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Modeling economic growth fuelled by science and technology

Author

Listed:
  • Américo Tristão Bernardes

    (UFOP)

  • Ricardo Machado Ruiz

    (Cedeplar-UFMG)

  • Leonardo Costa Ribeiro

    (UFMG)

  • Eduardo da Motta e Albuquerque

    (Cedeplar-UFMG)

Abstract

This paper suggests a simulation model to investigate how science and technology fuel economic growth. This model is built upon a synthesis of technological capabilities represented by national innovation systems. This paper gathers data of papers and patents for 183 countries between 1999 and 2003, GDP and population for 2003. These data show a strong correlation between science, technology and income. Three simulation exercises are performed. Feeding our algorithm with data for population, patents and scientific papers, we obtain the world income distribution (R=0.99). These results support our conjecture on the role of science and technology as a source of the wealth of nations.

Suggested Citation

  • Américo Tristão Bernardes & Ricardo Machado Ruiz & Leonardo Costa Ribeiro & Eduardo da Motta e Albuquerque, 2006. "Modeling economic growth fuelled by science and technology," Textos para Discussão Cedeplar-UFMG td294, Cedeplar, Universidade Federal de Minas Gerais.
    • Handle: RePEc:cdp:texdis:td294
    as

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    File URL: https://www.cedeplar.ufmg.br/pesquisas/td/TD%20294.pdf
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    References listed on IDEAS

    as
    1. S .G. Winter & Y. M. Kaniovski, 2000. "Modeling Industrial Dynamics with Innovative Entrants," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 16, pages 459-500, Edward Elgar Publishing.
    2. Soete, Luc & Verspagen, Bart & ter Weel, Bas, 2010. "Systems of Innovation," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1159-1180, Elsevier.
    3. Silverberg, Gerald & Verspagen, Bart, 2005. "A percolation model of innovation in complex technology spaces," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 225-244, January.
    4. Richard R. Nelson & Sidney G. Winter, 2002. "Evolutionary Theorizing in Economics," Journal of Economic Perspectives, American Economic Association, vol. 16(2), pages 23-46, Spring.
    5. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
    6. Leonardo C. Ribeiro & Ricardo M. Ruiz & Eduardo M. Albuquerque & Américo T. Bernardes, 2006. "National Systems Of Innovation And Technological Differentiation: A Multi-Country Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 247-257.
    7. Giovanni Dosi, 2000. "Sources, Procedures, and Microeconomic Effects of Innovation," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 2, pages 63-114, Edward Elgar Publishing.
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    10. Bernardes, Americo Tristao & Albuquerque, Eduardo da Motta e, 2003. "Cross-over, thresholds, and interactions between science and technology: lessons for less-developed countries," Research Policy, Elsevier, vol. 32(5), pages 865-885, May.
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    Cited by:

    1. Rašič Katja & Mulej Matjaž & Čančer Vesna, 2016. "The Influential Knowledge Factors of Companies’ Performance in Slovenia," Business Systems Research, Sciendo, vol. 7(1), pages 46-58, March.

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    More about this item

    Keywords

    simulation models; systems of innovation; economic growth;
    All these keywords.

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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