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Modelo para datos de recuentro de corte transversal con exceso de ceros. Aplicación a citas patentes

Author

Listed:
  • Margarita E. Romero Rodríguez

    (Universidad de la Laguna. Departamento de Economía de las Instituciones, Estadística Económica y Econometría)

  • Enrique Los Arcos

    (Oficina Europea de Patentes. The Hague, Holanda)

  • Victor Cano Fernández

    (Universidad de la Laguna. Departamento de Economía de las Instituciones, Estadística Económica y Econometría)

  • Miguel Sánchez Padrón

    (Universidad de La Laguna. Departamento de Economía Aplicada)

Abstract

En este trabajo se discuten diversos modelos de regresión para el análisis de datos de recuento de corte transversal,haciendo especial hincapié en la forma en que cada uno recoge dos de las características más comunes de este tipo de datos, el exceso de ceros y la heterogeneidad no observada. Además se lleva a cabo su aplicación en un conjunto de datos sobre patentes, concedidas por la Oficina Europea de Patentes (OEP). En concreto se analiza una de las relaciones propuestas en la literatura, la planteada entre el número de citas recibidas por las patentes y el alcance de las mismas, considerando, además, otro conjunto de características que pueden ser relevantes en la explicación del número de citas. La comparación de los resultados obtenidos con las distintas aproximaciones ilustra la influencia del tipo de modelo elegido sobre las conclusiones que pueden extraerse.

Suggested Citation

  • Margarita E. Romero Rodríguez & Enrique Los Arcos & Victor Cano Fernández & Miguel Sánchez Padrón, 2001. "Modelo para datos de recuentro de corte transversal con exceso de ceros. Aplicación a citas patentes," Documentos de trabajo conjunto ULL-ULPGC 2001-05, Facultad de Ciencias Económicas de la ULPGC.
    • Handle: RePEc:can:series:2001-05
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    References listed on IDEAS

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    1. Meyer, Martin, 2000. "Does science push technology? Patents citing scientific literature," Research Policy, Elsevier, vol. 29(3), pages 409-434, March.
    2. Joly, Pierre-Benoit & de Looze, Marie-Angele, 1996. "An analysis of innovation strategies and industrial differentiation through patent applications: the case of plant biotechnology," Research Policy, Elsevier, vol. 25(7), pages 1027-1046, October.
    3. Gurmu, Shiferaw & Rilstone, Paul & Stern, Steven, 1998. "Semiparametric estimation of count regression models1," Journal of Econometrics, Elsevier, vol. 88(1), pages 123-150, November.
    4. Mullahy, John, 1997. "Heterogeneity, Excess Zeros, and the Structure of Count Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 337-350, May-June.
    5. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    6. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    7. 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.
    8. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    9. Joshua Lerner, 1994. "The Importance of Patent Scope: An Empirical Analysis," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 319-333, Summer.
    10. Winkelmann, Rainer, 1995. "Duration Dependence and Dispersion in Count-Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 467-474, October.
    11. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    12. Albert, M. B. & Avery, D. & Narin, F. & McAllister, P., 1991. "Direct validation of citation counts as indicators of industrially important patents," Research Policy, Elsevier, vol. 20(3), pages 251-259, June.
    13. Cameron, A. Colin & Trivedi, Pravin K., 1990. "Regression-based tests for overdispersion in the Poisson model," Journal of Econometrics, Elsevier, vol. 46(3), pages 347-364, December.
    14. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
    15. Ozuna, Teofilo, Jr & Gomez, Irma Adriana, 1995. "Specification and Testing of Count Data Recreation Demand Functions," Empirical Economics, Springer, vol. 20(3), pages 543-550.
    16. A. C. Cameron & P. K. Trivedi & Frank Milne & J. Piggott, 1988. "A Microeconometric Model of the Demand for Health Care and Health Insurance in Australia," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 55(1), pages 85-106.
    17. Winkelmann, Rainer & Zimmermann, Klaus F., 1991. "A new approach for modeling economic count data," Economics Letters, Elsevier, vol. 37(2), pages 139-143, October.
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