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A Note on Consistency of Heckman-type two-step Estimators for the Multivariate Sample-Selection Model

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  • Harald Tauchmann

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Abstract

This analysis shows that multivariate generalizations to the classical Heckman (1976 and 1979) two-step estimator that account for cross-equation correlation and use the inverse Mills ratio as a correction-term are consistent only if certain restrictions apply to the true error-covariance structure.We derive an alternative class of generalizations to the classical Heckman two-step approach that conditions on the entire selection pattern rather than the selection of particular equations and, therefore, uses modified correction-terms. This class of estimators is shown to be consistent. In addition, Monte-Carlo results illustrate that these estimators display a smaller mean square prediction error.

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Bibliographic Info

Paper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung in its series RWI Discussion Papers with number 0040.

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Length: 28 pages
Date of creation: Apr 2006
Date of revision:
Handle: RePEc:rwi:dpaper:0040

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Related research

Keywords: Multivariate sample-selection model; censored system of equations; Heckman-correction;

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  1. 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.
  2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  3. Poirier, Dale J., 1980. "Partial observability in bivariate probit models," Journal of Econometrics, Elsevier, vol. 12(2), pages 209-217, February.
  4. Zhuo Chen & Steven Yen, 2005. "On bias correction in the multivariate sample-selection model," Applied Economics, Taylor & Francis Journals, vol. 37(21), pages 2459-2468.
  5. Steven T. Yen, 2005. "A Multivariate Sample-Selection Model: Estimating Cigarette and Alcohol Demands with Zero Observations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 453-466.
  6. Barry K. Goodwin & Monte L. Vandeveer & John L. Deal, 2004. "An Empirical Analysis of Acreage Effects of Participation in the Federal Crop Insurance Program," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1058-1077.
  7. Beverly Tepper & Lee Rosenzweig, 1999. "Assessing the importance of health and nutrition related factors on food demand: a variable preference investigation," Applied Economics, Taylor & Francis Journals, vol. 31(12), pages 1541-1549.
  8. Harald Tauchmann, 2005. "Efficiency of two-step estimators for censored systems of equations: Shonkwiler and Yen reconsidered," Applied Economics, Taylor & Francis Journals, vol. 37(4), pages 367-374.
  9. Steven Yen & Kamhon Kan & Shew-Jiuan Su, 2002. "Household demand for fats and oils: two-step estimation of a censored demand system," Applied Economics, Taylor & Francis Journals, vol. 34(14), pages 1799-1806.
  10. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
  11. Frederic Vermeulen, 2001. "A note on Heckman-type corrections in models for zero expenditures," Applied Economics, Taylor & Francis Journals, vol. 33(9), pages 1089-1092.
  12. Heien, Dale & Durham, Cathy, 1991. "A Test of the Habit Formation Hypothesis Using Household Data," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 189-99, May.
  13. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-71, July.
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