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Heckman method and switching regression model multivariate generalization

Author

Listed:
  • Kossova, Elena

    () (National Research University Higher School of Economics (NRU HSE), Moscow, Russian Federation)

  • Potanin, Bogdan

    () (National Research University Higher School of Economics (NRU HSE), Moscow, Russian Federation)

Abstract

The article is devoted to simultaneous estimation of one continuous and various binary equations under assumption of disturbances joint normality. It generalizes Heckman selection and switch-probit models to multivariate case. Following Heckman’s univariate model implementation both two step and maximum likelihood procedures are provided. In order to test model performance and correctness we execute analysis on simulated data. It shows that when there are two selection equations generalized model estimates accuracy noticeably outperforms those that are obtained using least squares or Heckman’s methods.

Suggested Citation

  • Kossova, Elena & Potanin, Bogdan, 2018. "Heckman method and switching regression model multivariate generalization," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 50, pages 114-143.
    • Handle: RePEc:ris:apltrx:0346
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    References listed on IDEAS

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    1. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    2. Manning, W. G. & Duan, N. & Rogers, W. H., 1987. "Monte Carlo evidence on the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 35(1), pages 59-82, May.
    3. Hay, Joel W & Leu, Robert & Rohrer, Paul, 1987. "Ordinary Least Squares and Sample-Selection Models of Health-Care Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 499-506, October.
    4. Paarsch, Harry J., 1984. "A Monte Carlo comparison of estimators for censored regression models," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 197-213.
    5. Joe, Harry, 2006. "Generating random correlation matrices based on partial correlations," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2177-2189, November.
    6. Vella, Francis, 1993. "A Simple Estimator for Simultaneous Models with Censored Endogenous Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(2), pages 441-457, May.
    7. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    8. 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.
    9. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, December.
    10. Murphy, Kevin M & Topel, Robert H, 2002. "Estimation and Inference in Two-Step Econometric Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 88-97, January.
    11. Nelson, Forrest D., 1984. "Efficiency of the two-step estimator for models with endogenous sample selection," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 181-196.
    12. Puhani, Patrick A, 2000. " The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    13. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    14. Zuehlke, Thomas W & Zeman, Allen R, 1991. "A Comparison of Two-Stage Estimators of Censored Regression Models," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 185-188, February.
    15. Nawata, Kazumitsu, 1994. "Estimation of sample selection bias models by the maximum likelihood estimator and Heckman's two-step estimator," Economics Letters, Elsevier, vol. 45(1), pages 33-40, May.
    16. Ulrich Rendtel, 1992. "On the Choice of a Selection-Model When Estimating Regressionmodels with Selectivity," Discussion Papers of DIW Berlin 53, DIW Berlin, German Institute for Economic Research.
    17. Nawata, Kazumitsu, 1993. "A note on the estimation of models with sample-selection biases," Economics Letters, Elsevier, vol. 42(1), pages 15-24.
    18. Yulia V. Marchenko & Marc G. Genton, 2012. "A Heckman Selection- t Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 304-317, March.
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    More about this item

    Keywords

    sample selection; switching regression model;

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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