We use a large data set of deductible choices in auto insurance contracts to estimate the distribution of risk preferences in our sample. To do so, we develop a structural econometric model, which accounts for adverse selection by allowing for unobserved heterogeneity in both risk (probability...

The presence of a heavy truck on the road can impose an externality if accidents occur that would not have otherwise. We find each additional truck on the road increases the risk of a truck accident--but also, at an even higher rate, the risk of a car-on-car collision. Our estimates imply two...

This study quantifies the importance of private information, separates the extent to which the positive correlation between the accident probability and insurance coverage reflects adverse selection and moral hazard, and analyzes market segmentation on objective accident risk. We use data we...

Americans drive 2,360,000,000,000 miles each year, far outstripping other nations. Every time a driver takes to the road, and with each mile she drives, she exposes herself and others to the risk of accident. Insurance premiums are only weakly linked to mileage, however, and have largely...

This paper studies a unique panel dataset of transactions with repeat customers of an insurer operating in a market in which insurers are not required by law or contract to share information about their customers' records. I use this dataset to test the asymmetric learning hypothesis that...

New technologies have enabled firms to elicit granular behavioral data from consumers in exchange for lower prices and better experiences. This data can mitigate asymmetric information and moral hazard, but it may also increase firms' market power if kept proprietary. We study a voluntary...