IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v607y2022ics0378437122007580.html
   My bibliography  Save this article

Incorporating auxiliary information in betweenness measure for input–output networks

Author

Listed:
  • Xiao, Shiying
  • Yan, Jun
  • Zhang, Panpan

Abstract

The betweenness centrality plays an important role in input–output analysis. Existing betweenness measures are mostly defined based on the intermediate flow network, without accounting for node-level information which can be of great value in some applications. Here we propose a novel betweenness centrality measure that incorporates available node-specific auxiliary information for weighted, directed networks with a specific focus on input–output network analysis. The proposed measure is defined upon strongest paths reflecting the pull effects of sectors in an economy, which distinguishes itself from many other classical versions. The search of strongest paths is done by the Dijkstra’s algorithm. The proposed betweenness integrates the structural information of a network and auxiliary information which may come from sources beyond the network. Through two simulation experiments and applications to the 2018 national input–output network of China, we demonstrate the importance and effectiveness of incorporating auxiliary information relevant to the research objectives for betweenness computation and node centrality assessment. The implementation is publicly available in an R package ionet.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007580
    DOI: 10.1016/j.physa.2022.128200
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122007580
    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.2022.128200?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.

    References listed on IDEAS

    as
    1. Abbasi, Alireza & Hossain, Liaquat & Leydesdorff, Loet, 2012. "Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks," Journal of Informetrics, Elsevier, vol. 6(3), pages 403-412.
    2. ten Raa,Thijs, 2006. "The Economics of Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521841795, January.
    3. Joseph STIGLITZ, 2013. "The global crisis, social protection and jobs," International Labour Review, International Labour Organization, vol. 152, pages 93-106, January.
    4. Tsekeris, Theodore, 2017. "Global value chains: Building blocks and network dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 187-204.
    5. 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).
    6. William H. Miernyk, 1965. "The Elements of Input-Output Analysis," Wholbk, Regional Research Institute, West Virginia University, number 04, November-.
    7. Federica Cerina & Zhen Zhu & Alessandro Chessa & Massimo Riccaboni, 2015. "World Input-Output Network," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    8. 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).
    9. Leonidov, Andrey & Serebryannikova, Ekaterina, 2019. "Dynamical topology of highly aggregated input–output networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 234-252.
    10. 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).
    11. Xing, Lizhi & Dong, Xianlei & Guan, Jun & Qiao, Xiaoyong, 2019. "Betweenness centrality for similarity-weight network and its application to measuring industrial sectors’ pivotability on the global value chain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 19-36.
    12. Rudolfs Bems & Robert C. Johnson & Kei-Mu Yi, 2011. "Vertical Linkages and the Collapse of Global Trade," American Economic Review, American Economic Association, vol. 101(3), pages 308-312, May.
    13. Tao Wang & Shiying Xiao & Jun Yan & Panpan Zhang, 2021. "Regional and Sectoral Structures and Their Dynamics of Chinese Economy: A Network Perspective from Multi-Regional Input-Output Tables," Papers 2102.12454, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. 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).
    4. 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.
    5. 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).
    6. 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.
    7. Stefano Costa & Federico Sallusti & Claudio Vicarelli, 2022. "Trade networks and shock transmission capacity: a new taxonomy of Italian industries," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(1), pages 133-153, March.
    8. Georgios Angelidis & Charalambos Bratsas & Georgios Makris & Evangelos Ioannidis & Nikos C. Varsakelis & Ioannis E. Antoniou, 2021. "Global Value Chains of COVID-19 Materials: A Weighted Directed Network Analysis," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    9. Joya, Omar & Rougier, Eric, 2019. "Do (all) sectoral shocks lead to aggregate volatility? Empirics from a production network perspective," European Economic Review, Elsevier, vol. 113(C), pages 77-107.
    10. Shen, Yi & Yang, Huang & Xie, Yuangcheng & Liu, Yang & Ren, Gang, 2023. "Adaptive robustness optimization against network cascading congestion induced by fluctuant load via a bilateral-adaptive strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    11. 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.
    12. Gunnella, Vanessa & Al-Haschimi, Alexander & Benkovskis, Konstantins & Chiacchio, Francesco & de Soyres, François & Di Lupidio, Benedetta & Fidora, Michael & Franco-Bedoya, Sebastian & Frohm, Erik & G, 2019. "The impact of global value chains on the euro area economy," Occasional Paper Series 221, European Central Bank.
    13. 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.
    14. Barauskaite, Kristina & Nguyen, Anh D.M., 2021. "Global intersectoral production network and aggregate fluctuations," Economic Modelling, Elsevier, vol. 102(C).
    15. Los, Bart & Timmer, Marcel P. & de Vries, Gaaitzen J., 2015. "How important are exports for job growth in China? A demand side analysis," Journal of Comparative Economics, Elsevier, vol. 43(1), pages 19-32.
    16. Tamat Sarmidi & Norlin Khalid & Muhamad Rias K. V. Zainuddin & Sufian Jusoh, 2021. "The COVID-19 Pandemic, Air Transport Perturbation, and Sector Impacts in ASEAN Plus Five: A Multiregional Input–Output Inoperability Analysis," Working Papers DP-2021-01, Economic Research Institute for ASEAN and East Asia (ERIA).
    17. Lechón, Y. & de la Rúa, C. & Rodríguez, I. & Caldés, N., 2019. "Socioeconomic implications of biofuels deployment through an Input-Output approach. A case study in Uruguay," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 178-191.
    18. Peter Gal & Alexander Hijzen, 2016. "The short-term impact of product market reforms: A cross-country firm-level analysis," OECD Economics Department Working Papers 1311, OECD Publishing.
    19. Christos Ap. LADIAS & Filipos RUXHO & Fernando Jos? Calado e Silva Nunes TEIXEIRA & Susana Soares Pinheiro Vieira PESCADA, 2023. "The Regional Economic Indicators And Economic Development Of Kosovo," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 73-83, June.
    20. André Lorentz & Maria Savona, 2009. "Evolutionary micro-dynamics and changes in the economic structure," Springer Books, in: Uwe Cantner & Jean-Luc Gaffard & Lionel Nesta (ed.), Schumpeterian Perspectives on Innovation, Competition and Growth, pages 137-160, Springer.

    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:607:y:2022:i:c:s0378437122007580. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.