The Journal of Technology Transfer

, Volume 44, Issue 6, pp 1720–1743 | Cite as

R&D funding and private R&D: empirical evidence on the impact of the leading-edge cluster competition

  • Dirk Engel
  • Verena Eckl
  • Michael RothgangEmail author


This paper analyzes the effects of the governmental financing instrument Spitzencluster-Wettbewerb (Leading-Edge Cluster Competition, LECC) on R&D expenditure of firms in Germany. The LECC promotes cooperative research among business firms and research institutions under the umbrella of a common strategy, which is pursued by regional cluster organizations. We measure the effect of LECC funding on private R&D spending as well as the effects of the policy instrument on the composition of R&D (internal vs. external). Our analysis is mainly based on data from the R&D survey for Germany. We combine propensity score matching (to identify statistical twins) with a difference-in-differences estimator in order to measure the causal effects of the LECC. These results are complemented with the findings from expert interviews. Our results show that the LECC significantly increases R&D expenditures in comparison to non-funded firms. On average, we did not find evidence of crowding out. At the same time, we identified a greater leverage effect of the LECC for small and medium-sized firms. A comparison with companies that have been funded in other R&D-programs shows that the LECC leads to a greater increase in R&D expenditure in small and medium-sized enterprises (SMEs). The expert interviews in general confirm these results and indicate that there are different patterns at firm level depending on firm size, strategy, and sector. In addition, they reveal that the effect of co-funding rules for R&D expenditure appears to be stronger for SMEs.


R&D Public subsidies Collaboration Policy evaluation 

JEL Classification

C14 C25 H50 O38 


  1. Acs, Z., Audretsch, D., & Feldman, M. (1994). R&D spillovers and recipient firm size. Review of Economics and Statistics,76(2), 336–340.CrossRefGoogle Scholar
  2. Akhilesh, R. B. (2014). R&D Management. New Delhi: Springer.CrossRefGoogle Scholar
  3. Ali-Yrkkö, J. (2005). Impact of Public R&D Financing on private R&D. Does financial constrain matter? Working Paper No. 30, ENEPRI, Brussels.Google Scholar
  4. Almus, M., & Czarnitzki, D. (2003). The effects of public R&D subsidies on firms’ innovation activities: The case of Eastern Germany. Journal of Business and Economic Statistics,21(2), 226–236.CrossRefGoogle Scholar
  5. Artz, K. W., Norman, P. M., Hatfield, D. E., & Cardinal, L. B. (2010). A longitudinal study of the impact of R&D, patents, and product innovation on firm performance. Journal of Product Innovation Management,27(5), 725–740.CrossRefGoogle Scholar
  6. Aschhoff, B. (2009). The effect of subsidies on R&D investment and success—Do subsidy history and size matter?, ZEW Discussion Paper No. 09-032, Mannheim.Google Scholar
  7. Aschhoff, B., Astor, M., Crass, D., Eckert, T., Heinrich, S., Licht, G., Rammer, C., Riesenberg, D., Rüffer, N., Strohmeyer, R., Tonoyan, V., Woywode, M. (2012). Systemevaluierung “KMU-innovativ”, ZEW Dokumentation Nr. 12-04, Mannheim.Google Scholar
  8. Audretsch, D., & Feldman, M. P. (1996). R&D spillovers and the geography of innovation and production. American Economic Review,86(3), 630–640.Google Scholar
  9. Austin, P. C. (2011). Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharmaceutical Statistics,10(2), 150–161. doi: 10.1002/pst.433.CrossRefGoogle Scholar
  10. Blundell, R., & Costa Dias, M. (2000). Evaluation methods for non-experimental data. Fiscal Studies,21(4), 427–468.CrossRefGoogle Scholar
  11. Brockhoff, K. (1999). Forschung und Entwicklung. Planung und Kontrolle. Munich: Oldenbourg.CrossRefGoogle Scholar
  12. Broekel, T., Fornahl, D., & Morrison, A. (2015). Another cluster premium: Innovation subsidies and R&D collaboration networks. Research Policy,44(2015), 1431–1444.CrossRefGoogle Scholar
  13. Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys,22(1), 31–72.CrossRefGoogle Scholar
  14. Cassiman, B., & Veugelers, R. (2006). In search of complementarity in innovation strategy: internal R&D and external knowledge acquisition. Management Science,52, 68–82.CrossRefGoogle Scholar
  15. Cohen, W. (1995). Empirical studies of innovative activity. In P. Stoneman (Ed.), Handbook of the Economics of Innovation and Technical Change ch 6. Oxford: Basil.Google Scholar
  16. Czarnitzki, D., Ebersberger, B., & Fier, A. (2007). The relationship between R&D collaboration, subsidies and R&D performance: Empirical evidence from Finland and Germany. Journal of Applied Econometrics,22(7), 1347–1366.CrossRefGoogle Scholar
  17. Czarnitzki, D., & Fier, A. (2002). Do innovation subsidies crowd out private investment? Evidence from the German service sector. Konjunkturpolitik—Applied Economics Quarterly,48, 1–25.Google Scholar
  18. DAMVAD (2011). The impact of innovation networks in denmark—an impact study on behaviour and possible economical effects, Project report. Kopenhagen.Google Scholar
  19. David, P. A., Hall, B. H., & Toole, A. A. (2000). Is public R&D a complement or a substitute for private R&D? Research Policy,29, 497–529.CrossRefGoogle Scholar
  20. Duguet, E. (2004). Are R&D subsidies a substitute or a complement to privately funded R&D? An econometric analysis at the firm level. Revue d’économie politique,114(2), 245–274.CrossRefGoogle Scholar
  21. EIRMA (1983). How much R&D? Working group report 28, Paris.Google Scholar
  22. Engel, D., Mitze, T., Patuelli, R., & Reinkowski, J. (2012). Does cluster policy trigger R&D activity? Evidence from German biotech contests. European Planning Studies, 21(11), 1735–1759.CrossRefGoogle Scholar
  23. Falck, O., Heblich, S., & Kipar, S. (2010). Industrial innovation: Direct evidence from a cluster-oriented policy. Regional Science and Urban Economics,40, 574–582.CrossRefGoogle Scholar
  24. Feldman, M. P., & Kelley, M. R. (2006). The ex ante assessment of knowledge spillovers: Government R&D policy, economic incentives and private firm behavior. Research Policy,35(10), 1509–1521.CrossRefGoogle Scholar
  25. Girma, S., Görg, H., & Hanley, A. (2008). R&D and exporting: A comparison of British and Irish firms. Review of World Economics, 144(4), 750–773.CrossRefGoogle Scholar
  26. Hall, B. (2009). The financing of innovative firms. EIB PAPERS,14(2), 8–29.Google Scholar
  27. Hambrick, D. C., MacMillan, I. C., & Barbosa, R. R. (1983). Business unit strategy and changes in the product R&D budget. Management Science,29(7), 757–769.CrossRefGoogle Scholar
  28. Heckman, J. J., Ichimura, P., & Todd, H. (1998). Matching as an econometric evaluation estimator. Review of Economic Studies,65, 261–294.CrossRefGoogle Scholar
  29. Jaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. The Quarterly Journal of Economics,108(3), 577–598.CrossRefGoogle Scholar
  30. Klette, T. J., & Kortum, S. (2004). Innovating firms and aggregate innovation. Journal of Political Economy,112(5), 986–1018.CrossRefGoogle Scholar
  31. Klette, T. J., & Moen, J. (1998). R&D investment responses to R&D subsidies: A theoretical analysis and econometric evidence. Presentation to the NBER Summer Institute, July.Google Scholar
  32. Koga, T. (2005). R&D subsidy and self-financed R&D: The case of Japanese high-technology start-ups. Small Business Economics,24(1), 53–62.CrossRefGoogle Scholar
  33. Lechner, M. (1998). Training the East German labor force: microeconometric evaluations of continuous vocational training after unification. Heidelberg: Physica Verlag.CrossRefGoogle Scholar
  34. Lechner, M. (2001). Identification and estimation of causal effects of multiple treatments under the conditional independence assumption. In M. Lechner & F. Pfeiffer (Eds.), Econometric Evaluation of Labor Market Policies (pp. 43–58). Heidelberg: Physica/Springer.CrossRefGoogle Scholar
  35. Leuven, E., & Sianesi, B. (2003). PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical Software Components, Boston College Department of Economics. This version: 3.1.4 17dec2008.Google Scholar
  36. Lin, T., & Vasarhelyi, M. A. (1980). Accounting and financial control for R&D expenditures. TIMS Studies in Management Science,15, 199–213.Google Scholar
  37. Marshall, A. (2009). Principles of Economics. Unabridged (8th ed.). New York: Cosimo.Google Scholar
  38. Martin, P. T., & Mayer, F. Mayneris. (2011). Public support to clusters. A firm level study of French local productive systems. Regional Science and Urban Economics,41, 108–123.CrossRefGoogle Scholar
  39. Porter, M. (2003). Locations, clusters, and company strategy. In G. L. Clark, M. P. Feldman, & M. S. Gertler (Eds.), Oxford Handbook of Economic Geography (pp. 253–274). Oxford: Oxford University Press.Google Scholar
  40. Rosenbaum, P. R. (2002). Observational studies. InObservational studies. Springer series in statistics (2nd ed., pp. 1–17). New York: Springer.CrossRefGoogle Scholar
  41. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrica,70, 41–55.CrossRefGoogle Scholar
  42. Rothgang, M., Cantner, U., Dehio, J., Engel, D., Fertig, M., Graf, H., et al. (2014). Begleitende Evaluierung des Förderinstruments “Spitzencluster-Wettbewerb” des BMBF. Essen: Abschlussbericht.Google Scholar
  43. Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall.CrossRefGoogle Scholar
  44. Smith, J., & Todd, P. (2005). Does matching overcome LaLonde’s Critique of nonexperimental estimators? Journal of Econometrics,125(1–2), 305–353.CrossRefGoogle Scholar
  45. Specht, G., Beckmann, C., & Amelingmeyer, J. (2002). F&E-Management (2nd ed.). Stuttgart: Schäffer-Poeschel.Google Scholar
  46. Stiebale, J., & Reize, F. (2011). The impact of FDI through Mergers and acquisitions on innovation in target firms. International Journal of Industrial Organisation,29(2), 155–167.CrossRefGoogle Scholar
  47. Wallsten, S. J. (2000). The small business innovation research program: encouraging technological innovation and commercialization in small firms? Rand Journal of Economics,31, 82–100.CrossRefGoogle Scholar
  48. Zúñiga Vicente, J. Á., et al. (2014). Assessing the effect of public subsidies on firm R&D investment: a survey. Journal of Economic Surveys,28(1), 36–67.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.University of Applied Sciences StralsundStralsundGermany
  2. 2.Wissenschaftsstatistik GmbH of the StifterverbandEssenGermany
  3. 3.RWI Leibniz Institute for Economic ResearchEssenGermany

Personalised recommendations