborate analysis about the connections of different violations, comparison with firms that have not become insolvent or drawing parallels with other countries, in case

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relevant datasets are available. Also, further investigation of the available data would allow setting up a theory how forthcoming insolvency is signaled through different violations.

Acknowledgements The study has been prepared with the financial support received from the Estonian Ministry of Education and Research’s funding No. SF0180037s08.

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Chapter 7

From Dishonesty to Disaster: The Reasons and Consequences of Rogue Traders’ Fraudulent Behavior Mark Kantsˇ ukov and Darja Medvedskaja

Abstract Purpose — The purpose of this chapter is to study the pattern of rogue trading, paying special attention to the aspects of the dishonest behavior of perpetrators. Design/methodology/approach — The chapter discusses selected cases of rogue trading that received the largest coverage by the mass media. Findings — No unique pattern of rogue trading schemes can be identified; however, certain similarities can be brought up based on the discussed cases. There are many aspects of dishonesty involved in fraudulent trading besides illicitness of unauthorized trading as such. Research limitations/implications — The chapter is based largely on a literature review and available data on the instances of rogue trading; probably, there is a vast amount of rogue trading cases undisclosed in order to draw a bigger picture. Originality/value — We apply the framework of white-collar crime process by McKay, Stevens, and Fratzl (2010) in order to clarify whether rogue trading schemes match the development of a typical white-collar crime. Conclusions are built on the analysis of several cases. Keywords: Rogue trading; dishonesty; financial crime

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 147–165 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010011

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Introduction Dorminey, Fleming, Kranacher, and Riley (2012, p. 556) stated that ‘‘Financial crime and fraud have probably existed since the beginning of commerce.’’ According to Abbasi, Albrecht, Vance, and Hansen (2012, p. 1293), ‘‘Financial fraud can have serious ramifications for the long-term sustainability of an organization, as well as adverse effects on its employees and investors, and on the economy as a whole.’’ The last several years were high-yield in terms of the number of disclosed instances of rogue trading; the phenomenon by which unauthorized (by superior managers) trades on financial markets are denoted. The term ‘‘rogue trading’’ can be considered to some extent as a euphemism for the term ‘‘dishonest behavior.’’ Dishonest behavior includes cheating, lying and disposition to deceive (Williamson, 1987), and in the world of finance many fraud schemes — bank fraud, insurance fraud, counterfeiting, and credit card fraud, among others — are based on cheating, lying, and forging. The authors believe that rogue trading should be considered as a banking-related fraud, taking into consideration its peculiarities, especially the fact that this type of fraud violates banks’ internal rules and banking best practices. Multiple incidents of unauthorized trading as well as banks’ internal regulations and failures in operational risk management are the reasons why rogue trading is a topical issue. The topicality may be also supported by the disastrous effects of rogue trading practice; one can think about the Barings’ Bank case (1995) or one of the latest incidents related with UBS bank (2011). A survey concerning white-collar crime awareness carried out among representatives of Swiss banks showed that in most of the cases it is perceived as embezzlement and the banking is the most vulnerable area (Isenring, 2008); well-known cases of unauthorized trading have taken place mostly in banks. Understanding motives and reasons behind rogue trading schemes may help to improve the system of operational risk management, restrain escalation of unauthorized trades on an early stage, and to avoid negative consequences of such schemes which may become burdensome not only for an organization but for the society in general. It is very crucial to construct a framework which explains the mechanism of rogue trading. Often rogue trading is not disclosed as long as it remains profitable for a bank. Traders’ failures and huge losses make rogue trading a crime which brings it to the public. It is not unrealistic to assume that many cases of rogue trading are being hidden from the public either due to their profitability for the bank or the management’s unwillingness to harm the bank’s reputation and lose customers. This in turn raises the question about the potentially dishonest behavior of the management. At a broader level dishonesty in the finance sector leads to a lower confidence toward financial institutions; the current financial economic crisis is largely the result of dishonest behavior of representatives of financial institutions (Stiglitz, 2008). Of course, in the focus of a rogue trading scheme is the personality of a rogue trader who can be considered as a special kind of a financial trader. But one must also pay attention to the trader’s relations with the management, peers, colleagues, and other employees at his/her institution. Because the crime is typically committed by

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senior staff of an institution, top management and executives are likely to be aware of the fraud. In the following sections, the authors discuss the nature of rogue trading and analyze the patterns of rogue trading. The chapter ends with managerial and research implications.

Rogue Trading as a White-Collar Crime Rogue trading is a sub-category of white-collar crimes; both of them have a relatively lengthy history. Such crimes are very diverse, and one can assume that every type of white-collar crime is as old as the field of economic activity where it was committed. In order to understand rogue trading, one must understand the nature of white-collar crime. There are several definitions for white-collar crime; one provided by Sutherland (1940) has become widely used. According to Sutherland (1940, pp. 2–3), white-collar crime in business is expressed most frequently in the form of misrepresentation in financial statements of corporations, manipulation in the stock exchange, commercial bribery, bribery of public officials directly or indirectly in order to secure favorable contracts and legislation, misrepresentation in advertising and salesmanship, embezzlement and mis-application of funds, short weights and measures and misgrading of commodities, tax frauds, misapplication of funds in receiverships and bankruptcies.

Sometimes it is better to define some phenomena by describing what they are not. Strader (2002, p. 2) notes that white-collar crimes do not contain force against a person or property — this sort of crimes are non-violent; they do not relate to organized crime activities, fields of state policy (immigration, national security), and drug-trafficking. White-collar crimes also do not refer to usual theft of property. All in all, to qualify for a white-collar criminal, one has to possess specific knowledge and skills in accounting, finance, or other management areas. There are two types of white-collar crime (Appelbaum & Chambliss, 1997, p. 117): (1) professional, performed by employees for personal gain, and (2) organizational, which are usually committed by the managers to improve organizational performance and achieve better financial indicators. Motivational factors (inducements) are influenced by the field of finance, management style, human resources, audit, and other economic aspects in combination as well as by organizational characteristics and qualities. General inducement for crimes is the combination of sphere of activity, management style, human, auditing, and economic aspects (Jacka, 2004, p. 52). It would be wrong to state that rogue trading or white-collar crimes in general depend only on an employee (a potential perpetrator). There are attributes and characteristics of an organization that are positively related to white-collar crime — poor performance, weakness, and size (Clinard & Yeager, 1980, pp. 26, 303). There are some stereotypes about the personality of a white-collar criminal issuing from the definition of a white-collar crime. One of the most widespread stereotypes is that a typical white-collar criminal is a rich, powerful person having a high social

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status with no previous criminal records. At the same time, practice shows that the majority employees convicted in white-collar crimes are not vigorous executives (although some recent research shows that upper-class individuals behave more unethically than low-class individuals, see, for instance, Piff, Stancato, Coˆte´, Mendoza-Denton, & Keltner, 2012). They are rather middle-class representatives with an average income working at a relatively conventional position — middle managers and small entrepreneurs. (Benson & Kerley, 2001, p. 123) Some authors note that many cases about white-collar crimes — especially largescale ones — have many things in common. In this situation it is possible to draw some patterns of a crime or dishonest behavior in general. For a better understanding of white-collar crimes McKay, Stevens, and Fratzl (2010) proposed a 12-step path to white-collar crime. These steps are the following (McKay et al., 2010): 1. Obtaining a position of power (the ‘‘perfect job’’). 2. Recognition of power by a future perpetrator. 3. Other high-rank executives turn a blind eye to malfeasances or even condone them. 4. Recognition of an opportunity by passive participants. 5. Involvement of reluctant participants into a fraud scheme. 6. Emergence of distrust of involved people by the perpetrator. 7. Exploitation of a vulnerable position of perpetrator’s accomplices (bravado) 8. Diffusion of bullying tactics due to aim for illegal goals 9. Greater involvement of reluctant participants, increasing risk of being caught. 10. Increasing conflict between participants’ values and their behavior (cognitive dissonance). 11. A whistleblower exits the fraud scheme, the leader loses control. 12. As the perpetrator is blamed he/she either denies everything or admits guilt and seeks forgiveness. Steps 1–4 of the process describe participants, and how they are attracted to and support each other. Also, these steps show how opportunities for illicit activities arise that cements relations between the participants. Steps 5–8 demonstrate how the truth of expanding illegality is silenced. Steps 9–12 show how the perpetrator’s activities are defied; revealed and publicized. (McKay et al., 2010, p. 17) Later in this chapter the authors apply the framework suggested by McKay et al. (2010) to analyze phenomenon of rogue trading. White collar crime has both financial and social consequences; however, social consequences are far more difficult to quantify and to measure. For organizations, losses from unauthorized trading consist, first of all, in reputational damage. Consequences for ordinary citizens result mainly in an increasing tax burden and job losses. White-collar crimes violate trust toward the financial sector. This lowers social morale and produces social disorganization. However, the society does not criminalize white-collar crimes to the same extent as street crimes, even though the financial costs of white-collar crimes are higher than those of street crimes. Nevertheless, white-collar criminals rarely go to jail, generally because official

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investigators cannot fully comprehend their complex financial schemes. There are also difficulties in determining the criminal charge, there is no sufficient law practice and white-collar criminals often have the opportunity to hire the best lawyers. (Hagan & Parker, 1985, p. 306; Long, 2007) The previously mentioned aspects of white-collar crime help to understand better the nature of rogue trading on financial markets. How does rogue trading work? Rogue, or unauthorized, trading takes places when a trader is buying or selling financial instruments in amounts beyond the organizational risk limits and conceals his/her activities. The rogue trader hopes to make higher (compared with the market average) profit or compensate losses from the previous unauthorized trades. This often results in even worse losses that can escalate with time; at some moment these losses become hard to hide. And even though rogue traders do not gain directly from their fraudulent behavior, they may proliferate from additional compensation, promotion, or other benefits (Slifker, 2008, p. 63). So, in the case of rogue trading we have several constituents of dishonest behavior: breach (unauthorized excess) of risk or loss limits, concealment of activities which may be expressed in several forms — forging statements and reports, lying to senior managers and colleagues, also bullying and threatening of accomplices in a more vulnerable position. The motivation of rogue traders appears through the above-discussed theoretical framework. Moreover, according to the literature, rogue traders are alleged to have been engaged in excessive risk taking, they are overconfident, and they are gamblers by nature. Traders are motivated by anxiety from risk-taking, good performance, the status of a ‘‘star’’ (or ‘‘superstar’’) trader to be achieved, and by increasing freedom of action. They are constantly encouraged to earn more money which is integral feature of securities industry. Traders are generally lacking career opportunities, thus their results are playing an important role in their reputation and bonuses. Rogue traders use previously acquired knowledge in other departments (e.g., back office) and they are also able to dominate or affect other employees. Rogue traders face difficulties in recognizing their mistakes, in particular to admit the fact that unauthorized trades were aimed to cover trading losses (Becker & Huselid, 1992, p. 337; Chapman, 2008; Forte & Power, 2008, pp. 18–19). Wexler (2010) provides an explanation for persistence of rogue trading. There are several inducements that make rogue trading possible (see Table 1). None of the rogue traders confessed that their actions that were oriented toward diminishing of losses, in fact led to worse results. Like for many gamblers, the biggest mistake for a rogue traders is an attempt to cover escalating losses by doubling stakes, and exploitation of back office knowledge to conceal the trader’s actions as long as possible. It is very hard for many rogue traders to recognize their failure because in this case they lose their star-trader position (Davis, 2011). One can think that rogue traders execute unauthorized trades in order to get abnormal gains or to demonstrate superiority of their performance compared with peer traders (as remuneration of traders is tied with their results). It is also possible to assume that law-breakers foster dishonest behavior and illegal activities being enticed by a small probability of being caught. Weighing up possible earnings from trade and

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Table 1: Inducement to rogue trading. Inducement Selection for autonomy seeking risk-taking personality Stimulation by the thrill of using skill to deal with chance

Provision of star-traders with intrinsic and extrinsic awards

Relaxing formal rules in order to increase confidence in star traders

Escalation of commitment to traders with initial poor returns

Reasoning Securities trading industry seeks for risk-taking and autonomously thinking people. The field encourages winners. The use of modern mathematical models and software provides rogue traders with belief that they have the skills to recognize market patterns and capitalize on risks that many others are not capable or are afraid of. The reward system favors those who make the most money instead of consistent traders. Monetary bonus and status are the greatest motivators for risk-taking traders. Star traders can distort and interpret subjectively the organizational rules on trading limits. In this manner a brokerage house colludes with traders in order to raise their profits even more. Decisions that resulted in trading losses induce traders not to exit the market too early. Traders remain confident that more risky deals can eventually turn things around.

Source: Based on Wexler (2010, p. 16).

the probability of non-detection, a rational subject shall commit the trade if the expected earnings from an illicit transaction exceed the expected earnings in the case of an authorized transaction. The seminal work by Kahneman and Tversky (1979) sheds light on another facet. A decision-maker is risk-averse when facing choice between certain and variable monetary gain (i.e., he/she is prone to preferring option with the highest expected value). However, if a person has to make choice between a certain loss and a variable loss (in latter situation there is a possibility of losing nothing) then he/she becomes risk-seeking (although the option preferred has a lower expected value compared with the other). So, financial decisions being made largely depend on the beginning point (or the reference point) and the prospect the decision-maker faces. The latter aspect leads to the notion of loss aversion, the tendency of preferring avoiding losses to obtaining gains (see Kahneman & Tversky, 1984). So, the bigger the loss, the more risk-seeking one becomes.

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However, in many cases of rogue trading, dishonest behavior was initiated not only by the possibility of excess returns. Here we can appeal to the statements by Ariely (2012), Gino and Ariely (2012), Chauhan and Kenkre (2011), Dorminey et al. (2012), and Forte and Power (2008) who proposed dishonesty shaping forces (see Figure 1). According to Ariely (2012), the amount of money to be gained, as well as the probability of being caught do not play a significant role in preventing or stimulating dishonest behavior. In the context of rogue trading we may think that traders exceed limits not because of the expected extra returns or abnormal earnings (as well as high probability of being caught is not that important in decreasing rogue trading practice). Dishonest behavior is stipulated by various factors, many of which are relevant for brokerage houses. For example, if other traders/brokers, especially seniors, behave dishonestly (for instance, by breaching risk limits), then it is hard not to follow the same line of conduct. One of the interesting findings is that creative persons are more prone to dishonesty (Marks, 2012) while intelligence — although it is associated with creativity — does not have a statistically significant effect on dishonest behavior (see, for instance, Gino & Ariely, 2012). Creativity increases moral flexibility which Gino and Ariely (2012, p. 447) define as the ability of a person to justify his/her immoral act(s) by proposing various arguments why a particular action can be considered as ethically sound. In order to decrease dishonesty among financial traders and other white-collar employees, various measures can be implemented supervision seems to be the most obvious one. Due to insufficient supervision (or lack of this), managers and supervisors may miss many warning signs that refer to potential rogue trading. These ‘‘red flags’’ include many facts and events: unusually a high number of trade cancellations,

Increase dishonesty • • • • • • • • • • • •

conflicts of interest creativity one immoral act ability to justify the dishonest act lack of control a great opportunity low personal integrity arrogance being depleted others benefiting from my dishonesty watching others behave dishonestly culture with examples of dishonesty

No effect • amount of money to be gained • probability of being caught • intelligence

Decrease dishonesty • • • • •

pledge signatures moral reminders supervision high personal integrity • a corporate culture of zero tolerance • lack of opportunity • whistle blowing policies

Figure 1: Forces that shape dishonesty (based on Ariely, 2012, p. 31; Chauhan and Kenkre, 2011; Dorminey et al., 2012, p. 561; Forte & Power, 2008, p. 19; Gino & Ariely, 2012).

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lack of confirmation of trades, the behavior of trading assistants, no mandatory vacation for traders, unusually high gross-to-net position ratios, breaches of trading limits, repeated or unusual requests by a trader to slack existing controls, and trading financial instruments beyond a trader’s expertise (without prior approval), among others (Allen, 2008).

Patterns of Rogue Trading — An Empirical Analysis According to the authors’ best knowledge, one of the earliest documented incidents of rogue trading took place in 1884 in the United States. It involved two partners at Grant & Ward who illegally rehypothecated securities that had already served as collateral for margin purchases. The incident caused nationwide panic; the country’s former President U. S. Grant (the partner at the company) was involved in the scandal. (Krawiec, 2002, p. 303) Over the past 20 years 17 major rogue trading cases have been discovered. In Table 2, the most significant documented instances of rogue trading are presented, including the names of rogue traders, their institutions, the used financial market instruments and the nominal loss caused by their transactions (not adjusted with inflation). The authors do not claim that this table contains all the instances of rogue trading during the last two decades; only those received substantial coverage by the media were selected. It is likely that financial institutions withhold information about many instances of rogue trading in their organization; especially if the inflicted loss is negligible in terms of assets or profit. The problems with concealing begin when the loss is too big to ignore. The necessary prerequisite for unauthorized trading on financial markets is the presence of developed financial markets. For this reason, the most of the cases are associated with institutions from countries with developed capital markets; also marketable instruments are tied with indicators of developed markets. Of course, basically anything traded on financial markets can be a subject of unauthorized trades. However, based on the information from Table 2 it is possible to state that derivative traders are more likely to become rogue. Intuitively, this is self-evident as trading options and futures, or simply buying and/or selling derivatives may seem similar to betting on certain events. Although the derivatives market cannot be equaled with betting exchange, this junction is important when one thinks of a rogue trader as of person possessing a mind-set of a gambler (Slifker, 2008). The gambling analogy may be useful in the context of gambling-trading strategies. Once a gambler/trader faces generated loss, one of the plain strategies is the martingale strategy according to which the player doubles his/her stakes at every loss in order to exit with profit provided that he/she once wins (Mansuy, 2009, p. 3). Also, one should keep in mind the prospect theory by Kahneman and Tversky (1979). Another probable reason why derivatives are so often involved in rogue trading may be the fact that only a few of a bank’s employees can comprehend them. It is

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Table 2: The most noticeable cases of rogue trading in 1992–2011. The rogue trader (year) Kweku Adoboli (2011) Evan Dooley (2010) Steve Perkins (2009) David Redmond (2009) Alexis Stenfors (2009) Boris PicanoNaci (2008) Je´roˆme Kerviel (2008) Bullen, Ficarra, Duffy, Gray (2004) Brian Hunter (2006) Chen Jiulin (2005) John Rusnak (2002) Scott Szach (2001) Joseph Jett (1998) Yasuo Hamanaka (1996) Toshihide Iguchi (1995) Nick Leeson (1995) Harshad Mehta (1992)

Institution UBS

Instruments

Nominal loss

MF Global

Equities ETF and Delta 1 Wheat futures

USD 141 mio

PVM Oil Futures

Oil futures

USD 10 mio

Morgan Stanley

Oil futures

Merrill Lynch

Swaps and forwardrate agreements (FRA) Stock derivatives

Groupe Caisse d’Epargne Socie´te´ Ge´ne´rale NAB

Hedge fund Amaranth Advisors LLC China Aviation oil

European index futures Foreign exchange options

USD 2.3 bn

USD 456 mio

EUR 751 mio (USD 1.1 bn) USD 7.22 bn USD 187 mio

Natural gas futures

USD 6.4 bn

Oil futures and options Foreign exchange options (Japanese yen) N/A

USD 550 mio

USD 5.56 mio

Kidder Peabody Sumitomo Corporation

Government bonds Copper futures

USD 350 mio USD 2.6 bn

Daiwa Bank

US Treasury bonds

USD 1.1 bn

Barings

NIKKEI index futures Funds from interbank transactions

USD 1.4 bn

AIB

Griffin Trading Co

N/A

Source: Compiled by the authors.

USD 691 mio

USD 1.3 bn

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possible to say that in this situation, the perpetrator gets an advantage from information asymmetry. Not all the instances of rogue trading cease with gigantic losses. Hereby, the cases of Scott Szach (2001), Steve Perkins (2009), and David Redmond (2009) are examples. David Redmond, after a series of unauthorized trades, finally even managed to earn profit to his employer. Situations with Stephen Perkins and David Redmond are especially interesting as concealed trades were made while traders were drunk (Final Notice, 2009, 2010). There are many articles, columns and papers written on different instances of rogue trading. Next we focus on the most reverberating cases which are following:    



Nick Leeson (Barings) Toshihide Iguchi (Daiwa) John Rusnak (AIB/Allfirst) David Bullen, Luke Duffy, Vince Ficarra, and Gianni Gray (National Australia Bank) Je´roˆme Kerviel (UBS)

One can argue whether these six instances are the best poster examples (or sufficient enough) to analyze rogue traders’ behavior but they tend to be the least opaque for the larger audience. Also, they offer a very interesting food for thought. The cases of Nick Leeson and Je´roˆme Kerviel received the largest coverage by the media. The Nick Leeson story was even turned into a film, Rogue Trader (1999) directed by James Dearden. Next we go through the 12-step process of white-collar crime by McKay et al. (2010) in order to ascertain whether illicit trading matches the scheme of evolution of white-collar crime. Step 1. What integrates all six cases is the fact that traders’ previous and current (at the moment of fraudulent transactions) position at organizations offered possibilities to achieve enough experience and knowledge to begin with fraud. Prior to the beginning of his unauthorized trades, Nick Leeson moved to Barings’ bank Singapore office where he was made responsible for back and middle office operations. Toshihide Iguchi and Je´roˆme Kerviel worked in back office where they had achieved necessary skills for swindle. Kweku Adoboli passed through many professional positions that provided better understanding of relations and functioning of banking system. John Rusnak was hired to work in the field of arbitrage which was not understand by many, and also was not controlled very well. In the case of NAB traders, the ‘‘perfect job’’ was expressed in the fact that people with similar thinking and objectives were able to operate together (Canac & Dykman, 2011; Chickowski, 2011; Cullinan, 2001; Dellaportas, Cooper, & Braica, 2007; Drummond, 2002; Greener, 2006; McNee, 2002; Moodie, 2008; Murphy, Burgess, Jones, & Simonian 2011; Previtali, 2008; PricewaterhouseCoopers y , 2004; Promontory Financial Group and y , 2002; The Blanch Law Firm y , 2009; Toshihide Iguchi and Daiwa y , 2008; Wright, Camber, & Greenwood, 2011). Step 2. Concerning motivation, then, based on different sources it is possible to conclude that the main inducements in selected cases were rather covering losses;

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the case of Kerviel is rather an exception to this rule because his first unauthorized positions brought huge profits. However, it is possible to state that the activities of two traders were also influenced by the events in their personal lives. Nick Leeson spent his childhood in poverty but despite of that, he made a quick career, as he wanted to be successful. Je´roˆme Kerviel did not graduate from a prestigious university which would make it possible to obtain a well-paid job. Getting a job at the Socie´te´ Ge´ne´rale was very important for him, and Kerviel wanted to prove that he was worthy of working at such a large and well-known organization. (Biography, 2012; Matlack, 2008) Kweku Adoboli was induced due to his strand, he was described as a gambler who thought that the whole life was a gamble where one could only win or lose (Wright et al., 2011) Among all the instances only the personality of Adoboli matches the description of a typical rogue trader. Many traders claimed that making profits is an inseparable part of the field of trading, and if a trader wants to be prosperous, then he/she is morally forced to make money for his/her organization (Davet, 2009; Iguchi, 2008; Matlack, 2008; PricewaterhouseCoopers y , 2004). Of course, it is obvious that making profits is necessary but problems may occur with the ends-justify-themeans approach. Step 3. In all the cases there was no direct driver for a rogue trade. Generally, the inducement was the reigning culture of profit earning in organizations. In the light of this, some aspects of division of work or the employees’ attitude can be considered as drivers: for instance, promotion of profit making by managers. Also, the lack of control over the trading division was, to some extent, a driver. Annual bonuses of Barings’ executives depended on Nick Leeson’s apparent profitability, so they were prepared to believe him (As The Economist quoted one of Leeson’s former colleague back in 1995: ‘‘There was no control system y Nick was the system.’’ (Economist, 1995)). Shortage of control also allowed J. Rusnak to cultivate fraudulent trading. NAB’s employees worked in a profit-oriented environment; expression ‘‘profit is king’’ was used very often in the bank. According to Kerviel, managers of Socie´te´ Ge´ne´rale actively favored profit making — later that allowed Kerviel to claim that managers were aware about his actions. The latter aspect suggests that no trader is rogue while he/she makes money for a company (Canac & Dykman, 2011; Davet, 2009; Drummond, 2002; Greener, 2006; Iguchi, 2008; Matlack, 2008; Pressman, 1997; PricewaterhouseCoopers y , 2004; Promontory Financial Group and y , 2002; Williams, 2005; Wexler, 2010, p. 8). Step 4. Regarding passive accomplices, their engagement was firmly established only in the case of Nick Leeson who generated a socio-technical network (Greener, 2006). There is little or deficient information about passive participants in other cases. Step 5. On the basis of the available information it is possible to state that reluctant participants can be senior managers of a company as well as others, especially back office workers. This is confirmed by cases of Nick Leeson, John Rusnak, Je´roˆme Kerviel, and partly by the case of Toshihide Iguchi. Leeson’s Singapore employees were loyal to him; he covered his staff when the employees made mistakes, and he paid them bonuses from his own pocket. Singapore International Monetary .

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Exchange (SIMEX) regulators were aware of uncommon trades and breach of regulations of the exchange but did not act in order to stop Leeson (Greener, 2006, pp. 430, 433). Rusnak was able to persuade Allfirst’s back office employee that there was no need to confirm the purported options pair as different trades would offset each other (Promontory Financial Group and y , 2002, p. 11). According to Kerviel, his chief consulted with him regarding taking a position while he officially had a vacation (Beattie, 2009; Biography, 2012; Davet, 2009; Drummond, 2002, pp. 232– 238; Matlack, 2008; McNee, 2002, pp. 1–6; Pressman, 1997, pp. 1136–1137). Steps 6 and 7. Distrust by the perpetrator of reluctant participants did not take place in the instances of rogue trading. Bravado was not also the characteristic of rogue traders. In the authors’ opinion, this can be explained by the point that both good and bad aspects of a fraud scheme have to be covert if a criminal wants to conceal his/her activities. For instance, 1999 was a profitable year for John Rusnak — during this year fraudulent positions were decreased (McNee, 2002, pp. 1–6; Promontory Financial Group and y , 2002). Nick Leeson was surrounded by peers who admired him, still he did not boast with his illicit activities (Biography, 2012; Drummond, 2002, pp. 232–238; Greener, 2006, pp. 421–441; Pressman, 1997, pp. 1136–1137). Step 8. Four rogue traders were able to dominate their workmates: Leeson and Kerviel thanks to their communication skills, especially among females, Rusnak and NAB traders thanks to bullying. John Rusnak bullied back office workers, threatening them with a layoff in case they did not do what he demanded. NAB traders also had a negative attitude toward everyone asking questions about their operations, including internal auditors (Dellaportas et al., 2007, pp. 1442–1452; Greener, 2006, pp. 421–444; McNee, 2002, pp. 1–6; Parry, 2011; PricewaterhouseCoopers y , 2004, pp. 1–58). Step 9. The risk of being caught was high in the case of only one reluctant participant — a back office worker at the Allied Irish Bank; the employee did not try to get confirmation for transactions that needed one (being persuaded by Rusnak). Although there were some suspicions, the management would not control further; non-confirmation of transactions continued for some time (Promontory Financial Group and y , 2002). There is no information regarding the other five cases but based on a detailed analysis of frauds, we can conclude that in the situation with rogue trading, perpetrators are those most likely to be caught in the act. Hence, nabbing of reluctant participants is not peculiar to rogue trading. Steps 10, 11, and 12. There is no evidence that passive and reluctant participants, also traders in most of the examined cases, experienced cognitive dissonance. There was not also a whistleblower who would leak information. Iguchi, Adoboli, and one of the NAB traders owned up themselves, but one cannot claim that confessions took place due to cognitive dissonance, not due to circumstances. All the confessed traders tried to justify their actions: Rusnak motivated fraud by the necessity to earn profits, Kerviel claimed that his managers promoted illicit activities, Adoboli at first confessed, but later submitted arguments against the accusation of being guilty. Many rogue traders substantiate their fraud schemes by profit-orientation of the field of trading, and the unacceptability of losses (Clark & Jolly, 2008; Cullinan, 2001,

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pp. 1–4; Dellaportas et al., 2007, pp. 1442–1452; Smitherman, 2005; Toshihide Iguchi and Daiwa y , 2008; Wright et al., 2011). Based on the previous analysis, we can conclude that the 12 steps of a white collar criminal, which were proposed by McKay et al. (2010), are not universal, and are not fully applicable to the instances of rogue trading. This statement concerns especially the participation of other employees and colleagues in the fraud, and their relationship with the perpetrator. In the authors’ opinion, such a disparity is most likely related to the peculiarities of financial trading. Traders usually do not work in teams, they are individualists; the nature of their work presumes competition between the peers and self-interest. When behaving dishonestly, traders are not inclined to trust someone else and share his/her ideas. The practical implication of the previously presented results is that employees transferring from the back or middle office to the front office must be paid special attention, as knowledge and skills needed for settling of accounts facilitate fraudulent trading. Also, relations between managers of trading departments and their subordinates must be under greater control. There are many overlapping episodes in the instances of rogue trading, more than it seems at the first sight. Although rogue traders have operated on different financial markets, different periods of time and different conditions, their incentives, fraud manners, and their fortune are relatively similar. Understanding the personality and life-style of a rogue trader is as important for preventing the fraud as knowing the peculiarities of financial trading and processing of transactions. Typically, a rogue trader is an arrogant (Dorminey et al., 2012; Marks, 2012) person in his late twenties-thirties, in the prevalent number of cases he is a male (to the authors’ best knowledge, there are no documented cases of female rogue traders). This fact can be attributed to the higher risk-taking behavior, overconfidence of males versus females. Hereby the study by Barber and Odean (2001) is an excellent supplement for the statement. The level of education and the positions at the moment of fraud detection vary. Among the examined six cases, only Je´roˆme Kerviel had received a Master’s degree in Economics (from Lumie`re University Lyon 2); the other traders had studied psychology (Iguchi and Leeson), computer science and management (Adoboli). There is no information on NAB traders and John Rusnak. (Biography, 2012; Cullinan, 2001; Matlack, 2008; Thompson, 2011; Toshihide Iguchi and Daiwa y , 2008; Williams, 2005; Wright et al., 2011) Many traders had been married, and in social terms they had been ordinary people who did not differ from others, except K. Adoboli who was raised in a presentable family. Adoboli’s family originates from Ghana, since 1991 they had lived in Great Britain. Kweku’s father was a representative of Ghana in the UN. For comparison, John Rusnak was a father of two; he actively participated in his community life and regularly visited a church. Many of the traders did not have the characteristics of a so-called ‘‘star trader.’’ They were perceived as trustworthy, loyal and committed employees. Perhaps only Kweku Adoboli matches the stereotype of a rogue trader, being described as ‘‘workhard play-hard’’ dealer. Although he liked to party he also worked a lot, often during

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nights (Allied orders fraud inquiry, 2002; McNee, 2002, pp. 1–6; Saltmarsh, 2011; Wright et al., 2011). The fact that many traders did not match the description of a typical white-collar criminal refers to point that in an organization, modest financial traders should be paid special attention. Also, most of the traders had no previous breach of law which is stereotypical to white-collar crime (see, e.g., Benson & Moore, 1992). In the authors’ opinion, one of the reasons of mismatch of theory and reality may be the fact that successful traders do not have to practice unauthorized trading in order to make money because they are skillful in earning profits with authorized trades. Among the six traders, only Nick Leeson had a previous criminal record at the moment of rogue trading. Although the main inducement for all the rogue traders was hiding the losses (or earning profits), every case of unauthorized transactions began differently. Rogue trading techniques have been very versatile, depending on the bank and the trader, because banks’ operating and control systems are different. However, almost all the observed cases involved bogus transactions and/or the production of false reports. Using IT solutions, Nick Leeson generated a secret account where he hid losses from his trading activities meanwhile reporting vast but fictive profits (Drummond, 2003). Toshihide Iguchi was also able to generate false statements. These custodian statements indicated that Daiwa bank and its customers had bonds and shares which were already sold by Iguchi (Cullinan, 2001). John Rusnak forged documents and bank entries systematically. His method was to enter simultaneously two bogus option positions with different expiration dates so that these positions looked hedged. Rusnak convinced the back office in the irrelevance of confirmation of transactions; manipulation of VaR indicators also took place (Promontory Financial Group and y , 2002, pp. 10, 14). NAB traders used false exchange rates for transactions that distorted profits and losses. They also manipulated back office daily reports exploiting the weaknesses of the system — reports were generated the next morning after the reporting day, traders entered false positions into it before the report was published. Later, this information was eliminated from reports (PricewaterhouseCoopers y , 2004). Kweku Adoboli and Je´roˆme Kerviel acted similarly in many ways, by taking directional positions that were not hedged, creating fictive offsetting trade. Both traders used extended forward settlement dates that helped hiding their activities, booked fictitious trades against internal counterparties (see Allen, 2008, pp. 29–34; Matlack, 2008; Moodie, 2008, pp. 169–180; Murphy et al., 2011; Previtali, 2008, pp. 24–36; Saltmarsh, 2011). The cases of rogue trades refer to the fact that despite peculiarities of each case, all the rogue traders rested on back office and/or information technology solutions; usually this was needed to enter fictitious trades in the system and generate forged reports. Taking into account that information technology and support-service systems differ by banks and that all they contain weak points, the problems of security of their IT systems are largely related to the internal users who may abuse information technology.

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Losses attributable to any case have been sufficient to affect the banks’ balance sheets. For instance, UBS’s losses were higher than the amount of money the bank planned to save from the previously announced job cuts (Comstock, 2011); the 233year-old Barings’ bank collapsed in 1995. In all the six cases, fraud was uncovered quickly and unexpectedly, except in Nick Leeson’s case. Criminals were sentenced to prison for a period in the range of 16 months (Gianni Gray from NAB) to 7.5 years (John Rusnak), some were additionally fined (at the moment of finishing this chapter, Adoboli’s trial was still ongoing). According to the source materials, no rogue trader has returned to the securities trading industry. Four of the fraudsters issued books; moreover, Nick Leeson nowadays is successfully capitalizing his rogue experience. It is possible to conclude that the board’s and the executives’ behavior plays an important role in all cases of unauthorized trading. In general, the behavior of the management board can be characterized in two ways — the lack of control or a ‘‘willful blindness’’ over fraud. The main priorities for the executives are profits (as their compensation usually depends on the profit the company earns), and good reputation which also influences the behavior of their subordinates. The analyzed cases show that some of the board managers and executives contributed (also unwittingly) to concealing of fraud; unfortunately, there is only little information about the behavior of the board in the UBS and Socie´te´ Ge´ne´rale cases to reach a conclusion about this issue. The authors believe that it is likely that this information has been intentionally not disclosed.

Conclusions In general, rogue trading refers to the situation when a financial trader breaches organizational risk or loss limits on financial transactions. While the most credible reason for a trader to become rogue is his/her ambition to earn excess returns, gaining additionally recognition and respect within the organization, in many cases illicit trades are cultivated to cover up losses from prior trades. These fraud schemes are excellent examples of individuals’ dishonest behavior. Besides illicitness of unauthorized trades as such there are many other unethical and illegal aspects related to fraudulent behavior: lying, forging, bullying and threatening, among others. The consequences of rogue trading on financial markets can be disastrous for the institution where it has been practiced: previous cases show that losses may vary from a few millions to billions of US dollars; in the extreme cases the institution may go bankrupt. There are no specific regulatory acts concerning unauthorized trading. Rogue trading falls under the category of operational risk. Its regulations can be adjusted according to the operational risk management framework. It has been extensively developed by the Basel Committee in Basel II capital accord which in turn defines an operational risk as a risk of loss resulting from inadequate or failed internal processes, from people and systems or from external events.

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The regulation of unauthorized trading is complicated by the facts that organizational leaders are often involved, but this does not always find official confirmation. In the authors’ opinion, the role of banks’ risk management and their control structure must be revised to incorporate alternative methods of control which may combine the already existing measures: for example, trading volume and profit/ loss amount comparison. From the authors’ point of view, it would be useful to rest on quality and adequacy, not on quantitative values of different parameters. Not only should the relevant department in a bank be responsible for operational risk management, but also all staff to some extent. Rogue trading leads to significant negative financial and social consequences. The internal threat of this kind of fraud is that organizations are willing to tolerate fraud, even to support and/or hide it in some cases. Although the ultimate aim of every organization is its shareholders’ wealth maximization, its activities should remain within the ambit of law and ethical limits. In case of failure of large financial institutions, they may count on bailout from the state (on the taxpayers’ account) or other institutions, because their bankruptcy would cause even a greater crisis. Of course, the costs of committing fraud for rogue traders and their accomplices should be much higher than the expected benefit. At the same time, in order to reduce the number of white-collar crimes in the finance industry — including rogue trading — it is important, first of all, to change the society’s attitude to such a type of crimes. All in all, fraudulent operations on financial markets can be financially more devastating than many street crimes. The consequences of dishonest behavior should not depend on the color of a perpetrator’s collar. The future research should encompass more cases on rogue trading and collect more primary evidence — for instance, though interviews — with rogue traders. Moreover, experiments should be conducted with traders to determine which character traits and other factors lead to rogue trading.

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PART III (DIS)HONESTY IN FIRM MANAGEMENT IN EUROPE AND AFRICA

Chapter 8

The Drivers and Moderators for Dishonest Behavior in the Service Sector Krista Jaakson, Jaan Masso and Maaja Vadi

Abstract Purpose — This chapter is aimed at testing the strength of three different drivers to engage in dishonest behavior at work — financial gain, response to injustice, and escape from boredom — and shedding light to the power of individual and organizational values to hold down the effect of these drivers. Design/methodology/approach — We analyze the data of 167 service employees from a large retail organization, who responded to questionnaires which manipulated drivers and organizational values. Findings — As a result we find that the financial and injustice drivers are effectively triggering several dishonest behaviors, whereas — contrary to the expectations — boredom at work does not threaten employers with employee engagement in dishonest behavior. We do find weak moderating effect of individual values in reacting to the drivers for some forms of dishonest behaviors, but the role of organizational values was marginal. Originality/value — In this chapter dishonest behavior is divided into nine specific dishonest acts involving management and customers as the stakeholders whose interests are at stake. We attempt to associate these behaviors with particular drivers. We also look at the moderators in this process: individual and organizational values. To date, espoused values of the organization is an underexplored organizational instrument compared to other situational variables, for instance, the existence of codes of ethics. Keywords: Dishonest behavior; drivers; individual values; organizational values; services

(Dis)honesty in Management: Manifestations and Consequences Advanced Series in Management, 169–193 Copyright r 2013 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 1877-6361/doi:10.1108/S1877-6361(2013)0000010012

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Introduction Stakeholders of business organizations are placing increasing pressure to take preventive measures against dishonest behavior to occur (Trevin˜o, Weaver, & Reynolds, 2006), but recent appalling frauds like Bernard Madoff or Kweku Adoboli, if to name some of the most notorious ones, have proved that serious misbehavior, not to mention minor deviance, is still a part of today’s working life. Thus, the reasons for dishonest behavior have not been eliminated and the society deals with its consequences — fraud, unethical deals, and so forth. For example, Madoff’s investment scam caused estimated losses of 65 billion USD for investors (Bray, 2009), and Adoboli’s trading cost the Swiss UBS bank around 2 billion USD (Sibun & Russell, 2011). According to the survey by the Association of Certified Fraud Examiners, it is estimated that the typical organization loses about 5 percent of its annual revenue to occupational fraud (Report to the nations on occupational fraud and abuse, 2012). The question arises which aspects factually induce dishonest behavior if we take into account the deepest roots of behavior? Here the study of individual and organizational values and drivers would be appropriate because these tacitly but strongly affect the behavior of employees. Dishonest behavior in this chapter is understood as unethical behavior with certain characteristics; that is, it is a narrower concept. While the topic is not new and has been researched for decades, theoretical and empirical research gaps have still remained. Kish-Gephart, Harrison, and Trevin˜o (2010) concluded that behavioral ethics researchers should empirically integrate multiple sets of predictors to fully understand this complicated phenomenon. De Cremer, Mayer, and Schminke (2010, p. 1) added that ‘‘we need to increase the understanding of why individuals within organizations engage in unethical behavior and decision-making.’’ The current chapter concentrates on the service sector, because in this sector employees’ unethical behavior is especially relevant due to its influence on both the organization and its customers and because of its immediate effects. In addition, employee behavior in service sector is the key determinant of customer satisfaction and organizational survival (Harris & Ogbonna, 2012; Litzky, Eddleston, & Kidder, 2006). Levitt (2006) elegantly demonstrated on U.S. data that there are systematic industry differences in employees’ honest behavior, whereas telecommunications, consumer services, and nonprofit sectors perform the poorest. This may indicate that ethical concerns are more topical in services; yet, only a few empirical studies on misbehavior have been conducted in service sector (see, for instance, Bamfield, 2004, 2006; Harris & Ogbonna, 2006, 2012). In the current chapter, we aim to explore what drives different forms of dishonest behavior and how far can individual and organizational values buffer against this process. In the literature of behavioral ethics, it is common to distinguish between individual, situational and organizational characteristics, known as ‘‘bad apples,’’ ‘‘bad cases,’’ and ‘‘bad barrels,’’ respectively (Kish-Gephart et al., 2010). In this discourse, we concentrate on one aspect of the ‘‘apple’’ and the ‘‘barrel’’ as moderators and, with some reservations, the drivers can be interpreted as ‘‘cases.’’ The novelty of the study lies in two aspects: first, we relate particular drivers for dishonest behavior with its specific manifestations. To date, research on unethical

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behavior looks at a bundle of misbehaviors with little attempt to associate certain behaviors with particular motives and determinants. However, it is evident that employees engage in many of these behaviors for a variety of motives elicited by many different conditions (Spector et al., 2006). Thus, understanding specific relationships between drivers and forms of dishonest behavior would be important for risk management in organizations. Second, situational perspective is operationalized via espoused values of the organization, which is an underexplored organizational instrument compared to other situational variables: for example, the existence of codes of ethics or perceived ethical climate. The strength of its presumably buffering effect on dishonest behavior is compared with another moderator — an individual value ‘‘honesty.’’ The study is based on a survey conducted in a large retail organization where service employees answered to manipulated questionnaires. In the next section, characteristics of dishonest behavior will be offered in the light of similarities with and differences from other closely related concepts. Also, specific forms of dishonest behavior will be presented. Thereafter, the drivers for dishonest behavior are discussed and hypotheses are developed in relation to the forms of dishonest behavior. The role of individual and organizational values in the adoption of dishonest behavior concludes the theoretical section, followed by the empirical study description and the results.

The Concept of Dishonest Behavior Among Service Employees Dishonest behavior relates to the literature discussing unethical behavior at the workplace and first, we shall describe the characteristics of it. A salient feature of unethical behavior is that it concerns misbehaviors where fundamental interests are at stake (Kaptein, 2008) and this author maintains that unethicality must be considered from the viewpoint of various stakeholders, including unethicality toward financiers, employees, customers, suppliers, and the society. Employees’ dishonest behavior, especially in the customer service function, is a narrower concept as these employees have only a limited interaction with certain stakeholders (for instance, suppliers, the society) and in this chapter we only look at dishonest behavior toward the management given that it acts on behalf of the firm’s owners, financiers, and customers. We rely on Shu, Gino, and Bazerman (2011, p. 330) who define cheating/dishonest behavior as ‘‘behavior accruing benefits to the self that violates accepted standards or rules.’’ What makes dishonest behavior difficult to define is the fact that it is possible to be more and less dishonest depending on the consequences of the act, motive, or other event characteristics (Scott & Jehn, 2003). There are many terms in use to describe unfavorable employee behaviors — misbehavior, deceptive behavior, dysfunctional behavior, counterproductive work behavior, employee deviance, antisocial behavior — see Kidwell and Martin (2005) and Harris and Ogbonna (2012) for a review. Below we clarify dishonest behavior in the context of unethical behavior and sabotage.

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There are two important aspects that distinguish dishonest behavior from an unethical one. First, the motive: we understand employee dishonesty as unethical behavior for personal gain, whereas unethical behavior can also occur for organizational, coworker, or customer benefit (Ashforth & Anand, 2003; Umphress, Campbell, & Bingham, 2010). Unethical behavior for organizational gain could be called organizational dishonesty and it is different from employee dishonest behavior in a crucial way. Organizational dishonesty is defined as ‘‘regularly teaching, encouraging, condoning or allowing the use of dishonest tactics in external dealings’’ (Cialdini, Petrova, & Goldstein, 2004, p. 67), thus it is a collective rather than an individual phenomenon. As such, it is not always a deliberate act by employees, but behavior that is learned via socialization process and perceived as group pressure, facilitated by organizational culture, and can even cause alienation of the employees involved. Employees’ dishonest behavior, in contrast, is deemed by the organization as the most undesirable. Second, it is important to note that employees demonstrating dishonest behavior are aware of its unethicality, whereas it does not have to be the case for unethical behavior (Kaptein, 2008). Thus, dishonest behavior is similar to deceptive behavior or cheating, where an employee’s conscious intention to deceive is an integral component (Grover, 1993; Scott & Jehn, 2003; Shu et al., 2011). Dishonest behavior specifically targeted at customers is what Harris and Ogbonna (2012) call ‘‘service sabotage’’: that is, practices of an organizational member that are intentionally designed to negatively affect the service. In turn, workplace sabotage according to Analoui (1995) involves willful destruction and damage to the work environment and is deliberately undertaken to destroy what is perceived to be of importance and value to the firm’s management. Hence, sabotage is a specific form of unethical and dishonest behavior, characterized by the intention of malice to the target individual(s). Sabotage may and may not be dishonest behavior depending on the motive: people may consciously engage in sabotage that is also self-defeating as long as the other party bears the damage, and dishonest behavior can occur with no intention to harm anybody given that self-interest is served. Figure 1 is a simple illustration of the related concepts based on two axes: motivation and awareness. While behavioral ethics asserts that most people may commit unethical behavior, given the right circumstances (Bazerman & Banaji, 2004; De Cremer et al., 2010), we do not assume the same for dishonest behavior based on the arguments above. Several categorizations for dishonest behavior have been suggested (see Scott & Jehn, 2003 for a review). In this chapter, we rely on the studies by Scott (2003), Analoui (1995), and Hollinger (1986) who have tried to map the terrain of various forms of dishonesty. Scott (2003) was mainly interested in deceit when asking airline industry employees about dishonest behavior, but she also found evidence of theft. Analoui (1995) used the participant observation method in a service company lasting for six years and depicted the following forms of ‘‘unconventional behavior’’: a. misuse of facilities for personal benefit (assuming that the employer would not accept it if he/she knew it);

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Unaware of unethicality

Aware of unethicality

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Unethical behavior

Sabotage

Dishonest behavior

Motivated by causing harm to Motivated by selfinterest the target individual(s)

Other motives

Figure 1: Dishonest behavior in relation to unethical behavior and sabotage. Source: Compiled by the authors.

b. pilferage: that is, stealing from the employer or the customer; c. destructive practices (sabotage): that is, the damage of the employer’s property; d. noncooperation; e. disruptive practices; f. indiscipline. According to Hollinger (1986) dishonest behavior may manifest itself in damaging the employer’s property, stealing, shirking, and negative behavior. Shirking is a form of cheating — if targeted at the employer — but cheating may be as well be targeted at the customers: for example, lying about the quality of the product or its expected delivery time in order to conclude the sale. Negative behavior by Hollinger (1986) is a rather broad concept and would include points (d–f) above: it might be, for example, ignoring or bullying the customer or otherwise harming the company’s reputation. Thus, there is a variety of manifestations of dishonest behavior and they are grouped dissimilarly in the literature. In the current chapter, broader categories are cheating, stealing, sabotage, and negative behavior. Each encompasses specific actions, the list of which can never become fully exhaustive. One might raise the question how sabotage and negative behavior serve the interest of the misbehaving employee to be categorized as dishonest behavior. The answer lies in the rise of self-esteem via personal and/or group approval for unethical acts (Harris & Ogbonna, 2006, 2012). In this case, engaging in dishonest behavior increases the employee’s status within the group as incidents of sabotage pass into firm legend, with the perpetrators often depicted as heroes. But again, from the organization management’s or customers’ point of view, such behavior is subject to condemnation.

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Drivers of Dishonest Behavior and the Development of Hypotheses In this section, the discussion on the drivers stems mainly from unethical behavior research. As dishonest behavior is a subcategory of unethical one, most apply to our topic, too; exceptions will be pointed out. Recent studies — for example, Detert, Trevin˜o and Sweitzer (2008) and Barsky (2011) — analyze how unethical behavior comes about and it is confirmed in line with the moral disengagement theory that moral justification and (to a lesser extent) displacement of responsibility explain perpetration of unethical behavior. However, this highly relevant theory gives an answer to the ‘‘how’’ rather than ‘‘why’’ question; specific drivers must precede moral disengagement. Kish-Gephart et al. (2010) report in their meta-analysis that antecedents for unethical behavior can be classified as characteristics of the individual (‘‘bad apples’’), the ethical issue itself (‘‘bad cases’’), or the organizational environment (‘‘bad barrels’’). These antecedents are based on three theoretical perspectives (Kidder, 2005).  



The first perspective is the personality trait theory stating that certain traits predict certain (unethical) behaviors. The second perspective is the agency theory, which presumes that employees as agents will adopt opportunistic behavior if adequate monitoring is not in place. The agency theory has led to look for mechanisms that make employees to think and act in the interest of organization without explicit surveillance — organizational values are one of such ‘‘instruments.’’ The third view is provided by the social contract theory, which states that misconduct occurs by otherwise honest and ethical employees only when the psychological contract has been violated in the workplace.

Apart from these broad antecedents, direct motives for unethical behavior have been proposed: personal gain (or self-enrichment), revenge as a response to perceived injustice, and altruism (Scott & Jehn, 1999). It can be noted that personal gain, best operationalized by monetary incentives, is in accordance with the agency theory and revenge relies on the social contract theory. In the context of this chapter, altruism (for instance, lying to the patient in order to cheer him/her up, or in the interest of a passenger’s safety lying about the rules) can be omitted as it does not contain direct personal benefit that defined dishonest behavior. Instead, emotional self-enrichment as an escape from boredom will be observed (Crino, 1994). Inclination to seek excitement has its roots both in the trait theory (some people cannot tolerate routine and are constantly looking for challenges) as well as in the social contract theory: for instance, when an employee was rightly or not expecting nonroutine work and feels deceived.

Financial Gain and Forms of Dishonest Behavior Jones and Kavanagh (1996) suggest that being underpaid and overworked with no (financial) appreciation from the organization leads to behavioral intention for

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property or time theft: that is, cheating. Harris and Ogbonna (2012) reported that 25 percent of the incidents of sabotage could be accounted for employees’ financial motives. Ermongkonchai (2010) inquired personally beneficial wrongdoings in several companies and reported various forms of deceit, including forbidden transactions to earn an extra income, exaggerating one’s overtime work report, forging hotel bills to get cash allowance for business trips, accepting bribery, appropriation of customer gifts, and so forth. Support to this is given by Levitt (2006) who found that while employees were surprisingly disciplined when they could cheat with a little threat of getting caught, dishonest behavior increased with the monetary cost of honest behavior. Thus, dishonest acts such as theft, cheating, and sabotage are adopted due to financial considerations. Therefore: Hypothesis 1. Compared to the base scenario, employees probed with a financial driver consider the use of cheating, stealing, and sabotage more likely. Perceived Injustice and Forms of Dishonest Behavior Feeling of mistreatment is the next powerful driver for dishonest behavior (Greenberg & Scott, 1996; Harris & Ogbonna, 2012; Jones, 2010; Jones & Kavanagh, 1996) and it might be triggered by organizational policies or procedures, but also by certain customers. Greenberg and Scott (1996) find that employees who perceive that they have been treated inequitably by the organization are more likely to steal from the organization. They suggest that the theft could have been motivated by feelings of resentment and frustration toward the organization. However, Spector et al. (2006) report only modest correlation between theft and procedural justice. Employee theft motivated by revenge found empirical support also by Hollinger and Clark (1983). Van Eerde and Peper (2008) analyze actual deviant service behavior including most forms of dishonest behaviors and find that negative attitude toward management is a significant predictor. Harris and Ogbonna (2012) describe various cheating and hostility acts targeted at customers to ‘‘get back’’ at them. Jones (2010) reports all types of dishonest behavior except for damaging property triggered by the revenge, but when vandalism was inquired by DeMore, Fisher, and Baron (1988), revenge was typically behind it. Hypothesis 2. Compared to the base scenario, employees probed with the injustice driver consider the use of all forms of dishonest behavior more likely. Boredom and Forms of Dishonest Behavior In addition to financial gain and injustice, some authors propose that misbehavior is adopted in order to escape from the work routine or too little stimulation (Ackroyd & Thompson, 1999; Bruursema, Kessler, & Spector, 2011; Crino, 1994; Harris & Ogbonna, 2012). In this case, dishonest acts are motivated by a desire to alleviate boredom and generate some excitement and stimulation. Boredom is typically

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associated with milder forms of misbehavior, such as misuse of resources in order to see if one can get away with it, withdrawal; and negative behavior (Harris & Ogbonna, 2012; Seabright, Ambrose, & Schminke, 2010; Spector et al., 2006). Spector et al. (2006) and Bruursema et al. (2011) found that boredom had the strongest correlation with ‘‘withdrawal’’ behaviors that correspond to shirking in our study, but even production deviance and theft were used. Therefore, perhaps surprisingly, boredom is a dangerous motive for organizations that might bring along various forms of dishonest behavior, even though serious harm to others is probably avoided: Hypothesis 3. Compared to the base scenario, employees probed with the boredom driver consider the use of all forms of dishonest behavior more likely. Apart from the above drivers to behave dishonestly, individual and situational variables are believed to play a role in the behavior of the employee (Glover, Bumpus, Logan, & Ciesla 1997; Jones & Kavanagh, 1996; Kish-Gephart et al., 2010) and complex models that encompass the interaction of both variables have been tested. In the following section, we outline the arguments for including individual and organizational values as moderators to the research framework (see Figure 2). We start from the individual level: that is, ‘‘bad apples.’’

Individual Values and Dishonest Behavior It has been suggested that several individual variables (in addition to demographic ones) — for instance, individual values, locus of control, moral intensity, commitment,

Theory perspectives

The agency theory

The social contract theory

The trait theory

Relationships and moderators Organizational values H5 The financial driver H1

Cheating

Stealing The injustice driver H2 Negative behavior The boredom driver H3

Sabotage Individual values H4

Figure 2: Research framework for the study of dishonest behavior. Source: Compiled by the authors.

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moral intent, idealism, and relativism, among others — are significant predictors of ethical behavior (Grover, 1993; Kish-Gephart et al., 2010; Loe, Ferrell, & Mansfield, 2000). In this chapter we focus on individual values. Suar and Khuntia (2010) demonstrated that personal values, including ‘‘honesty’’ had even a more powerful impact on ethical behavior than on the value congruence between the person and the organization, whereas Glover et al. (1997) found the value ‘‘honesty’’ insignificant. As we are not interested in unethical behavior but dishonest behavior, the value ‘‘honesty’’ would be the most appropriate ground for analysis. ‘‘Honesty’’ is defined as the ‘‘individual’s beliefs about the way he or she ought to tell the truth and do what he or she thinks is right’’ (Glover et al., 1997, p. 1320). Even though Litzky et al. (2006 p. 93) note that ‘‘honest employees seem to commit most deviant acts,’’ we propose that if ‘‘honesty’’ is important for a person, he/she has a disposition toward refraining from dishonest behavior regardless of the drivers. Moreover, if a person deems ‘‘honesty’’ important for him/herself, it is highly likely that he/she deems ‘‘honesty’’ important for colleagues, too (Vadi & Jaakson, 2011), and expects ethical behavior from others. Hypothesis 4. Employees with a relatively high importance of the individual value ‘‘honesty’’ consider the use of all forms of dishonest behavior less likely compared to the employees with a relatively low importance of ‘‘honesty.’’ Organizational Values and Dishonest Behavior There is a consensus that the organizational context affects the adoption or rejection of unethical behavior. Among the organizational factors that influence unethical behavior, the existence and content of the code of ethics (code of conduct) is the most researched variable (Coughlan, 2005; Erwin, 2011; Kaptein, 2011; Shu et al., 2011; Somers, 2001). For instance, Shu et al. (2011) demonstrated that having participants to sign the code eliminated cheating, whereas even reading it reduced it significantly. But generally, a mere existence of such codes does not affect ethical choice whereas enforcement does (Kish-Gephart et al., 2010). This demonstrates that the code of ethics only acts as an instrument for a more fundamental attribute in organizational life: organizational values. Coughlan (2005) maintains that for the code to be effective it must address important values and it is the code’s important yet underemphasized function to make corporate values explicit. Somers (2001) concludes that organizations with a code of ethics differ in respect to organizational values from those without such a code. There is some evidence that clarity of values is related to the perception of ethicality of organization (Ardichvili, Mitchell, & Jondle, 2009; Posner, 2010), professional ethics (Jin & Drozdenko, 2010), ethical intentions (Marta et al., 2012), and ethical behavior (Baker, Hunt, & Andrews, 2006). As for the content, the authors stress ‘‘corporate ethical values’’ as positive determinants of outcomes related to ethics. It is proposed that the effect of organizational variables on employees’ ethical behavior is even stronger than the influence of individual variables (Akaah & Lund, 1994). The reasons are not clear, but it is conjectured that first, personal and

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organizational values are correlated to each other, and second, if employees support their organization, it heightens the correlation between organizational values and ethicality. Barsky (2011) proposes that explication of organizational values matters because they effectively limit the availability of moral justifications. This is very likely given the result by Marta et al. (2012), which showed that organizational values are more effective means of fostering ethical intentions for the managers high in relativism, whereas values do not work to the same extent for those managers exhibiting high idealism. Hypothesis 5. The employees probed with organizational values stressing ‘‘honesty’’ consider the use of all forms of dishonest behavior less likely compared to the employees probed with organizational values that are neutral with respect to ‘‘honesty.’’

Method and Sample We test our hypotheses with an experimental study in which the participants, who are asked to play the role of floor managers for service employees in a fictitious service organization in Estonia, read a description of a situation and evaluate the likelihood of employees’ dishonest behavior under the given circumstances on 7-point Likerttype scales. The study employs a 2  3 mixed factorial design that manipulates (1) the values of a hypothetical organization and (2) drivers to behave dishonestly.

Moderators — Organizational Values and the Individual Value ‘‘Honesty’’ The respondents were randomly assigned to receive one of the two different sets of organizational core values, one set that emphasized corporate ethical values with values such as honesty, responsibility, and professionalism1 versus another set that did not emphasize honesty: in this set creativity, joyfulness, and product quality were indicated as the company’s core values. Otherwise the description of the organization was identical. The company was described as a retailer that is relatively known in Estonia, has been on the market for almost 20 years, and is affiliated with an international corporation. Its stores are located in major cities in Estonia and these are open seven days a week. In addition to (manipulated) values the aim of the organization was to become a market leader in its field. This condition is called basescenario in the following section. To be as realistic as possible, we drew on information from real organizations’ core values and objectives operating in retail industry. To make sure the participants read and considered the core values statements given to them carefully, we asked them to indicate how realistic the description was in their opinion. 1

Organizational values of the sample organization do not include those words: that is, the organizational context did not create any preconception of those values for the respondents.

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The individual value ‘‘honesty’’ was measured by the ranking-procedure of Rokeach’s instrumental values. Together with the questionnaire each participant received 18 small value tags with one value written on each plus a colored tag to check that the participant has actually answered the question. The instruction in the questionnaire asked the respondent to look at these tags and compile them in the order of their personal importance to the respondent. It was also asked to place the colored tag as the last item in the pile so that it would be next to the value tag that is of the least importance to the respondent (in the original pile, it was placed in the middle). The rank for ‘‘honesty’’ equaled the position of this tag in the pile — the first position denoting the most important and 18th the least important place among the instrumental values. In case the colored tag was left in the middle of the pile, we treated it as a missing value for the individual value ‘‘honesty.’’ This somewhat unconventional method was applied in order to decrease the stress that the ranking of values causes to a respondent. In the pilot study, we got complaints about the ranking as all values are ‘‘so important’’ and as once the rank is written down, it cannot be changed. Thus, we decided to adhere to the original procedure used by Rokeach (1973).

Independent Measure — Drivers In the test scenario, the company’s description was repeated, but the experimental manipulation of the driver was added to it: the respondents were randomly given one driver out of the three as was depicted in Figure 2. In the financial driver-condition the instruction stated: You as a floor manager of service employees constantly struggle with one and the same problem: employees complain that their salary is not sufficient to make their ends meet. In the case of a job opening, many candidates apply, but many lose interest as they hear about their potential salary. At the same time, you know well that your organization pays to service employees as much as the competitors, and the financial situation of the company would not enable raising their pay level.

The boredom driver-condition read as follows: You as a floor manager of service employees constantly struggle with one and the same problem: employee turnover in your store is high and your primary task is to hire new employees. Talking to another service employee who is about to leave reveals that the main reason for quitting is the nature of the job. Service employees say that their job is routine or outright tedious; especially on weekdays when there are only a few customers visiting the store.

In the injustice driver-condition, the scenario built on a recent economic crisis that was especially harsh in Estonia, where GDP declined more than 14 percent in 2009: You are concerned because in your opinion the commitment to the organization of service employees has drastically decreased. Because of the economic crisis, the management of the organization analyzed the existing network of stores and as a result, two stores in the neighboring towns were closed down. The employees in these stores got compensation as stipulated by the law, but nothing beyond it. However, soon after the decision the management raised its own salaries and this has caused disapproval among employees.

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Again, the respondents were asked to give an assessment of how realistic the description was. The results for this question were only analyzed in the pilot study that took place in the end of 2011 and the beginning of 2012 using a different sample. Then it became apparent that some manipulations were more realistic than others and wording of the scenarios was changed at some points. In the current study, the extent of realism had no independent role other than to make the respondents carefully read the scenario. Dependent Measure — Dishonest Behavior Both for the base scenario and the test scenario, the participants rated the likelihood of nine dishonest behaviors (from 1 — completely unlikely to 7 — very likely) presented in Table 1 in the fictive organization. In doing this, the respondents were asked to play a role of a floor-manager of 10 service employees of the described company. As such, the form and extent of dishonest behavior concerned an imaginary setting and was not related to the actual situation in the company of the respondents. Yet, honesty is socially constructed (Vadi & Jaakson, 2011) and we assume that the main basis for forming an opinion is the respondents’ previous experience with their own and their colleagues’ actual behavior in fairly similar situations. Statistical tests were run in STATA using a nonparametric test of significance between the base and test scenarios and Fischer’s exact tests were used to measure the effect of moderators. Sample The data for the study were collected from a large organization in Estonia selling a wide selection of goods for construction, furnishing, and gardening. The organization had been on the market for 10 years; it operates 12 stores in Estonia, and has also

Table 1: Selected forms of employee dishonest behavior. Stakeholder interests at stake Broad forms of dishonest behavior Cheating Stealing Sabotage Negative behavior

Employer: management and financiers Shirking, misuse of facilities, hiding relevant information Stealing property Damaging property Behaving disloyally (impair the reputation of organization)

Source: Compiled by the authors.

Customers Lying to the customer Stealing from the customer – Impolite behavior (ignoring, bullying, assault, etc.)

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expanded abroad. In Estonia, it employs approximately 500 people, most being service employees. Three hundred and three questionnaires were sent out on paper to all Estonian stores using store managers as contact persons to distribute the questionnaires to their personnel (themselves excluded). The employees returned the questionnaire in a sealed envelope and their anonymity was guaranteed. Data collection lasted for two weeks in February 2012. One hundred and eighty employees (59 percent) returned the questionnaire, but 13 were not usable — questionnaires were either empty or the data showed no variation between dishonest behaviors as well as between the base and test scenarios. These were omitted as the answers reflected resentment and protest against the survey rather than information for the research purpose. The final sample included 167 service employees (57 male and 105 female, 5 did not specify their gender). The average age of respondents was 36.7 (with a standard deviation of 9.6 years; 14 did not specify their age); they had an average of 4.1 years of work experience (with a standard deviation of 2.7 years; 15 did not specify their tenure). Approximately a quarter of the respondents had higher education or was enrolled in the program at the time; 67.6 percent of the respondents had a high school/college degree or less, the remainder did not specify their education achievement. The effect of demographic variables was not analyzed as it has been demonstrated that gender, age, and education add nothing to the explanation of unethical choice or behavior if individual psychological characteristics such as values, locus of control, moral intensity, commitment, idealism, Machiavellianism, and others are included (KishGephart et al., 2010).

Results and Discussion Results To address the influence of drivers on different forms of dishonest behavior, Figure 3 presents the overall results. One can immediately see that stealing and damaging property (i.e., sabotage) are rather unlikely compared to other forms and while the drivers increase their likelihood to some extent they still remain relatively unimportant. It is also notable that shirking and misuse of employer facilities are quite likely even under the base scenario. This may refer to the fact that these behaviors are not viewed as explicitly dishonest among service employees in the particular organization, but this pattern is similar to the results by Spector et al. (2006), who showed remarkable variation between the frequencies of reported counterproductive behaviors — incidents of stealing were reported the least and taking a longer break than permitted the most. When it comes to Hypothesis 1 (compared to the base scenario, employees probed with a financial driver consider the use of cheating, stealing, and sabotage more likely) we can see that the financial driver is the most influential one that significantly increases all forms of dishonest behaviors, except for ‘‘hiding relevant information from the customer’’ (see Table 2).

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Figure 3: The proclivity to dishonest behaviors under the base and test scenarios. Source: Compiled by the authors. Table 2: Test of significance between base and test scenarios. Drivers

Dishonest behaviors Cheating 1

Financial driver Boredom driver Injustice driver

2

3

Stealing 4

5

Sabotage 6

7

Negative behavior 8

9

0.000** 0.001** 0.088 0.001** 0.000** 0.000**

0.000**

0.000** 0.000**

0.068

0.039*

0.076

0.000**

0.008** 0.000**

0.885

0.010** 0.088

0.575 0.132

0.119

0.132

0.262 0.001** 0.001** 0.000**

0.035*

Source: Compiled by the authors. The numbers have the following meanings: 1, shirking; 2, misuse of the firm’s facilities; 3, hiding relevant information from the customer; 4, hiding relevant information from the employer; 5, stealing the employer’s property; 6, stealing from the customer; 7, damaging property; 8, impolite behavior; 9, behaving disloyally. * po0.05; **po0.01.

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Therefore, this hypothesis is partly confirmed, but it would have been more correct to associate it with a wider spectrum of dishonest behavior. The only form of behavior where the financial driver did not outperform other drivers was ‘‘Behaving disloyally’’ in case of the injustice driver, which also leads us to our Hypothesis 2 (compared to the base scenario, employees probed with the injustice driver consider the use of all forms of dishonest behavior more likely). Table 2 reveals that this hypothesis cannot fully be confirmed because injustice that is attributed to the employer does not influence cheating the customer; in fact, it even slightly decreases. Interestingly, the change is insignificant also for the misuse of the employer’s facilities, whereas shirking and hiding relevant information from the employer show remarkable rise. Nevertheless, the first candidate to cope with injustice is to undermine the company’s reputation; this driver-behavior combination demonstrated the highest increase of all: 1.32 points on average. All in all, the hypothesis can be partly confirmed. We expected that boredom is a guileful phenomenon that is of high risk for the employer because it generates various forms of dishonest behaviors (Hypothesis 3: compared to the base scenario, employees probed with the boredom driver consider the use of all forms of dishonest behavior more likely). This does not seem to hold as compared to the financial and revenge drivers it is relatively harmless. Boredom is marginally significant for damaging property and behaving disloyally, but overall, boredom does not significantly increase dishonest behaviors, at least in the opinion of the service employees themselves. Next, we take a look at the role of the individual value ‘‘honesty.’’ One hundred and fifty-nine persons in the sample indicated the rank of this value for themselves. In the following analysis two groups are distinguished: 44 respondents that ranked this value at the first place (i.e., the most important one among 18 values), compared to 46 persons that considered ‘‘honesty’’ between ranks 7 and 18. This distinction should reveal if individual ‘‘honesty’’ makes a difference in responses regarding dishonest behavior. First, let us look at the base scenario, where no motive was introduced to the respondent (see Figure 4). The above picture shows clearly that proclivity to all forms of dishonest behavior is a little higher when the respondent places less importance to ‘‘honesty’’ for him/ herself. This demonstrates well that personal values influence expectations toward others and when it comes to dishonest behavior, the focal person is more inclined to believe that colleagues act dishonestly when his/her own valuation of ‘‘honesty’’ is relatively lower (Vadi & Jaakson, 2011). It is interesting that customer-related dishonest behaviors under the base scenario are not sensitive to individual values, whereas behaviors against the employer do vary. This goes to show that employers should seek honest employees not so much to protect their customers, but to prevent misbehavior toward the company. Thus far, research on unethicality has not implied that different stakeholders may not suffer to the same extent due to employees’ individual characteristics. But this does not yet give an answer to whether honest employees react differently to drivers: in other words, does the individual value ‘‘honesty’’ moderate the relationships between the drivers and forms of behavior? Unfortunately, the sample is too small to say anything about different drivers separately, but all the drivers

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Krista Jaakson et al. Behaving disloyally Impolite behavior Honesty rank 1 Damaging property Honesty rank 7-18

Stealing from the customer Stealing employer property Hiding relevant information from employer Hiding relevant information from customer Misuse of facilities Shirking 1

2

3

4

5

Figure 4: The proclivity to dishonest behaviors under the base scenario depending on the respondent’s rank of the individual value ‘‘honesty.’’ Source: Compiled by the authors.

combined show the result depicted by Figure 5. The picture shows the average change of the responses between the test scenarios and base scenario. The higher the score, the more likely it was in the respondent’s opinion that dishonest behavior would occur after imposing a certain motive. In general, both groups react to the test scenarios, but ‘‘dishonest’’ respondents are more sensitive to those, the only exception being ‘‘Hiding relevant information from the employer,’’ where ‘‘honest’’ respondents show a slightly sharper reaction. Yet, most of the dishonest behaviors are not significantly different between these two groups. Some items are especially robust to the respondents’ values — for instance, cheating as a reaction seems to be equally likely for both groups. Significant differences, however, can be seen in such items as damaging property (sabotage) and disloyal behavior. Respondents who consider ‘‘honesty’’ relatively unimportant expect more sabotage and negation of the company’s reputation than those who rank ‘‘honesty’’ as a top value. Thus, Hypothesis 4 (employees with a relatively high importance of the individual value ‘‘honesty’’ consider the use of all forms of dishonest behavior less likely compared to the employees with a relatively low importance of ‘‘honesty’’) can partly be confirmed. Finally, let us turn to organizational values. There were 91 filled questionnaires with organizational values of ‘‘creativity,’’ ‘‘cheerfulness,’’ and ‘‘quality of products’’ and 76 questionnaires with organizational values ‘‘honesty,’’ ‘‘responsibility,’’ and ‘‘professionalism.’’ Similarly to the individual values, the first check concerns the base scenario (see Figure 6) and thereafter the moderating effect (Figure 7). The above picture shows inconclusive results — generally the differences are marginal. In our final hypothesis we expected that honesty-related values suppress cheating, stealing, sabotage, and negative behavior (Hypothesis 5: the employees probed with organizational values stressing ‘‘honesty’’ consider the use of all forms of

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1.4 Honesty rank 1 1.2 Honesty rank 7-18 1 0.8 0.6 0.4

**Behaving disloyally

*Impolite behavior

Damaging property

Stealing from the customer

Stealing employer property

Hiding relevent information from employer

Hiding relevent information from customer

* p