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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.

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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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Bibliographic Info

Paper provided by Kyushu Sangyo University, Faculty of Economics in its series Discussion Papers with number 34.

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Length: 27 pages
Date of creation: Jun 2009
Date of revision:
Handle: RePEc:kyu:dpaper:34

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Related research

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

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References

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  1. 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 243-63, May-June.
  2. 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.
  3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  4. Blundell, Richard & Griffith, Rachel & van Reenen, John, 1999. "Market Share, Market Value and Innovation in a Panel of British Manufacturing Firms," Review of Economic Studies, Wiley Blackwell, vol. 66(3), pages 529-54, July.
  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. Richard Blundell & Rachel Griffith & Frank Windmeijer, 1999. "Individual effects and dynamics in count data models," IFS Working Papers W99/03, Institute for Fiscal Studies.
  7. Lancaster, Tony, 2002. "Orthogonal Parameters and Panel Data," Review of Economic Studies, Wiley Blackwell, vol. 69(3), pages 647-66, July.
  8. Frank Windmeijer, 2006. "GMM for panel count data models," Bristol Economics Discussion Papers 06/591, Department of Economics, University of Bristol, UK.
  9. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, April.
  10. Yoshitsugu Kitazawa, 2009. "Equidispersion and moment conditions for count panel data model," Discussion Papers 33, Kyushu Sangyo University, Faculty of Economics.
  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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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.

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