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Reconciling contrasting views on economic complexity

Author

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  • Carla Sciarra

    (Politecnico di Torino)

  • Guido Chiarotti

    (Politecnico di Torino)

  • Luca Ridolfi

    (Politecnico di Torino)

  • Francesco Laio

    (Politecnico di Torino)

Abstract

Summarising the complexity of a country’s economy in a single number is the holy grail for scholars engaging in data-based economics. In a field where the Gross Domestic Product remains the preferred indicator for many, economic complexity measures, aiming at uncovering the productive knowledge of countries, have been stirring the pot in the past few years. The commonly used methodologies to measure economic complexity produce contrasting results, undermining their acceptance and applications. Here we show that these methodologies – apparently conflicting on fundamental aspects – can be reconciled by adopting a neat mathematical perspective based on linear-algebra tools within a bipartite-networks framework. The obtained results shed new light on the potential of economic complexity to trace and forecast countries’ innovation potential and to interpret the temporal dynamics of economic growth, possibly paving the way to a micro-foundation of the field.

Suggested Citation

  • Carla Sciarra & Guido Chiarotti & Luca Ridolfi & Francesco Laio, 2020. "Reconciling contrasting views on economic complexity," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16992-1
    DOI: 10.1038/s41467-020-16992-1
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    Citations

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    Cited by:

    1. Gnecco Giorgio & Nutarelli Federico & Riccaboni Massimo, 2021. "Matrix Completion of World Trade," Papers 2109.03930, arXiv.org.
    2. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(3).
    3. Yang, Shuhui & Li, Zhongkai & Zhou, Jianlin & Gao, Yancheng & Cui, Xuefeng, 2024. "Evolving patterns of agricultural production space in China: A network-based approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(1), pages 121-134.
    4. Athanasios Lapatinas & Marina-Selini Katsaiti, 2023. "EU MECI: A Network-Structured Indicator for a Union of Equality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(2), pages 465-483, April.
    5. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "Reprint of The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(8).
    6. Felipe Orsolin Teixeira & Fabricio Jose Missio & Ricardo Dathein, 2022. "Economic complexity, structural transformation and economic growth in a regional context: Evidence for Brazil," PSL Quarterly Review, Economia civile, vol. 75(300), pages 63-79.
    7. C'esar A. Hidalgo, 2022. "Knowledge is non-fungible," Papers 2205.02167, arXiv.org.
    8. Castañeda, Gonzalo & Pietronero, Luciano & Romero-Padilla, Juan & Zaccaria, Andrea, 2022. "The complex dynamic of growth: Fitness and the different patterns of economic activity in the medium and long terms," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 231-246.
    9. Hidalgo, César A., 2023. "The policy implications of economic complexity," Research Policy, Elsevier, vol. 52(9).
    10. Koch, Philipp & Schwarzbauer, Wolfgang, 2021. "Yet another space: Why the Industry Space adds value to the understanding of structural change and economic development," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 198-213.
    11. Fabozzi, Frank J. & Focardi, Sergio & Ponta, Linda & Rivoire, Manon & Mazza, Davide, 2022. "The economic theory of qualitative green growth," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 242-254.
    12. Hardik Rajpal & Omar A Guerrero, 2023. "Synergistic Small Worlds that Drive Technological Sophistication," Papers 2301.04579, arXiv.org, revised Jul 2023.
    13. James McNerney & Yang Li & Andres Gomez-Lievano & Frank Neffke, 2021. "Bridging the short-term and long-term dynamics of economic structural change," Papers 2110.09673, arXiv.org, revised Mar 2023.
    14. Parcu, Pier Luigi & Innocenti, Niccolò & Carrozza, Chiara, 2022. "Ubiquitous technologies and 5G development. Who is leading the race?," Telecommunications Policy, Elsevier, vol. 46(4).
    15. Cesar A. Hidalgo, 2022. "Knowledge is non-fungible," Papers in Evolutionary Economic Geography (PEEG) 2229, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Nov 2022.
    16. Ye, Yucheng & Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan, 2022. "Forecasting countries' gross domestic product from patent data," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    17. Wang, Feng & Wu, Min & Wang, Jingcao, 2023. "Can increasing economic complexity improve China's green development efficiency?," Energy Economics, Elsevier, vol. 117(C).

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