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Research and Productivity


  • Boyan Jovanovic
  • Yaw Nyarko


We model research as a signal on an unknown parameter of a technology. We distinguish applied from basic research and show that firms in the same industry can optimally choose different research portfolios, and that basic research can seem to have a higher rate of return than applied research, even though it really doesn't -- essentially, firms on a 'fast track' upgrading policy opt for basic research but fast and slow-track upgrading policies can coexist in a long-run equilibrium. We also derive the lag structure for how R&D affects the firm's stock of knowledge. To a first approximation, the lags decay geometrically (as is typically assumed in practice) but the rate of decay is endogenous, and depends on how fast the firm is upgrading its technology.

Suggested Citation

  • Boyan Jovanovic & Yaw Nyarko, 1995. "Research and Productivity," NBER Working Papers 5321, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:5321
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    References listed on IDEAS

    1. Bronwyn H. Hall, 1990. "The Impact of Corporate Restructuring on Industrial Research and Development," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 21(1990 Micr), pages 85-135.
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    4. Mansfield, Edwin, 1980. "Basic Research and Productivity Increase in Manufacturing," American Economic Review, American Economic Association, vol. 70(5), pages 863-873, December.
    5. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    6. Ricardo J. Caballero & Adam B. Jaffe, 1993. "How High are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth," NBER Chapters,in: NBER Macroeconomics Annual 1993, Volume 8, pages 15-86 National Bureau of Economic Research, Inc.
    7. Pakes, Ariel & Schankerman, Mark A., 1978. "The Rate of Obsolescence of Knowledge, Research Gestation Labs, and the Private Rate of Return to Research Resources," Working Papers 78-13, C.V. Starr Center for Applied Economics, New York University.
    8. Stephen D. Oliner, 1993. "New evidence on the retirement and depreciation of machine tools," Working Paper Series / Economic Activity Section 147, Board of Governors of the Federal Reserve System (U.S.).
    9. Bahk, Byong-Hong & Gort, Michael, 1993. "Decomposing Learning by Doing in New Plants," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 561-583, August.
    10. Link, Albert N, 1981. "Basic Research and Productivity Increase in Manufacturing: Additional Evidence," American Economic Review, American Economic Association, vol. 71(5), pages 1111-1112, December.
    11. Manuel Trajtenberg & Rebecca Henderson & Adam Jaffe, 1992. "Ivory Tower Versus Corporate Lab: An Empirical Study of Basic Research and Appropriability," NBER Working Papers 4146, National Bureau of Economic Research, Inc.
    12. Lichtenberg, Frank R & Siegel, Donald, 1991. "The Impact of R&D Investment on Productivity--New Evidence Using Linked R&D-LRD Data," Economic Inquiry, Western Economic Association International, vol. 29(2), pages 203-229, April.
    13. Hulten, Charles R. & Wykoff, Frank C., 1981. "The estimation of economic depreciation using vintage asset prices : An application of the Box-Cox power transformation," Journal of Econometrics, Elsevier, vol. 15(3), pages 367-396, April.
    14. Adams, James D, 1990. "Fundamental Stocks of Knowledge and Productivity Growth," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 673-702, August.
    15. Doms, Mark & Dunne, Timothy & Roberts, Mark J., 1995. "The role of technology use in the survival and growth of manufacturing plants," International Journal of Industrial Organization, Elsevier, vol. 13(4), pages 523-542, December.
    16. Ariel Pakes & Mark Schankerman, 1984. "The Rate of Obsolescence of Patents, Research Gestation Lags, and the Private Rate of Return to Research Resources," NBER Chapters,in: R&D, Patents, and Productivity, pages 73-88 National Bureau of Economic Research, Inc.
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    Cited by:

    1. Wang, Eric C., 2010. "Determinants of R&D investment: The Extreme-Bounds-Analysis approach applied to 26 OECD countries," Research Policy, Elsevier, vol. 39(1), pages 103-116, February.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General


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