The Estimation of Causal Effects by Difference-in-Difference Methods

This survey gives a brief overview of the literature on the difference-in-difference (DiD) estimation strategy and discusses major issues using a treatment effects perspective. In this sense, this survey gives a somewhat different view on DiD than the standard textbook discussion of the DiD model, but it will not be as complete as the latter. It contains some extensions of the literature, for example, a discussion of, and suggestions for nonlinear DiD estimators as well as DiD estimators based on propensity-score type matching methods.