We develop a flexible semiparametric time series estimator that is then used to assess the causal effect of monetary policy interventions on macroeconomic aggregates. Our estimator captures the average causal response to discrete policy interventions in a macro-dynamic setting, without the need...

Time series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a...

We evaluate the effects of academic achievement awards for first and second-year college students on a Canadian commuter campus. The award scheme offered linear cash incentives for course grades above 70. Awards were paid every term. Program participants also had access to peer advising by...

This paper develops a covariate-based approach to the external validity of instrumental variables (IV) estimates. Assuming that differences in observed complier characteristics are what make IV estimates differ from one another and from parameters like the effect of treatment on the treated, we...

Estimates using admissions lotteries suggest that urban charter schools boost student achievement, while charter schools in other settings do not. We explore student-level and school-level explanations for these differences using a large sample of Massachusetts charter schools. Our results show...