IDEAS home Printed from https://ideas.repec.org/p/ecm/wc2000/0263.html
   My bibliography  Save this paper

Semiparametric Estimation of Heteroscedastic Binary Sample Selection Model

Author

Listed:
  • Song Nian Chen

    (Hong Kong University of Science and Technology)

Abstract

Binary choice sample selection models are widely used in applied economics with large cross-sectional data where heteroscedaticity is typically a serious concern. Existing parametric and semiparametric estimators for the binary selection equation and the outcome equation in such models suffer from serious drawbacks in the presence of heteroscedasticity of unknown form in the latent errors. In this paper we propose some new estimators to overcome these drawbacks under a symmetry condition, robust to both nonnormality and general heterscedasticity. The estimators are shown to be $\sqrt{n}$-consistent and asymptotically normal. We also indicate that our approaches may be extended to other important models.

Suggested Citation

  • Song Nian Chen, 2000. "Semiparametric Estimation of Heteroscedastic Binary Sample Selection Model," Econometric Society World Congress 2000 Contributed Papers 0263, Econometric Society.
    • Handle: RePEc:ecm:wc2000:0263
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/RePEc/es2000/0263.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    2. Chen, Songnian & Lee, Lung-Fei, 1998. "Efficient Semiparametric Scoring Estimation Of Sample Selection Models," Econometric Theory, Cambridge University Press, vol. 14(4), pages 423-462, August.
    3. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-318, May.
    4. Chamberlain, Gary, 1992. "Efficiency Bounds for Semiparametric Regression," Econometrica, Econometric Society, vol. 60(3), pages 567-596, May.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Songnian & Zhou, Yahong, 2010. "Semiparametric and nonparametric estimation of sample selection models under symmetry," Journal of Econometrics, Elsevier, vol. 157(1), pages 143-150, July.
    2. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
    3. Zhewen Pan, 2023. "On semiparametric estimation of the intercept of the sample selection model: a kernel approach," Papers 2302.05089, arXiv.org.
    4. Liu, Ruixuan & Yu, Zhengfei, 2022. "Sample selection models with monotone control functions," Journal of Econometrics, Elsevier, vol. 226(2), pages 321-342.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    6. 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.
    7. Heckman, James, 2001. "Accounting for Heterogeneity, Diversity and General Equilibrium in Evaluating Social Programmes," Economic Journal, Royal Economic Society, vol. 111(475), pages 654-699, November.
    8. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    9. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    10. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    11. Gordon B. Dahl, 2002. "Mobility and the Return to Education: Testing a Roy Model with Multiple Markets," Econometrica, Econometric Society, vol. 70(6), pages 2367-2420, November.
    12. Casey B. Mulligan & Yona Rubinstein, 2004. "The Closing of the Gender Gap as a Roy Model Illusion," NBER Working Papers 10892, National Bureau of Economic Research, Inc.
    13. Pradhan, Menno & van Soest, Arthur, 1995. "Formal and informal sector employment in urban areas of Bolivia," Labour Economics, Elsevier, vol. 2(3), pages 275-297, September.
    14. 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.
    15. Peter Hull & Michal Kolesár & Christopher Walters, 2022. "Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 603-645, July.
    16. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2007. "Changes in the Distribution of Male and Female Wages Accounting for Employment Composition Using Bounds," Econometrica, Econometric Society, vol. 75(2), pages 323-363, March.
    17. Klein, Roger & Shen, Chan & Vella, Francis, 2011. "Semiparametric Selection Models with Binary Outcomes," IZA Discussion Papers 6008, Institute of Labor Economics (IZA).
    18. Angrist, Joshua D., 1997. "Conditional independence in sample selection models," Economics Letters, Elsevier, vol. 54(2), pages 103-112, February.
    19. Cunha, Flavio & Heckman, James J., 2007. "Identifying and Estimating the Distributions of Ex Post and Ex Ante Returns to Schooling," Labour Economics, Elsevier, vol. 14(6), pages 870-893, December.
    20. Philipp Eisenhauer & James J. Heckman & Edward Vytlacil, 2015. "The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 413-443.

    More about this item

    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:ecm:wc2000:0263. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .

    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.