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On measuring complexity in a post-industrial economy: the ecosystem’s approach

Author

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  • Inga Ivanova

    (National Research University Higher School of Economics (NRU HSE))

  • Nataliya Smorodinskaya

    (Institute of Economics of the Russian Academy of Sciences)

  • Loet Leydesdorff

    (University of Amsterdam)

Abstract

We propose the Modified Economic Complexity Index (MECI) as a possible refinement to two relevant complexity measures: the Economic Complexity index (ECI) and the Fitness and Complexity index (FCI). Both ECI and FCI are used for the evaluation of competitive advantages and growth potentials of countries. ECI and FCI assume bipartite country-network data, whereas MECI provides an ecosystem-based design using technology as a third dimension. We test the three complexity measures with respect to Balassa’s Revealed Comparative Advantage index (RCA) and the newly introduced Revealed Effectiveness Advantage index (REA) using empirical data for 41 countries. Regression analysis shows that the predictive power of the three measures with respect to GDP per capita growth improves using the REA index instead of RCA. MECI improves the prediction when compared with ECI and FCI. However, the results for the three measures converge in terms of initial diversity scores and GDP per capita correlation in the case of using the REA index. MECI is based on an eco-system’s approach and can therefore be further developed into simulations.

Suggested Citation

  • Inga Ivanova & Nataliya Smorodinskaya & Loet Leydesdorff, 2020. "On measuring complexity in a post-industrial economy: the ecosystem’s approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 197-212, February.
    • Handle: RePEc:spr:qualqt:v:54:y:2020:i:1:d:10.1007_s11135-019-00844-2
    DOI: 10.1007/s11135-019-00844-2
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    References listed on IDEAS

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