This paper considers estimation methods and inference for linear dynamic panel data models with unit-specific heterogeneity and a short time dimension. In particular, we focus on the identification of the coefficients of time-invariant variables in a dynamic version of the Hausman and Taylor...

This paper considers estimation methods and inference for linear dynamic panel data models with unit-specific heterogeneity and a short time dimension. In particular, we focus on the identification of the coefficients of time-invariant variables in a dynamic version of the Hausman and Taylor...

In this paper we examine the properties of a simple criterion-based, likelihood ratio type test of parameter restristions for standard GMM estimators in autoregressive panel data models. A comparison is made with recent test proposals based in the continuously-updated GMM criterion (Hansen,...

We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small T and large N. The moments used are derived for each period from a first order approximation of the mean of the dependent...

The well-known problem of too many instruments in dynamic panel data GMM is dealt with in detail in Roodman (2009, Oxford Bull. Econ. Statist.). The present paper goes one step further by providing a solution to this problem: factorisation of the standard instrument set is shown to be a valid...

The well-known problem of too many instruments in dynamic panel data GMM is dealt with in detail in Roodman (2009, Oxford Bull. Econ. Statist.). The present paper goes one step further by providing a solution to this problem: factorisation of the standard instrument set is shown to be a valid...

The finite sample behaviour is analysed of particular least squares (LS) andmethod of moments (MM) estimators in panel data models with individual effectsand both a lagged dependent variabIe regressor and another explanatory variabIewhich may be affected by lagged feedbacks from the dependent...

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error....

An autoregressive fixed effects panel data equation in error-ridden endogenous and exogenous variables, with finite memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators are explored by Monte Carlo (MC) simulations. Two kinds...

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors is assumed. Two specializations of GMM are...