We consider censored structural latent variables models where some exogenous variables are subject to additive measurement errors. We demonstrate that overidentification conditions can be exploited to provide natural instruments for the variables measured with errors, and we propose a two-stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting reduced form parameters using consistent censored regression methods. The second stage obtains structural form parameters using the conventional linear simultaneous equations model estimators.Published versio
Statistical models whose independent variables are subject to measurement errors are often referred ...
This paper aims to overview the numerous approaches that have been developed to estimate the parame...
In the process of model modification, parameters of residual covariances are often treated as free p...
We consider censored structural latent variables models where some exogenous variables are subject ...
We consider censored structural latent variables models where some exogenous variables are subject t...
It is well known that measurement error in observable variables induces bias in estimates in standar...
Misspecifications of econometric models can lead to biased coefficients and incorrect interpretation...
A,,general computer program for estimating the 'unknown coefficients in a set of linear structu...
Abstract. We consider random variables which can be subject to both censoring and measurement errors...
We study the properties of a three-step approach to estimating the parameters of a latent structure ...
This paper proposes a structural analysis for generalized linear models when some explanatory variab...
A consideration of model structural error leads to some particularly interesting tensions in the mod...
Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behaviora...
The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of str...
[[abstract]]In estimating a linear measurement error model, extra information is generally needed to...
Statistical models whose independent variables are subject to measurement errors are often referred ...
This paper aims to overview the numerous approaches that have been developed to estimate the parame...
In the process of model modification, parameters of residual covariances are often treated as free p...
We consider censored structural latent variables models where some exogenous variables are subject ...
We consider censored structural latent variables models where some exogenous variables are subject t...
It is well known that measurement error in observable variables induces bias in estimates in standar...
Misspecifications of econometric models can lead to biased coefficients and incorrect interpretation...
A,,general computer program for estimating the 'unknown coefficients in a set of linear structu...
Abstract. We consider random variables which can be subject to both censoring and measurement errors...
We study the properties of a three-step approach to estimating the parameters of a latent structure ...
This paper proposes a structural analysis for generalized linear models when some explanatory variab...
A consideration of model structural error leads to some particularly interesting tensions in the mod...
Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behaviora...
The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of str...
[[abstract]]In estimating a linear measurement error model, extra information is generally needed to...
Statistical models whose independent variables are subject to measurement errors are often referred ...
This paper aims to overview the numerous approaches that have been developed to estimate the parame...
In the process of model modification, parameters of residual covariances are often treated as free p...