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Trans-Provincial Convergence of per Capita Energy Consumption in Urban China, 1990–2015

Author

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  • Chao Bao

    (Institute of Geographic Sciences and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
    Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Hongjie Wang

    (Institute of Geographic Sciences and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
    Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Recognizing the change in regulation of energy consumption may help China to control total energy consumption and realize sustainable development during rapid urbanization and industrialization. This paper re-examined the trans-provincial convergence of per capita energy consumption from 1990–2015 using five different kinds of methods for 30 Chinese provinces. Results show that per capita energy consumption across Chinese provinces was convergent. However, the results obtained by different methods were slightly different. First, it shows a weak beta-unconditional convergence during the entire period, as well as a significant beta-unconditional and conditional piecewise convergence from 1990–2000 and 2001–2015. Second, it shows a significant sigma-convergence indicated by a marked decrease in the standard deviation of logarithm (SDlog) and the coefficient of variation (CV). Third, the kernel density curve became narrower during 1990–2015, indicating that the per capita energy consumption of each Chinese province converged to a common equilibrium level, which was about 80% of the national average. Fourth, the intra-distributional mobility index implied a weak gamma-convergence. Fifth, the first difference of DF (Dickey-Fuller), ADF (Augmented Dickey-Fuller), and PP (Phillips-Perron) unit-root tests all suggested a stochastic convergence. On the whole, the results from this paper contribute to a more in-depth understanding of the status quo of per capita energy consumption in China, as well as a meaningful implication for differentiated energy policies and sustainable development strategies.

Suggested Citation

  • Chao Bao & Hongjie Wang, 2019. "Trans-Provincial Convergence of per Capita Energy Consumption in Urban China, 1990–2015," Sustainability, MDPI, vol. 11(5), pages 1-15, March.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1431-:d:212071
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    as
    1. Jakob, Michael & Haller, Markus & Marschinski, Robert, 2012. "Will history repeat itself? Economic convergence and convergence in energy use patterns," Energy Economics, Elsevier, vol. 34(1), pages 95-104.
    2. Mohammadi, Hassan & Ram, Rati, 2017. "Convergence in energy consumption per capita across the US states, 1970–2013: An exploration through selected parametric and non-parametric methods," Energy Economics, Elsevier, vol. 62(C), pages 404-410.
    3. Herrerias, M.J. & Aller, Carlos & Ordóñez, Javier, 2017. "Residential energy consumption: A convergence analysis across Chinese regions," Energy Economics, Elsevier, vol. 62(C), pages 371-381.
    4. Payne, James E. & Vizek, Maruška & Lee, Junsoo, 2017. "Is there convergence in per capita renewable energy consumption across U.S. States? Evidence from LM and RALS-LM unit root tests with breaks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 715-728.
    5. Wu, Jianxin & Wu, Yanrui & Guo, Xiumei & Cheong, Tsun Se, 2016. "Convergence of carbon dioxide emissions in Chinese cities: A continuous dynamic distribution approach," Energy Policy, Elsevier, vol. 91(C), pages 207-219.
    6. Chao Bao & Jianjun Zou, 2017. "Exploring the Coupling and Decoupling Relationships between Urbanization Quality and Water Resources Constraint Intensity: Spatiotemporal Analysis for Northwest China," Sustainability, MDPI, vol. 9(11), pages 1-17, October.
    7. Paramati, Sudharshan Reddy & Alam, Md Samsul & Apergis, Nicholas, 2018. "The role of stock markets on environmental degradation: A comparative study of developed and emerging market economies across the globe," Emerging Markets Review, Elsevier, vol. 35(C), pages 19-30.
    8. Paramati, Sudharshan Reddy & Bhattacharya, Mita & Ozturk, Ilhan & Zakari, Abdulrasheed, 2018. "Determinants of energy demand in African frontier market economies: An empirical investigation," Energy, Elsevier, vol. 148(C), pages 123-133.
    9. 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.
    10. Feng Dong & Bolin Yu & Jixiong Zhang, 2018. "What Contributes to Regional Disparities of Energy Consumption in China? Evidence from Quantile Regression-Shapley Decomposition Approach," Sustainability, MDPI, vol. 10(6), pages 1-26, May.
    11. Mulder, Peter & de Groot, Henri L.F., 2012. "Structural change and convergence of energy intensity across OECD countries, 1970–2005," Energy Economics, Elsevier, vol. 34(6), pages 1910-1921.
    12. Mohammadi, Hassan & Ram, Rati, 2012. "Cross-country convergence in energy and electricity consumption, 1971–2007," Energy Economics, Elsevier, vol. 34(6), pages 1882-1887.
    13. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    14. Jingqi Sun & Jing Shi & Boyang Shen & Shuqing Li & Yuwei Wang, 2018. "Nexus among Energy Consumption, Economic Growth, Urbanization and Carbon Emissions: Heterogeneous Panel Evidence Considering China’s Regional Differences," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    15. Fallahi, Firouz, 2017. "Stochastic convergence in per capita energy use in world," Energy Economics, Elsevier, vol. 65(C), pages 228-239.
    16. Meng, Ming & Payne, James E. & Lee, Junsoo, 2013. "Convergence in per capita energy use among OECD countries," Energy Economics, Elsevier, vol. 36(C), pages 536-545.
    17. Tian, Xu & Zhang, Xiaoheng & Zhou, Yingheng & Yu, Xiaohua, 2016. "Regional income inequality in China revisited: A perspective from club convergence," Economic Modelling, Elsevier, vol. 56(C), pages 50-58.
    18. Mishra, Vinod & Smyth, Russell, 2014. "Convergence in energy consumption per capita among ASEAN countries," Energy Policy, Elsevier, vol. 73(C), pages 180-185.
    19. Zhao, Haoran & Guo, Sen & Zhao, Huiru, 2019. "Provincial energy efficiency of China quantified by three-stage data envelopment analysis," Energy, Elsevier, vol. 166(C), pages 96-107.
    20. Joseph E. Aldy, 2007. "Divergence in State-Level Per Capita Carbon Dioxide Emissions," Land Economics, University of Wisconsin Press, vol. 83(3), pages 353-369.
    21. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    22. Sheng, Pengfei & Guo, Xiaohui, 2018. "Energy consumption associated with urbanization in China: Efficient- and inefficient-use," Energy, Elsevier, vol. 165(PB), pages 118-125.
    23. Bhattacharya, Mita & Awaworyi Churchill, Sefa & Paramati, Sudharshan Reddy, 2017. "The dynamic impact of renewable energy and institutions on economic output and CO2 emissions across regions," Renewable Energy, Elsevier, vol. 111(C), pages 157-167.
    24. Ali M. Kutan & Sudharshan Reddy Paramati & Mallesh Ummalla & Abdulrasheed Zakari, 2018. "Financing Renewable Energy Projects in Major Emerging Market Economies: Evidence in the Perspective of Sustainable Economic Development," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1761-1777, June.
    25. Jiang, Zhujun & Lin, Boqiang, 2012. "China's energy demand and its characteristics in the industrialization and urbanization process," Energy Policy, Elsevier, vol. 49(C), pages 608-615.
    26. Liddle, Brantley, 2010. "Revisiting world energy intensity convergence for regional differences," Applied Energy, Elsevier, vol. 87(10), pages 3218-3225, October.
    27. Herrerias, M.J., 2012. "World energy intensity convergence revisited: A weighted distribution dynamics approach," Energy Policy, Elsevier, vol. 49(C), pages 383-399.
    28. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    29. Hao, Yu & Peng, Hui, 2017. "On the convergence in China's provincial per capita energy consumption: New evidence from a spatial econometric analysis," Energy Economics, Elsevier, vol. 68(C), pages 31-43.
    30. Bao, Chao & Fang, Chuang-lin, 2013. "Geographical and environmental perspectives for the sustainable development of renewable energy in urbanizing China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 464-474.
    31. Jiang, Lei & Folmer, Henk & Ji, Minhe & Zhou, P., 2018. "Revisiting cross-province energy intensity convergence in China: A spatial panel analysis," Energy Policy, Elsevier, vol. 121(C), pages 252-263.
    32. Marco Barassi & Matthew Cole & Robert Elliott, 2011. "The Stochastic Convergence of CO 2 Emissions: A Long Memory Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 49(3), pages 367-385, July.
    33. Wang, Yiming & Zhang, Pei & Huang, Dake & Cai, Changda, 2014. "Convergence behavior of carbon dioxide emissions in China," Economic Modelling, Elsevier, vol. 43(C), pages 75-80.
    34. Maza, Adolfo & Villaverde, José, 2008. "The world per capita electricity consumption distribution: Signs of convergence?," Energy Policy, Elsevier, vol. 36(11), pages 4255-4261, November.
    35. Herrerias, M.J. & Liu, G., 2013. "Electricity intensity across Chinese provinces: New evidence on convergence and threshold effects," Energy Economics, Elsevier, vol. 36(C), pages 268-276.
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