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The Sample Selection Model from a Method of Moments Perspective


  • Erik Meijer
  • Tom Wansbeek


It is shown how the usual two-step estimator for the standard sample selection model can be seen as a method of moments estimator. Standard GMM theory can be brought to bear on this model, greatly simplifying the derivation of the asymptotic properties of this model. Using this setup, the asymptotic variance is derived in detail and a consistent estimator of it is obtained that is guaranteed to be positive definite, in contrast with the estimator given in the literature. It is demonstrated how the MM approach easily accommodates variations on the estimator, like the two-step IV estimator that handles endogenous regressors, and a two-step GLS estimator. Furthermore, it is shown that from the MM formulation, it is straightforward to derive various specification tests, in particular tests for selection bias, equivalence with the censored regression model, normality, homoskedasticity, and exogeneity.

Suggested Citation

  • Erik Meijer & Tom Wansbeek, 2007. "The Sample Selection Model from a Method of Moments Perspective," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 25-51.
  • Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:25-51 DOI: 10.1080/07474930600972194

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    References listed on IDEAS

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    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
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    7. Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 1-16, February.
    8. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    9. Robert Russell, R., 1990. "Continuity of measures of technical efficiency," Journal of Economic Theory, Elsevier, vol. 51(2), pages 255-267, August.
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    Cited by:

    1. Semykina, Anastasia & Wooldridge, Jeffrey M., 2010. "Estimating panel data models in the presence of endogeneity and selection," Journal of Econometrics, Elsevier, vol. 157(2), pages 375-380, August.
    2. Michael Pfaffermayr, 2014. "A GMM-Based Test for Normal Disturbances of the Heckman Sample Selection Model," Econometrics, MDPI, Open Access Journal, vol. 2(4), pages 1-18, October.
    3. Erik Meijer & Arie Kapteyn & Tatiana Andreyeva, 2008. "Health Indexes and Retirement Modeling in International Comparisons," Working Papers 614, RAND Corporation.
    4. Adeline Delavande & Hans-Peter Kohler, 2012. "The Impact of HIV Testing on Subjective Expectations and Risky Behavior in Malawi," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 1011-1036, August.
    5. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute for the Study of Labor (IZA).
    6. Erik Meijer & Arie Kapteyn & Tatiana Andreyeva, 2008. "Health Indexes and Retirement Modeling in International Comparisons," Working Papers WR-614, RAND Corporation.

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    GMM; Heckman estimator; Tobit;


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