IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-16992-1.html
   My bibliography  Save this article

Reconciling contrasting views on economic complexity

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-16992-1
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-16992-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Saima Shadab & Firoz Alam, 2024. "High-Technology Exports, Foreign Direct Investment, Renewable Energy Consumption and Economic Growth: Evidence from the United Arab Emirates," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 394-401, March.
    6. 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).
    7. Ren, Zhuo-Ming & Zhao, Li & Du, Wen-Li & Weng, Tong-Feng & Liu, Chuang & Kong, Yi-Xiu & Zhang, Yi-Cheng, 2024. "Tunable resource allocation dynamics for interpreting economic complexity," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    8. 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.
    9. C'esar A. Hidalgo, 2022. "Knowledge is non-fungible," Papers 2205.02167, arXiv.org.
    10. 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.
    11. Hidalgo, César A., 2023. "The policy implications of economic complexity," Research Policy, Elsevier, vol. 52(9).
    12. 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.
    13. 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.
    14. Hardik Rajpal & Omar A Guerrero, 2023. "Synergistic Small Worlds that Drive Technological Sophistication," Papers 2301.04579, arXiv.org, revised Jul 2023.
    15. 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.
    16. Parcu, Pier Luigi & Innocenti, Niccolò & Carrozza, Chiara, 2022. "Ubiquitous technologies and 5G development. Who is leading the race?," Telecommunications Policy, Elsevier, vol. 46(4).
    17. 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.
    18. 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).
    19. Wang, Feng & Wu, Min & Wang, Jingcao, 2023. "Can increasing economic complexity improve China's green development efficiency?," Energy Economics, Elsevier, vol. 117(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16992-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.