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Natural resource dependence and innovation efficiency reconsidered

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  • Wilson, Kenneth
  • Vellinga, Nico

Abstract

In a recent contribution to Resources Policy titled ‘Natural resource dependence and economic growth: A TOPSIS/DEA analysis of innovation efficiency’, Mehdi Namazi and Emran Mohammadi (2018) propose a method for analyzing innovation efficiency and how it may help countries blighted by the resource curse to develop their innovation policies. Namazi and Mohammadi provide the first published research that combines data envelopment analysis (DEA) and the technique for order of preferences by similar to ideal solution (TOPSIS) to evaluate innovation efficiencies of countries. Their method enables them to also generate the innovation efficiency ‘improvability’ scores and innovation efficiency ‘resilience’ scores. However, their results are generated by infeasible linear programs and they committed a number of other errors that make their innovation efficiencies ‘inefficient’ and their findings meaningless. In this paper we suggest a way to overcome their infeasibility problems and correct their other errors. Once their errors are corrected and their method is used properly we believe their approach has merit.

Suggested Citation

  • Wilson, Kenneth & Vellinga, Nico, 2022. "Natural resource dependence and innovation efficiency reconsidered," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001325
    DOI: 10.1016/j.resourpol.2022.102684
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    2. Li, Kanyong, 2023. "Can resource endowment and industrial structure drive green innovation efficiency in the context of COP 26？," Resources Policy, Elsevier, vol. 82(C).
    3. Vyacheslav V. Volchik & Elena V. Fursa, 2023. "Russian innovation system: Narratives and economic policy," Journal of New Economy, Ural State University of Economics, vol. 24(4), pages 22-40, January.

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