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Who Does R&D and Who Patents?

Author

Listed:
  • John Bound
  • Clint Cummins
  • Zvi Griliches
  • Bronwyn H. Hall
  • Adam B. Jaffe

Abstract

This paper describes the construction of a large panel data set covering about 2600 firms in the U.S. manufacturing sector for up to twenty years which contains annual data on financial variables, employment, research and development expenditures, and aggregate patent applications. This data set is to be used in a larger study of R&D, inventive output and technological change. In the present paper we present preliminary results on the R&D and patenting behavior of the 1976 cross section of these firms. We find an elasticity of R&D with respect to sales of close to unity, with both very small and very large firms being slightly more R&D intensive than average. Because only 60% of the firms report R&D expenditures, we attempt to correct for selectivity bias and find that though the correction is small, it increases the estimated complementarity between capital intensity and R&D intensity. In exploring the relationship of the patenting activity of these firms to their contemporaneous R&D expenditures, we look with some care at the choice of econometric specifications since the discrete nature of the patents variable for our smaller firms may cause difficulties with the conventional log linear model. The choice of specification does indeed make a difference, and the negative binomial model, which is a Poisson-type model with a disturbance, is preferred. Substantively, we find a much larger output of patents per R&D dollar for the small firms, with a decreasing propensity to patent with size of R&D programs throughout the sample. However, this conclusion is highly tentative both because of its sensitivity to specification and choice of sample and also because we expect that errors in variables bias due to our focus on R&D and patent applications in a single year is far worse for the small firms.

Suggested Citation

  • John Bound & Clint Cummins & Zvi Griliches & Bronwyn H. Hall & Adam B. Jaffe, 1982. "Who Does R&D and Who Patents?," NBER Working Papers 0908, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:0908 Note: PR
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    • John Bound & Clint Cummins & Zvi Griliches & Bronwyn H. Hall & Adam B. Jaffe, 1984. "Who Does R&D and Who Patents?," NBER Chapters,in: R&D, Patents, and Productivity, pages 21-54 National Bureau of Economic Research, Inc.

    References listed on IDEAS

    as
    1. Forrest D. Nelson, 1974. "Censored Regression Models with Unobserved Stochastic Censoring Thresholds," NBER Working Papers 0063, National Bureau of Economic Research, Inc.
    2. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    3. Fisher, Franklin M & Temin, Peter, 1973. "Returns to Scale in Research and Development: What Does the Schumpeterian Hypothesis Imply ?," Journal of Political Economy, University of Chicago Press, vol. 81(1), pages 56-70, Jan.-Feb..
    4. William S. Comanor, 1967. "Market Structure, Product Differentiation, and Industrial Research," The Quarterly Journal of Economics, Oxford University Press, vol. 81(4), pages 639-657.
    5. Kamien, Morton I & Schwartz, Nancy L, 1975. "Market Structure and Innovation: A Survey," Journal of Economic Literature, American Economic Association, vol. 13(1), pages 1-37, March.
    6. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    7. Nelson, Forrest D., 1977. "Censored regression models with unobserved, stochastic censoring thresholds," Journal of Econometrics, Elsevier, vol. 6(3), pages 309-327, November.
    8. Pakes, Ariel & Griliches, Zvi, 1980. "Patents and R&D at the firm level: A first report," Economics Letters, Elsevier, vol. 5(4), pages 377-381.
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