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Network analysis of inter-sectoral relationships and key sectors in the Greek economy

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  • Theodore Tsekeris

    (Centre of Planning and Economic Research (KEPE))

Abstract

The rapidly growing theories of networks and complex systems have been recently adopted to interpret the efficiency and robustness of various economic markets. Based on these theoretical underpinnings, the present paper describes a structural input–output analysis of the inter-sectoral linkages and main activity clusters of the Greek economy, which is modeled as a complex network. Such an analysis employs suitable network metrics to measure the centrality and influence of each sector-agent on the other ones, and the possibilities for clustering of related (groups of) activities. Key sectors related to the production of tradable goods and services are identified, in terms of their marginal ability to pull the total economic activity. Critical sectors are also determined in terms of their ability to retain the interconnectivity and strengthen the stability of the whole economic system. It is argued that more synergies within and among the activity clusters, through the creation of integrated value chains, would allow better coordination of policies, more efficient allocation of resources and enhanced diffusion of knowledge.

Suggested Citation

  • Theodore Tsekeris, 2017. "Network analysis of inter-sectoral relationships and key sectors in the Greek economy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 413-435, July.
  • Handle: RePEc:spr:jeicoo:v:12:y:2017:i:2:d:10.1007_s11403-015-0171-7
    DOI: 10.1007/s11403-015-0171-7
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    Cited by:

    1. 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.
    2. 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.
    3. Persefoni Zeri & Charalambos Tsekeris & Theodore Tsekeris, 2019. "The social power dynamics of post-truth politics: How the Greek youth perceives the “powerful” foreigners and constructs the image of the European partners," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 142, Hellenic Observatory, LSE.
    4. Ariel L. Wirkierman & Monica Bianchi & Anna Torriero, 2022. "Leontief Meets Markov: Sectoral Vulnerabilities Through Circular Connectivity," Networks and Spatial Economics, Springer, vol. 22(3), pages 659-690, September.
    5. Qingru Sun & Xiangyun Gao & Shaobo Wen & Sida Feng & Ze Wang, 2019. "Modeling the impulse response complex network for studying the fluctuation transmission of price indices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 835-858, December.
    6. Kelly Benetatou & Yannis Katsoulacos, 2020. "Legal Standards and Economic Analysis in Antitrust Enforcement: An Empirical Investigation for the Case of Greece," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 144, Hellenic Observatory, LSE.
    7. Yanxin Liu & Huajiao Li & Jianhe Guan & Xueyong Liu & Yajie Qi, 2019. "The role of the world’s major steel markets in price spillover networks: an analysis based on complex network motifs," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 697-720, December.
    8. Qingru Sun & Xiangyun Gao & Ze Wang & Siyao Liu & Sui Guo & Yang Li, 2020. "Quantifying the risk of price fluctuations based on weighted Granger causality networks of consumer price indices: evidence from G7 countries," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 821-844, October.
    9. Yue, Youfu & Hou, Junjun & Zhang, Meichen & Ye, Jiabai, 2024. "Does the sticky relationships of global value chains help stabilize employment? Evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 632-651.
    10. José Ramírez-Álvarez & Vanessa Chungandro-Carranco & Nathaly Montenegro-Rosero & Carolina Guevara-Rosero, 2024. "Central Industries in the Ecuadorian Input–Output Network. An Application of Social Network Analysis," Networks and Spatial Economics, Springer, vol. 24(1), pages 131-164, March.
    11. 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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    More about this item

    Keywords

    Input–output tables; Network analysis; Key sectors; Clusters; Development;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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