Semiparametric econometric estimators for a truncated regression model: A review with an extension

M. J. Lee, H. Kim

Research output: Contribution to journalReview article

11 Citations (Scopus)

Abstract

Econometric estimators for a truncated regression model are reviewed. For each estimator, the motivations, the key assumptions, the asymptotic distribution and estimates for the asymptotic variance matrix are presented; also a new estimator is suggested. We select five practical estimators among those, and compare them through a Monte Carlo study where the response variable is simulated but the covariates are drawn from a real data set. Some practical and computational issues are addressed as well.

Original languageEnglish
Pages (from-to)200-225
Number of pages26
JournalStatistica Neerlandica
Volume52
Issue number2
DOIs
Publication statusPublished - 1998 Jul

Keywords

  • Robustness
  • Semiparametric
  • Truncated

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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