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A responsiveness-based (composite) indicator with an application to countries’ innovative performance



The aim of this paper is twofold: on one hand, from a methodological-statistical perspective, it develops a responsiveness-based index for a series of input factors on a specific target variable (assumed to capture the phenomenon the analyst wishes to look at), by means of an extended version of a random coefficient regression approach; on the other hand, it applies this methodology to the case of countries’ innovation performance, where the target variable is the country number of patents (as proxy of “innovativeness”), and where inputs are chosen according to the literature dealing with the measurement of country technological capabilities. The novelty of the approach presented in the paper regards the possibility of extracting from data a country-specific “reactivity effect” or “responsiveness” (that is, mathematically, a derivative) to each single input feeding into the regression. Thus, the paper provides a promising approach for ranking countries according to their responsiveness to specific inputs, an approach that can be complementary to the analysis on “level” performed, for instance, in the canonical composite indicators’ literature. As for results on countries’ innovation function, besides a (new) ranking of countries, this approach allows also for testing - in an original and straightforward way - the (possible) presence of increasing (decreasing) returns. Two years are considered and compared, 1995 and 2007, on 42 countries. Our tests conclude that in both years innovative increasing returns are at work, although in 2007 their strength drops considerably compared to 1995. According to a huge literature on the subject (both neoclassical and evolutionary), we conclude that a self-reinforcing mechanism in new knowledge production, absorption and diffusion is at the basis of these results. As for the structural change found between 1995 and 2007, we deem it to depend on the growing globalization of production and innovation processes and on the brilliant growth of some developing countries worldwide, with a remarkable role played – according to our results – by post-communist economies.

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  • Giovanni Cerulli, 2010. "A responsiveness-based (composite) indicator with an application to countries’ innovative performance," CERIS Working Paper 201010, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
  • Handle: RePEc:csc:cerisp:201010

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    References listed on IDEAS

    1. Godin, Benoit, 2007. "Science, accounting and statistics: The input-output framework," Research Policy, Elsevier, vol. 36(9), pages 1388-1403, November.
    2. Angrist, J.D. & Imbens, G.W., 1992. "Average causal response with variable treatment intensity," Discussion Paper 1992-34, Tilburg University, Center for Economic Research.
    3. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 287-343 National Bureau of Economic Research, Inc.
    4. A. Filippetti & A. Peyrache, 2010. "The Globalization of Technological Capabilities of Countries: A Dual Approach Using Composite Indicators & Data Envelopment Analysis," CEPA Working Papers Series WP102010, School of Economics, University of Queensland, Australia.
    5. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
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    9. Barro, Robert J & Sala-i-Martin, Xavier, 1997. "Technological Diffusion, Convergence, and Growth," Journal of Economic Growth, Springer, vol. 2(1), pages 1-26, March.
    10. Rivera-Batiz, Luis A. & Romer, Paul M., 1991. "International trade with endogenous technological change," European Economic Review, Elsevier, vol. 35(4), pages 971-1001, May.
    11. Nathan ROSENBERG, 2009. "Why do firms do basic research (with their own money)?," World Scientific Book Chapters,in: Studies On Science And The Innovation Process Selected Works of Nathan Rosenberg, chapter 11, pages 225-234 World Scientific Publishing Co. Pte. Ltd..
    12. Fagerberg, Jan & Srholec, Martin, 2008. "National innovation systems, capabilities and economic development," Research Policy, Elsevier, vol. 37(9), pages 1417-1435, October.
    13. James, M.J., 2006. "An institutional critique of recent attempts to measure technological capabilities across countries," Other publications TiSEM 05175942-7ecf-410c-9e17-b, Tilburg University, School of Economics and Management.
    14. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, vol. 56(2), pages 129-133, October.
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    More about this item


    Responsiveness; Country indicators; Random coefficient regression; Innovation function;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development

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