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A Full InformationMaximum Likelihood Approach to Estimating the Sample Selection Model with Endogenous Covariates

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  • Schwiebert, Jörg

Abstract

In this paper we establish a full information maximum likelihood approach to estimating the sample selection model with endogenous covariates. We also provide a test for exogeneity which indicates whether endogeneity is in fact a matter or not. In contrast to other methods proposed in the literature which deal with sample selection and endogeneity, our approach is computationally simple and provides exact asymptotic standard errors derived from common maximum likelihood theory. A Monte Carlo study and an empirical example are presented which indicate that not accounting for endogeneity in sample selection models may lead to severely biased parameter estimates.

Suggested Citation

  • Schwiebert, Jörg, 2011. "A Full InformationMaximum Likelihood Approach to Estimating the Sample Selection Model with Endogenous Covariates," Hannover Economic Papers (HEP) dp-483, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-483
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    File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-483.pdf
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    References listed on IDEAS

    as
    1. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863, Elsevier.
    2. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    3. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Sample Selection Model; Endogeneity; Maximum Likelihood Estimation; Female Labor Supply;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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