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Patents, R&D And Lag Effects: Evidence From Flexible Methods For Count Panel Data On Manufacturing Firms

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Author Info
Fidel Pérez Sebastián () (Universidad de Alicante)
Shiferaw Gurmu () (Georgia State University)
Abstract

Hausman, Hall and Griliches (1984) and Hall, Griliches and Hausman (1986) investigated whether there was a lag in the patent-R&D relationship for the U.S. manufacturing sector using 1970¿s data. They found that there was little evidence of anything but contemporaneous movement of patents and R&D. We reexamine this important issue employing new longitudinal patent data at the firm level for the U.S. manufacturing sector from 1982 to 1992. To address unique features of the data, we estimate various distributed lag and dynamic multiplicative panel count data models. The paper also develops a new class of count panel data models based on series expansion of the distribution of individual effects. The empirical analyses show that, although results are somewhat sensitive to different estimation methods, the contemporaneous relationship between patenting and R&D expenditures continues to be rather strong, accounting for over 60% of the total R&D elasticity. Regarding the lag structure of the patents-R&D relationship, we do find a significant lag in all empirical specifications. Moreover, the estimated lag effects are higher than have previously been found, suggesting that the contribution of R&D history to current patenting has increased from the 1970¿s to the 1980¿s.

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Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2007-03.

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Length: 32 pages
Date of creation: Mar 2007
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Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2007-03

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Keywords: Innovative activity Patents and R&D Individual effects count panel data methods.

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Find related papers by JEL classification:
C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General

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  1. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Blackwell Publishing, vol. 58(2), pages 277-97, April. [Downloadable!] (restricted)
  2. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December. [Downloadable!] (restricted)
    Other versions:
  3. Wang, Peiming & Cockburn, Iain M & Puterman, Martin L, 1998. "Analysis of Patent Data--A Mixed-Poisson-Regression-Model Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 27-41, January.
  4. Blundell, Richard & Griffith, Rachel & Van Reenen, John, 1995. "Dynamic Count Data Models of Technological Innovation," Economic Journal, Royal Economic Society, vol. 105(429), pages 333-44, March. [Downloadable!] (restricted)
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  5. Bronwyn H. Hall & Zvi Griliches & Jerry A. Hausman, 1986. "Patents and R&D: Is There A Lag?," NBER Working Papers 1454, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  6. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March. [Downloadable!] (restricted)
  7. Frank Windmeijer, 2002. "ExpEnd, A Gauss programme for non-linear GMM estimation of exponential models with endogenous regressors for cross section and panel data," CeMMAP working papers CWP14/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  8. Crepon, Bruno & Duguet, Emmanuel, 1997. "Estimating the Innovation Function from Patent Numbers: GMM on Count Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 243-63, May-June. [Downloadable!]
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  9. repec:fth:harver:1473 is not listed on IDEAS
  10. repec:cup:etheor:v:13:y:1997:i:5:p:667-78 is not listed on IDEAS
  11. Guo, Jie Q & Trivedi, Pravin K, 2002. " Flexible Parametric Models for Long-Tailed Patent Count Distributions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(1), pages 63-82, February. [Downloadable!] (restricted)
  12. Montalvo, Jose G, 1997. "GMM Estimation of Count-Panel-Data Models with Fixed Effects and Predetermined Instruments," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 82-89, January.
  13. Gurmu, Shiferaw & Rilstone, Paul & Stern, Steven, 1998. "Semiparametric estimation of count regression models1," Journal of Econometrics, Elsevier, vol. 88(1), pages 123-150, November. [Downloadable!] (restricted)
  14. Acs, Zoltan J & Audretsch, David B, 1989. "Patents as a Measure of Innovative Activity," Kyklos, Blackwell Publishing, vol. 42(2), pages 171-80.
  15. Richard Blundell & Rachel Griffith & Frank Windmeijer, 1999. "Individual effects and dynamics in count data models," IFS Working Papers W99/03, Institute for Fiscal Studies. [Downloadable!]
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