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GMM for panel count data models

Authors: Frank Windmeijer
Date: 11 October 2006
Type: cemmap Working Papers, CWP21/06
doi: 10.1920/wp.cem.2006.2106

Abstract

This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parameters by GMM. As standard Wald tests based on efficient two-step GMM estimation results are known to have poor finite sample behaviour, alternative test procedures that have recently been proposed in the literature are evaluated by means of a Monte Carlo study.

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New version: Frank Windmeijer, April 2008,  GMM for panel count data models,  Book Chapters , Springer Verlag

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