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Human Capital, Social Capital And Scientific Research In Europe: An Application Of Linear Hierarchical Models

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  • MATHIEU GOUDARD
  • MICHEL LUBRANO

Abstract

The theory of human capital is one way to explain individual decisions to produce scientific research. However, this theory, even if it reckons the importance of time in science, is too short for explaining the existing diversity of scientific output. The present paper introduces the social capital of Bourdieu (1980), Coleman (1988) and Putnam (1995) as a necessary complement to explain the creation of scientific human capital. This paper connects these two concepts by means of a hierarchical econometric model which makes the distinction between the individual level (human capital) and the cluster level of departments (social capital). The paper shows how a collection of variables can be built from a bibliographic data base indicating both individual behaviour including mobility and collective characteristics of the department housing individual researchers. The two level hierarchical model is estimated on fourteen European countries using bibliometric data in the fields of economics.
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  • Mathieu Goudard & Michel Lubrano, 2013. "Human Capital, Social Capital And Scientific Research In Europe: An Application Of Linear Hierarchical Models," Manchester School, University of Manchester, vol. 81(6), pages 876-903, December.
  • Handle: RePEc:bla:manchs:v:81:y:2013:i:6:p:876-903
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    File URL: http://hdl.handle.net/10.1111/manc.2013.81.issue-6
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    References listed on IDEAS

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    1. Luc Bauwens & Giordano Mion & Jacques-François Thisse, 2011. "The Resistible Decline of European Science," Recherches économiques de Louvain, De Boeck Université, vol. 77(4), pages 5-31.
    2. Michel Lubrano & Luc Bauwens & Alan Kirman & Camelia Protopopescu, 2003. "Ranking Economics Departments in Europe: A Statistical Approach," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1367-1401, December.
    3. James J. Heckman & Lance J. Lochner & Petra E. Todd, 2003. "Fifty Years of Mincer Earnings Regressions," NBER Working Papers 9732, National Bureau of Economic Research, Inc.
    4. Stephan, Paula E., 2010. "The Economics of Science," Handbook of the Economics of Innovation, Elsevier.
    5. Lubrano, Michel & Protopopescu, Camelia, 2004. "Density inference for ranking European research systems in the field of economics," Journal of Econometrics, Elsevier, vol. 123(2), pages 345-369, December.
    6. Levin, Sharon G & Stephan, Paula E, 1991. "Research Productivity over the Life Cycle: Evidence for Academic Scientists," American Economic Review, American Economic Association, vol. 81(1), pages 114-132, March.
    7. Michael Rauber & Heinrich W. Ursprung, 2008. "Life Cycle and Cohort Productivity in Economic Research: The Case of Germany," German Economic Review, Verein für Socialpolitik, vol. 9, pages 431-456, November.
    8. McDowell, John M, 1982. "Obsolescence of Knowledge and Career Publication Profiles: Some Evidence of Differences among Fields in Costs of Interrupted Careers," American Economic Review, American Economic Association, vol. 72(4), pages 752-768, September.
    9. Yoram Ben-Porath, 1967. "The Production of Human Capital and the Life Cycle of Earnings," Journal of Political Economy, University of Chicago Press, vol. 75, pages 352-352.
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    Cited by:

    1. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2017. "Economists, Research Performance and National Inbreeding: North Versus South," Economic Notes, Banca Monte dei Paschi di Siena SpA, pages 145-163.

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