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Social interactions and households’ flood insurance decisions

Journal of Financial Economics 2022 144(2), 414-432
Flooding is the most costly natural disaster faced by US households, yet policymakers are puzzled by the low take-up rates for flood insurance. Leveraging novel transaction-level data, this paper studies the influence of social interactions on households’ insurance decisions. I show that households increase flood insurance purchases by 1–5 percent when their geographically distant friends are exposed to flooding events or to campaigns for flood insurance. These exogenous shocks to far-away friends should not affect local households’ own insurance decisions except through peer effects. I provide evidence suggesting that social interactions facilitate learning through information dissemination and attention triggering.

The Response of Mortgage Supply to Expected Flood Insurance Lapses

Review of Financial Studies 2026
Flooding is among the costliest natural disasters in many countries. To protect collateral, many mortgage borrowers in the United States are legally required to maintain flood insurance. However, lax enforcement leads to frequent policy lapses. This paper shows that lenders provide credit contingent on borrowers’ insurance incentives. Exploiting exogenous premium rises ($266 annually) that disincentivize insurance take-up, I find mortgage denial rates dramatically increase by 0.49–0.81 pp. By comparison, lowering income by $266 has an effect of only 0.01 pp. Mortgage applicants’ composition remains unchanged, refuting demand-side explanations. Evidence suggests lenders internalize ex-post monitoring costs into ex-ante credit restrictions.

Information Dispersion across Employees and Stock Returns

Review of Financial Studies 2021 34(10), 4785-4831 open access
Rank-and-file employees are becoming increasingly critical for many firms, yet we know little about how their employment dynamics matter for stock prices. We analyze new data from the individual CV’s of public company employees and find that rank-and-file labor flows can be used to predict abnormal stock returns. Accounting data and survey evidence indicate that workers’ labor market decisions reflect information about future corporate earnings. Investors, however, do not appear to fully incorporate this information into their earnings expectations. The findings support the hypothesis that rank-and-file employees’ entry and exit decisions reveal valuable insights into their employers’ future stock performance.