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Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal

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Author Info

  • Danilo Coelho

    ()

  • Helena Veiga

    ()

  • R?rt Veszteg

    ()

Abstract

This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).

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Bibliographic Info

Paper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number 636.05.

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Length: 6
Date of creation: 10 Jan 2005
Date of revision:
Handle: RePEc:aub:autbar:636.05

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Keywords: parametric estimation; semiparametric estimation; sample selection model;

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  1. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-94, July.
  2. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
  3. Ana Fernandez & Juan Rodriquez-Poo, 1997. "Estimation and specification testing in female labor participation models: parametric and semiparametric methods," Econometric Reviews, Taylor & Francis Journals, vol. 16(2), pages 229-247.
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