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GMM Estimation of Count-Panel-Data Models with Fixed Effects and Predetermined Instruments

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  • Montalvo, Jose G
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    Abstract

    The 'traditional' approach to the estimation of count panel data models with fixed effects is the conditional maximum-likelihood estimator. This paper proposed a GMM estimator for count panel data models with fixed effects, based on a transformation of the conditional mean specification, that is consistent even when the explanatory variables are predetermined. Two applications are discussed: the relationship between patents and R&D expenditures and the explanation of technology transfer.

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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

    Volume (Year): 15 (1997)
    Issue (Month): 1 (January)
    Pages: 82-89

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    Handle: RePEc:bes:jnlbes:v:15:y:1997:i:1:p:82-89

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    Cited by:
    1. Frank Windmeijer, 2006. "GMM for panel count data models," Bristol Economics Discussion Papers 06/591, Department of Economics, University of Bristol, UK.
    2. Hagedoorn, John & Wang, Ning, 2010. "Is there complementarity or substitutability between internal and external R&D strategies?," MERIT Working Papers 005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    3. Hagedoorn, John & Wang, Ning, 2012. "Is there complementarity or substitutability between internal and external R&D strategies?," Research Policy, Elsevier, vol. 41(6), pages 1072-1083.
    4. Rentocchini, Francesco, 2011. "Sources and characteristics of software patents in the European Union: Some empirical considerations," Information Economics and Policy, Elsevier, vol. 23(1), pages 141-157, March.
    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. Alka Chadha, 2005. "Trips and Patenting Activity: Evidence from the Indian Pharmaceutical Industry," Departmental Working Papers wp0512, National University of Singapore, Department of Economics.
    7. 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.
    8. Mann, Ronald J. & Sager, Thomas W., 2007. "Patents, venture capital, and software start-ups," Research Policy, Elsevier, vol. 36(2), pages 193-208, March.
    9. Koski, Heli, 2000. "Regulators and Competition Spurring or Retarding Innovation in the Telecommunications Sector?," Discussion Papers 724, The Research Institute of the Finnish Economy.
    10. Fidel Pérez Sebastián & Shiferaw Gurmu, 2007. "Patents, R&D And Lag Effects: Evidence From Flexible Methods For Count Panel Data On Manufacturing Firms," Working Papers. Serie AD 2007-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    11. 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.
    12. Rincke, Johannes, 2007. "Policy diffusion in space and time: The case of charter schools in California school districts," Regional Science and Urban Economics, Elsevier, vol. 37(5), pages 526-541, September.

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