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A consistent estimator for the binomial distribution in the presence of "incidental parameters": an application to patent data

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  • Machado, Matilde P.

Abstract

In this paper a consistent estimator for the Binomial distribution in the presence of incidental parameters, or fixed effects, when the underlying probability is a logistic function is derived. The consistent estimator is obtained from the maximization of a conditional likelihood function in light of Andersen's work. Monte Carlo simulations show its superiority relative to the traditional maximum likelihood estimator with fixed effects also in small samples, particularly when the number of observations in each cross-section, T, is small. Finally, this new estimator is applied to an original dataset that allows the estimation of the probability of obtaining a patent.

Suggested Citation

  • Machado, Matilde P., 2003. "A consistent estimator for the binomial distribution in the presence of "incidental parameters": an application to patent data," UC3M Working papers. Economics we031905, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we031905
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    1. Archibugi, Daniele & Pianta, Mario, 1992. "Specialization and size of technological activities in industrial countries: The analysis of patent data," Research Policy, Elsevier, vol. 21(1), pages 79-93, February.
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    3. Machado, Matilde P., 2001. "Dollars and performance: treating alcohol misuse in Maine," Journal of Health Economics, Elsevier, vol. 20(4), pages 639-666, July.
    4. 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.
    5. 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.
    6. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
    7. Machado, Matilde P., 2004. "A consistent estimator for the binomial distribution in the presence of "incidental parameters": an application to patent data," Journal of Econometrics, Elsevier, vol. 119(1), pages 73-98, March.
    8. Manuel Arellano, 2003. "Discrete choices with panel data," Investigaciones Economicas, Fundación SEPI, vol. 27(3), pages 423-458, September.
    9. Aigner, Dennis J. & Hsiao, Cheng & Kapteyn, Arie & Wansbeek, Tom, 1984. "Latent variable models in econometrics," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 23, pages 1321-1393 Elsevier.
    10. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 225-238.
    11. J. Pfanzagl, 1993. "On the consistency of conditional maximum likelihood estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(4), pages 703-719, December.
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    Cited by:

    1. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Machado, Matilde P., 2004. "A consistent estimator for the binomial distribution in the presence of "incidental parameters": an application to patent data," Journal of Econometrics, Elsevier, vol. 119(1), pages 73-98, March.
    3. David S. Jacks & Krishna Pendakur & Hitoshi Shigeoka, 2017. "Infant Mortality and the Repeal of Federal Prohibition," Working Papers 2017-036, Human Capital and Economic Opportunity Working Group.

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