IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v527y2019ics0378437119307095.html
   My bibliography  Save this article

Input–output networks offer new insights of economic structure

Author

Listed:
  • Xu, Ming
  • Liang, Sai

Abstract

An input–output (IO) model can be regarded as a network in which nodes represent sectors and directional, weighted links stand for IO transactions between sectors. The integration of IO models with modern network analysis can potentially provide additional insights for better understanding the structure of economies. We introduce the framework of IO network analysis including several popular metrics and tools. We also demonstrate the framework using a hypothesized six-sector economy. The World Input–Output Database (WIOD) 2009 model is used as well for a real-world demonstration. This research shows the potential of IO network analysis in understanding the structure of economies using IO models and data. Our work lays the ground for future studies in developing new methods for IO network analysis and real-world case studies.

Suggested Citation

  • Xu, Ming & Liang, Sai, 2019. "Input–output networks offer new insights of economic structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307095
    DOI: 10.1016/j.physa.2019.121178
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119307095
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.121178?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    2. Wang, Tao & Xiao, Shiying & Yan, Jun & Zhang, Panpan, 2021. "Regional and sectoral structures of the Chinese economy: A network perspective from multi-regional input–output tables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    3. Zhang, Panpan & Wang, Tiandong & Yan, Jun, 2022. "PageRank centrality and algorithms for weighted, directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    4. Marco Capasso & Michael Spjelkavik Mark, 2019. "Visualizing the Evolving Fit of Education and Economy: The Case of ICT Education in Norway," LEM Papers Series 2019/40, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Han, Yang, 2022. "The impact of the COVID-19 pandemic on China's economic structure: An input–output approach," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 181-195.
    6. Huang, Jian-Bai & Chen, Xi & Song, Yi, 2020. "What drives embodied metal consumption in China's imports and exports," Resources Policy, Elsevier, vol. 69(C).
    7. Yanling Jin & Yi Xu & Rui Li & Changping Zhao & Zhenghui Yuan, 2022. "Comprehensive Evaluation of China’s Input–Output Sector Status Based on the Entropy Weight-Social Network Analysis Method," Sustainability, MDPI, vol. 14(21), pages 1-25, November.
    8. Rodolfo Metulini & Giorgio Gnecco & Francesco Biancalani & Massimo Riccaboni, 2023. "Hierarchical clustering and matrix completion for the reconstruction of world input–output tables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 575-620, September.
    9. Marco Capasso & Michael Spjelkavik Mark, 2021. "The Evolving Economic Employment of ICT Education: The Case of Norway," Sustainability, MDPI, vol. 13(15), pages 1-18, July.
    10. Martha G. Alatriste-Contreras & Martín Puchet Anyul, 2021. "The Spreading of Shocks in the North America Production Network and Its Relation to the Properties of the Network," Mathematics, MDPI, vol. 9(21), pages 1-19, November.
    11. Xiao, Shiying & Yan, Jun & Zhang, Panpan, 2022. "Incorporating auxiliary information in betweenness measure for input–output networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    12. Li, Yongqing & Ma, Huimin & Xiong, Jie & Zhang, Jinlong & Ponnamma Divakaran, Pradeep Kumar, 2022. "Manufacturing structure, transformation path, and performance evolution: An industrial network perspective," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    13. Domínguez, Alvaro & Santos-Marquez, Felipe & Mendez, Carlos, 2021. "Sectoral productivity convergence, input-output structure and network communities in Japan," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 582-599.
    14. Eszter Moln'ar & D'enes Csala, 2022. "Topology-dependence of propagation mechanisms in the production network," Papers 2205.08874, arXiv.org.
    15. Barauskaite, Kristina & Nguyen, Anh D.M., 2021. "Global intersectoral production network and aggregate fluctuations," Economic Modelling, Elsevier, vol. 102(C).
    16. Han, Yang & Zhang, Haotian & Zhao, Yong, 2021. "Structural evolution of real estate industry in China: 2002-2017," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 45-56.

    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:eee:phsmap:v:527:y:2019:i:c:s0378437119307095. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.