Canada Research Chair in Risk Management
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Handbook of Insurance, Third Edition, Volume I, 2025
The Handbook of Insurance reviews the last fifty years of research developments in insurance economics and its related fields. A single reference source for professors, researchers, graduate students, regulators, consultants, and practitioners. Volume I starts with the history and foundations of risk and insurance. The new edition covers many topics that have risen in importance since the 2nd edition in 2013, such as climate risk, pandemic risk, insurtech, digital insurance, cyber risk, causality in econometrics, capital in life insurance, life insurance products, telematics, insurance fraud detection, and machine learning. ​
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Excerpts from the two prefaces:
It is a tour de force to provide to the insurance industry and its stakeholders a structured, complete, intelligent and critical synthesis of insurance economics in the twenty-first century.
Christian Gollier, Director, Toulouse School of Economics
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This collective work not only offers a remarkable synthesis of cutting-edge research in insurance economics but also provides a rare resource, both comprehensive and authoritative, for professionals seeking a deeper understanding of insurance industry fundamentals and emerging trends.
Jad Ariss, Managing director, The Geneva Association​​
Handbook of Insurance, Third Edition, Volume II, 2025
The Handbook of Insurance reviews the last fifty years of research developments in insurance economics and its related fields. A single reference source for professors, researchers, graduate students, regulators, consultants, and practitioners. Volume II starts with the evolution of the theory of risk since the second edition in 2013. The new edition covers many other topics that have risen in importance since the 2nd edition, such as moral hazard, adverse selection, self protection, risk classification, insurance fraud, insurance distribution, insurance pricing, enterprise risk management, insurance company rating, insurance market regulation, solvency regulation, insurance markets in USA and China, corporate governance, and microinsurance.​
The effect of inflation on US insurance markets: A Markov-switching model analysis
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We analyze the characteristics of the U.S. inflation rate series observed over the 1973-2023 period in order to capture and model the effect of inflation on the insurance industry. Two important conclusions emerge from the data: The US inflation rate series is characterized by a random trend and non-linear dynamics (asymmetry). These results led us to select the two-regime Markov-switching model to study the impact of inflation on various fundamental indicators of insurance industry performance in the US. We show that performance indicators are differently affected by inflation in the Life and P&C insurance sectors according to the inflation regime considered.
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Source: World Bank.
The effect of inflation on US insurance markets
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We analyze the effects of inflation on the US insurance industry. The analysis is based initially on a VAR (Vector AutoRegressive) model. The shock of the COVID-19 pandemic had a significant positive short-term impact on inflation, probably explained by the recent contractionary of the Fed monetary policy against inflation. We then analyze the characteristics of the U.S. inflation rate series observed over the 1973-2023 period in order to capture and model the effect of inflation on the insurance industry. Two important conclusions emerge from this analysis: The US inflation rate series is characterized by nonlinear dynamics (asymmetry) and a random trend. The results obtained led us to select the two-regime Markov model to analyze the impact of inflation on the various fundamental indicators of insurance company performance in the US. We show that performance indicators are differently affected by inflation in the Life and P&C insurance sectors according to the inflation regime considered.
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Impulse response function of post-COVID-19 inflation.
Nonparametric testing for information asymmetry in the mortgage servicing market
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Our objective is to test for evidence of information asymmetry in the mortgage servicing market. Does the sale of mortgage servicing rights (MSR) by the initial lender to a second servicing institution unveil any residual asymmetric information? We are the first to analyze the originator’s selling choice of MSR. We use a large sample of U.S. mortgages that were securitized through the private-label channel during the period of January 2000 to December 2013 (more than 5 million observations). We propose a new nonparametric instrumental variable testing procedure to account for potential endogeneity. For robustness, we present parametric analyses to corroborate our results using instrumental variables. Our empirical results provide strong support for the presence of second-stage asymmetric information in the mortgage servicing market during the period of analysis and before the risk retention reform of 2014.
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In presence of asymmetric information, we observe a higher loan default probability (red line) when the Mortgage Servicing Rights are sold by the bank to a third-party servicer.
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Data source: Jedidi and Dionne Risks, 2024.
High price impact trades identification and its implication for volatility and price efficiency
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We include Limit Order Book (LOB) matchedness as a new trade attribute to
identify High Price Impact Trades (HPITs). HPITs are trades associated with large price changes relative to their volume proportion. We show that the inclusion of matchedness provides a finer analysis of the relationship between price contribution and trade categories. We further verify that a stronger presence of HPITs leads to a decline in volatility and improves price efficiency, which suggests a link between HPITs and informed trades.
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Average Intraday Dynamics of DAX Spread
Data source: Dionne and Zhou, Risk Sciences, 2024.
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We investigate the causes of the gap in mergers and acquisitions (M&A) between life and nonlife insurers in the US from 1990 to 2022. Our DID analysis indicates a parallel trend between M&As in the life insurance and nonlife insurance sectors from 1990 to 2012, and a significant difference after 2012. There was a shock in the life insurance market that resulted in a reduction in M&As after 2012. Variable annuity sales in the life insurance sector declined after 2012. We find evidence that low interest rates observed during the implementation of the quantitative easing policy of the Fed from 2008 to 2012 caused the difference in M&As in the life sector after 2012.
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Fed’s interest rate and 10-year T-bond interest rate
Data source: World Bank database.
Developments in risk and insurance economics: The past 50 years
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The chapter reviews the evolution in risk and insurance economics over the past 50 years, first recalling the situation in 1973, then presenting the developments and new approaches that have flourished since then. We argue that these developments were only possible because steady advances were made in the economics of risk and uncertainty and in financial theory. Insurance economics has grown in importance to become a central theme in modern economics, providing not only practical examples and original data to illustrate new theories, but also inspiring new ideas that are relevant to the overall economy.
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Climate risk is becoming a real challenge for the insurance industry.
Adverse selection in insurance
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In this survey we present some of the more signiÂ…cant results in the literature on adverse selection in insurance markets. Sections 1 and 2 introduce the subject, and Section 3 discusses the monopoly model developed by Stiglitz (1977) for the case of single-period contracts, which has been extended by many authors to the multi-period case. The introduction of multi-period contracts raises issues that are discussed in detail; time horizon, discounting, commitment of the parties, contract renegotiation, and accident underreporting. Section 4 covers the literature on competitive contracts, where the analysis is more complicated because insurance companies must take competitive pressures into account when they set incentive contracts. As pointed out by Rothschild and Stiglitz (1976), there is not necessarily a Nash equilibrium when there is adverse selection. However, market equilibrium can be sustained when principals anticipate competitive reactions to their behavior. Multi-period contracting is discussed. We show that different predictions on the evolution of insurer profits over time can be obtained from different assumptions concerning the sharing of information between insurers about an individualÂ’s choice of contracts and accident experience. The roles of commitment and renegotiation between the parties to the contract are important. Section 5 introduces models that consider moral hazard and adverse selection simultaneously, and Section 6 covers adverse selection when people can choose their risk status. Section 7 discusses many extensions to the basic models such as risk categorization, multidimensional adverse selection, symmetric imperfect information, double-sided adverse selection, participating contracts, and nonexclusive contracting.
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A pooling solution cannot be a Nash equilibrium.
Causality in empirical analyses with emphasis on asymmetric information and risk management
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We discuss the difficult question of measuring causality effects in empirical analyses, with applications to asymmetric information and risk management. It is now well documented in the economic literature that policy analysis must be causal. Hence, the measurement of its effects must also be causal. After having presented the main frameworks for causality analysis, including instrumental variable, difference-in-differences, and generalized method of moments, we analyze the following questions: Does risk management affect firm value and risk? Do we face a moral hazard problem in the insurance data? How can we separate moral hazard from adverse selection and asymmetric learning? Is liquidity creation a causal factor for reinsurance demand? We show that residual information problems are often present in different markets, while risk management may increase firm value when appropriate methodologies are applied.
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We observe a significant decrease in accidents three quarters after the policy change.
The profitability of lead–lag arbitrage at high frequency
Any lead-lag effect in an asset pair implies the future returns on the lagging asset have the potential to be predicted from past and present prices of the leader, thus creating statistical arbitrage opportunities. We utilize robust lead-lag indicators to uncover the origin of price discovery and we propose an econometric model exploiting that effect with level 1 data of limit order books (LOB). We also develop a high-frequency trading strategy based on the model predictions to capture arbitrage opportunities. The framework is then evaluated on six months of DAX 30 cross-listed stocks’ LOB data obtained from three European exchanges in 2013: Xetra, Chi-X, and BATS. We show that a high-frequency trader can profit from lead-lag relationships because of predictability, even when trading costs, latency, and execution-related risks are considered.
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