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Endogeneity in semiparametric binary response models

Author

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  • Richard Blundell

    () (Institute for Fiscal Studies and IFS and UCL)

  • James L. Powell

    () (Institute for Fiscal Studies and University of California, Berkeley)

Abstract

This paper develops and implements semiparametric methods for estimating binary response (binary choice) models withcontinuous endogenous regressors. It extends the existing literature on semiparametric estimation in single index binary response models to the case of endogenous regressors. It develops a control function approach to accounting for endogeneity in triangular and fully simulataneous binary response models. An application is given to the case of estimating the income effect in a labor market participation problem using a large micro data set from the British FES. The semiparametric estimator is found to perform well detecting a significant attenuation bias. The proposed estimator is contrasted to the corresponding Probit and Linear Probability specifications.

Suggested Citation

  • Richard Blundell & James L. Powell, 2001. "Endogeneity in semiparametric binary response models," CeMMAP working papers CWP05/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:05/01
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    File URL: http://www.cemmap.ac.uk/wps/cwp0501.pdf
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    References listed on IDEAS

    as
    1. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    2. Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation for Research in Economics, Yale University.
    3. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    4. Richard Blundell & James L. Powell, 2001. "Endogeneity in nonparametric and semiparametric regression models," CeMMAP working papers CWP09/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    6. Blundell, Richard & Smith, Richard J., 1994. "Coherency and estimation in simultaneous models with censored or qualitative dependent variables," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 355-373.
    7. Richard W. Blundell & Richard J. Smith, 1989. "Estimation in a Class of Simultaneous Equation Limited Dependent Variable Models," Review of Economic Studies, Oxford University Press, vol. 56(1), pages 37-57.
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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