Add to ORKGABSTRACT. We present an iterative estimation procedure to estimate panel data models when some observations are missed or grouped with arbitrary clas-sification intervals. The analysis is carried out from the perspective of panel data models, in which the error terms may follow an arbitrary distribution. We propose an easy-to-implement algorithm to estimate all of the model parameters and the asymptotic stochastic properties of the resulting estimate are investigated as the number of individuals and the number of time periods increase. 1
ABSTRACT. This paper considers fixed effects estimation and inference in linear and nonlin-ear panel...
Panel data sets, also called longitudinal data sets, are sets of data where the same units (for inst...
This work investigates mainly panel data models in which cross-sections can be considered independen...
This paper proposes a data-dependent, semi-parametric method for estimating panel data models with g...
This paper considers two ways of estimating panel data models with group specific parameters when gr...
Panel data are repeated observations on the same cross section unit, typically of individuals or fir...
The main purpose of this paper is to estimate panel data models with endogenous regressors and nonad...
This chapter gives an account of the recent literature on estimating models for panel count data. Sp...
AbstractA dynamic panel data model is considered that contains possibly stochastic individual compon...
The article discusses statistical inference in parametric models for panel data. The models feature ...
textabstractThis paper reviews research issues in modeling panels of time series. Examples of this t...
This paper studies the estimation of a panel data model with latent structures where individuals can...
A dynamic panel data model is considered that contains possibly stochastic individual components and...
This article discusses the statistical analysis of panel count data when the underlying recurrent ev...
We study kmeans clustering estimation of panel data models with a latent group structure and N units...
ABSTRACT. This paper considers fixed effects estimation and inference in linear and nonlin-ear panel...
Panel data sets, also called longitudinal data sets, are sets of data where the same units (for inst...
This work investigates mainly panel data models in which cross-sections can be considered independen...
This paper proposes a data-dependent, semi-parametric method for estimating panel data models with g...
This paper considers two ways of estimating panel data models with group specific parameters when gr...
Panel data are repeated observations on the same cross section unit, typically of individuals or fir...
The main purpose of this paper is to estimate panel data models with endogenous regressors and nonad...
This chapter gives an account of the recent literature on estimating models for panel count data. Sp...
AbstractA dynamic panel data model is considered that contains possibly stochastic individual compon...
The article discusses statistical inference in parametric models for panel data. The models feature ...
textabstractThis paper reviews research issues in modeling panels of time series. Examples of this t...
This paper studies the estimation of a panel data model with latent structures where individuals can...
A dynamic panel data model is considered that contains possibly stochastic individual components and...
This article discusses the statistical analysis of panel count data when the underlying recurrent ev...
We study kmeans clustering estimation of panel data models with a latent group structure and N units...
ABSTRACT. This paper considers fixed effects estimation and inference in linear and nonlin-ear panel...
Panel data sets, also called longitudinal data sets, are sets of data where the same units (for inst...
This work investigates mainly panel data models in which cross-sections can be considered independen...