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

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  • Daniel Millimet

    (Southern Methodist University)

  • Rusty Tchernis

    (Indiana University Bloomington)

Abstract

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.

Suggested Citation

  • Daniel Millimet & Rusty Tchernis, 2006. "On the Specification of Propensity Scores: with Applications to the Analysis of Trade Policies," CAEPR Working Papers 2006-013, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington, revised Jan 2008.
  • Handle: RePEc:inu:caeprp:2006013
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    References listed on IDEAS

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    More about this item

    Keywords

    Treatment Effects; Program Evaluation; WTO; Environment; Currency Union;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • F18 - International Economics - - Trade - - - Trade and Environment

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