Abstract What distribution best characterizes the time series and cross-section of individual stock returns? To answer this question, we estimate the degree of cross-sectional return skewness relative to a benchmark that nests many models considered in the literature. We find that cross-sectional skewness in monthly returns far exceeds what this benchmark model predicts. However, cross-sectional skewness in long-run returns in the data is substantially below what the model predicts. We show that fat-tailed idiosyncratic events appear to be necessary to explain skewness in the data. (JEL, G10, G11, G12, G13, G14).

ABSTRACT Homeowners insurance is central to managing the rising losses from climate‐related disasters. We show that insurance premiums are subject to starkly different regulations across states, creating persistent cross‐subsidies and price distortions. We employ states' regulatory rules in an instrumental variable estimation and a border discontinuity design to show insurers do not adjust rates in highly regulated states and compensate by raising rates in less regulated states. Rates and risks diverge in the long run, distorting cross‐state risk‐sharing and increasing insurer exits from highly regulated states. We argue these patterns stem from the interactions between rate regulation and insurers' financing constraints.