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Treatment effects in sample selection models and their nonparametric estimation

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  • Lee, Myoung-jae

Abstract

In a sample-selection model with the ‘selection’ variable Q and the ‘outcome’ variable Y∗, Y∗ is observed only when Q=1. For a treatment D affecting both Q and Y∗, three effects are of interest: ‘participation’ (i.e., the selection) effect of D on Q, ‘visible performance’ (i.e., the observed outcome) effect of D on Y≡QY∗, and ‘invisible performance’ (i.e., the latent outcome) effect of D on Y∗. This paper shows the conditions under which the three effects are identified, respectively, by the three corresponding mean differences of Q, Y, and Y|Q=1 (i.e., Y∗|Q=1) across the control (D=0) and treatment (D=1) groups. Our nonparametric estimators for those effects adopt a two-sample framework and have several advantages over the usual matching methods. First, there is no need to select the number of matched observations. Second, the asymptotic distribution is easily obtained. Third, over-sampling the control/treatment group is allowed. Fourth, there is a built-in mechanism that takes into account the ‘non-overlapping support problem’, which the usual matching deals with by choosing a ‘caliper’. Fifth, a sensitivity analysis to gauge the presence of unobserved confounders is available. A simulation study is conducted to compare the proposed methods with matching methods, and a real data illustration is provided.

Suggested Citation

  • Lee, Myoung-jae, 2012. "Treatment effects in sample selection models and their nonparametric estimation," Journal of Econometrics, Elsevier, vol. 167(2), pages 317-329.
  • Handle: RePEc:eee:econom:v:167:y:2012:i:2:p:317-329
    DOI: 10.1016/j.jeconom.2011.09.018
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    References listed on IDEAS

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    14. Myoung-Jae Lee, 2004. "Selection correction and sensitivity analysis for ordered treatment effect on count response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 323-337.
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    Cited by:

    1. Lee, M-J & Kim, Y-S, 2011. "Effects of Informal Family Care on Formal Health Care: Zero-Inflated Endogenous Count for Censored Response," Health, Econometrics and Data Group (HEDG) Working Papers 11/10, HEDG, c/o Department of Economics, University of York.
    2. repec:bla:jorssa:v:180:y:2017:i:3:p:817-839 is not listed on IDEAS
    3. Myoung-Jae Lee, 2015. "Reference parameters in Blinder-Oaxaca decomposition: Pooled-sample versus intercept-shift approaches," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(1), pages 69-82, March.

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