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R&D efficiency and heterogeneity - a latent class application for the OECD

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  • Astrid Cullmann
  • Petra Zloczysti

Abstract

Expenditures devoted to research and development (R&D) are scarce and thus need to be used as efficiently as possible given the financial constraints countries are facing. This article assesses the relative efficiency of R&D expenditures for 26 OECD member countries and two nonmember countries. As countries differ in their national innovation systems and states of economic development and industrialization, e.g. transition economies in Eastern Europe versus Asian countries versus Anglo-Saxon countries, the measurement of R&D efficiency needs to consider differences in the technology of knowledge production. By means of a latent class model for stochastic frontiers, we relax the assumption of a homogeneous technology frontier and model technological differences in knowledge production among countries. Empirical evidence suggests the existence of different classes stressing the importance of accounting for countries' disparities within R&D efficiency analysis.

Suggested Citation

  • Astrid Cullmann & Petra Zloczysti, 2014. "R&D efficiency and heterogeneity - a latent class application for the OECD," Applied Economics, Taylor & Francis Journals, vol. 46(30), pages 3750-3762, October.
    • Handle: RePEc:taf:applec:v:46:y:2014:i:30:p:3750-3762
    DOI: 10.1080/00036846.2014.939410
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    References listed on IDEAS

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    1. Griliches, Zvi, 1998. "R&D and Productivity," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226308869, December.
    2. Zvi Griliches, 1998. "R&D and Productivity: The Econometric Evidence," NBER Books, National Bureau of Economic Research, Inc, number gril98-1, March.
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    Cited by:

    1. Agrell, Per J. & Brea-Solís, Humberto, 2017. "Capturing heterogeneity in electricity distribution operations: A critical review of latent class modelling," Energy Policy, Elsevier, vol. 104(C), pages 361-372.
    2. Francisco J. A. Cysneiros & Víctor Leiva & Shuangzhe Liu & Carolina Marchant & Paulo Scalco, 2019. "A Cobb–Douglas type model with stochastic restrictions: formulation, local influence diagnostics and data analytics in economics," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1693-1719, July.

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