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Input–output networks offer new insights of economic structure

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  • 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
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. 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).
    5. 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).
    6. 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.
    7. 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).
    8. 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.
    9. 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).
    10. 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.
    11. 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).
    12. 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.
    13. Eszter Moln'ar & D'enes Csala, 2022. "Topology-dependence of propagation mechanisms in the production network," Papers 2205.08874, arXiv.org.
    14. Barauskaite, Kristina & Nguyen, Anh D.M., 2021. "Global intersectoral production network and aggregate fluctuations," Economic Modelling, Elsevier, vol. 102(C).
    15. 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.
    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.

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