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Semiparametric econometric estimators for a truncated regression model: a review with an extension
Author(s) -
Lee M.J.,
Kim H.
Publication year - 1998
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/1467-9574.00078
Subject(s) - estimator , covariate , econometrics , mathematics , extension (predicate logic) , monte carlo method , statistics , econometric model , regression analysis , variance (accounting) , delta method , computer science , economics , accounting , programming language
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.