On the Specification of Propensity Scores: with Applications to the Analysis of Trade Policies

The use of propensity score models for program evaluation with non-experimental data typically requires the propensity score be estimated, often with a model whose specification is unknown. While theoretical results suggest that estimators utilizing more flexible propensity score specifications perform better, this has not filtered into applied research. Here, we provide Monte Carlo evidence indicating benefits of over-specifying the propensity score that are robust across a number of different covariate structures and estimators. We illustrate these results with two applications, one assessing the environmental effects of GATT/WTO membership and the other assessing the impact of euro adoption on bilateral trade.