IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v158y2017icp84-87.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517302665
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2017.06.039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    5. 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.
    6. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-1143, Nov.-Dec..
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Vira Semenova, 2023. "Adaptive Estimation of Intersection Bounds: a Classification Approach," Papers 2303.00982, arXiv.org.
    3. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    4. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    5. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    6. Demuynck, Thomas, 2015. "Bounding average treatment effects: A linear programming approach," Economics Letters, Elsevier, vol. 137(C), pages 75-77.
    7. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    8. Wenlong Ji & Lihua Lei & Asher Spector, 2023. "Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects," Papers 2310.08115, arXiv.org.
    9. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    10. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    11. Kjetil Bjorvatn & Alexander W. Cappelen & Linda Helgesson Sekei & Erik Ø. Sørensen & Bertil Tungodden, 2020. "Teaching Through Television: Experimental Evidence on Entrepreneurship Education in Tanzania," Management Science, INFORMS, vol. 66(6), pages 2308-2325, June.
    12. Jiannan Lu & Peng Ding & Tirthankar Dasgupta, 2018. "Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 540-567, October.
    13. McGovern, Mark E. & Canning, David & Bärnighausen, Till, 2018. "Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers," Economics Letters, Elsevier, vol. 171(C), pages 239-244.
    14. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    15. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    16. Matthias Westphal & Daniel A Kamhöfer & Hendrik Schmitz, 2022. "Marginal College Wage Premiums Under Selection Into Employment," The Economic Journal, Royal Economic Society, vol. 132(646), pages 2231-2272.
    17. Imbens, Guido W., 2014. "Instrumental Variables: An Econometrician's Perspective," IZA Discussion Papers 8048, Institute of Labor Economics (IZA).
    18. Bo E. Honoré & Luojia Hu, 2020. "Selection Without Exclusion," Econometrica, Econometric Society, vol. 88(3), pages 1007-1029, May.
    19. Bia, Michela & Flores-Lagunes, Alfonso & Mercatanti, Andrea, 2018. "Evaluation of Language Training Programs in Luxembourg using Principal Stratification," GLO Discussion Paper Series 289, Global Labor Organization (GLO).
    20. Michael Lechner & Blaise Melly, 2007. "Earnings Effects of Training Programs," University of St. Gallen Department of Economics working paper series 2007 2007-28, Department of Economics, University of St. Gallen.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:158:y:2017:i:c:p:84-87. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.