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Identification and Confidence Regions for Treatment Effect and its Distribution under Stochastic Dominance

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  • Sungwon Lee

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper considers identification of treatment effect and its distribution under some distributional assumptions. I assume that a binary treatment is endogenously determined. The main identification objects are the quantile treatment effect and the distribution of the treatment effect. To examine the identification problems, I construct a counterfactual model without specifying an underlying economic model and apply Manski's approach (Manski (1990)) to find the quantile treatment effects. For the distribution of the treatment effect, I follow the approach proposed by Fan and Park (2010). Some distributional assumptions called stochastic dominance are imposed on the model. Stochastic dominance assumptions are consistent with economic theories in many areas and the results show that those distributional assumptions help to tighten the bounds on the parameters of interest. This paper also provides confidence regions for identified sets that are pointwise consistent in level. An empirical study on the return to college is provided. The empirical results confirm that the stochastic dominance assumptions improve the bounds on the distribution of the treatment effect.

Suggested Citation

  • Sungwon Lee, 2020. "Identification and Confidence Regions for Treatment Effect and its Distribution under Stochastic Dominance," Working Papers 2011, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    • Handle: RePEc:sgo:wpaper:2011
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    References listed on IDEAS

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