Add to ORKGWe suggest using a class of semiparametric dynamic panel data models to capture individual variations in panel data. The model assumes linearity in some continuous/discrete variables that can be exogenous/endogenous and allows for nonlinearity in other weakly exogenous variables. We propose a nonparametric generalized method of moments (NPGMM) procedure to estimate the functional coefficients, and we establish the consistency and asymptotic normality of the resulting estimators.
Motivated by the first differencing method for linear panel data models, we propose a class of itera...
This paper develops new estimation and inference procedures for dynamic panel data models with fixed...
We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Pruc...
This is the publisher's version, also available electronically from http://journals.cambridge.org/ac...
This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data mo...
This paper is concerned with the statistical inference of partially linear varying coefficient dynam...
We show that the Generalized Method of Moments (GMM) methodology is a useful tool to obtain the asym...
This paper studies a new class of semiparametric dynamic panel data models, in which some coefficien...
A computationally simple bias correction for linear dynamic panel data models is proposed and its as...
In this paper,we investigate the effect of mean-nonstationarity on the first-difference generalized ...
Motivated by the first-differencing method for linear panel data models, we propose a class of itera...
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating s...
An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-...
We develop the panel limited information maximum likelihood (PLIML) approach for estimating dynamic ...
In this article, we consider the estimation of semiparametric panel data smooth coefficient models. ...
Motivated by the first differencing method for linear panel data models, we propose a class of itera...
This paper develops new estimation and inference procedures for dynamic panel data models with fixed...
We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Pruc...
This is the publisher's version, also available electronically from http://journals.cambridge.org/ac...
This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data mo...
This paper is concerned with the statistical inference of partially linear varying coefficient dynam...
We show that the Generalized Method of Moments (GMM) methodology is a useful tool to obtain the asym...
This paper studies a new class of semiparametric dynamic panel data models, in which some coefficien...
A computationally simple bias correction for linear dynamic panel data models is proposed and its as...
In this paper,we investigate the effect of mean-nonstationarity on the first-difference generalized ...
Motivated by the first-differencing method for linear panel data models, we propose a class of itera...
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating s...
An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-...
We develop the panel limited information maximum likelihood (PLIML) approach for estimating dynamic ...
In this article, we consider the estimation of semiparametric panel data smooth coefficient models. ...
Motivated by the first differencing method for linear panel data models, we propose a class of itera...
This paper develops new estimation and inference procedures for dynamic panel data models with fixed...
We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Pruc...