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Issues Inside the Field of Economics of Innovation: Definitions, Data Sources, Estimation Procedures and Comparability of Results

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  • Marek Vokoun

Abstract

Innovation economics requires an interdisciplinary approach and at least knowledge in economics and history. A historiographical approach to data representativeness is necessary to perform literature review without producing errors when comparing studies with datasets lacking small companies. Knowledge in econometrics is necessary to assess the possibility to compare results from two innovation papers. An identification strategy is necessary for comprehension because the definitions of innovators are most of the time rather incomparable. Some papers recognize only successful innovators in terms of delivering the product new to the market. In other papers, innovators are companies, which imitated their competitors or trained staff recently. These issues are dependent on the understanding of the definition of the term innovation. Comparison of innovation economics research results or using them in an argument is not possible without complex understanding of data (representativeness), methods (set of control variables) and other limits of dependent variables.

Suggested Citation

  • Marek Vokoun, 2017. "Issues Inside the Field of Economics of Innovation: Definitions, Data Sources, Estimation Procedures and Comparability of Results," Littera Scripta, VSTE, vol. 10(2), pages 165-176, May.
    • Handle: RePEc:rsg:littra:2017-023
    DOI: 10.36708/LS.2017.I02.011
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    References listed on IDEAS

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    3. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
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