Daniele Girardi (U of Mass, Amherst)

Abstract:

Recent applied microeconometrics research proposes various difference-in-differences (DiD) estimators for the problem of dynamic heterogeneous treatment effects. We show that the problem can be resolved by the local projection (LP) estimators of the sort used in applied macroeconometrics. Our proposed LP-DiD estimator provides an overarching toolkit with several advantages. First, the method is clear, simple, easy to compute, and transparent and flexible in its handling of treated and control units. Second, it is quite general, including its ability to control for pre-treatment values of the outcome and of other covariates, as under conditional common trends. Third, the LP-DiD can nest other estimators, providing a framework that is not only rigorous but also encompassing. The LP-DiD estimator does not suffer from the negative weighting problem, and indeed can be implemented with any weighting scheme the investigator desires. Simulations demonstrate the good performance of the LP-DiD estimator in common settings. Two empirical applications illustrate how LP-DiD addresses the bias of conventional fixed effects estimators, leading to potentially different results