Assessing Some Determinants of the Regional Patenting: An Essay from the Mexican States

Abstract

The aim of this work is to study the environment that affects and influences in the creation of regional patents. With this purpose the patenting process is modeled as dynamic one where, beside other factors, its past values contribute to create synergies to continue patenting in a feedback process. Using a dynamic panel data estimator we find that past patenting level trends to encourage the actual one. Also, a positive and significant effect from education, university expenditure, population density and industrial concentration on patents is reported in the Mexican states set. Conclusions highlight that agglomeration forces are the main factors for patenting, followed by university expenditure and industrial concen- tration.

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V. German-Soto and L. Gutiérrez Flores, "Assessing Some Determinants of the Regional Patenting: An Essay from the Mexican States," Technology and Investment, Vol. 4 No. 3B, 2013, pp. 1-9. doi: 10.4236/ti.2013.43B001.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] J. Aboites, “Innovación, Patentes y Globalización”. In Jaime Aboites and Gabiela Dutrénit (Eds.), Innovación, Aprendizaje y Creación de Capacidades Tecnológicas, México: Universidad Autónoma Metropolitana-Porrúa, 2003, pp. 163-206.
[2] Z. Acs, L. Anselin and A. Varga, “Patents and Innovation Counts as Measures of Regional Production of New Knowledge,” Research Policy, Vol. 31, 2002, pp. 1069-1085. doi:10.1016/S0048-7333(01)00184-6
[3] P. Aghion, C. Harris, P. Howitt and J. Vickers, “Competition, Imitation and Growth with Step-by-Step Innovation,” Review of Economic Studies, Vol. 68, 1998, pp. 467-492. doi:10.1111/1467-937X.00177
[4] M. Arellano, “Modelling Optimal Instrumental Variables for Dynamic Panel Data Models,” Econometrics Invited Lecture, European Meeting of the Econometric Society, Venice, August 2002. CEMFI Working Paper no. 0310.
[5] M. Arellano, Panel Data Econometrics. Advanced Texts in Econometrics, Oxford University Press, Oxford, 2003. doi:10.1093/0199245282.001.0001
[6] M. Arellano and S. Bond, “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” Review of Economic Studies, Vol. 58, No. 2, 1991, pp. 277-297. doi:10.2307/2297968
[7] M. Arellano and S. Bond, “Dynamic Panel Data Estimation Using DPD98 for Gauss: A Guide for Users,” Unpublished, 1998.
[8] B. H. Baltagi, Econometrics, Springer-Verlag, New York, 2008.
[9] R. Barro and X. Sala-i-Martin, 2004, Economic Growth. MA: The MIT Press, Cambridge, 2004.
[10] R. L. Basmann, M. McA-leer and D. Slottje, “Patent Activity and Technical Change,” Journal of Econometrics, Vol. 139, 2007, pp. 355-375. doi:10.1016/j.jeconom.2006.10.019
[11] P. Beneito, P. Coscollá-Girona, M. E. Rochina-Barrachina and A. San-chis-Llopis, “Competitive Pressure Determinants and Innovation at the Firm Level,” Ivie Working Paper Series 2011-02, InstitutoValenciano de Investigaciones Económicas, 2011, p. 40.
[12] R. Blundell and S. Bond, “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models,” Journal of Econometrics, Vol. 87, No. 1, 1998, pp. 115-143. doi:10.1016/S0304-4076(98)00009-8
[13] M. Capdevielle, Composición Tecnológica de la Industria Manufacturera Mexicana. In Aboites J. y Gabriela Dutrénit (Eds). Innovación, Aprendizaje y Creación de Capacidades Tecnológicas. México: Universidad Autónoma Metropolitana-Porrúa. 2003, pp. 249-284.
[14] M. H. Fallah and S. Ibrahim “Knowledge Spillover and Innovation in Technological Clusters,” Mimeo, International Association for Management of Technology, 2004, p. 16.
[15] M. Feldman and D. Kogler, “The contribution of public entities to innovation and technological change”, In S. Shane (ed.) The Handbook of Technology and Innovation Management, Wiley Publishing, West Sussex, 2008, pp. 431-460.
[16] M. Feldman and M. Kelley, “How States Augment the Capabilities of Technology-Pioneering Firms,” Growth and Change, Vol. 33, No. 2, 2002, pp. 173-195.
[17] K. J. Gotvassli, “Com-munity Knowledge - A Catalyst for Innovation,” The Journal of Regional Analysis and Policy Vol. 38, No. 2, 2008, pp. 145-158.
[18] U. Grasj?, “Accesibility to R&D and Patent Production,” CESIS Electronic Working Paper Series, No. 37, 2005, p. 35
[19] V. German-Soto, L. Gutiérrez and S. H. Tovar Montiel, “Factores y relevancia geográfica del proceso de innovación regional en México, 1994-2006,” Estudios Económicos, Vol. 24, No. 2, 2009, pp. 225-248.
[20] V. German-Soto and L. Gutiérrez, “Time Series Tests of Structural Change among Innovation and Trade Liberalization in Mexico”, Journal of the Knowledge Economy, Vol. 1, No. 3, 2010, pp. 219-237. doi:10.1007/s13132-010-0015-6
[21] V. German-Soto and L. Gutiérrez, “Measurement of the Agglomeration and the Geographic Concentration of the Innovation across Mexican States”. In F. Vargas, A. Ivanova, G. Meijer and B. Burgos (eds.), New Challenges, New methodologies. Proceedings of the XI ISINI Conference. Hermosillo: Pearson Education and Universidad de Sonora, 2011, pp. 118-134.
[22] W. H. Greene, Econometric Analysis, New Jersey: Pearson Prentice Hall, 2008.
[23] G. M. Grossman and E. E. Helpman, “Endogenous Innovation in the Theory of Growth,” The Journal of Economic Perspectives, Vol. 8, No. 1, 1994, pp. 23-44. doi:10.1257/jep.8.1.23
[24] A. Jaffe, “Technological Opportunity and Spillovers of R&D: Evidence from Firms’ Patents, Profits and Market Value,” The American Economic Review, Vol. 7, No. 5, 1986, pp. 984-1001.
[25] A. Jaffe, M. Trajtenberg and R. Henderson, “Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations,” Quarterly Journal of Economics, Vol. 108, No. 3, 1993, pp. 577-598. doi:10.2307/2118401
[26] C. Jones I., “The Shape of Production Functions and the Direction of Technical Change,” The Quarterly Journal of Economics, Vol. 120, No. 2, 2005, pp. 517-549.
[27] R. A. Judson and A. L. Owen, “Estimating Dynamic Panel Data Models: A Guide for Macroeconomists,” Economics Letters, Vol. 65, 1999, pp. 9-15. doi:10.1016/S0165-1765(99)00130-5
[28] B. Karlsson and C. Johansson “Towards a Dynamic Theory for the Spatial Knowledge Economy,” CESIS Electronic Working Paper Series, No. 20, 2004, p. 31.
[29] S. S. Kortum, “Research, Patenting, and Technological Change,” Econometrica, Vol. 65, 1997, pp. 1389-1419. http://dx.doi.org/10.2307/2171741
[30] O. Lehtoranta, “Innovation, Collaboration in Innovation and the Growth Performance of Finnish Firms,” VTT Publications 279, Technical Research Center of Finland, 2010, p. 136.
[31] K. Meagher and M. Rogers, “Networks, spil-lovers and models of economic growth”, Discussion Papers, Sidney, The University of New South Wales, 1998, pp. 1-34.
[32] M. Orlando, “On the importance of geographic and technological proximity for R&D spillovers: An empirical investigation,” Mimeo, Department of Economic Investigation, Federal Reserve Bank of San Luis, 2000.
[33] C. Ornaghi, “Spillovers in product and process innovation: Evidence from manufacturing firms,” International Journal of Industrial Organization, Vol. 24, 2006, pp. 349-380. doi:10.1016/j.ijindorg.2005.07.002.
[34] A. Panagopoulos, “The Effect of IP Protection on Radical and Incremental Innovation,” Journal of the Knowledge Economy, Vol. 2, 2011, pp. 393-404. http://dx.doi.org/10.1007/s13132-011-0039-6
[35] M. P. Pérez, G. Dutrénit and F. Barceinas, “Actividad innovadora y desempeño económico de las empresas mexicanas,” document presented at the VI workshop of science and technology indicators, Buenos Aries, September, 2004.
[36] O. Raspe and F. van Oort, “Firm Growth and Localized Externalities,” The Journal of Regional Analysis and Policy, Vol. 38, No. 2, 2008, pp. 100-116.
[37] A. J. Scott and M. Storper, “Regions, Globalization and Development,” Regional Studies, Vol. 37 No. 6&7, 2003, pp. 579-593.

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