First-difference estimator for panel censored-selection models

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Abstract

We propose a semiparametric first-difference estimator for panel censored-selection models where the selection equation is of tobit type. The estimator allows the unit-specific term to be arbitrarily related to regressors. The estimator minimizes a convex function and does not require any smoothing. A simulation study is provided comparing our proposal with the estimators of Wooldridge (Journal of Econometrics 68 (1995) 115) and Honoré and Kyriazidou (Econometric Reviews (2000)).

Original languageEnglish
Pages (from-to)43-49
Number of pages7
JournalEconomics Letters
Volume70
Issue number1
DOIs
Publication statusPublished - 2001 Jan 1

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Keywords

  • C24
  • C34
  • Censored model
  • Panel data
  • Related-effect
  • Sample selection

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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