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Some additional moment conditions for a dynamic count panel data model

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Author Info

  • 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.

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File URL: http://www.ip.kyusan-u.ac.jp/keizai-kiyo/dp29.pdf
File Function: First version, 2007
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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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Bibliographic Info

Paper provided by Kyushu Sangyo University, Faculty of Economics in its series Discussion Papers with number 29.

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Length: 70 pages
Date of creation: Dec 2007
Date of revision: Aug 2008
Handle: RePEc:kyu:dpaper:29

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Related research

Keywords: count panel data; linear feedback model; implicit operation; moment conditions; generalized method of moments; Monte Carlo experiments;

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References

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  1. 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.
  2. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  3. Blundell, Richard & Griffith, Rachel & Van Reenen, John, 1995. "Dynamic Count Data Models of Technological Innovation," Economic Journal, Royal Economic Society, vol. 105(429), pages 333-44, March.
  4. Michele Cincera, 1997. "Patents, R&D and technological spillovers at the firm level: some evidence from econometric count models for panel data," ULB Institutional Repository 2013/851, ULB -- Universite Libre de Bruxelles.
  5. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  6. 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, 01.
  7. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  8. 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.
  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 243-63, May-June.
  10. Frank Windmeijer, 2006. "GMM for panel count data models," Bristol Economics Discussion Papers 06/591, Department of Economics, University of Bristol, UK.
  11. 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, 08.
  12. Richard Blundell & Rachel Griffith & Frank Windmeijer, 1999. "Individual effects and dynamics in count data models," IFS Working Papers W99/03, Institute for Fiscal Studies.
  13. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  14. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  15. 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.
  16. 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.
  17. Gerald Marschke & Jinyoung Kim, 2001. "Labor Mobility of Scientists, Technological Diffusion, and the Firm's Patenting Decision," Discussion Papers 01-03, University at Albany, SUNY, Department of Economics.
  18. Windmeijer, Frank, 2000. "Moment conditions for fixed effects count data models with endogenous regressors," Economics Letters, Elsevier, vol. 68(1), pages 21-24, July.
  19. 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, 06.
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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.

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