Abstract: Flooding is the costliest natural disaster in the US. To protect collateral, many mortgage borrowers are legally required to maintain flood insurance. However, lax enforcement leads to frequent policy lapses. This paper hypothesizes that lenders, facing high monitoring costs, provide credit contingent on borrowers' insurance incentives. Exploiting exogenous premium rises ($266 annually) that disincentivize insurance take-up, I find lenders increase mortgage denial rates dramatically by 0.56-0.81pp. As a comparison, lowering income by $266 has an effect of only 0.01pp. Total applications and borrower characteristics remain unchanged, refuting demand-side explanations. Evidence suggests that lenders internalize ex-post monitoring costs into ex-ante credit restrictions.

[link]

Abstract: 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.

[link]

Abstract: 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 CVs 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 convey valuable insight into their employers’ future stock performance.

[link]

Abstract: This paper explores how venture capitalists add value by examining the labor dynamics of founders. Using new hand-collected data, I show that VCs establish an internal labor market (ILM) to facilitate entrepreneurial mobility across their portfolio firms. Survey evidence suggests that VCs make referrals primarily based on their private information about founders' quality or skills, creating value for the recipient firms. Consistent with this mechanism, I find that (a) former VC partners continue to influence founder mobility, (b) ILM intensity positively predicts VC fund returns, and (c) ILM is stronger where information asymmetry is greater.

[link]

Using a large-scale field experiment, we test whether high-skilled employees discriminate against female-led firms. We build 18 high-growth startups in nine identical pairs differing only by founder gender, signaled by matched AI-generated headshots. Founders email prospective employees about a role and request a meeting. Male founders secure a 10% acceptance rate, while identical female founders receive 30-50% fewer acceptances. Finding no in-group preferences, we implement an intervention to shift beliefs about success. Priming respondents with information on funding initiatives for female entrepreneurs reduces the gap by 90%, consistent with third-party discrimination: employees internalize discrimination of other market participants against employers.