Estimating policy impact in a difference-in-differences hazard model : a simulation study

This article estimates the impact of a policy change on an event probability in a difference-in-differences hazard model using four estimators. We examine the error distributions of the estimators via a simulation experiment with twelve different scenarios. In four simulation scenarios when all relevant variables are known, three of the four methods yield accurate estimates of the policy impact. In eight simulation scenarios when an individual characteristic is unobservable to the researcher, only one method (nonparametric maximum likelihood) achieves accurate estimates of the policy change. The other three methods (standard Cox, three-step Cox, and linear probability) are severely biased.