Estimation of sample selection models with spatial dependence

Alfonso Flores-Lagunes, Kurt Erik Schnier

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

We consider the estimation of a sample selection model that exhibits spatial autoregressive errors (SAE). Our methodology is motivated by a two-step strategy where in the first step we estimate a spatial probit model and in the second step (outcome equation) we include an estimated inverse Mills ratio (IMR) as a regressor to control for selection bias. Since the appropriate IMR under SAE depends on a parameter from the second step, both steps are jointly estimated employing the generalized method of moments. We explore the finite sample properties of the estimator using simulations and provide an empirical illustration.

Original languageEnglish (US)
Pages (from-to)173-204
Number of pages32
JournalJournal of Applied Econometrics
Volume27
Issue number2
DOIs
StatePublished - Mar 1 2012
Externally publishedYes

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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