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Risk Transmission of the Regions in the Yangtze River Economic Belt

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  • Xianbo Wu
  • Xiaofeng Hui

Abstract

This study mainly uses the method of effective transfer entropy (ETE) to study the risk transmission in each year among the 11 provinces and municipalities in the Yangtze River Economic Belt during the last five years. From the results of the risk transmission network, centralities of the regions, and maximum spanning trees, it can be seen that, in the years of 2015 and 2016, the risk transmission in the Yangtze River Economic Belt is relatively large, and in 2015, Shanghai is the main risk exporter. This may be mainly due to the violent turbulence in the Chinese stock market, and in 2016, although Chinese stock market is in a stable position, the whole risk transmission is still high, but the difference from 2015 is that the input and output risk of each province and municipality are more uniform and are no longer like Shanghai as the main exporter of risk in 2015. From the perspective of risk spillover, the overall trend is from the western region of China to the central region, and finally to the eastern region. Specifically, from the results of the maximum spanning tree, except the stock market crash period in 2015, Chongqing, Guizhou, and Yunnan (the western region) are the main exporters of risk, while Jiangsu, Zhejiang, and Shanghai (the eastern region) are often at the edge at this time, and from the results of the centrality of the region indexes, Hubei, Jiangxi, and Anhui (the central region) are in the hub position of risk transmission.

Suggested Citation

  • Xianbo Wu & Xiaofeng Hui, 2020. "Risk Transmission of the Regions in the Yangtze River Economic Belt," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-10, November.
  • Handle: RePEc:hin:jnddns:8876883
    DOI: 10.1155/2020/8876883
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    Cited by:

    1. Xin Zhang & Jinghu Pan, 2021. "Spatiotemporal Pattern and Driving Factors of Urban Sprawl in China," Land, MDPI, vol. 10(11), pages 1-16, November.

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