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Sensitivity of the bounds on the ATE in the presence of sample selection

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  • Lafférs, Lukáš
  • Nedela, Roman

Abstract

This paper reformulates the problem of bounding average treatment effects under sample selection studied in Lee (2009) as an optimization problem. This allows researchers to easily conduct sensitivity analyses of the identifying assumptions while the bounds remain sharp. We provide a mathematical formulation of the problem, replicate the existing analytical results and extend them to a sensitivity analysis.

Suggested Citation

  • Lafférs, Lukáš & Nedela, Roman, 2017. "Sensitivity of the bounds on the ATE in the presence of sample selection," Economics Letters, Elsevier, vol. 158(C), pages 84-87.
    • Handle: RePEc:eee:ecolet:v:158:y:2017:i:c:p:84-87
    DOI: 10.1016/j.econlet.2017.06.039
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    References listed on IDEAS

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    1. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    2. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
    3. Demuynck, Thomas, 2015. "Bounding average treatment effects: A linear programming approach," Economics Letters, Elsevier, vol. 137(C), pages 75-77.
    4. Zhang, Junni L. & Rubin, Donald B. & Mealli, Fabrizia, 2009. "Likelihood-Based Analysis of Causal Effects of Job-Training Programs Using Principal Stratification," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 166-176.
    5. Paco Martorell & Isaac McFarlin, 2011. "Help or Hindrance? The Effects of College Remediation on Academic and Labor Market Outcomes," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 436-454, May.
    6. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    7. Bo E. Honoré & Elie Tamer, 2006. "Bounds on Parameters in Panel Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 74(3), pages 611-629, May.
    8. Suresh de Mel & David McKenzie & Christopher Woodruff, 2009. "Returns to Capital in Microenterprises: Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(1), pages 423-423.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-1143, Nov.-Dec..
    11. Gustavo J. Bobonis, 2009. "Is the Allocation of Resources within the Household Efficient? New Evidence from a Randomized Experiment," Journal of Political Economy, University of Chicago Press, vol. 117(3), pages 453-503, June.
    12. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 1071-1102.
    13. Christopher Blattman & Jeannie Annan, 2010. "The Consequences of Child Soldiering," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 882-898, November.
    14. Freyberger, Joachim & Horowitz, Joel L., 2015. "Identification and shape restrictions in nonparametric instrumental variables estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 41-53.
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    Cited by:

    1. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.

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    More about this item

    Keywords

    Bounds; Sample selection bias; Average treatment effects; Sensitivity analysis;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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