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Finite sample behavior of two step estimators in selection models

Author

Listed:
  • Ana Fernandez Sainz

    (Universidad del Pais Vasco)

  • Juan Rodriguez-Poo

    (Universidad de Cantabria)

  • Inmaculada Villanua Martin

    (Universidad de Zaragoza)

Abstract

Summary The problem of specification errors in sample selection models has received considerable attention both theoretically and empirically. Originally proposed in Heckman (1979) within a fully parametric context, Ahn and Powell (1993) have proposed a semiparametric alternative that is claimed to be asymptotically robust against several misspecification errors. However, very few is known about the finite sample behavior of these estimators. In this paper we investigate theoretically and by simulations both bias and finite sample distribution of these estimators when ignoring heteroskedasticity in the sample selection mechanism.

Suggested Citation

  • Ana Fernandez Sainz & Juan Rodriguez-Poo & Inmaculada Villanua Martin, 2002. "Finite sample behavior of two step estimators in selection models," Computational Statistics, Springer, vol. 17(1), pages 1-16, March.
    • Handle: RePEc:spr:compst:v:17:y:2002:i:1:d:10.1007_s001800200087
    DOI: 10.1007/s001800200087
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    References listed on IDEAS

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    Cited by:

    1. Lee Adkins & R. Carter Hill, 2007. "Bootstrap Inferences in Heteroscedastic Sample Selection Models: A Monte Carlo Investigation," Economics Working Paper Series 0710, Oklahoma State University, Department of Economics and Legal Studies in Business.

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