Estimating risk preferences integrating insurance choices with subjective beliefs

This paper combines real-world decisions with experimental elicitations to estimate risk preferences by incorporating individuals’ subjective beliefs in the analysis of insurance data. Unlike most studies estimating risk preferences “in the field”, we refrain from making specific assumptions regarding expectations; rather, we elicit them directly from the respondents. This approach yields risk aversion estimates compatible with a variety of deviations from rational expectations, such as biased subjective risk perceptions. Our results reveal that agents tend to overestimate the probability of recent rare events happening again in the recent future, and that the standard assumption of rational beliefs can lead to biased estimates and policy recommendations. Our empirical application offers new insights into the current debate on crop insurance subsidies. Correcting biased beliefs appears to be an effective strategy to reduce government support and, at the same time, maintain a high level of enrollment.