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Effectiveness of Public R&D Subsidies in East Germany – Is it a Matter of Firm Size?

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  • Reinkowski, Janina
  • Alecke, Björn
  • Mitze, Timo
  • Untiedt, Gerhard

Abstract

This paper analyses the impact of public subsidies on private sector research and development (R&D) activity for East German firms. Using propensity score matching, our empirical results indicate that subsidized firms indeed show a higher level of R&D intensity and a higher probability for patent application compared to non-subsidized firms for our sample year 2003. On average we find an increase in the R&D intensity of about 3.7 percentage points relative to non-subsidized firms. The probability for patent applications rises by 21 percentage points. These results closely match earlier empirical results for East Germany. Given the fact that the East German innovation system is particularly driven by small and medium sized enterprises (SME), we put a special focus on the effectiveness of the R&D subsidies for this latter subgroup. Here no previous empirical evidence is available so far. Our findings indicate that policy effectiveness also holds for private R&D activity of SMEs, where the highest increase in terms of R&D intensity is estimated for micro businesses with up to 10 employees.

Suggested Citation

  • Reinkowski, Janina & Alecke, Björn & Mitze, Timo & Untiedt, Gerhard, 2010. "Effectiveness of Public R&D Subsidies in East Germany – Is it a Matter of Firm Size?," Ruhr Economic Papers 204, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Handle: RePEc:zbw:rwirep:204
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    3. Conte, Andrea & Vivarelli, Marco, 2005. "One or Many Knowledge Production Functions? Mapping Innovative Activity Using Microdata," IZA Discussion Papers 1878, Institute of Labor Economics (IZA).
    4. David, Paul A. & Hall, Bronwyn H. & Toole, Andrew A., 2000. "Is public R&D a complement or substitute for private R&D? A review of the econometric evidence," Research Policy, Elsevier, vol. 29(4-5), pages 497-529, April.
    5. Augurzky, Boris & Schmidt, Christoph M., 2001. "The Propensity Score: A Means to An End," IZA Discussion Papers 271, Institute of Labor Economics (IZA).
    6. Dirk Czarnitzki & Georg Licht, 2006. "Additionality of public R&D grants in a transition economy," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 14(1), pages 101-131, March.
    7. Günther, Jutta & Wilde, Katja & Sunder, Marco & Titze, Mirko, 2010. "20 Jahre nach dem Mauerfall: Stärken, Schwächen und Herausforderungen des ostdeutschen Innovationssystems heute," Studien zum deutschen Innovationssystem 17-2010, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    8. José García‐Quevedo, 2004. "Do Public Subsidies Complement Business R&D? A Meta‐Analysis of the Econometric Evidence," Kyklos, Wiley Blackwell, vol. 57(1), pages 87-102, February.
    9. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
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    Cited by:

    1. Basit Shoaib Abdul & Kuhn Thomas & Ahmed Mumtaz, 2018. "The Effect of Government Subsidy on Non-Technological Innovation and Firm Performance in the Service Sector: Evidence from Germany," Business Systems Research, Sciendo, vol. 9(1), pages 118-137, March.
    2. Reiljan, Janno & Paltser, Ingra, 2013. "The implementation of research and development policy in European and Asian countries," Discourses in Social Market Economy 2013-03, OrdnungsPolitisches Portal (OPO).
    3. Thomas H. W. Ziesemer, 2021. "The Effects of R&D Subsidies and Publicly Performed R&D on Business R&D: A Survey," Hacienda Pública Española / Review of Public Economics, IEF, vol. 236(1), pages 171-205, March.

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    More about this item

    Keywords

    propensity score matching; R&D subsidies; East Germany; SME;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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