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A Schumpeter-inspired approach to the construction of R&D capital stocks

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  • Jurgen Bitzer
  • Andreas Stephan

Abstract

A new method for constructing R&D capital stocks is proposed and tested. Following Schumpeter, the development of R&D capital stocks is modelled as a process of creative destruction. Newly generated knowledge is assumed not only to add to the existing R&D capital stocks but also, by displacing old knowledge, to destroy part of that capital. This is in stark contrast to the perpetual inventory method, which postulates a constant rate of depreciation. We compare both methods by estimating the impact of R&D and spillovers on output of 9 industries in 12 OECD countries, and find that the new approach leads to more sensible and robust results.

Suggested Citation

  • Jurgen Bitzer & Andreas Stephan, 2007. "A Schumpeter-inspired approach to the construction of R&D capital stocks," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 179-189.
    • Handle: RePEc:taf:applec:v:39:y:2007:i:2:p:179-189
    DOI: 10.1080/00036840500427973
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    Cited by:

    1. Robert Wieser, 2005. "Research And Development Productivity And Spillovers: Empirical Evidence At The Firm Level," Journal of Economic Surveys, Wiley Blackwell, vol. 19(4), pages 587-621, September.
    2. Wong, Siang Leng & Chang, Youngho & Chia, Wai-Mun, 2013. "Energy consumption, energy R&D and real GDP in OECD countries with and without oil reserves," Energy Economics, Elsevier, vol. 40(C), pages 51-60.
    3. Fabio Montobbio & Valerio Sterzi, 2011. "Inventing together: exploring the nature of international knowledge spillovers in Latin America," Journal of Evolutionary Economics, Springer, vol. 21(1), pages 53-89, February.
    4. Alexandre Almeida & Aurora A.C. Teixeira, 2007. "Does Patenting negatively impact on R&D investment?An international panel data assessment," FEP Working Papers 255, Universidade do Porto, Faculdade de Economia do Porto.
    5. Bastian Rake, 2017. "Determinants of pharmaceutical innovation: the role of technological opportunities revisited," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 691-727, September.
    6. 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.
    7. Asim, Aysha & Ismail, Aisha, 2019. "Impact of Leverage on Earning Management: Empirical Evidence from the Manufacturing Sector of Pakistan," Journal of Finance and Accounting Research, University of Management and Technology, Lahore, vol. 1(1), pages 70-91, February.
    8. Pedro Mazeda Gil & Oscar Afonso, 2011. "Technological-knowledge dynamics in lab-equipment models of quality ladders," Applied Economics Letters, Taylor & Francis Journals, vol. 18(4), pages 333-336.
    9. Hall, Bronwyn H. & Mairesse, Jacques & Mohnen, Pierre, 2010. "Measuring the Returns to R&D," 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 1033-1082, Elsevier.
    10. Leng Wong, Siang & Chia, Wai-Mun & Chang, Youngho, 2013. "Energy consumption and energy R&D in OECD: Perspectives from oil prices and economic growth," Energy Policy, Elsevier, vol. 62(C), pages 1581-1590.
    11. Mason-D'Croz, Daniel & Sulser, Timothy B. & Wiebe, Keith & Rosegrant, Mark W. & Lowder, Sarah K. & Nin-Pratt, Alejandro & Willenbockel, Dirk & Robinson, Sherman & Zhu, Tingju & Cenacchi, Nicola & Duns, 2019. "Agricultural investments and hunger in Africa modeling potential contributions to SDG2 – Zero Hunger," World Development, Elsevier, vol. 116(C), pages 38-53.
    12. Almas Heshmati, 2003. "Productivity Growth, Efficiency and Outsourcing in Manufacturing and Service Industries," Journal of Economic Surveys, Wiley Blackwell, vol. 17(1), pages 79-112, February.

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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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