We consider the problem of consistent estimation of nonlinear models with mismeasured explanatory variables, when marginal information on the true values of these variables is available. The marginal distribution of the true variables is used to identify the distrib-ution of the measurement error, and the distribution of the true variables conditional on the mismeasured and the other explanatory variables. The estimator is shown to be n consistent and normally distributed. The simulation results are in line with the asymptotic results. The semi-parametric MLE is applied to a duration model for AFDC welfare spells with misreported welfare benefits. The marginal distribution of welfare benefits is obtained from an administrative source. JEL c...
We consider least absolute error estimation in a nonlinear dynamic model with neither independent no...
Estimation of the parameters of the functional nonlinear measurement error model is considered. A si...
In this paper we develop a simple maximum likelihood estimator for probit models where the regressor...
We consider the problem of consistent estimation of nonlinear models with mis-measured explanatory v...
We consider the estimation of nonlinear models with mismeasured explanatory variables, when informat...
This paper presents a solution to an important econometric problem, namely the root n consistent est...
It has long been an area of interest to consider a consistent estimation of nonlinear models with me...
Nonlinear regression with measurement error is important for estimation from microeconomic data. One...
The issues of identification and estimation of nonlinear errors-in-variables models are explored. Th...
In many applications, observations from some distribution of interest are contaminated with errors...
A major difficulty in applying a measurement error model is that one is required to have additional ...
This paper considers consistent estimation of generalized linear models with covariate measurement e...
Nonlinear models arise naturally in economics. Both least squares and maximum-likelihood estimators ...
Semiparametric nonlinear mixed-effects (NLME) models are flexible for modelling complex longitudinal...
The present article considers the problem of consistent estimation in measurement error models. A li...
We consider least absolute error estimation in a nonlinear dynamic model with neither independent no...
Estimation of the parameters of the functional nonlinear measurement error model is considered. A si...
In this paper we develop a simple maximum likelihood estimator for probit models where the regressor...
We consider the problem of consistent estimation of nonlinear models with mis-measured explanatory v...
We consider the estimation of nonlinear models with mismeasured explanatory variables, when informat...
This paper presents a solution to an important econometric problem, namely the root n consistent est...
It has long been an area of interest to consider a consistent estimation of nonlinear models with me...
Nonlinear regression with measurement error is important for estimation from microeconomic data. One...
The issues of identification and estimation of nonlinear errors-in-variables models are explored. Th...
In many applications, observations from some distribution of interest are contaminated with errors...
A major difficulty in applying a measurement error model is that one is required to have additional ...
This paper considers consistent estimation of generalized linear models with covariate measurement e...
Nonlinear models arise naturally in economics. Both least squares and maximum-likelihood estimators ...
Semiparametric nonlinear mixed-effects (NLME) models are flexible for modelling complex longitudinal...
The present article considers the problem of consistent estimation in measurement error models. A li...
We consider least absolute error estimation in a nonlinear dynamic model with neither independent no...
Estimation of the parameters of the functional nonlinear measurement error model is considered. A si...
In this paper we develop a simple maximum likelihood estimator for probit models where the regressor...