Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?
This paper applies cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work (NSW) Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1999,2002). We ﬁnd that estimates of the impact of NSW based on propensity score matching are highly sensitive to both the set of variables included in the scores and the particular analysis sample used in the estimation. Among the estimators we study, the diﬀerence-in-diﬀerences matching estimator performs the best. We attribute its performance to the fact that it eliminates potential sources of temporally-invariant bias present in the NSW data, such as geographic mismatch between participants and non-participants and the use of a dependent variable measured in diﬀerent ways for the two groups. Our analysis demontrates that while propensity score matching is a potentially useful econometric tool, it does not represent a general solution to the evaluation problem.