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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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  • Shiferaw Gurmu

    ()

  • Fidel Pérez-Sebastián

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.

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 35 (2008)
Issue (Month): 3 (November)
Pages: 507-526

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Handle: RePEc:spr:empeco:v:35:y:2008:i:3:p:507-526

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Keywords: Innovative activity; Patents and R&D; Individual effects; Count panel data methods; C20; O30;

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References

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  1. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
  2. 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.
  3. Ariel Pakes & Zvi Griliches, 1984. "Patents and R&D at the Firm Level: A First Look," NBER Chapters, in: R & D, Patents, and Productivity, pages 55-72 National Bureau of Economic Research, Inc.
  4. 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.
  5. 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.
  6. Richard Blundell & Rachel Griffith & Frank Windmeijer, 1999. "Individual effects and dynamics in count data models," IFS Working Papers W99/03, Institute for Fiscal Studies.
  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.
  8. 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.
  9. Zvi Griliches, 1990. "Patent Statistics as Economic Indicators: A Survey," NBER Working Papers 3301, National Bureau of Economic Research, Inc.
  10. Gurmu, Shiferaw & Rilstone, Paul & Stern, Steven, 1998. "Semiparametric estimation of count regression models1," Journal of Econometrics, Elsevier, vol. 88(1), pages 123-150, November.
  11. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  12. 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.
  13. Wooldridge, Jeffrey M., 1997. "Multiplicative Panel Data Models Without the Strict Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 13(05), pages 667-678, October.
  14. Ariel Pakes & Zvi Griliches, 1980. "Patents and R and D at the Firm Level: A First Look," NBER Working Papers 0561, National Bureau of Economic Research, Inc.
  15. repec:cup:etheor:v:13:y:1997:i:5:p:667-78 is not listed on IDEAS
  16. repec:fth:harver:1473 is not listed on IDEAS
  17. 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.
  18. 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.
  19. 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, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  20. Acs, Zoltan J & Audretsch, David B, 1989. "Patents as a Measure of Innovative Activity," Kyklos, Wiley Blackwell, vol. 42(2), pages 171-80.
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Cited by:
  1. Gallié, Emilie-Pauline & Legros, Diego, 2012. "Firms’ human capital, R&D and innovation: a study on French firms," Economics Papers from University Paris Dauphine 123456789/6962, Paris Dauphine University.
  2. Yoshitsugu Kitazawa, 2012. "An improved theoretical ground for the linear feedback model and a new indicator," Discussion Papers 58, Kyushu Sangyo University, Faculty of Economics.
  3. Hagedoorn, John & Wang, Ning, 2010. "Is there complementarity or substitutability between internal and external R&D strategies?," MERIT Working Papers 005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  4. Qiang Liang & Xinchun Li & Xueru Yang & Danming Lin & Danhui Zheng, 2013. "How does family involvement affect innovation in China?," Asia Pacific Journal of Management, Springer, vol. 30(3), pages 677-695, September.
  5. Hagedoorn, John & Wang, Ning, 2012. "Is there complementarity or substitutability between internal and external R&D strategies?," Research Policy, Elsevier, vol. 41(6), pages 1072-1083.

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