IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/6099.html
   My bibliography  Save this paper

The Structure of Firm R&D and the Factor Intensity of Production

Author

Listed:
  • James D. Adams

Abstract

This paper studies the influence of the structure of firm R&D, industry R&D spillovers, and plant level physical capital on the factor intensity of production. By the structure of firm R&D we mena its distribution across states and products. By factor intensity we mena the cost shares of variable factors, which in this paper are blue collar labor, white collarlabor, and materials. We characterize the effect of the structure of firm R&D on factor intensity using a Translog cost function with quasi-fixed factors. This cost function gives rise to a system of variable cost shares that depends on factor prices, firm and industry R&D, and physical capital. The paper turns to estimation of this system using a sample of plants owned by chemical firms. We find that total firm R&D, industry R&D spillovers, and plant level physical capital are factor biased towards labor as a whole, and factor saving in materials. None of these three factors consistently increase the factor intensity of white collar workers relative to blue collar workers. Since white collar workers are the more skilled of the two grades of labor, none of these factors is strongly associated with skill bias. When we turn to the structure of firm R&D, we find that the strongest effect of firm R&D on the factor intensity of white collar workers occurs when the R&D is conducted in the same product area as the plant. Indeed, the skill bias effect of firm R&D in the same product dominates all other variables, implying that skill bias is technologically 'localized' within firms. All told, the findings suggest that skill bias is governed by portions of the firm's R&D program that are targeted on articular plants, rather than transmitted through capital or by general firm and industry know-how.

Suggested Citation

  • James D. Adams, 1997. "The Structure of Firm R&D and the Factor Intensity of Production," NBER Working Papers 6099, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:6099 Note: PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w6099.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
    4. Jacques Mairesse & Bronwyn H. Hall, 1996. "Estimating the Productivity of Research and Development: An Exploration of GMM Methods Using Data on French & United States Manufacturing Firms," NBER Working Papers 5501, National Bureau of Economic Research, Inc.
    5. Griliches, Zvi, 1969. "Capital-Skill Complementarity," The Review of Economics and Statistics, MIT Press, vol. 51(4), pages 465-468, November.
    6. Eli Berman & John Bound & Zvi Griliches, 1993. "Changes in the Demand for Skilled Labor within U.S. Manufacturing Industries: Evidence from the Annual Survey of Manufacturing," NBER Working Papers 4255, National Bureau of Economic Research, Inc.
    7. Tor Jakob Klette, 1996. "R&D, Scope Economies, and Plant Performance," RAND Journal of Economics, The RAND Corporation, vol. 27(3), pages 502-522, Autumn.
    8. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
    9. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
    10. Boozer, Michael A., 1997. "Econometric Analysis of Panel Data Badi H. Baltagi Wiley, 1995," Econometric Theory, Cambridge University Press, vol. 13(05), pages 747-754, October.
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gray, Richard S. & Malla, Stavroula & Tran, Kien C., 2003. "An Empirical Analysis Of Public And Private Spillovers Within The Canola Biotech Industry," 2003 Annual meeting, July 27-30, Montreal, Canada 22137, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Piva, Mariacristina & Santarelli, Enrico & Vivarelli, Marco, 2005. "The skill bias effect of technological and organisational change: Evidence and policy implications," Research Policy, Elsevier, vol. 34(2), pages 141-157, March.
    3. TESTE, Thierry, 1999. "Technologies de l'information et de la communication : Approches économètriques sur le paradoxe de productivité," LATEC - Document de travail - Economie (1991-2003) 1999-06, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    4. Lucy Chennells & John Van Reenen, 1999. "Has technology hurt less skilled workers? A survey of the micro-econometric evidence," IFS Working Papers W99/27, Institute for Fiscal Studies.
    5. Guido Friebel & Gerard McCullough & Laura Padilla Angulo, 2014. "Patterns of Restructuring The US Class 1 Railroads from 1984 to 2004," Journal of Transport Economics and Policy, University of Bath, vol. 48(1), pages 115-135, January.
    6. Ljubica Nedelkoska & Simon Wiederhold, 2010. "Technology, outsourcing, and the demand for heterogeneous labor: Exploring the industry dimension," Jena Economic Research Papers 2010-052, Friedrich-Schiller-University Jena.
    7. Hollanders, Hugo & ter Weel, Bas, 2002. "Technology, knowledge spillovers and changes in employment structure: evidence from six OECD countries," Labour Economics, Elsevier, vol. 9(5), pages 579-599, November.
    8. Harabi, Najib, 2000. "Employment Effects of Ecological Innovations: An Empirical Analysis," MPRA Paper 4395, University Library of Munich, Germany.
    9. K. Raabe & I. Arnold & C.J.M. Kool, 2006. "Firm Size and Monetary Policy Transmission: A Theoretical Model on the Role of Capital Investment Expenditures," Working Papers 06-14, Utrecht School of Economics.
    10. Lucia Foster & Cheryl Grim, 2010. "Characteristics of the Top R&D Performing Firms in the U.S.: Evidence from the Survey of Industrial R&D," Working Papers 10-33, Center for Economic Studies, U.S. Census Bureau.

    More about this item

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:6099. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.