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A Small-Sample Estimator for the Sample-Selection Model

Author

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  • Amos Golan
  • Enrico Moretti
  • Jeffrey M.Perloff

Abstract

A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans.

Suggested Citation

  • Amos Golan & Enrico Moretti & Jeffrey M.Perloff, 2004. "A Small-Sample Estimator for the Sample-Selection Model," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 71-91.
    • Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:71-91
    DOI: 10.1081/ETC-120028837
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    Cited by:

    1. Peeters, Ludo M. K., 2004. "Estimating a random-coefficients sample-selection model using generalized maximum entropy," Economics Letters, Elsevier, vol. 84(1), pages 87-92, July.
    2. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute of Labor Economics (IZA).
    3. Bublik, Nikolas & Mittag, Franziska & Hess, Sebastian, 2024. "What influence do school lessons have on youths' knowledge about agriculture? An empirical study in a Bavarian district," GEWISOLA 64th Annual Conference, Giessen, Germany, September 25–27, 2024 364711, GEWISOLA.

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