Recently there has been a surge in econometric and epidemiologic works focusing on estimating average treatment effects under various sets of assumptions. Estimation of average treatment effects in observational studies often requires adjustment for differences in pretreatment variables. Rosenbaum and Rubin have proposed the propensity score method for estimating the average treatment effect by adjusting pretreatment variables. In this paper, the empirical likelihood method is used to estimate average treatment effects on the treated under the difference-in-differences framework. The advantage of this approach is that the common marginal covariate information can be incorporated naturally to enhance the estimation of average treatment effects. Compared with other approaches in the literature, the method proposed can provide more efficient estimation. A simulation study and a real economic data analysis are presented. Copyright (c) 2008 The Authors.
