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GMM for panel count data models

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  • Frank Windmeijer

    (Institute for Fiscal Studies and University of Bristol)

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.

Suggested Citation

  • Frank Windmeijer, 2006. "GMM for panel count data models," CeMMAP working papers CWP21/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:21/06
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    File URL: http://cemmap.ifs.org.uk/wps/cwp2106.pdf
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    References listed on IDEAS

    as
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. GMM and its application outside finance
      by Chris Auld in ChrisAuld.com on 2013-10-22 00:55:38

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    More about this item

    Keywords

    GMM; exponential models; hypothesis testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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