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Knowledge Spillovers and their Impact on Innovation Success - A New Approach Using Patent Backward Citations

We propose a new patent-based measure of knowledge spillovers that calculates technological proximity based on firms that were identified via patent backward citations links. We argue that this measure has a couple of advantages as compared to the 'standard' measure proposed by Jaffe: First, it reflects spillovers from both domestic and foreign technologically 'relevant' firms, second, it is more precise because it only takes into account knowledge relations with technologically 'relevant' firms. Our empirical results indeed show that the measure performs better than the standard measure in an innovation model. We find - for a representative sample of Swiss firms - that knowledge spillovers measured in this way have a positive and significant impact on innovation success. However, the knowledge spillovers appear to be localized: Spillovers from geographically distant areas such as the USA and Japan matter less than spillovers from near destinations such as Europe and particularly Switzerland itself. Moreover, the spillover effect on innovation performance decreases with increasing number of competitors on the main product market so that this effect would appear only in niche markets or oligopolistic market structures. However, an additional effect of competition can only be detected for more radical innovation success.

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File URL: http://dx.doi.org/10.3929/ethz-a-010737115
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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 16-414.

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Length: 46 pages
Date of creation: Oct 2016
Handle: RePEc:kof:wpskof:16-414
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  1. Li, Yao Amber, 2014. "Borders and distance in knowledge spillovers: Dying over time or dying with age?—Evidence from patent citations," European Economic Review, Elsevier, vol. 71(C), pages 152-172.
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  3. Paola Cardamone, 2010. "The role of R&D spillovers in product and process innovation," Applied Economics Letters, Taylor & Francis Journals, vol. 17(5), pages 483-493.
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  5. Yasusada Murata & Ryo Nakajima & Ryosuke Okamoto & Ryuichi Tamura, 2014. "Localized Knowledge Spillovers and Patent Citations: A Distance-Based Approach," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 967-985, December.
  6. Emmanuel Duguet & Megan MacGarvie, 2005. "How well do patent citations measure flows of technology? Evidence from French innovation surveys," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(5), pages 375-393.
  7. Criscuolo, Paola & Verspagen, Bart, 2008. "Does it matter where patent citations come from? Inventor vs. examiner citations in European patents," Research Policy, Elsevier, vol. 37(10), pages 1892-1908, December.
  8. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, July.
  9. de Rassenfosse, Gaétan & Dernis, Hélène & Guellec, Dominique & Picci, Lucio & van Pottelsberghe de la Potterie, Bruno, 2013. "The worldwide count of priority patents: A new indicator of inventive activity," Research Policy, Elsevier, vol. 42(3), pages 720-737.
  10. Lybbert, Travis J. & Zolas, Nikolas J., 2014. "Getting patents and economic data to speak to each other: An ‘Algorithmic Links with Probabilities’ approach for joint analyses of patenting and economic activity," Research Policy, Elsevier, vol. 43(3), pages 530-542.
  11. Ariél Pakes & Zvi Griliches, 1984. "Estimating Distributed Lags in Short Panels with an Application to the Specification of Depreciation Patterns and Capital Stock Constructs," Review of Economic Studies, Oxford University Press, vol. 51(2), pages 243-262.
  12. Ramani, Shyama V. & El-Aroui, Mhamed-Ali & Carrère, Myriam, 2008. "On estimating a knowledge production function at the firm and sector level using patent statistics," Research Policy, Elsevier, vol. 37(9), pages 1568-1578, October.
  13. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
  14. Uwe Jirjahn & Kornelius Kraft, 2011. "Do Spillovers Stimulate Incremental or Drastic Product Innovations? Evidence from German Establishment Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 509-538, 08.
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