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Academic Science, Industrial R&D, and the Growth of Inputs


  • James D Adams
  • Leo Sveikauskas


This paper is a theoretical and empirical investigation of the connection between science, R&D, and the growth of capital. Studies of high technology industries and recent labor studies agree in assigning a large role to science and technology in the growth of human and physical capital, although direct tests of these relationships have not been carried out. This paper builds on the search approach to R&D of Evenson and Kislev (1976) to unravel the complex interactions between science, R&D, and factor markets suggested by these studies. In our theory lagged science increases the returns to R&D, so that scientific advance later feeds into growth of R&D. In turn, product quality improvements and price declines lead to the growth of industry by shifting out new product demand, perhaps at the expense of traditional industries. All this tends to be in favor of the human and physical capital used intensively by high technology industries. This is the source of the factor bias which is implicit in the growth of capital per head. Our empirical work overwhelmingly supports the contention that growth of labor skills and physical capital are linked to science and R&D. It also supports the strong sequencing of events that is a crucial feature of our model, first from science to R&D, and later to output and factor markets.

Suggested Citation

  • James D Adams & Leo Sveikauskas, 1993. "Academic Science, Industrial R&D, and the Growth of Inputs," Working Papers 93-1, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:93-1

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    References listed on IDEAS

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    2. Kevin M. Murphy & Finis Welch, 1992. "The Structure of Wages," The Quarterly Journal of Economics, Oxford University Press, vol. 107(1), pages 285-326.
    3. Gary S. Becker & Kevin M. Murphy, 1994. "The Division of Labor, Coordination Costs, and Knowledge," NBER Chapters,in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education (3rd Edition), pages 299-322 National Bureau of Economic Research, Inc.
    4. D. W. Jorgenson & Z. Griliches, 1967. "The Explanation of Productivity Change," Review of Economic Studies, Oxford University Press, vol. 34(3), pages 249-283.
    5. Jeffrey I. Bernstein & M. Ishaq Nadiri, 1989. "Research and Development and Intra-industry Spillovers: An Empirical Application of Dynamic Duality," Review of Economic Studies, Oxford University Press, vol. 56(2), pages 249-267.
    6. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    7. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    8. Bresnahan, Timothy F & Reiss, Peter C, 1991. "Entry and Competition in Concentrated Markets," Journal of Political Economy, University of Chicago Press, vol. 99(5), pages 977-1009, October.
    9. Timothy Dunne & Mark J. Roberts & Larry Samuelson, 1989. "The Growth and Failure of U. S. Manufacturing Plants," The Quarterly Journal of Economics, Oxford University Press, vol. 104(4), pages 671-698.
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    12. Schmitz, James A, Jr, 1989. "Imitation, Entrepreneurship, and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 721-739, June.
    13. Bartel, Ann P & Lichtenberg, Frank R, 1987. "The Comparative Advantage of Educated Workers in Implementing New Technology," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 1-11, February.
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    Cited by:

    1. James D Adams, 1994. "Recent Twists of the Wage Structure and Technology Diffusion," Working Papers 94-5, Center for Economic Studies, U.S. Census Bureau.
    2. Kauffman, Stuart & Lobo, Jose & Macready, William G., 2000. "Optimal search on a technology landscape," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 141-166, October.
    3. Stuart Kauffman & Jose Lobo & William G. Macready, 1998. "Optimal Search on a Technology Landscape," Research in Economics 98-10-091e, Santa Fe Institute.

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    CES; economic; research; micro; data; microdata; chief; economist;


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