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Some additional moment conditions for a dynamic count panel data model

Author

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  • Yoshitsugu Kitazawa

    () (Faculty of Economics, Kyushu Sangyo University)

Abstract

This paper proposes some additional moment conditions for the linear feedback model formulated in count panel data model, proposed by Blundell et al.(2002). It is shown that the moment conditions based on the quasi-differenced transformation proposed by Chamberlain (1992) and Wooldridge (1997) and some additional moment conditions are derived by using a new operation which the assumptions for disturbances underlie. Two kinds of the additional moment conditions are conceptually equivalent to those proposed by Windmeijer (2000) and Crepon and Duguet (1997) in some regards. Some GMM estimators are constructed using these moment conditions. The small sample performances for the GMM estimators are investigated with some Monte Carlo experiments and it is shown that the GMM estimators perform well when using the additional moment conditions, with minor exceptions.

Suggested Citation

  • 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.
  • Handle: RePEc:kyu:dpaper:29
    as

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    File URL: http://www.ip.kyusan-u.ac.jp/keizai-kiyo/dp29.pdf
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    File URL: http://www.ip.kyusan-u.ac.jp/J/kitazawa/SEMINARS/korea_u080307.pdf
    File Function: Revised version, 2008
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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. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    3. Frank Windmeijer, 2006. "GMM for panel count data models," CeMMAP working papers CWP21/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    5. 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.
    6. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    7. Montalvo, Jose G, 1997. "GMM Estimation of Count-Panel-Data Models with Fixed Effects and Predetermined Instruments," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 82-89, January.
    8. Robert M. Salomon & J. Myles Shaver, 2005. "Learning by Exporting: New Insights from Examining Firm Innovation," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 14(2), pages 431-460, June.
    9. Yuichiro Uchida & Paul Cook, 2007. "Innovation and Market Structure in the Manufacturing Sector: An Application of Linear Feedback Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(4), pages 557-580, August.
    10. Cincera, Michele, 1997. "Patents, R&D, and Technological Spillovers at the Firm Level: Some Evidence from Econometric Count Models for Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 265-280, May-June.
    11. 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.
    12. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    13. Blundell, Richard & Griffith, Rachel & Van Reenen, John, 1995. "Dynamic Count Data Models of Technological Innovation," Economic Journal, Royal Economic Society, vol. 105(429), pages 333-344, March.
    14. Jože P. Damijan & Sašo Polanec & Janez Prašnikar, 2007. "Outward FDI and Productivity: Micro-evidence from Slovenia," The World Economy, Wiley Blackwell, vol. 30(1), pages 135-155, January.
    15. 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.
    16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    17. 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.
    18. 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.
    19. 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, 2009. "Equidispersion and moment conditions for count panel data model," Discussion Papers 33, Kyushu Sangyo University, Faculty of Economics.
    2. Yoshitsugu Kitazawa, 2010. "Size of economic activity and occurrence of fatal traffic accidents: a count panel data analysis on Fukuoka prefecture in Japan," Discussion Papers 41, Kyushu Sangyo University, Faculty of Economics.
    3. Yoshitsugu Kitazawa, 2009. "A negative binomial model and moment conditions for count panel data," Discussion Papers 34, Kyushu Sangyo University, Faculty of Economics.
    4. Yoshitsugu Kitazawa, 2010. "A forward demeaning transformation for a dynamic count panel data model," Discussion Papers 39, Kyushu Sangyo University, Faculty of Economics.
    5. Yoshitsugu Kitazawa, 2012. "An improved theoretical ground for the linear feedback model and a new indicator," Discussion Papers 58, Kyushu Sangyo University, Faculty of Economics.

    More about this item

    Keywords

    count panel data; linear feedback model; implicit operation; moment conditions; generalized method of moments; 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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