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R&D Efficiency and Barriers to Entry: A Two Stage Semi-Parametric DEA Approach

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  • Schmidt-Ehmcke, Jens
  • Cullmann, Astrid
  • Zloczysti, Petra
Abstract
This paper assesses the relative efficiency of knowledge production in the OECD using a nonparametric DEA approach. In general, resources allocated to R&D are limited and therefore must be used efficiently, given the institutional and legal constraints. The efficiency scores presented are based on an intertemporal frontier estimation for the period 1995 to 2004. We analyze the impact of the regulatory environment using the single bootstrap procedure suggested by Simar and Wilson (2007a). The empirical evidence supports our hypothesis that barriers to entry aimed at reducing competition actually lower R&D efficiency by attenuating the incentives to innovate and to allocate resources efficiently.

Suggested Citation

  • Schmidt-Ehmcke, Jens & Cullmann, Astrid & Zloczysti, Petra, 2010. "R&D Efficiency and Barriers to Entry: A Two Stage Semi-Parametric DEA Approach," CEPR Discussion Papers 8047, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:8047
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    References listed on IDEAS

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    1. de Rassenfosse, Gaetan & van Pottelsberghe de la Potterie, Bruno, 2009. "A policy insight into the R&D-patent relationship," Research Policy, Elsevier, vol. 38(5), pages 779-792, June.
    2. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
    3. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    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. Geroski, P. A., 1995. "What do we know about entry?," International Journal of Industrial Organization, Elsevier, vol. 13(4), pages 421-440, December.
    6. John R. Baldwin & Paul K. Gorecki, 1990. "Firm Entry and Exit in the Canadian Manufacturing Sector," Working Paper 767, Economics Department, Queen's University.
    7. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Vladimír Holý & Karel Šafr, 2018. "Are economically advanced countries more efficient in basic and applied research?," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 933-950, December.
    2. Xie, Luqun & Zhou, Jieyu & Zong, Qingqing & Lu, Qian, 2020. "Gender diversity in R&D teams and innovation efficiency: Role of the innovation context," Research Policy, Elsevier, vol. 49(1).
    3. Vitor Miguel Ribeiro & Celeste Varum & Ana Dias Daniel, 2021. "Introducing microeconomic foundation in data envelopment analysis: effects of the ex ante regulation principle on regional performance," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(3), pages 1215-1244, September.
    4. Bengoa, Marta & Román, Valeriano Martínez-San & Pérez, Patricio, 2017. "Do R&D activities matter for productivity? A regional spatial approach assessing the role of human and social capital," Economic Modelling, Elsevier, vol. 60(C), pages 448-461.
    5. Uluc Aysun & Zeynep Yom, 2021. "R&D Characteristics, Innovation Spillover, and Technology-Driven Business Cycles," Journal of Industry, Competition and Trade, Springer, vol. 21(3), pages 339-365, September.
    6. Cullmann, Astrid & Zloczysti, Petra, 2013. "Towards an Efficient Use of R&D ? Accounting for Heterogeneity in the OECD," CEPR Discussion Papers 9345, C.E.P.R. Discussion Papers.
    7. Kyriakos Drivas & Claire Economidou & Efthymios G. Tsionas, 2018. "Production of output and ideas: efficiency and growth patterns in the United States," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 105-118, January.
    8. Xionghe Qin & Debin Du & Mei-Po Kwan, 2019. "Spatial spillovers and value chain spillovers: evaluating regional R&D efficiency and its spillover effects in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 721-747, May.
    9. Sungmin Park, 2015. "The R&D logic model: Does it really work? An empirical verification using successive binary logistic regression models," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1399-1439, December.
    10. Cai, Yuezhou & Hanley, Aoife, 2012. "Building BRICS: 2-Stage DEA analysis of R&D efficiency," Kiel Working Papers 1788, Kiel Institute for the World Economy (IfW Kiel).
    11. Siran Fang & Xiaoshan Xue & Ge Yin & Hong Fang & Jialin Li & Yongnian Zhang, 2020. "Evaluation and Improvement of Technological Innovation Efficiency of New Energy Vehicle Enterprises in China Based on DEA-Tobit Model," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    12. Alessandro Fiorini, 2016. "Technical efficiency in a technological innovation system perspective: The case of bioenergy technologies R&D resources mobilisation in a sample from EU-28," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2016(2), pages 107-127.
    13. Ron Boschma & Simona Iammarino & Raffaele Paci & Jordy Suriñach & Corinne Autant-Bernard & Sylvie Chalaye & Elisa Gagliardini & Stefano Usai, 2017. "European Knowledge Neighbourhood: Knowledge Production in EU Neighbouring Countries and Intensity of the Relationship with EU Countries," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 108(1), pages 52-75, February.
    14. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    15. Massimo Filippini & Lin Zhang, 2013. "Measurement of the “Underlying energy efficiency” in Chinese provinces," CER-ETH Economics working paper series 13/183, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    16. Holý, Vladimír, 2024. "Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education," Operations Research Perspectives, Elsevier, vol. 12(C).

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    More about this item

    Keywords

    R&d efficiency; Data envelopment analysis; Truncated regulation;
    All these keywords.

    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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