Nos derniers articles

This paper explores moral hazard in insurance when individuals test for risk severity. It highlights how regulations and loss reduction costs impact behavior. Monetary costs lead to uniform loss reduction, while convex costs drive higher-risk individuals to reduce losses more. Insurers can incentivize risk discovery and reduction through tailored contracts.

We explore the challenge of measuring causal effects in empirical analyses, particularly in areas like asymmetric information and risk management. It emphasizes the importance of causal analysis in policy evaluation and discusses various frameworks such as instrumental variable, difference-in-differences, and generalized method of moments. The analysis addresses questions related to risk management's impact on firm value, moral hazard in insurance data, separating moral hazard from adverse selection, and the causal relationship between liquidity creation and reinsurance demand. The findings suggest that appropriate methodologies can enhance the value of risk management in firms despite residual information problems in various markets.