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A negative binomial model and moment conditions for count panel data

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  • Yoshitsugu Kitazawa

    () (Faculty of Economics, Kyushu Sangyo University)

Abstract

This paper proposes some moment conditions associated with an appropriate specification of negative binomial model for count panel data, which is proposed by Hausman et al. (1984). The newly proposed moment conditions enable researchers to conduct the consistent estimation of the model under much weaker assumptions than those configured by Hausman et al. (1984). In some Monte Carlo experiments, it is shown that the GMM estimators using the new moment conditions perform well in the DGP configurations conforming to the specification above.

Suggested Citation

  • Yoshitsugu Kitazawa, 2009. "A negative binomial model and moment conditions for count panel data," Discussion Papers 34, Kyushu Sangyo University, Faculty of Economics.
  • Handle: RePEc:kyu:dpaper:34
    as

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    File URL: http://www.ip.kyusan-u.ac.jp/keizai-kiyo/dp34.pdf
    File Function: First version, 2009
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Frank Windmeijer, 2006. "GMM for panel count data models," CeMMAP working papers CWP21/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    4. Cameron,A. Colin & Trivedi,Pravin K., 2008. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9787111235767, March.
    5. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    6. Tony Lancaster, 2002. "Orthogonal Parameters and Panel Data," Review of Economic Studies, Oxford University Press, vol. 69(3), pages 647-666.
    7. Yoshitsugu Kitazawa, 2009. "Equidispersion and moment conditions for count panel data model," Discussion Papers 33, Kyushu Sangyo University, Faculty of Economics.
    8. Yoshitsugu Kitazawa, 2007. "Some additional moment conditions for a dynamic count panel data model," Discussion Papers 29, Kyushu Sangyo University, Faculty of Economics, revised Aug 2008.
    9. Crepon, Bruno & Duguet, Emmanuel, 1997. "Estimating the Innovation Function from Patent Numbers: GMM on Count Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 243-263, May-June.
    10. Richard Blundell & Rachel Griffith & John van Reenen, 1999. "Market Share, Market Value and Innovation in a Panel of British Manufacturing Firms," Review of Economic Studies, Oxford University Press, vol. 66(3), pages 529-554.
    11. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    12. Windmeijer, Frank, 2000. "Moment conditions for fixed effects count data models with endogenous regressors," Economics Letters, Elsevier, vol. 68(1), pages 21-24, July.
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    Citations

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    Cited by:

    1. Yoshitsugu Kitazawa, 2010. "A forward demeaning transformation for a dynamic count panel data model," Discussion Papers 39, Kyushu Sangyo University, Faculty of Economics.

    More about this item

    Keywords

    count panel data; predetermined explanatory variable; linear feedback model; overdispersion; negative binomial model; implicit operation; cross-linkage moment conditions; GMM; Monte Carlo experiments;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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