In a banking model with imperfect information, I find that more precise information increases the economy's vulnerability to bank runs. For low transparency levels, depositors cannot distinguish bad from good states based on their private signals and, absent liquidity shocks, have no incentives to withdraw early. As transparency increases, and private signals become more informative, depositors' incentives to withdraw strengthen and run-proof contracts become costlier...

We examine the optimal financing of infrastructure when governments can expropriate rents from private sector firms that manage infrastructure. While private firms need incentives to implement projects well, governments need incentives to limit expropriation. This double moral hazard limits the willingness of outside investors to fund infrastructure projects. Optimal financing contracts involve government guarantees to investors against project failure to incentivize the government to agree not to expropriate which...

We study how competition between asymmetrically informed banks, one specialized and one non-specialized, affects loan prices. Both banks possess “general” signals regarding the borrower’s quality, which they use to screen loans. The specialized bank also has access to a “specialized” signal on which it bases its loan pricing. This private-information-based pricing makes the specialized bank bid more aggressively, mitigating the informational rent effect that gives...

Recent technological change in lending converts previously subjective assessments into structured, easily accessible data. We study this transformation in a credit market competition model that distinguishes between information span (breadth) and signal precision (quality). Borrower quality depends on multidimensional fundamentals, assessed through hard or soft signals. Two banks observe private hard signals, but only the specialized bank receives a soft signal. Expanding the span of...

We study the optimal design of stress scenarios. A principal manages the unknown risk exposures of agents by asking them to report losses under hypothetical scenarios before taking remedial actions. We apply a Kalman filter to solve the learning problem and we relate the optimal design to the risk environment, the principal’s preferences, and available interventions. Applied to banking stress tests, optimal capital requirements cover losses under an adverse scenario...