What is the impact of granular credit risk on banks and on the economy? We provide the first causal identification of single-name counterparty exposure risk in bank portfolios by applying a new empirical approach on an administrative matched bank-firm dataset from Norway. Exploiting the fat tail...

Because individuals with HIV are more likely to fall into poverty, and the poor may be at higher risk of contracting HIV, simple estimates of the effect of HIV status on economic outcomes will tend to be biased. In this paper, we use two econometric methods based on the propensity score to...

We propose several econometric measures of systemic risk to capture the interconnectedness among the monthly returns of hedge funds, banks, brokers, and insurance companies based on principal components analysis and Granger-causality tests. We find that all four sectors have become highly...

Many empirical microeconomic studies estimate econometric models that assume a single finite-valued discrete endogenous regressor (for example: different levels of schooling), exogenous regressors that are additively separable and enter the equation linearly; and coefficients (including per-unit...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

Economists are increasingly turning to the experimental method as a means to estimate causal effects. By using randomization to identify key treatment effects, theories previously viewed as untestable are now scrutinized, efficacy of public policies are now more easily verified, and stakeholders...

Can managers influence the liquidity of their firms' shares? We use plausibly exogenous variation in the supply of public information to show that firms seek to actively shape their information environments by voluntarily disclosing more information than is mandated by market regulations and...

The purpose of this paper is to help empirical economists think through when and how to weight the data used in estimation. We start by distinguishing two purposes of estimation: to estimate population descriptive statistics and to estimate causal effects. In the former type of research,...

Economists are increasingly turning to the experimental method as a means to estimate causal effects. By using randomization to identify key treatment effects, theories previously viewed as untestable are now scrutinized, efficacy of public policies are now more easily verified, and stakeholders...

Haavelmo's seminal 1943 paper is the first rigorous treatment of causality. In it, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining...