Estimation in truncated samples when there is heteroscedasticity
From MaRDI portal
Publication:1138337
DOI10.1016/0304-4076(79)90039-3zbMath0431.62078OpenAlexW2068134108MaRDI QIDQ1138337
Publication date: 1979
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4076(79)90039-3
heteroscedasticitymaximum likelihood estimatorinconsistencycensored sampletruncated normal, asymptotic bias
Related Items (14)
Two-step estimation of heteroskedastic sample selection models ⋮ The asymptotically efficient version of the information matrix test in binary choice models. A study of size and power ⋮ Robust estimation based on grouped-adjusted data in censored regression models ⋮ Specification tests for distributional assumptions in the Tobit model ⋮ A Monte Carlo comparison of estimators for censored regression models ⋮ Testing for heteroskedasticity in the tobit and probit models ⋮ Estimation and specification testing in female labor participation models: parametric and semiparametric methods ⋮ A Generalized Heckman Model With Varying Sample Selection Bias and Dispersion Parameters ⋮ A tobit model with garch errors ⋮ Discrete factor approximations in simultaneous equation models: Estimating the impact of a dummy endogenous variable on a continuous outcome ⋮ Handling dropout and clustering in longitudinal multicentre clinical trials ⋮ Finite sample properties for the semiparametric estimation of the intercept of a censored regression model ⋮ Tobit models: A survey ⋮ Finite sample behavior of two step estimators in selection models
Cites Work
This page was built for publication: Estimation in truncated samples when there is heteroscedasticity
