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Nonparametric conditional density estimation of labour force participation

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Author Info
Anil Kumar
Abstract

Labour force participation decision has been studied primarily in a parametric framework. The weaknesses of the parametric estimators to misspecification of the error distribution and to functional form assumptions are well known. This paper compares the predictive performance of widely used parametric and semiparametric estimators with results obtained from nonparametric kernel conditional density estimation with likelihood cross-validated bandwidth selection and mixed data type. The results are striking. The predictive performance of the nonparametric estimator is 95% against 71% to 77% of the parametric and semiparametric estimators. The nonparametric estimator is able to correctly predict the outcome for 83% of non-participants in the labour force as against 15% by probit and logit models. This underscores the need to use nonparametric estimators in studying labour market behaviour.

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Article provided by Taylor and Francis Journals in its journal Applied Economics Letters.

Volume (Year): 13 (2006)
Issue (Month): 13 (October)
Pages: 835-841
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Handle: RePEc:taf:apeclt:v:13:y:2006:i:13:p:835-841

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Heckman, James J, 1993. "What Has Been Learned about Labor Supply in the Past Twenty Years?," American Economic Review, American Economic Association, vol. 83(2), pages 116-21, May. [Downloadable!] (restricted)
  2. Michael Gerfin, 1993. "Parametric and Semiparametric Estimation of the Binary Response Model of Labor Market Participation," Diskussionsschriften dp9315, Universitaet Bern, Departement Volkswirtschaft.
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  3. Stern, Steven, 1996. "Semiparametric estimates of the supply and demand effects of disability on labor force participation," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 49-70. [Downloadable!] (restricted)
  4. Gabler, Siegfried & Laisney, Francois & Lechner, Michael, 1993. "Seminonparametric Estimation of Binary-Choice Models with an Application to Labor-Force Participation," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 61-80, January.
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  1. Martin Huber, 2009. "Treatment evaluation in the presence of sample selection," University of St. Gallen Department of Economics working paper series 2009 2009-07, Department of Economics, University of St. Gallen. [Downloadable!]
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