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Measuring the Impact of Direct and Indirect R&D on the Productivity Growth of Industries: Using the Yale Technology Concordance

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  • Hans van Meijl

Abstract

This paper investigates the impact of direct and indirect R&D on the productivity growth of 30 French industries during the period 1978-92. The main aim of this paper is to assess the appropriateness of the Yale Technology Concordance (YTC) as a proxy for indirect R&D flows. We compare the effect on productivity growth of the Yale proxy with the traditional proxy based on goods input-output flows, and assess their suitability for different groups of industries. Results indicate that the indirect YTC proxy performs slightly better than the traditional proxy, as a result of superior performance in the high-tech and service sectors in particular.

Suggested Citation

  • Hans van Meijl, 1997. "Measuring the Impact of Direct and Indirect R&D on the Productivity Growth of Industries: Using the Yale Technology Concordance," Economic Systems Research, Taylor & Francis Journals, vol. 9(2), pages 205-211.
  • Handle: RePEc:taf:ecsysr:v:9:y:1997:i:2:p:205-211
    DOI: 10.1080/09535319700000014
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    References listed on IDEAS

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    1. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    2. Hans van Meijl, 1997. "Measuring Intersectoral Spillovers: French Evidence," Economic Systems Research, Taylor & Francis Journals, vol. 9(1), pages 25-46.
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    Cited by:

    1. Cerina, Fabio & Mureddu, Francesco, 2014. "Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth," Journal of Urban Economics, Elsevier, vol. 84(C), pages 9-22.
    2. Eduardo Gonçalves & Fernando Salgueiro Perobelli & Inácio Fernandes Araújo, 2017. "Estimating intersectoral technology spillovers for Brazil," The Journal of Technology Transfer, Springer, vol. 42(6), pages 1377-1406, December.
    3. Henryk Gurgul, 2007. "Product-embodied diffusion of innovations in Poland: R&D multiplier analysis," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 1, pages 101-120.
    4. Giorgio Garau & Patrizio Lecca, 2015. "The Impact of Regional R&D Subsidy in a Computable General Equilibrium Model," International Regional Science Review, , vol. 38(4), pages 319-357, October.
    5. Bart Verspagen, 2004. "Structural Change and Technology. A Long View," Revue économique, Presses de Sciences-Po, vol. 55(6), pages 1099-1125.
    6. Zuzana Smeets Kristkova & Cornelis Gardebroek & Michiel van Dijk & Hans van Meijl, 2017. "The impact of R&D on factor-augmenting technical change – an empirical assessment at the sector level," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 385-417, July.
    7. López-Pueyo, Carmen & Barcenilla-Visús, Sara & Sanaú, Jaime, 2008. "International R&D spillovers and manufacturing productivity: A panel data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 19(2), pages 152-172, June.
    8. Petr Hanel & Alain St-Pierre, 2002. "Effects of R & D Spillovers on the Profitability of Firms," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 20(4), pages 305-322, June.
    9. Chanyoung Hong & Jeong-Dong Lee, 2016. "Macroeconomic effects of R&D tax credits on small and medium enterprises," Economic Systems Research, Taylor & Francis Journals, vol. 28(4), pages 467-481, October.
    10. Raquel Ortega-Argilés, 2013. "R&D, knowledge, economic growth and the transatlantic productivity gap," Chapters, in: Frank Giarratani & Geoffrey J.D. Hewings & Philip McCann (ed.), Handbook of Industry Studies and Economic Geography, chapter 11, pages 271-302, Edward Elgar Publishing.

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