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Technology frontier, labor productivity and economic growth: Evidence from OECD countries

  • Théophile T. Azomahou
  • Bity Diene
  • Mbaye Diene

    ()

    (CREA, University of Luxembourg)

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    We use 29 OECD countries data spanning over 1960-2000 to study the growth strategy when countries are close to the technology frontier. Relying on a semi-parametric generalized additive model, we estimate labor productivity equations. We find that the number of agents enrolled in higher education is a determinant of growth. Moreover, when a country is sufficiently near the technology frontier thanks to an increasing R&D expenditure, it becomes optimal to invest in fundamental research, since after a short period of efficiency, business R&D can no longer ensure the transition toward the technology frontier, while higher education presents the opposite shape. These findings support the main assertion of Aghion and Cohen (2004) that countries which are near the technology frontier have to invest in higher education while those far away from the frontier make their technology level growing up by investing in primary and secondary schooling.

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    File URL: http://wwwen.uni.lu/content/download/24335/294833/file/2009-19_Technology%20frontier,%20labor%20productivity%20and%20economic%20growth_Evidence%20from%20OECD%20countries.pdf
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    Paper provided by Center for Research in Economic Analysis, University of Luxembourg in its series CREA Discussion Paper Series with number 09-19.

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    Date of creation: 2009
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    Handle: RePEc:luc:wpaper:09-19
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    1. Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
    2. Boucekkine, Raouf & de la Croix, David & Licandro, Omar, 2002. "Vintage Human Capital, Demographic Trends, and Endogenous Growth," Journal of Economic Theory, Elsevier, vol. 104(2), pages 340-375, June.
    3. N. Gregory Mankiw & David Romer & David N. Weil, 1990. "A Contribution to the Empirics of Economic Growth," NBER Working Papers 3541, National Bureau of Economic Research, Inc.
    4. Linton, Oliver B., 2000. "Efficient Estimation Of Generalized Additive Nonparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 16(04), pages 502-523, August.
    5. Paul M Romer, 1999. "Endogenous Technological Change," Levine's Working Paper Archive 2135, David K. Levine.
    6. Eric A. Hanushek & Dongwook Kim, 1995. "Schooling, Labor Force Quality, and Economic Growth," NBER Working Papers 5399, National Bureau of Economic Research, Inc.
    7. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin.
    8. Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228 Elsevier.
    9. Andrea Bassanini & Stefano Scarpetta, 2001. "Les moteurs de la croissance dans les pays de l'OCDE : Analyse empirique sur des données de panel," Revue économique de l'OCDE, OECD Publishing, vol. 2001(2), pages 7-58.
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