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The Emergence and Evolution of Regional Convergence Clusters in China’s Energy Markets

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Abstract

Employing the new regression tests for Convergence, Club Convergence and Clustering proposed by Phillips and Sul (2007), this paper models and analyzes the behavior of China‘s energy sectors. Energy market =convergence clusters‘ are identified using new price data and their regional spatial distributions are mapped for four major fuel types; coal, gasoline, diesel and electricity. It is found that: i) as yet, there are no fully integrated national energy markets in China as more than one convergence cluster is identified for all four fuels; ii) some regional energy markets can be regarded as =quite mature‘ as evidenced by the existence of some highly concentrated convergence clusters connected geographically; iii) some regional markets remain in a =state of transition‘ as witnessed by convergence clusters that are scattered geographically and growing in membership; vi) it seems that there is more regional-based integration for coal and electricity than for gasoline and diesel as more convergent clusters were identified for coal and electricity than for gasoline and diesel v) Overall, China still appears to be in the process of energy market integration as demonstrated by the number and evolution of convergence clusters over time.

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  • Hengyun Ma & Les Oxley, 2010. "The Emergence and Evolution of Regional Convergence Clusters in China’s Energy Markets," Working Papers in Economics 10/14, University of Canterbury, Department of Economics and Finance.
    • Handle: RePEc:cbt:econwp:10/14
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    10. Sheng, Yu & Shi, Xunpeng & Zhang, Dandan, 2014. "Economic growth, regional disparities and energy demand in China," Energy Policy, Elsevier, vol. 71(C), pages 31-39.
    11. Zhang, Xiao-Bing & Fei, Yinxin & Zheng, Ying & Zhang, Lei, 2020. "Price ceilings as focal points to reach price uniformity: Evidence from a Chinese gasoline market," Energy Economics, Elsevier, vol. 92(C).
    12. Zhao, Xueting & Wesley Burnett, J. & Lacombe, Donald J., 2015. "Province-level convergence of China’s carbon dioxide emissions," Applied Energy, Elsevier, vol. 150(C), pages 286-295.
    13. Akhmedjonov, Alisher & Lau, Chi Keung, 2012. "Do energy prices converge across Russian regions?," Economic Modelling, Elsevier, vol. 29(5), pages 1623-1631.
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    15. Zhao, Xueting & Burnett, J. Wesley & Lacombe, Donald J., 2014. "Province-level Convergence of China CO2 Emission Intensity," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169403, Agricultural and Applied Economics Association.
    16. Suvankulov, Farrukh & Lau, Marco Chi Keung & Ogucu, Fatma, 2012. "Price regulation and relative price convergence: Evidence from the retail gasoline market in Canada," Energy Policy, Elsevier, vol. 40(C), pages 325-334.
    17. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    18. Aweng Peter Majok Garang & Hatice Erkekoglu, 2021. "Convergence Triggers in Africa: Evidence from Convergence Clubs and Panel Models," South African Journal of Economics, Economic Society of South Africa, vol. 89(2), pages 218-245, June.
    19. Yanjie Zhu & Les Oxley & Hengyun Ma & Wenchao Wang, 2016. "The emergence of convergent price clusters in China," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(1), pages 69-98, January.
    20. Apergis, Nicholas & Fontini, Fulvio & Inchauspe, Julian, 2017. "Integration of regional electricity markets in Australia: A price convergence assessment," Energy Economics, Elsevier, vol. 62(C), pages 411-418.
    21. Shi, Xunpeng & Rioux, Bertrand & Galkin, Philipp, 2018. "Unintended consequences of China’s coal capacity cut policy," Energy Policy, Elsevier, vol. 113(C), pages 478-486.
    22. Cheong, Tsun Se & Li, Victor Jing & Shi, Xunpeng, 2019. "Regional disparity and convergence of electricity consumption in China: A distribution dynamics approach," China Economic Review, Elsevier, vol. 58(C).

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    More about this item

    Keywords

    China; Energy market; Convergence cluster;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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