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.
|Date of creation:||Jan 2008|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.iub.edu/~caepr
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:inu:caeprp:2006013_updated. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Center for Applied Economics and Policy Research)
If references are entirely missing, you can add them using this form.