Topic: Difference in Differences with Time-Varying Covariate
Abstract: This paper considers identification and estimation of causal effect parameters from participating in a binary treatment in a difference in differences (DID) setup when the parallel trends assumption holds after conditioning on observed covariates. Relative to existing work in the econometrics literature we consider the case where the value of covariates can change over time and potentially, where participating in the treatment can affect the covariates themselves. We propose new empirical strategies in both cases. We also consider two-way fixed effects (TWFE) regressions that include time-varying regressors, which is the most common way that DID identification strategies are implemented under conditional parallel trends. We show that TWFE regressions can deliver misleading estimates of causal effect parameters in a number of empirically relevant cases. We propose both doubly robust estimands and regression adjustment/imputation strategies that are robust to these issues while not being substantially more challenging to implement.
Speaker Brief Bio: Brantly Callaway
Brantly Callaway is an Assistant Professor in the Economics Department at the University of Georgia. His primary research interests are Microeconometrics and Labor Economics. Most of his research has concerned how to use panel data to think about causal effects of economic policies. He has been particularly interested in developing methods related to understanding how effects of policies vary across different individuals. His work has been published in Journal of Econometrics (4) Oxford Bulletin of Economics and Statistics Empirical Economics and etc.
MS Team Meeting ID：414904397