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Another Look at the Identification at Infinity of Sample Selection Models

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  • D'Haultfoeuille, Xavier

    (CREST)

  • Maurel, Arnaud

    (Duke University)

Abstract

It is often believed that without instrument, endogenous sample selection models are identified only if a covariate with a large support is available (see Chamberlain, 1986, and Lewbel, 2007). We propose a new identification strategy mainly based on the condition that the selection variable becomes independent of the covariates when the outcome, not one of the covariates, tends to infinity. No large support on the covariates is required. Moreover, we prove that this condition is testable. We finally show that our strategy can also be applied to the identification of generalized Roy models.

Suggested Citation

  • D'Haultfoeuille, Xavier & Maurel, Arnaud, 2009. "Another Look at the Identification at Infinity of Sample Selection Models," IZA Discussion Papers 4334, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp4334
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    References listed on IDEAS

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    1. Willis, Robert J & Rosen, Sherwin, 1979. "Education and Self-Selection," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 7-36, October.
    2. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    3. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    4. D'Haultfoeuille, Xavier & Maurel, Arnaud, 2009. "Inference on a Generalized Roy Model, with an Application to Schooling Decisions in France," IZA Discussion Papers 4606, Institute of Labor Economics (IZA).
    5. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
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    8. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    9. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    10. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
    11. Sokbae Lee, 2006. "Identification of a competing risks model with unknown transformations of latent failure times," Biometrika, Biometrika Trust, vol. 93(4), pages 996-1002, December.
    12. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    13. George J. Borjas, 2021. "Self-Selection and the Earnings of Immigrants," World Scientific Book Chapters, in: Foundational Essays in Immigration Economics, chapter 4, pages 69-91, World Scientific Publishing Co. Pte. Ltd..
    14. Jaap H. Abbring & Gerard J. Van Den Berg, 2003. "The identifiability of the mixed proportional hazards competing risks model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 701-710, August.
    15. Chamberlain, Gary, 1986. "Asymptotic efficiency in semi-parametric models with censoring," Journal of Econometrics, Elsevier, vol. 32(2), pages 189-218, July.
    16. Donald W. K. Andrews & Marcia M. A. Schafgans, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 497-517.
    17. Patrick Bayer & Shakeeb Khan & Christopher Timmins, 2008. "Nonparametric Identification and Estimation in a Generalized Roy Model," NBER Working Papers 13949, National Bureau of Economic Research, Inc.
    18. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
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    Cited by:

    1. Xavier D’Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2020. "Estimating selection models without an instrument with Stata," Stata Journal, StataCorp LP, vol. 20(2), pages 297-308, June.
    2. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    3. Jochmans, Koen & Henry, Marc & Salanié, Bernard, 2017. "Inference On Two-Component Mixtures Under Tail Restrictions," Econometric Theory, Cambridge University Press, vol. 33(3), pages 610-635, June.
    4. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    5. D’Haultfœuille, Xavier & Maurel, Arnaud, 2013. "Inference on an extended Roy model, with an application to schooling decisions in France," Journal of Econometrics, Elsevier, vol. 174(2), pages 95-106.
    6. D’Haultfœuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2018. "Extremal quantile regressions for selection models and the black–white wage gap," Journal of Econometrics, Elsevier, vol. 203(1), pages 129-142.
    7. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2021. "Intercept Estimation in Nonlinear Selection Models," IZA Discussion Papers 14364, Institute of Labor Economics (IZA).
    8. D'Haultfoeuille, Xavier & Maurel, Arnaud, 2009. "Inference on a Generalized Roy Model, with an Application to Schooling Decisions in France," IZA Discussion Papers 4606, Institute of Labor Economics (IZA).
    9. Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
    10. Zhewen Pan & Zhengxin Wang & Junsen Zhang & Yahong Zhou, 2024. "Marginal treatment effects in the absence of instrumental variables," Papers 2401.17595, arXiv.org.

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    More about this item

    Keywords

    identification at infinity; sample selection model; Roy model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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