We study the impact of succession tournaments on risk-taking in family firms. More sons (less daughters) in controlling families are associated with higher income volatility and lower performance – especially, in opaque private firms with pyramidal ownership structure. Contestants exhibit...

State governments receive an exogenous tax windfall whenever their residents win a multi-state lottery. These lottery tax windfalls are counter-cyclical but occur during a range of economic conditions. Therefore, lottery tax windfalls enable us to estimate the impact of fiscal policy on...

We study the role of insurance companies in propagating liquidity shocks to the real economy. We use natural disasters as our instrument to identify exogenous shifts in capital market liquidity, and study whether capital market liquidity affects regional-level fiscal conditions and drives GDP...

Electricity consumption is a useful real-time proxy for economic activities, as most modern-day economic activities involve the use of electricity, which cannot be easily stored. Empirically, electricity consumption data is widely available in high frequency at both aggregate and disaggregate...

We show that provision of public liquidity has real consequences for firms. Comparing A-1 rated non-financial commercial paper issuers using Commercial Paper Funding Facility (CPFF) eligibility criteria, we show that firms with access to the CPFF were able to mitigate financing disruptions...

We study dynamic incentive contracts in a continuous-time agency model with productivity switching between two unobserved states, about which an investor may learn by deviating from the myopically optimal action. The optimal contract balances short-run profits from myopic actions and the...

This research investigates the real effects of public liquidity provision. Using the Commercial Paper Funding Facility's (CPFF) eligibility criteria for non-financial commercial paper issuers as the identification strategy, we show that firms with access to the CPFF were able to mitigate the...

This paper uses a machine-learning-based framework to analyze lending decisions. We develop an adversarial learning model that learns the mortgage lending rules for non-minority borrowers and decompose loan decisions into model explained, favorable disagreement, and unfavorable disagreement...