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Patents and R&D: Is There A Lag?

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  • Bronwyn H. Hall
  • Zvi Griliches
  • Jerry A. Hausman

Abstract

This paper extends earlier work on the RID to patents relationship (Pakes-Griliches 1980, and Hausman, Hall, and Griliches,1984) to a larger but shorter panel of firms. The focus of the paper is on solving a number of econometric problems associated with the discreteness of the dependent variable and the shortness of the panel in the time dimension. We compare weighted nonlinear least squares as wellas Poisson-type models as solutions to the former problem. In attempting to estimate a lag structure on R&D in the absence of a sufficient history of the variable, we take two approaches: first, we use the conditional version of the negative binomial model, and second, we estimate the R&D variable itself as a low order stochastic process and use this information to control for unobserved R&D. R&D itself turns out to befairly well approximated by a random walk. Neither approach yields strong evidence of a long lag. The available sample, though numerically large, turns out not to be particularily informative on this question. It does reconfirm, however, a significant effect of R&D on patenting (with most of it occuring in the first year) and the presence of rather wide and semi-permanent differences among firms in their patenting policies.

Suggested Citation

  • Bronwyn H. Hall & Zvi Griliches & Jerry A. Hausman, 1984. "Patents and R&D: Is There A Lag?," NBER Working Papers 1454, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:1454
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    References listed on IDEAS

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    1. Alok Bhargava & J. D. Sargan, 2006. "Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods," World Scientific Book Chapters,in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 1, pages 3-27 World Scientific Publishing Co. Pte. Ltd..
    2. White, Halbert, 1982. "Instrumental Variables Regression with Independent Observations," Econometrica, Econometric Society, vol. 50(2), pages 483-499, March.
    3. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    4. 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.
    5. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
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