Semiparametric two-stage estimation of sample selection models subject to Tobit-type selection rules

DOI10.1016/0304-4076(94)90088-4zbMath0796.62103OpenAlexW2109494911MaRDI QIDQ1318975

Lung-fei Lee

Publication date: 16 October 1994

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2027.42/31675

zbMATH Keywords

Monte Carlo simulationssample selectionsemiparametric estimationcensored regression modeltruncated regression modelchoice-based models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Density estimation (62G07)

Related Items (12)

A semi-parametric estimator for censored selection models with endogeneity ⋮ Endogenous selection or treatment model estimation ⋮ Estimating a generalized correlation coefficient for a generalized bivariate probit model ⋮ Estimation of a regression spline sample selection model ⋮ Estimation of Type 3 Tobit models using symmetric trimming and pairwise comparisons ⋮ Semiparametric estimation of the type-3 Tobit model ⋮ Two-step semiparametric estimation of the type-3 Tobit model ⋮ Comparing principal stratification and selection models in parametric causal inference with nonignorable missingness ⋮ Sliced inverse regression under linear constraints ⋮ Bayesian inference in a sample selection model ⋮ Two-step series estimation of sample selection models ⋮ Tobit without apology.

Cites Work

• Least absolute deviations estimation for the censored regression model
• Asymptotic efficiency in semi-parametric models with censoring
• Adaptive estimation of regression models via moment restrictions
• Root-N-Consistent Semiparametric Regression
• Shadow Prices, Market Wages, and Labor Supply
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Semiparametric two-stage estimation of sample selection models subject to Tobit-type selection rules