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Innovation, R&D Efficiency and the Impact of the Regulatory Environment: A Two-Stage Semi-Parametric DEA Approach

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  • Astrid Cullmann
  • Jens Schmidt-Ehmcke
  • Petra Zloczysti

Abstract

This paper assesses the relative efficiency of knowledge production in the OECD using a nonparametric DEA approach. Resources allocated to R&D are limited and should therefore be used efficiently given the institutional and legal constraints. This paper presents efficiency scores based on an intertemporal frontier estimation for the period 1995 to 2004 and analyzes the impact of the regulatory environment using the single bootstrap procedure suggested by Simar and Wilson (2007). The empirical evidence supports the hypothesis that barriers to entry, aimed at reducing competition, lower research efficiency by attenuating the incentive to innovate and to allocate resources efficiently.

Suggested Citation

  • Astrid Cullmann & Jens Schmidt-Ehmcke & Petra Zloczysti, 2009. "Innovation, R&D Efficiency and the Impact of the Regulatory Environment: A Two-Stage Semi-Parametric DEA Approach," Discussion Papers of DIW Berlin 883, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp883
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    Cited by:

    1. Benedikt Herrmann & Alexander Kritikos, 2013. "Growing out of the crisis: hidden assets to Greece's transition to an innovation economy," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-23, December.
    2. Maxim Kotsemir, 2013. "Measuring National Innovation Systems Efficiency - A Review of DEA Approach," Post-Print hal-00865875, HAL.
    3. repec:spr:scient:v:94:y:2013:i:3:d:10.1007_s11192-012-0811-9 is not listed on IDEAS
    4. Luh, Yir-Hueih & Jiang, Wun-Ji & Huang, Szu-Chi, 2016. "Trade-related spillovers and industrial competitiveness: Exploring the linkages for OECD countries," Economic Modelling, Elsevier, vol. 54(C), pages 309-325.
    5. Proksch, Dorian & Haberstroh, Marcus Max & Pinkwart, Andreas, 2017. "Increasing the national innovative capacity: Identifying the pathways to success using a comparative method," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 256-270.
    6. Chia-Chin Chang, 2015. "Influences of knowledge spillover and utilization on the NIS performance: a multi-stage efficiency perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(5), pages 1945-1967, September.
    7. Drivas, Kyriakos & Economidou, Claire & Tsionas, Efthymios G., 2014. "A Poisson Stochastic Frontier Model with Finite Mixture Structure," MPRA Paper 57485, University Library of Munich, Germany.
    8. repec:fan:efeefe:v:html10.3280/efe2016-002006 is not listed on IDEAS
    9. M. Foddi & S. Usai, 2012. "Regional innovation performance in Europe," Working Paper CRENoS 201221, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Marta Foddi & Stefano Usai, 2013. "Regional Knowledge Performance in Europe," Growth and Change, Wiley Blackwell, vol. 44(2), pages 258-286, June.

    More about this item

    Keywords

    R&D efficiency; data envelopment analysis; truncated regression; regulation;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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