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Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community

Author

Listed:
  • Leila Mirtajadini
  • Shamsollah Shirin Bakhsh
  • Mir Hossein Mousavi
  • Kioumars Heydari
  • Saman Yousefvand

Abstract

This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27

Suggested Citation

  • Leila Mirtajadini & Shamsollah Shirin Bakhsh & Mir Hossein Mousavi & Kioumars Heydari & Saman Yousefvand, 2023. "Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community," Foreign Trade Review, , vol. 58(4), pages 544-557, November.
    • Handle: RePEc:sae:fortra:v:58:y:2023:i:4:p:544-557
    DOI: 10.1177/00157325231166242
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    References listed on IDEAS

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    More about this item

    Keywords

    Electricity trade; trade network; community; link prediction;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • Q27 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Issues in International Trade

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