Science and Technology Policy in Latino America Countries: A Panel Data approach

  • José Carlos Rodríguez Chávez Instituto de Investigaciones Económicas y Empresariales


This paper analyzes science and technology policy in Latino America. Making use of panel data methods, we test for successful science and technology policy, and sup­porting innovation practices in Argentina, Brazil, Chile and Mexico. There are three paradigms that explain science and technology policy: the market failure paradigm, the mission paradigm, and the cooperative technology paradigm. The market failu­re paradigm assumes that market mechanisms will lead to optimal rates of science production and technical change. The mission technology paradigm assumes that governments may play an important role in the programmatic mission of agencies. The cooperative technology policy paradigm assumes that markets are not always the most efficient route to innovation. The results suggest that there is room for go­vernment involvement when defining a science and technology policy that aims to support the development of innovative capabilities. We conclude that mission and/ or the cooperative technology paradigms are adequate for defining a successful scien­ce and technology policy in Latino America.


Arrow, K. J. 1962. Economic Welfare and the Allocation of Resources for Invention. In R. R. Nelson (ed.), The Rate and Direction of Inventive Activity: Economic and Social Factor. Princeton: Princeton University Press.

Asteriou, D., and S. G. Hall. 2007. Applied Econometrics: A Modern Approach. Pal¬grave MacMillan.

Baltagi, B. H. 2005. Econometric Analysis of Panel Data. New York, USA. John Wi¬ley and Sons.

Barrere, R., M. Bageneta, and L. Matas. 2008. Sistemas Científicos Complejos y su Abordaje Metodológico. In M. Albornoz, C. Vogt, and C. Alfarez (eds.), Indi¬cadores de Ciencia y Tecnología en Iberoamérica: Agenda 2008. Buenos Aires: Ricyt.

Bozeman, B. 2000. Technology transfer and public policy: A review of research and policy. Research Policy 29: 627-655.

Dutrénit, G., M. Puchet, L. Sanz-Menendez, M. Teubal, and A. O. Vera-Cruz. 2003. A Policy Model to Foster Coevolutionary Processes of Science, Technology and Innovation: The Mexican Case. Working Paper Series 08-03. Globelics.

Emiliozzi, S., G. A. Lemarchand, and A. Gordon. 2009. Inventario de Instrumentos y Modelos de Políticas de Ciencia Tecnología e Innovación en América Latina y el Caribe. Working Paper 9. Banco Interamericano de Desarrollo.

Gómez, M., and J. C. Rodríguez. 2008. Innovative Activity in NAFTA and EU Countries: An Analysis of Structural Change in Patent Granted Trends. Procee¬dings of the Applied Econometrics Association. AEA: Tokyo, Japan.

Gómez, M., and J. C. Rodríguez. 2009. Multiple Structural Changes in Patent Gran¬ted Series and Innovative Performance: The Case of NAFTA and EU Countries. Proceedings of the International Society for Professional Innovation Manage¬ment. ISPIM: New York, United States.

Katz, J. 2006. Cambios Estructurales y Ciclos de Destrucción y Creación de Capaci¬dades Productivas y Tecnológicas en América Latina. Working Paper Series 07- 06. Globelics.

Katz, J. M. 2007. Structural Reforms, Productivity and Technological Change in La¬tin America. Santiago: CEPAL.

Kim, L. 1997. From Imitation to Innovation: The Dynamics of Korea’s Technologi¬cal Learning. Boston, MA: Harvard Business School Press.

López-Acevedo, G. 2002. Determinants of Technology Adoption in Mexico. Policy Research Working Paper. World Bank. Washington, DC.

Lundvall, B. A. 1996. Information technology in the learning economy: Challenges for development strategies. Working Paper – Group on IT and Development. UNCSTD.

Nelson, R. R. 1959. The simple economics of basic scientific research. Journal of Political Economy 76: 297-306.

Nelson, R. R. 1994. The coevolution of technology, industrial structure and suppor¬tinginstitutions. Industrial and Corporate Change 3: 47-63.

Nelson, R. R. 1995. Coevolution of industry structure, technology and supporting institutions, and the making of competitive advantage. International Journal of the Economics of Business 2: 171-184.

Vilela, C., and S. Moro. Investigating the interaction and mutual dependence bet-ween science and technology. Research Policy 36: 1204-1220.

Wooldridge, J. 2002. Econometric Analysis of Cross Section and Panel Data. Cam¬bridge, MA: MIT Press.