Georges Dionne

Bio: Georges Dionne is an academic researcher from HEC Montréal. The author has contributed to research in topics: Moral hazard & Adverse selection. The author has an hindex of 48, co-authored 421 publications receiving 7838 citations. Previous affiliations of Georges Dionne include École Normale Supérieure & Université de Montréal.

Credit Risk: Pricing, Measurement, and Management

Abstract: Credit Risk: Pricing, Measurement, and Management, by Darrell Duffie and Kenneth J Singleton, 2003, Princeton, NJ: Princeton University Press Credit risk is the major challenge for risk managers and market regulators International regulation of banks' credit risk was put in place in 1988 and since that time there has been no consensus on how to improve that regulatory framework Part of the explanation resides in the complexity of this risk Banks, regulators, and central banks do not agree on how to measure credit risk and, more particularly, on how to compute the optimal capital that is necessary for protecting the different partners that share this risk For example, what proportion of yield spreads on corporate bonds is explained by credit risk? Is it 30 percent, 50 percent, or even 90 percent? Is the credit risk proportion of the observed spreads solely a function of variations in the default probability or is it also explained by variations in the recovery rate over time or across cycles? Are macroeconomic cycles themselves or default risk premia, market liquidity, and even market risk significant determinants of yield spreads? These questions are important because some models such as CreditMetrics use the entire yield spread to compute the capital for credit risk If credit risk explains only a small fraction of yield spreads, these models compute too much capital for regulation and even for credit risk management (Dionne et al, 2004 and references therein) Asking banks to keep too much capital in reserve to cover credit risk can be a source of market distortion in risk management behavior (Allen and Gale, 2003; Dionne and Harchaoui, 2003) For example, it may generate some asset substitution activities that increase the risky position of banks, in order to set the level of risk at its optimal rather than regulatory level All these issues arise in part because credit risk is not well understood So the book by Duffie and Singleton will be welcomed by the academics, regulators, and practitioners who consult it The book has 13 chapters, three appendices (two on affine processes), a comprehensive list of references, and an index (authors and subjects) It covers all subjects related to credit risk It is designed for three broad audiences: academics and graduate students; those involved in the measurement and control of financial risks; and those involved in trading and marketing products with significant credit risk The main focus is modeling credit risk: measuring portfolio credit risk and pricing different securities exposed to credit risk The focus on credit risk management is less important in the book The introduction (indeed the entire book) is very well written and presents the subjects treated with clarity Credit risk is distinguished from other sources of risk such as market risk, liquidity risk, operational risk, systemic risk, and regulatory and legal risk The distinctions take many dimensions such as time horizon, liquidity, the parties implicated, methodology, and information asymmetries However, the authors insist on the fact that this does not mean that all these different risks should be managed separately These different risks may be correlated over time, so integrated frameworks for measuring and pricing them are necessary, particularly for market, credit, and liquidity risks For example, factors underlying changes in credit risk are often correlated with those underlying market risk and changes in liquidity risk can be viewed as a component of market risk and may generate credit risk The last chapter proposes an original way of integrating credit and market risks in a portfolio model The introduction also provides an overview of the book The chapters are organized to highlight the major topics related to credit risk, such as "Definition and Management" (Chapter 2), "Default and Transition" (Chapters 3 and 4), "Valuation" (including valuation of credit derivatives, Chapters 5-9), "Default Correlation" and "Portfolio Valuation" (Chapters 10 and 11), "Credit Risk in OTC Derivatives Positions" and "Portfolio Risk Measurement" (Chapters 12 and 13) …

Foundations of Economic Analysis of Law

Abstract: Foundations of Economic Analysis of Law, by Steven Shavell, 2004, The Belknap Press of Harvard University Press, 737 pages Steven Shavell has contributed to the foundations of economic analysis of law in different manners According to Posner (2006), he is a member of the third generation of economic analysts of law-Coase, Becker, and Calabresi being the first group, with Posner himself, Landes, and Ehrlich forming the second Shavell has published several books and more than 100 articles on economics and on the economics of law He has contributed to the principal-agent theory (Shavell, 1979b) and, more particularly, to the moral hazard literature (Shavell, 1979a) This book proposes an overview of the fields in the economics of law to which the author has contributed It also covers in detail other fields and many contributions to the literature The emphasis is on theory, but some empirical facts are mentioned The book has twenty-nine chapters in seven parts or sections, a comprehensive list of references (786 references in the References section of the book), and two indexes (authors and subjects) It covers many subjects related to the economic analysis of basic law Particular attention is devoted to the positive analysis of law, although the normative aspect is also well covered The book is addressed to two broad audiences: economists and individuals interested in law with no formal background in economics There is no formal economic analysis in the text (but formal models are sometimes sketched in footnotes) and no detailed discussion of legal doctrine The subjects covered are important for any legal system: laws related to property, accidents, contracts, crimes, and their litigation process Specialized subjects such as labor, bankruptcy, or environmental law are not covered However, for the readers of the Journal of Risk and Insurance, accident law is discussed in detail (one section including five chapters that will be analyzed below) Chapter 1, the introduction to the book, presents the author's basic philosophy with regard to the economics of law He first distinguishes the positive analysis of the economics of law from its normative analysis Using his example for automobile accidents, the positive analysis is concerned with how a liability system affects accidents and litigation expenses, whereas the normative analysis looks at the social desirability of a liability system Two standard and important assumptions are made for the normative analysis First, the normative analysis does not take any of the distributive aspects into account; this is left to the income tax system and other transfer mechanisms Second, the notions of fairness and morality are not integrated in the analysis, although a significant effort is made to do so in part seven of the book The first four parts of the book treat areas related to private law: property law, liability for accidents, contract law, and civil litigation They are called private because they are enforced by the activities or suits of private parties The first of the four parts is devoted to property law Chapter 2 covers the rationale of ownership and the emergence of property rights The chapter defines concepts that are not often discussed in the standard economic literature For example, the author treats property rights, their justification, and their emergence Property rights are themselves divided into two types of rights: possessory rights and transfer rights The justification of property rights is mainly related to incentives: incentives to work, incentives to maintain and improve things, and incentives to transfer things Their emergence occurs when the advantages are greater than the costs of instituting and maintaining them Chapter 3 is devoted to the division of property rights while chapter 4 discusses, in detail, the acquisition and transfer of property rights, including transfer after death Chapter 5 concerns the issues of conflict and cooperation associated with the use of property rights …

Testing for Evidence of Adverse Selection in the Automobile Insurance Market: A Comment

Abstract: In 1994, Puelz and Snow presented empirical evidence of adverse selection in the market for automobile collision insurance. Using data from a private insurer, they claimed to have found strong evidence of adverse selection in the insurer’s portfolio. Their test was based on individuals’ choice of deductible in each risk class. From the models of Rothschild and Stiglitz (1976) and Wilson (1977), it is well known that if residual adverse selection is present in some risk classes, insurers will offer menus of contracts from which insureds will self-select. At equilibrium, higher-risk individuals will choose the smaller deductible and will be charged the higher price per unit of insurance (Dionne, Doherty, and Fombaron 2000). An empirical test of the theory is to verify, in each risk class, whether lower deductibles are chosen by insureds with higher accident proba-

Handbook of insurance

Abstract: Preface.- Introduction.- Part 1: History.- Developments in Risk and Insurance Economics: the Past 40 Years.- Part 2 : Risk and Insurance Theory Without Information Problems.- Higher-Order Risk Attitudes.- Non-Expected Utility and the Robustness of the Classical Insurance Paradigm.- The Economics of Optimal Insurance Design.- The Effects of Changes in Risk on Risk Taking: A Survey.- Risk Measures and Dependence Modeling.- The Theory of Insurance Demand.-Prevention and Precaution.- Part 3 : Asymmetric Information: Theory.- Optimal Insurance Contracts under Moral Hazard.- Adverse Selection in Insurance Contracting.- The Theory of Risk Classification.- The Economics of Liability Insurance.- Economic Analysis of Insurance Fraud.- Part 4: Asymmetric Information: Empirical Analysis.- Asymmetric Information in Insurance Markets: Predictions and Tests.- The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data.- Workers' Compensation: Occupational Injury Insurance's Influence on the Workplace.- Experience Rating in Non-Life Insurance.- Part 5 : Risk Management.- On the Demand for Corporate Insurance - Creating Value.- Managing Catastrophic Risks through Redesigned Insurance: Challenges and Opportunities.- Innovations in Insurance Markets: Hybrid and Securitized Risk-Transfer Solutions.- Risk Sharing and Pricing in the Reinsurance Market.- Part 6 : Insurance Pricing.- Financial Pricing of Insurance.- Insurance Price Volatility and Underwriting Cycles.- Part 7 : Industrial Organization of Insurance Markets.- On the Choice of Organizational Form: Theory and Evidence from the Insurance Industry.- Insurance Distribution.- Corporate Governance in the Insurance Industry: A Synthesis.- Systemic Risk and the Insurance Industry.- Analyzing Firm Performance in the Insurance Industry Using Frontier Efficiency and Productivity Methods.- Capital Allocation and its Discontents.- Capital and Risks Interrelationships in the Life and Health Insurance Industries: Theories and Applications.- Insurance Market Regulation: Catastrophe Risk, Competition, and Systemic Risk.- Insurance Markets in Developing Countries: Economic Importance and Retention Capacity.- Part 8: Health and Long-Term Care Insurance, Longevity Risk, Life Insurance, and Social Insurance.- Health Insurance in the United States.- Longevity Risk and Hedging Solutions.- Long-Term Care Insurance.- New Life Insurance Financial Products.- The Division of Labor Between Private and Social Insurance.

Econometric Analysis of Panel Data

Abstract: Preface.1. Introduction.1.1 Panel Data: Some Examples.1.2 Why Should We Use Panel Data? Their Benefits and Limitations.Note.2. The One-way Error Component Regression Model.2.1 Introduction.2.2 The Fixed Effects Model.2.3 The Random Effects Model.2.4 Maximum Likelihood Estimation.2.5 Prediction.2.6 Examples.2.7 Selected Applications.2.8 Computational Note.Notes.Problems.3. The Two-way Error Component Regression Model.3.1 Introduction.3.2 The Fixed Effects Model.3.3 The Random Effects Model.3.4 Maximum Likelihood Estimation.3.5 Prediction.3.6 Examples.3.7 Selected Applications.Notes.Problems.4. Test of Hypotheses with Panel Data.4.1 Tests for Poolability of the Data.4.2 Tests for Individual and Time Effects.4.3 Hausman's Specification Test.4.4 Further Reading.Notes.Problems.5. Heteroskedasticity and Serial Correlation in the Error Component Model.5.1 Heteroskedasticity.5.2 Serial Correlation.Notes.Problems.6. Seemingly Unrelated Regressions with Error Components.6.1 The One-way Model.6.2 The Two-way Model.6.3 Applications and Extensions.Problems.7. Simultaneous Equations with Error Components.7.1 Single Equation Estimation.7.2 Empirical Example: Crime in North Carolina.7.3 System Estimation.7.4 The Hausman and Taylor Estimator.7.5 Empirical Example: Earnings Equation Using PSID Data.7.6 Extensions.Notes.Problems.8. Dynamic Panel Data Models.8.1 Introduction.8.2 The Arellano and Bond Estimator.8.3 The Arellano and Bover Estimator.8.4 The Ahn and Schmidt Moment Conditions.8.5 The Blundell and Bond System GMM Estimator.8.6 The Keane and Runkle Estimator.8.7 Further Developments.8.8 Empirical Example: Dynamic Demand for Cigarettes.8.9 Further Reading.Notes.Problems.9. Unbalanced Panel Data Models.9.1 Introduction.9.2 The Unbalanced One-way Error Component Model.9.3 Empirical Example: Hedonic Housing.9.4 The Unbalanced Two-way Error Component Model.9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data.9.6 The Unbalanced Nested Error Component Model.Notes.Problems.10. Special Topics.10.1 Measurement Error and Panel Data.10.2 Rotating Panels.10.3 Pseudo-panels.10.4 Alternative Methods of Pooling Time Series of Cross-section Data.10.5 Spatial Panels.10.6 Short-run vs Long-run Estimates in Pooled Models.10.7 Heterogeneous Panels.Notes.Problems.11. Limited Dependent Variables and Panel Data.11.1 Fixed and Random Logit and Probit Models.11.2 Simulation Estimation of Limited Dependent Variable Models with Panel Data.11.3 Dynamic Panel Data Limited Dependent Variable Models.11.4 Selection Bias in Panel Data.11.5 Censored and Truncated Panel Data Models.11.6 Empirical Applications.11.7 Empirical Example: Nurses' Labor Supply.11.8 Further Reading.Notes.Problems.12. Nonstationary Panels.12.1 Introduction.12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence.12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence.12.4 Spurious Regression in Panel Data.12.5 Panel Cointegration Tests.12.6 Estimation and Inference in Panel Cointegration Models.12.7 Empirical Example: Purchasing Power Parity.12.8 Further Reading.Notes.Problems.References.Index.

Estimation and Inference in Econometrics

Abstract: Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Table Of Integrals Series And Products

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