Financial Microeconometrics

Marek Gruszczyński

Financial MicroeconometricsA Research Methodology in CorporateFinance and Accounting

Marek GruszczyńskiInstitute of EconometricsSGH Warsaw School of EconomicsWarsaw, Poland

ISBN 978-3-030-34218-0 ISBN 978-3-030-34219-7 (eBook)https://doi.org/10.1007/978-3-030-34219-7

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Preface

This book explores topics of modern research in corporate finance and accounting.Emphasis is placed on both methodology and applications, jointly labeled as finan-cial microeconometrics. How can financial distress in companies be predicted? Iscorporate governance associated with financial results? What are the determinants ofaccounting disclosures? These and other questions may be reliably examined utiliz-ing the methods explored in this book. The clear presentation of methods is but-tressed by numerous examples from corporate finance and accounting literature.

Reportedly, this is the first English-language monograph on financialmicroeconometrics, the term first coined by the author in a publication in 2008.Financial microeconometrics covers topics known as “empirical corporate finance”and “applied accounting” especially in the subjects connected with the econometricanalysis of microdata. “Financial microeconometrics emerges as a natural conse-quence of applying statistical and econometric methods to corporate finance,accounting and other fields of finance. The applied research in accounting andcorporate finance is inevitably linked with the use of notions like statistical sample,population, and the operation on sets of microdata” (Gruszczyński 2018a).

This book demonstrates perhaps in a somewhat simplified form how quantitative(statistical, econometric) methods may be applied in corporate finance and account-ing research. It is intended for practitioners, researchers, and students who are not yetfamiliar with the variety of approaches extant in data analysis/microeconometrics.

Textbooks and monographs on financial econometrics typically do not includeanalyses of financial microdata (Wang 2009 being a notable exception). Two recenttextbooks on financial econometrics are time series oriented: Bofetti and Urga(2016) and Fan and Yao (2017). “On the other hand, microeconometrics tools arejustifiably included in modern classes on empirical corporate finance (e.g., Ph.D.class of prof. Da Rin at Bocconi, 2016–2017) and in some basic textbooks, likeDamodaran (2014) or Berk and DeMarzo (2017, Chap. 16)” (Gruszczyński 2018a).

The backstory of this book begins in the early transformation period in Poland.After the 1989 roundtable accord between Solidarity and the authorities, the newgovernment—with Leszek Balcerowicz at the helm of the country’s finances—

v

introduced Western-style management and opened the country to investors. In the1990s, I was involved in numerous projects of privatization and restructuring ofstate-owned companies. As an academic econometrician and lecturer at SGH War-saw School of Economics, I worked hard to expand my knowledge base and adddepth to my expertise. This period—challenging for all Poles—was professionallyfruitful for many of us academics. We learned—and immediately applied in the realworld—the basics of Western-style corporate finance, accounting, corporate law,management, etc. Obviously, the constantly changing laws governing business inPoland had to be monitored and implemented.

Simultaneously, the field of econometrics, as always, was expanding into newfrontiers. My research interest in microeconometrics was enhanced by major devel-opments in data quality and accessibility. In 2000, two microeconometricians DanielMcFadden and James Heckman were awarded the Nobel Prize in Economics. Thefields of microeconometrics and data analysis were continuing to advance in appli-cations, both operationally and as vehicles for expanding scientific research.

After returning full-time to academia around 2000, I employed my new corporatefinance and accounting experience in research grounded in statistical-econometricmethodology. The results were research projects, books, and papers. My majortheme has been the application of microeconometric methods in corporate financeand accounting. This book is about those applications as I see them from aneconometrician’s perspective and as I advocate their application (or not) to financeand accounting researchers and practitioners in those fields.

The author’s earlier version of this book was published in Polish in 2012 and hasfound success among researchers, students, and practitioners in corporate financeand accounting within Poland (Gruszczyński 2012a). This new book, written inEnglish, is rooted in the fundamental concept of the author’s earlier Polish text. Ihave borrowed from it the structural framework for this book and the main elementsof the presentation of financial microeconometrics. The major narratives on eachtopic have been rewritten, incorporating new developments. The set of examples—the core of this book—has been updated and expanded. Completely new are sectionson the “new microeconometrics” in Chap. 2 as well as a fresh look at good practicesin financial microeconometrics, also in Chap. 2. Chapters 3–6 also include substan-tial new parts. Overall, about 50% of this book contains new text (as compared withthe 2012 Polish version).

The primary message of this undertaking is as follows: While making decisionsor preparing opinions about specific companies—their finances, transactions, gov-ernance, etc.—do not forget the statistical (econometric) evidence about how thosesubjects fare or fared among other companies (in a sample). On a cautionary note,the book warns that evidence from statistical-econometric research is often flawedand, at a minimum, should not be taken as applicable to other time periods, to othersets of data, and to other industries.

My approach is to demonstrate ample research-based evidence to refer to in caseit is needed. Also, I strive to present—perhaps in simplified terms—how research isbeing conducted and how (easily) its results can be challenged. This book attempts toshow the current state of financial microeconometrics as presented by researchers

vi Preface

and lecturers worldwide. Inevitably, the content does not encompass all possibletopics, aspects, or solutions that comprise the expanding field of empirical corporatefinance and applied accounting.

My gratitude goes to the participants of numerous conferences in Poland andworldwide for the discussions on my presentations pertaining to various topicsmentioned in this book. Especially important for me were the conferences of theInternational Atlantic Economic Society in the USA, Canada, and Europe and theconferences on investment and finance organized by the University of Szczecin,Wrocław University of Economics, the University of Łódź, and other institutions. Ialso thank my MA and PhD students at SGH Warsaw School of Economics. Thisbook includes several results presented in their theses. Finally, I would like to thankJ. Richard Quigley for his thorough proofreading and useful suggestions that Iincorporated into this book. Obviously, all remaining errors are mine.

Warsaw, Poland Marek GruszczyńskiSeptember 2019

References

Berk J, DeMarzo P (2017) Corporate finance, 4th edn. Pearson, SydneyBofetti S, Urga G (2016) Financial econometrics using Stata. Stata Press, College

Station, TXDamodaran A (2014) Applied corporate finance, 4th edn. Wiley, Hoboken, NJFan J, Yao Q (2017) Elements of financial econometrics. Cambridge University

Press, CambridgeGruszczyński M (2012a) Empiryczne finanse przedsiębiorstw. Mikroekonometria

finansowa [Empirical corporate finance. Financial microeconometrics]. Difin,Warszawa

Gruszczyński M (2018a) Financial microeconometrics as research methodology incorporate finance and accounting. In: Dudycz T, Osbert-Pociecha G, Brycz B(eds) Efficiency in business and economics. Springer proceedings in business andeconomics. Springer, New York, pp 71–80

Wang P (2009) Financial econometrics, 2nd edn. Routledge, London

Preface vii

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 The Core of This Book: Microdata, Microeconometrics,

Corporate Finance, and Accounting . . . . . . . . . . . . . . . . . . . . . . 1Microeconometrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Microdata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2Financial Microeconometrics . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Empirical Corporate Finance and Applied Accounting . . . . . . . . . 3FM and ECF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4A Pragmatic Approach in Corporate Finance and Accounting . . . 5FM and ECF in the Classroom . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.2 Corporate Finance, the Theory of Corporate Finance, and theTheory of Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3 The Theory of Corporate Finance: Tirole . . . . . . . . . . . . . . . . . . 81.4 Empirical Corporate Finance/Financial Microeconometrics:

Eckbo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Eckbo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Literature on ECF/FM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.5 Sample Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Sources of Microdata for FM . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Analyzing the Entire Population . . . . . . . . . . . . . . . . . . . . . . . . . 14Purposive Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

1.6 ECF and FM: An Introductory Resume . . . . . . . . . . . . . . . . . . . 15ECF ¼ FM? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Financial Econometrics and FM . . . . . . . . . . . . . . . . . . . . . . . . . 16Examples of FM Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16What Comes Next and What Has Been Omitted? . . . . . . . . . . . . 18

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

ix

2 Models of Financial Microeconometrics . . . . . . . . . . . . . . . . . . . . . . 232.1 The Types of Models Used in Empirical Corporate Finance

and Accounting Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Types of Microdata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Types of Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Modeling Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Modeling Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.2 The Binomial Model: An Auditor Change Aftera Going-Concern-Modified Audit Opinion in Australia . . . . . . . . 28Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28The Logit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31The Marginal Effect and the Odds Ratio . . . . . . . . . . . . . . . . . . . 32Statistical Validity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Comment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.3 Practical Use of the Binomial Logit: Prior Correction . . . . . . . . . 342.4 Multinomial Ordered Variables Model: The Security Choice

by US Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36More on Ordered Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

2.5 The Multinomial Unordered Variables Model: The Choiceof Auditor by Chinese Companies . . . . . . . . . . . . . . . . . . . . . . . 40

2.6 The Tobit Model: Why Foreign Outside Investors ProvideCapital to a Country’s Firms? . . . . . . . . . . . . . . . . . . . . . . . . . . 43

2.7 Multiple Regression: CEO Cash Compensation, AccountingPerformance, and Compensation Committee Quality . . . . . . . . . . 46More on Multiple Regression and Statistical Signification . . . . . . 48

2.8 How to Prove Causality in Regression: The Adventof “Metrics” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

2.9 Treatment Effects in Empirical Corporate Finance: Effectsof French IPOs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52ATE and ATT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52Propensity Score Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54More on Treatment Effects Methodology . . . . . . . . . . . . . . . . . . 56

2.10 Self-Selection Modeling in Empirical Corporate Finance andAccounting Research: Dividend Decisions, Dividend Payments,and Corporate Social Responsibility . . . . . . . . . . . . . . . . . . . . . . 59Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59The Heckit Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60Self-Selection, the Tobit, and Treatment Effects Modeling . . . . . . 61

2.11 Endogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Endogeneity in Examining Company Performance Versus CEO“Power” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Reverse Causality and Unobserved Heterogeneity . . . . . . . . . . . . 64Instrumental Variables Approach . . . . . . . . . . . . . . . . . . . . . . . . 64

x Contents

The Surveys of Roberts and Whited (2013), Atanasov and Black(2016), and Gippel et al. (2015) . . . . . . . . . . . . . . . . . . . . . . . . . 65

2.12 Difference-in-Differences Estimators and RegressionDiscontinuity Designs in Corporate Finance and AccountingResearch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66Difference-in-Differences Estimators . . . . . . . . . . . . . . . . . . . . . 66Regression Discontinuity Design . . . . . . . . . . . . . . . . . . . . . . . . 67

2.13 Good Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68Modeling Strategy in Financial Microeconometrics . . . . . . . . . . . 68The Deficiencies of the Regression Model . . . . . . . . . . . . . . . . . 69Good Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3 Modeling Financial Distress and Bankruptcy . . . . . . . . . . . . . . . . . . 773.1 Research on Corporate Financial Distress and Bankruptcy . . . . . . 77

Fifty Years of the Altman Z-Score . . . . . . . . . . . . . . . . . . . . . . . 77The Notion of Financial Distress . . . . . . . . . . . . . . . . . . . . . . . . 79Does Financial Distress Lead to Bankruptcy? . . . . . . . . . . . . . . . 80Going-Concern Opinions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

3.2 Microeconometric Models of Bankruptcy and FinancialDistress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Methods for Predicting Bankruptcy/Distress . . . . . . . . . . . . . . . . 82The Choice of Predictors and the Drawbacks of Modeling . . . . . . 84Comparing Financial Distress and Bankruptcy Models . . . . . . . . 86Multinomial Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Binomial Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

3.3 Unbalanced Samples in Bankruptcy Prediction . . . . . . . . . . . . . . 97Bankruptcy: A Rare Event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97Unbalanced Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97Sampling Bias, Weighting, WoE, and Resampling . . . . . . . . . . . 99Prior Correction in the Logit Model . . . . . . . . . . . . . . . . . . . . . . 100

3.4 Models of Firm Exit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105Two States of Exit: Binomial Models and LDA . . . . . . . . . . . . . 105Models for Many States of Exit . . . . . . . . . . . . . . . . . . . . . . . . . 106

3.5 Models of Firm Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109Microeconometric Models of Firm Survival . . . . . . . . . . . . . . . . 109Single Spell Duration Models . . . . . . . . . . . . . . . . . . . . . . . . . . 111Competing Risks Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

4 Accounting Research and Disclosure Microeconometrics . . . . . . . . . 1214.1 Topics in Empirical Accounting Research and Sources

of Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Categories of Research Topics and Methods . . . . . . . . . . . . . . . . 122

Contents xi

Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123USA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Probability Expressions in Accounting . . . . . . . . . . . . . . . . . . . . 126

4.2 Microeconometric Methodology in Accounting Research . . . . . . 127Surveys by Maddala (1991) and Ge and Whitmore (2010) . . . . . . 128Choice-Based and Matched Samples . . . . . . . . . . . . . . . . . . . . . 128Sample Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129Financial Microeconometrics in Accounting: Two Examples . . . . 130

4.3 Financial Disclosure, Investor Protection, and DisclosureIndices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Accounting Disclosure and Corporate Governance . . . . . . . . . . . 135Investor Protection, Disclosure, and Legal Systems . . . . . . . . . . . 136Disclosure Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Disclosure Ratings and Rankings . . . . . . . . . . . . . . . . . . . . . . . . 140Text Analyses for Disclosure Research . . . . . . . . . . . . . . . . . . . . 140

4.4 The Microeconometrics of Disclosure . . . . . . . . . . . . . . . . . . . . 141Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141Studies on the Association Between Disclosure and InvestorProtection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143Comparative Cross-Country Studies . . . . . . . . . . . . . . . . . . . . . . 144Research on a Specific Type of Disclosure . . . . . . . . . . . . . . . . . 145Single Country Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

4.5 The Polish Corporate Disclosure Index (PCDI) and InvestorProtection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148Composition of the PCDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148PCDI for Companies Listed on the Warsaw Stock Exchange . . . . 149PCDI and Investor Protection . . . . . . . . . . . . . . . . . . . . . . . . . . 150Disclosure Types and Market Sentiment . . . . . . . . . . . . . . . . . . . 150

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

5 The Microeconometrics of Corporate Governance . . . . . . . . . . . . . . 1595.1 Sources of Knowledge and Areas of Corporate Governance . . . . . 159

Literature on CG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160The Areas of CG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161CG in Common Law and Civil Law Countries . . . . . . . . . . . . . . 164Codes of Good Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

5.2 Research Topics in Corporate Governance . . . . . . . . . . . . . . . . . 166Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166Methodological Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167Corporate Governance and the Performance of Companies:Two Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168Firm Performance and CEO Change: Two Studies . . . . . . . . . . . 173The Accounting Effects of CG: Two Studies . . . . . . . . . . . . . . . 175

5.3 Indices and Ratings of Corporate Governance . . . . . . . . . . . . . . . 178

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CG Ratings and CG Indices at the Country Level . . . . . . . . . . . . 179International CG Ratings and Indices . . . . . . . . . . . . . . . . . . . . . 179CG Ratings and CG Indices in the USA . . . . . . . . . . . . . . . . . . . 180Discussion on Uses and Misuses of CG Indices: Klausner(2018) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180Six Myths: Armstrong et al. (2010), Brickley and Zimmerman(2010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181Seven (Other) Myths: Larcker and Tayan (2011, 2015b) . . . . . . . 182CG Indices and Company Performance . . . . . . . . . . . . . . . . . . . 182

5.4 Corporate Governance and Firm Performance in Poland . . . . . . . 183CG Ratings for Polish Companies . . . . . . . . . . . . . . . . . . . . . . . 183

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

6 Topics in Empirical Corporate Finance and Accounting . . . . . . . . . . 1976.1 Value Relevance of Companies’ Financial Statements . . . . . . . . . 197

The NYSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199The Warsaw Stock Exchange (WSE) . . . . . . . . . . . . . . . . . . . . . 199

6.2 Microeconometrics for Equity Valuation . . . . . . . . . . . . . . . . . . 202Fundamental Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Relative Valuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Regression Models for Relative Valuation . . . . . . . . . . . . . . . . . 204Fundamental Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

6.3 Mergers and Acquisitions, IPOs, and Dividend Payouts . . . . . . . . 208Mergers and Acquisitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208Initial Public Offerings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209Dividend Payout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

Contents xiii

List of Abbreviations

Methodology

2SLS Two-stage least squaresATE Average treatment effectATT Treatment effect on the treatedAUC Area under curveCDF Cumulative distribution functionCIA Conditional dependence assumptionCPH Cox proportional hazardDiff-in-Diff Difference-in-differencesDPS-GMM Dynamic panel system GMMECF Empirical corporate financeEV1 Extreme value distribution type 1FE Financial econometricsFM Financial microeconometricsGLS Generalized least squaresGMM Generalized method of momentsIID Independent and identically distributedIMR Inverse Mills ratioIV Instrumental variableLDA Linear discriminant analysisLPM Linear probability modelLS Least squares methodME Marginal effectML Maximum likelihood methodOLS Ordinary least squaresOR Odds ratioPSM Propensity score matchingRDD Regression discontinuity design

xv

ROC Receiver operating characteristicROWR Random oversampling with replicationRU Random undersamplingSMOTE Synthetic minority oversampling techniqueSVM Support vector machineTE Treatment effectWoE Weights of evidence

Other

AIMD Artificial intelligence measurement of disclosureAIMR Association for Investment Management and ResearchASA American Statistical AssociationASX Australian Stock ExchangeBCDI Brazilian Corporate Disclosure IndexBV Book valueCEO Chief executive officerCFA Chartered financial analystCG Corporate governanceCIFAR The Center for International Financial Analysis and ResearchCSR Corporate social responsibilityEAA European Accounting AssociationEBIT Earnings before interest and taxesEBITDA Earnings before interest, taxes, depreciation, and amortizationECGI European Corporate Governance InstituteEPS Earnings per shareFCPA Foreign Corrupt Practices ActFD Financial distressGEM Hong Kong Growth Enterprise MarketIAS International Accounting StandardIFRS International Financial Reporting StandardsIPO Initial public offeringIRRCI Investor Responsibility Research Center InstituteM&A Mergers and acquisitionsMBAR Market-based accounting researchNYSE New York Stock ExchangeOECD Organisation for Economic Co-operation and DevelopmentP/E Price-earnings ratioPCDI Polish Corporate Disclosure IndexPFCG Polish Corporate Governance ForumPID Polish Institute of DirectorsR&D Research and developmentROA Return on assets

xvi List of Abbreviations

ROE Return on equitySDC Securities Data CorporationSOX Sarbanes–Oxley ActSRD II Shareholder Rights Directive IIVR Value relevanceWSE Warsaw Stock Exchange

List of Abbreviations xvii

List of Examples

Example 2.1 A Change of Auditor After a Going-Concern-ModifiedAudit Opinion: Australian Audit Market . . . . . . . . . . . . . . . . . . . . . . . 33

Example 2.2 The Security Choice by US Companies . . . . . . . . . . . . . . . . . . . . . . . . 38Example 2.3 Choosing Big 4 Companies as IPO Auditors in China . . . . . . . . 42Example 2.4 Why Foreign Outside Investors Provide Capital

to a Country’s Firms? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Example 2.5 CEO Cash Compensation, Accounting Performance,

and Compensation Committee Quality . . . . . . . . . . . . . . . . . . . . . . . . . . 47Example 2.6 The Post-Issue Operating Performance of French IPOs: Use

of PSM .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Example 2.7 Dividend Decisions, Dividend Payments, and Corporate

Social Responsibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Example 3.1 Predicting Financial Distress and Bankruptcy for USCompanies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Example 3.2 Mixed Multinomial Logit: FD of Australian Companies . . . . . . 89Example 3.3 The Ordered Multinomial Logit: FD of Polish Companies . . . 91Example 3.4 Binomial Logit: Bankruptcy of Companies in Poland . . . . . . . . . 94Example 3.5 “In Search of Distress Risk”: Investing in US Distress

Stocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Example 3.6 Exit of Firms in Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106Example 3.7 Survival of Spanish Aquaculture Firms . . . . . . . . . . . . . . . . . . . . . . . . . 111Example 3.8 Survival of Firms in Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

Example 4.1 Choice of Audit Office After Auditor Change: AuditAnalytics’ Auditor Changes Data for US Firms . . . . . . . . . . . . . . . . 130

Example 4.2 Auditors’ Going-Concern Opinions and ManagerialEarnings Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

Example 5.1 Best Practice for Warsaw Stock Exchange Companiesand Tobin’s q . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

Example 5.2 Tobin’s q and Corporate Governance for Companies Listedon the Oslo Stock Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

xix

Example 5.3 Women on Boards and Firm Risk in the USA . . . . . . . . . . . . . . . . . 170Example 5.4 CEO Turnover in Fortune 500 Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . 173Example 5.5 CEO Turnover and Mandatory IFRS Adoption in Europe . . . . 174Example 5.6 CG Quality and Earnings Management: European

Companies Cross-Listed in the USA .. . . . . . . . . . . . . . . . . . . . . . . . . . . 175Example 5.7 Corporate Governance and Earnings Manipulation

in Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

Example 6.1 Value Relevance Models for Earnings and Book Valuefor NYSE-Listed Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199

Example 6.2 Use of Principal Component Analysis in VR Research . . . . . . . 200Example 6.3 E/P as the Dependent Variable in VR Research . . . . . . . . . . . . . . . 201Example 6.4 Model for Comparative Valuation of Listed Companies

in Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205Example 6.5 Returns Versus Fundamentals for WSE-Listed Companies . . . 207Example 6.6 Mergers and Acquisitions in the WSE . . . . . . . . . . . . . . . . . . . . . . . . . . 208Example 6.7 IPOs on the Warsaw Stock Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . 209Example 6.8 Dividends in European Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

xx List of Examples