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The Sample Selection Model from a Method of Moments Perspective

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Author Info
Erik Meijer
Tom Wansbeek

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Abstract

It is shown how the usual two-step estimator for the standard sample selection model can be seen as a method of moments estimator. Standard GMM theory can be brought to bear on this model, greatly simplifying the derivation of the asymptotic properties of this model. Using this setup, the asymptotic variance is derived in detail and a consistent estimator of it is obtained that is guaranteed to be positive definite, in contrast with the estimator given in the literature. It is demonstrated how the MM approach easily accommodates variations on the estimator, like the two-step IV estimator that handles endogenous regressors, and a two-step GLS estimator. Furthermore, it is shown that from the MM formulation, it is straightforward to derive various specification tests, in particular tests for selection bias, equivalence with the censored regression model, normality, homoskedasticity, and exogeneity.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 26 (2007)
Issue (Month): 1 ()
Pages: 25-51
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Handle: RePEc:taf:emetrv:v:26:y:2007:i:1:p:25-51

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Related research
Keywords: GMM; Heckman estimator; Tobit;

Cited by:
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  1. Erik Meijer & Arie Kapteyn & Tatiana Andreyeva, 2008. "Health Indexes and Retirement Modeling in International Comparisons," Working Papers 614, RAND Corporation Publications Department. [Downloadable!]
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