GMM for panel count data models

Frank Windmeijer

No CWP21/06, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

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.

Keywords: GMM; exponential models; hypothesis testing (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 (search for similar items in EconPapers)
Date: 2006-10-11
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (29)

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http://cemmap.ifs.org.uk/wps/cwp2106.pdf (application/pdf)

Related works:
Working Paper: GMM for panel count data models (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:21/06

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