This paper considers estimation of truncated.and censored regression models with fixed effects. Up until now, no estimator has been shown to be consistent as the cross-section dimension increases with the time dimension fixed. Trimmed least absolute deviations and trimmed least squares estimators are proposed for the case where the panel is of length two, and it is proven that they are consistent and asymptotically normal. It is not necessary to maintain parametric assumptions on the error terms to obtain this result. A small scale Monte Carlo study demonstrates that these estimators can perform well in small samples. Copyright 1992 by The Econometric Society.
Estimation in the linear regression model Y = beta'Z + epsilon is considered for the left trunc...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
This thesis contributes in several ways to the existing knowledge on estimation of truncated, censor...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
[[abstract]]The ordinary least squares (OLS) method is popular for analyzing linear regression model...
This article provides a semi parametric method for the estimation of truncated regression models wh...
This paper proposes new estimators of the latent regression function in nonparametric censored and t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
summary:From the practical point of view the regression analysis and its Least Squares method is cle...
We detail the basic theory for regression models in which dependent variables are censored or underl...
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero...
We detail the basic theory for regression models in which dependent variables are censored or underl...
Estimation in the linear regression model Y = beta'Z + epsilon is considered for the left trunc...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
This thesis contributes in several ways to the existing knowledge on estimation of truncated, censor...
Many estimation methods of truncated and censored regression models such as the maximum likelihood a...
[[abstract]]The ordinary least squares (OLS) method is popular for analyzing linear regression model...
This article provides a semi parametric method for the estimation of truncated regression models wh...
This paper proposes new estimators of the latent regression function in nonparametric censored and t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of t...
summary:From the practical point of view the regression analysis and its Least Squares method is cle...
We detail the basic theory for regression models in which dependent variables are censored or underl...
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero...
We detail the basic theory for regression models in which dependent variables are censored or underl...
Estimation in the linear regression model Y = beta'Z + epsilon is considered for the left trunc...
Truncated sample arise when one do not observe a certain segment of a population. This typically hap...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...