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The hidden costs of R&D collaboration

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Abstract

The paper investigates the barriers to collaboration in terms of hidden transaction costs, by deriving the distribution of the operating costs and sunk costs associated with firms investment choices in R&D and innovation activities with or without a research partner. To retrieve both fixed and sunk costs of R&D and innovation activities with or without a research partner, we develop and estimate a structural dynamic monopoly model to quantify the linkages between R&D spending, innovation and cooperation investment choices, and endogenous productivity. We find that the sunk costs of innovations are smaller when collaborating with a research partner; the probability to spend in R&D or to innovate increases with the level of productivity, when collaborating in R&D and innovation; finally, we find that the sunk costs of innovation are 1.5 to 3 times smaller than the sunk costs of R&D. Additionally, the suggested structural framework of firm heterogeneity in cost functions offers a straightforward extension to policy impact evaluation.

Suggested Citation

  • Sara Amoroso, 2014. "The hidden costs of R&D collaboration," JRC Working Papers on Corporate R&D and Innovation 2014-02, Joint Research Centre (Seville site).
  • Handle: RePEc:ipt:wpaper:201402
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    File URL: https://iri.jrc.ec.europa.eu/documents/10180/1eaedd9e-08e8-4826-96cb-4c40c850bf70
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    1. Ariel Pakes & Michael Ostrovsky & Steven Berry, 2007. "Simple estimators for the parameters of discrete dynamic games (with entry/exit examples)," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 373-399, June.
    2. Bee Yan Aw & Mark J. Roberts & Daniel Yi Xu, 2011. "R&D Investment, Exporting, and Productivity Dynamics," American Economic Review, American Economic Association, vol. 101(4), pages 1312-1344, June.
    3. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    4. Susumu Imai & Neelam Jain & Andrew Ching, 2009. "Bayesian Estimation of Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 77(6), pages 1865-1899, November.
    5. Lopez, Alberto, 2008. "Determinants of R&D cooperation: Evidence from Spanish manufacturing firms," International Journal of Industrial Organization, Elsevier, vol. 26(1), pages 113-136, January.
    6. Griliches, Zvi, 1980. "R & D and the Productivity Slowdown," American Economic Review, American Economic Association, vol. 70(2), pages 343-348, May.
    7. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    8. Patrick Bajari & C. Lanier Benkard & Jonathan Levin, 2007. "Estimating Dynamic Models of Imperfect Competition," Econometrica, Econometric Society, vol. 75(5), pages 1331-1370, September.
    9. Carboni, Oliviero A., 2012. "An empirical investigation of the determinants of R&D cooperation: An application of the inverse hyperbolic sine transformation," Research in Economics, Elsevier, vol. 66(2), pages 131-141.
    10. Sabien Dobbelaere & Jacques Mairesse, 2013. "Panel data estimates of the production function and product and labor market imperfections," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 1-46, January.
    11. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    12. Thierry Magnac & David Thesmar, 2002. "Identifying Dynamic Discrete Decision Processes," Econometrica, Econometric Society, vol. 70(2), pages 801-816, March.
    13. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 497-529.
    14. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    15. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    16. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    17. Christoph Grimpe & Ulrich Kaiser, 2010. "Balancing Internal and External Knowledge Acquisition: The Gains and Pains from R&D Outsourcing," Journal of Management Studies, Wiley Blackwell, vol. 47(8), pages 1483-1509, December.
    18. Peters, Bettina & Roberts, Mark J. & Vuong, Van Anh & Fryges, Helmut, 2013. "Estimating dynamic R&D demand: An analysis of costs and long-run benefits," ZEW Discussion Papers 13-089, ZEW - Leibniz Centre for European Economic Research.
    19. Filip Abraham & Jozef Konings & Stijn Vanormelingen, 2009. "The effect of globalization on union bargaining and price-cost margins of firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(1), pages 13-36, April.
    20. Dobbelaere, Sabien, 2004. "Estimation of price-cost margins and union bargaining power for Belgian manufacturing," International Journal of Industrial Organization, Elsevier, vol. 22(10), pages 1381-1398, December.
    21. Ackerberg, Daniel & Lanier Benkard, C. & Berry, Steven & Pakes, Ariel, 2007. "Econometric Tools for Analyzing Market Outcomes," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 63, Elsevier.
    22. Carlos Daniel Santos, 2009. "Recovering the Sunk Costs of R&D: the Moulds Industry Case," CEP Discussion Papers dp0958, Centre for Economic Performance, LSE.
    23. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," Review of Economic Studies, Oxford University Press, vol. 62(1), pages 53-82.
    24. Belderbos, Rene & Carree, Martin & Diederen, Bert & Lokshin, Boris & Veugelers, Reinhilde, 2004. "Heterogeneity in R&D cooperation strategies," International Journal of Industrial Organization, Elsevier, vol. 22(8-9), pages 1237-1263, November.
    25. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
    26. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    27. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    28. X. Henry Wang & Bill Z. Yang, 2001. "Fixed and Sunk Costs Revisited," The Journal of Economic Education, Taylor & Francis Journals, vol. 32(2), pages 178-185, January.
    29. Hopenhayn, Hugo A, 1992. "Entry, Exit, and Firm Dynamics in Long Run Equilibrium," Econometrica, Econometric Society, vol. 60(5), pages 1127-1150, September.
    30. Andriy Norets, 2009. "Inference in Dynamic Discrete Choice Models With Serially orrelated Unobserved State Variables," Econometrica, Econometric Society, vol. 77(5), pages 1665-1682, September.
    31. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
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    2. Spanos, Yiannis E., 2021. "Exploring heterogeneous returns to collaborative R&D: A marginal treatment effects perspective," Research Policy, Elsevier, vol. 50(5).

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    More about this item

    Keywords

    R&D cooperation; transaction costs; dynamic structural model.;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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