Blundell, R.; Griffith, R.; Windmeijer, F.; (1999) Individual effects and dynamics in count data models. (IFS Working Papers W99/03). Institute for Fiscal Studies: London, UK.

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Abstract

In this paper we examine the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables. Use of a linear feedback model ls proposed. The standard Poisson conditional maximum llkelihood estimator for non-dynamic models, which ls shown to be the same as the Poisson maximum llkelihood estimator in a model with individual specific constants, ls inconsistent when regressors are predetermined. A quasi-differenced GMM estimator ls consistent for the parameters in the dynamic model, but when series are highly persistent, there ls a problem of weak instrument bias. An estimator ls proposed that utilises pre-sample information of the dependent count variable, which is shown in Monte Carlo simulations to possess desirable small sample properties. The models and estimators are applied to data on US patents and R&D expenditure.

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