IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/204.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/45325/1/63564357X.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Augurzky, Boris & Schmidt, Christoph M., 2001. "The Propensity Score: A Means to An End," IZA Discussion Papers 271, Institute of Labor Economics (IZA).
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Janina Reinkowski & Björn Alecke & Timo Mitze & Gerhard Untiedt, 2010. "Effectiveness of Public R&D Subsidies in East Germany – Is it a Matter of Firm Size?," Ruhr Economic Papers 0204, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    2. repec:zbw:rwirep:0204 is not listed on IDEAS
    3. Janina Reinkowski & Timo Mitze & Björn Alecke & Gerhard Untiedt, 2011. "R&D Subsidies and Private Sector Innovativeness: New Empirical Evidence for East German Firms," ERSA conference papers ersa10p1071, European Regional Science Association.
    4. Janina Reinkowski, 2014. "Empirical Essays in the Economics of Ageing and the Economics of Innovation," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 53.
    5. Enrico Vanino & Stephen Roper & Bettina Becker, 2020. "Knowledge to Money: Assessing the Business Performance Effects of Publicly Funded R&D Grants," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(04), pages 20-24, January.
    6. Arvid Raknerud & Diana-Cristina Iancu & Øivind A. Nilsen, 2018. "Public R&D Support and Firms’ Performance. A Panel Data Study," Discussion Papers 878, Statistics Norway, Research Department.
    7. Serenella Caravella & Francesco Crespi, 2021. "The role of public procurement as innovation lever: evidence from Italian manufacturing firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 30(7), pages 663-684, October.
    8. Johar, Meliyanni, 2009. "The impact of the Indonesian health card program: A matching estimator approach," Journal of Health Economics, Elsevier, vol. 28(1), pages 35-53, January.
    9. Guerzoni, Marco & Raiteri, Emilio, 2015. "Demand-side vs. supply-side technology policies: Hidden treatment and new empirical evidence on the policy mix," Research Policy, Elsevier, vol. 44(3), pages 726-747.
    10. Guerzoni, Marco & Raiteri, Emilio, 2012. "Innovative public procurement and R&D Subsidies: hidden treatment and new empirical evidence on the technology policy mix in a quasi-experimental setting," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201218, University of Turin.
    11. Andrea Pufahl & Christoph R. Weiss, 2009. "Evaluating the effects of farm programmes: results from propensity score matching," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(1), pages 79-101, March.
    12. Aiello, Francesco & Albanese, Giuseppe & Piselli, Paolo, 2019. "Good value for public money? The case of R&D policy," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1057-1076.
    13. Asad K. Ghalib & Issam Malki & Katsushi S. Imai, 2012. "Microfinance and its role in household poverty reduction: findings from Pakistan," Global Development Institute Working Paper Series 17312, GDI, The University of Manchester.
    14. Ramírez-Álvarez, Aurora Alejandra, 2019. "Land titling and its effect on the allocation of public goods: Evidence from Mexico," World Development, Elsevier, vol. 124(C), pages 1-1.
    15. Ghisetti, Claudia, 2017. "Demand-pull and environmental innovations: Estimating the effects of innovative public procurement," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 178-187.
    16. Marisa Coetzee, 2013. "Finding the Benefits: Estimating the Impact of The South African Child Support Grant," South African Journal of Economics, Economic Society of South Africa, vol. 81(3), pages 427-450, September.
    17. Aschhoff, Birgit & Sofka, Wolfgang, 2009. "Innovation on demand--Can public procurement drive market success of innovations?," Research Policy, Elsevier, vol. 38(8), pages 1235-1247, October.
    18. Sánchez-Braza, Antonio & Pablo-Romero, María del P., 2014. "Evaluation of property tax bonus to promote solar thermal systems in Andalusia (Spain)," Energy Policy, Elsevier, vol. 67(C), pages 832-843.
    19. Dan Pan, 2014. "The Impact of Agricultural Extension on Farmer Nutrient Management Behavior in Chinese Rice Production: A Household-Level Analysis," Sustainability, MDPI, vol. 6(10), pages 1-22, September.
    20. Czarnitzki, Dirk & Lopes-Bento, Cindy, 2013. "Value for money? New microeconometric evidence on public R&D grants in Flanders," Research Policy, Elsevier, vol. 42(1), pages 76-89.
    21. Paudel, G. & Krishna, V. & McDonald, A., 2018. "Why some inferior technologies succeed? Examining the diffusion and impacts of rotavator tillage in Nepal Terai," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277149, International Association of Agricultural Economists.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:rwirep:204. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.