Estimation of sample selection bias models by the maximum likelihood estimator and Heckman's two-step estimator

DOI10.1016/0165-1765(94)90053-1zbMath0803.62098OpenAlexW2079239849MaRDI QIDQ1327988

Kazumitsu Nawata

Publication date: 3 July 1994

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0165-1765(94)90053-1

zbMATH Keywords

maximum likelihood estimatorfinite sample propertiestwo-step estimatorsample selection biases

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Monte Carlo methods (65C05)

Related Items (12)

On the choice between sample selection and two-part models ⋮ The small sample performance of the Wald test in the sample selection model under the multicollinearity problem ⋮ Birnbaum–Saunders sample selection model ⋮ Estimation of the female labor supply models by Heckman's two-step estimator and the maximum likelihood estimator. ⋮ Estimation of sample selection bias models ⋮ Evaluation of the DPC-based inclusive payment system in Japan for cataract operations by a new model ⋮ A Generalized Heckman Model With Varying Sample Selection Bias and Dispersion Parameters ⋮ On Testing Sample Selection Bias Under the Multicollinearity Problem ⋮ SIZE CHARACTERISTICS OF TESTS FOR SAMPLE SELECTION BIAS: A MONTE CARLO COMPARISON AND EMPIRICAL EXAMPLE ⋮ The Sample Selection Model from a Method of Moments Perspective ⋮ Fuzzy parametric sample selection model: Monte Carlo simulation approach ⋮ Evaluating the performance of simple estimators for probit models with two dummy endogenous regressors

Cites Work

• A Monte Carlo comparison of estimators for censored regression models
• Distributional Tests for Selectivity Bias and a More Robust Likelihood Estimator
• Shadow Prices, Market Wages, and Labor Supply
• Sample Selection Bias as a Specification Error

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