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Set pair prediction for Chinese natural gas energy security based on higher-order Markov chain with risk attitude

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  • Yuan, Jiahang
  • Wang, Li
  • Li, Yating
  • Wang, Yuwei
  • Ma, Tao
  • Luo, Xinggang

Abstract

Due to the continuous increasing energy consumption demand and low carbon target, natural gas, regarded as a promising energy resource around the world, has been paid more attention. As the gap between China's natural gas production and consumption continues to rise, natural gas security becomes a key problem concerned by the whole society. This paper proposes a comprehensive evaluation criteria system, including four dimensions and eight indicators, and constructs an evaluation and prediction model based on set pair analysis, variable weight and high-order Markov chain. Firstly, the state sets of natural gas security evaluation criteria are formed to a set pair. Secondly, the variable weight method was used to calculate the association degree of the set pair and state transferring probability matrix in different time to overcome the problem that the constant weight can not reflect the order importance of the value of criteria. Thirdly, the higher-order Markov chain was proposed to predict the association degree of set pair and to analyze natural gas security situation. Finally, the proposed model is used for China's natural gas security evaluation based on data from 2014 to 2018. The result indicates that natural gas security level shows rising trend in general, and the prediction value shows the future security is still not safe. Thus, some suggestions for improving security are given. Furthermore, the risk attitude of experts has great influence on short-term security analysis and prediction, while the effects on long-term evaluation and prediction are less.

Suggested Citation

  • Yuan, Jiahang & Wang, Li & Li, Yating & Wang, Yuwei & Ma, Tao & Luo, Xinggang, 2022. "Set pair prediction for Chinese natural gas energy security based on higher-order Markov chain with risk attitude," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001891
    DOI: 10.1016/j.resourpol.2022.102741
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