Essays on optimal insurance design

Abstract

This dissertation consists of three chapters analyzing the optimal design of insurance contracts. I consider three relevant contexts that change the central trade-off between the provision of insurance and the provision of incentives. The first chapter analyzes the role of biased beliefs for the optimal design of static and dynamic insurance contracts. Biased risk perceptions change the perceived value of insurance and the perceived returns to avoiding these risks. I show empirically that unemployed workers overestimate how quickly they will find work, but underestimate the return to their search efforts. I analyze how these biases drive a wedge between social and private insurance, and between naive and optimal policy implementation. The second chapter analyzes the role of training for the design of unemployment insurance. A worker's human capital falls upon displacement and depreciates during unemployment. Training counters the decrease in human capital, but also changes the willingness of the unemployed to search. I characterize the optimal unemployment insurance contract and analyze the optimal timing of unemployment benefits and training programs during unemployment. The third chapter analyzes the role of heterogeneity in risk perceptions for the optimal design of screening contracts in a model with moral hazard and adverse selection. I show how optimists receive less insurance than pessimists and I contrast the distortions in insurance coverage that arise with competing and monopolistic insurers.

(cont.) Heterogeneity in beliefs strengthens the case for government intervention in insurance markets and can explain the negative correlation between risk occurrence and insurance coverage found in empirical studies.