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R&D and productivity: evidence from large UK establishments with substantial R&D activities

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  • Stephen R. Bond
  • Irem Guceri

Abstract

We use Office for National Statistics' micro data for large UK establishments in the production industries in the period 1997–2008 to study the relationship between their productivity and the presence of substantial R&D activities, either at the production unit itself, or at other UK reporting units owned by the same enterprise group. We estimate that total factor (revenue) productivity is on average about 14% higher at the establishments which have substantial R&D themselves, compared to those with no R&D. Among the establishments with no R&D themselves, we estimate that productivity is on average about 9% higher at those which belong to enterprise groups which do have substantial R&D elsewhere in the UK in the same sub-sector. For the establishments with substantial R&D themselves, we also estimate a significant positive relationship between current productivity and past R&D expenditure using dynamic specifications which allow for both establishment-specific ‘fixed effects’ and a serially correlated error component.

Suggested Citation

  • Stephen R. Bond & Irem Guceri, 2017. "R&D and productivity: evidence from large UK establishments with substantial R&D activities," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(1-2), pages 108-120, February.
    • Handle: RePEc:taf:ecinnt:v:26:y:2017:i:1-2:p:108-120
    DOI: 10.1080/10438599.2016.1203525
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    1. Crepon, B. & Duguet, E. & Mairesse, J., 1998. "Research Investment, Innovation and Productivity: An Econometric Analysis at the Firm Level," Papiers d'Economie Mathématique et Applications 98.15, Université Panthéon-Sorbonne (Paris 1).
    2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    3. Richard Harris & John Moffat, 2015. "Plant-level determinants of total factor productivity in Great Britain, 1997–2008," Journal of Productivity Analysis, Springer, vol. 44(1), pages 1-20, August.
    4. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    5. Schankerman, Mark, 1981. "The Effects of Double-Counting and Expensing on the Measured Returns to R&D," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 454-458, August.
    6. Bronwyn H. Hall & Nathan Rosenberg (ed.), 2010. "Handbook of the Economics of Innovation," Handbook of the Economics of Innovation, Elsevier, edition 1, volume 1, number 1.
    7. Bruno Crepon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation And Productivity: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
    8. James D. Adams & Adam B. Jaffe, 1996. "Bounding the Effects of R&D: An Investigation Using Matched Establishment-Firm Data," RAND Journal of Economics, The RAND Corporation, vol. 27(4), pages 700-721, Winter.
    9. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    11. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    12. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
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