As rapid economic growth in China in recent decades, the quality of economic growth through improvement of energy efficiency has attracted great attention. This paper evaluated energy efficiency of 29 provinces in China between 2000 and 2016 based on a global non-radial directional distance function. Moreover, the dynamics of energy efficiency were investigated using the non-radial global Malmquist-type efficiency index. The paper also sheds light on the evolution of inequalities in energy efficiency by decomposing interprovincial inequality into its within-region and between-region components. The findings of the study are as follows. First, the national energy efficiency was 0.49 in 2016, which indicated that 51% improvement could be made to reach the global technology frontier. Tianjin, Shanghai, Jiangsu, Shandong and Guangdong had the best energy efficiency in 2016, while Ningxia and Xinjiang had the lowest performance. Second, the national annual growth rate of energy efficiency was 3.4% between 2011 and 2016, which was a positive sign of energy efficiency improvement. Shandong made the biggest improvement in energy efficiency from 2011 to 2016, with 26.2% annual growth rate. Lastly, within-region inequality saw a decreasing trend after 2010 and was overtaken by between-region inequality in 2016.
References
[1]
British Petroleum (BP) (2018) Statistical Review of World Energy 2018.
https://www.bp.com/content/dam/bp/end/corporate/pdf/energy-economics/statistical-review/bp-stats-review-2018-full-report.pdf
[2]
The Chinese Government (2015) Enhanced Actions on Climate Change: China’s Intended Nationally Determined Contributions.
http://www.scio.gov.cn/xwfbh/xwbfbh/wqfbh/33978/35364/xgzc35370/Document/1514539/151
4539.htm
[3]
Ang, B.W. (1999) Is the Energy Intensity a Less Useful Indicator than the Carbon Factor in the Study of Climate Change? Energy Policy, 27, 943-946.
https://doi.org/10.1016/S0301-4215(99)00084-1
[4]
Sun, J.W. (2005) The Decrease of CO Emission Intensity Is Decarbonization at National and Global Levels. Energy Policy, 33, 975-978.
https://doi.org/10.1016/j.enpol.2003.10.023
[5]
Tol, R.S.J., Pacala, S.W. and Socolow, R.H. (2009) Understanding Long-Term Energy Use and Carbon Dioxide Emissions in the USA. Journal of Policy Modeling, 31, 425-445. https://doi.org/10.2139/ssrn.927741
[6]
Hu, J.-L. and Wang, S.-C. (2006) Total-Factor Energy Efficiency of Regions in China. Energy Policy, 34, 3206-3217. https://doi.org/10.1016/j.enpol.2005.06.015
[7]
Li, K. and Lin, B. (2015) Metafroniter Energy Efficiency with CO2 Emissions and Its Convergence Analysis for China. Energy Economics, 48, 230-241.
https://doi.org/10.1016/j.eneco.2015.01.006
[8]
Wang, H., Zhou, P. and Zhou, D.Q. (2013) Scenario-Based Energy Efficiency and Productivity in China: A Non-Radial Directional Distance Function Analysis. Energy Economics, 40, 795-803. https://doi.org/10.1016/j.eneco.2013.09.030
[9]
Lin, B. and Du, K. (2015) Energy and CO2 Emissions Performance in China’s Regional Economies: Do Market-Oriented Reforms Matter? Energy Policy, 78, 113-124. https://doi.org/10.1016/j.enpol.2014.12.025
[10]
Yao, X., Zhou, H.C., Zhang, A.Z. and Li, A.J. (2015) Regional Energy Efficiency, Carbon Emission Performance and Technology Gaps in China: A Meta-Frontier Non-Radial Directional Distance Function Analysis. Energy Policy, 84, 142-154.
https://doi.org/10.1016/j.enpol.2015.05.001
[11]
Zhang, N., Wang, B. and Chen, Z.F. (2016) Carbon Emissions Reductions and Technology Gaps in the World’s Factory, 1990-2012. Energy Policy, 91, 28-37.
https://doi.org/10.1016/j.enpol.2015.12.042
[12]
Chung, Y.H., Färe, R. and Grosskopf, S. (1997) Productivity and Undesirable Outputs: A Directional Distance Function Approach. Journal of Environmental Management, 51, 229-240. https://doi.org/10.1006/jema.1997.0146
[13]
Weber, W.L. and Domazlicky, B. (2001) Productivity Growth and Pollution in State Manufacturing. Review of Economics and Statistics, 83, 195-199.
https://doi.org/10.1162/rest.2001.83.1.195
[14]
Fare, R., Grosskopf, S. and Pasurka Jr., C.A. (2001) Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth. Journal of Regional Science, 41, 381-409. https://doi.org/10.1111/0022-4146.00223
[15]
Yörük, B.K. and Zaim, O. (2005) Productivity Growth in OECD Countries: A Comparison with Malmquist Indices. Journal of Comparative Economics, 33, 401-420. https://doi.org/10.1016/j.jce.2005.03.011
[16]
Zhang, N., Wang, B. and Liu, Z. (2016) Carbon Emissions Dynamics, Efficiency Gains, and Technological Innovation in China’s Industrial Sectors. Energy, 99, 10-19. https://doi.org/10.1016/j.energy.2016.01.012
[17]
Zhou, P., Ang, B.W. and Wang, H. (2012) Energy and CO2 Emission Performance in Electricity Generation: A Non-Radial Directional Distance Function Approach. European Journal of Operational Research, 221, 625-635.
https://doi.org/10.1016/j.ejor.2012.04.022
[18]
Oh, D. (2010) A Global Malmquist-Luenberger Productivity Index. Journal of Productivity Analysis, 34, 183-197. https://doi.org/10.1007/s11123-010-0178-y
[19]
Cantore, N. and Padilla, E. (2010) Equality and CO Emissions Distribution in Climate Change Integrated Assessment Modelling. Energy, 35, 298-313.
https://doi.org/10.1016/j.energy.2009.09.022
[20]
Cantore, N. (2011) Distributional Aspects of Emissions in Climate Change Integrated Assessment Models. Energy Policy, 39, 2919-2924.
https://doi.org/10.1016/j.enpol.2011.02.070
[21]
Fan, C.C. and Sun, M. (2008) Regional Inequality in China, 1978-2006. Eurasian Geography and Economics, 49, 1-18. https://doi.org/10.2747/1539-7216.49.1.1
[22]
Sauter, C., Grether, J.-M. and Mathys, N.A. (2016) Geographical Spread of Global Emissions: Within-Country Inequalities Are Large and Increasing. Energy Policy, 89, 138-149. https://doi.org/10.1016/j.enpol.2015.11.024
[23]
Alcantara, V. and Duro, J.A. (2004) Inequality of Energy Intensities across OECD Countries: A Note. Energy Policy, 32, 1257-1260.
https://doi.org/10.1016/S0301-4215(03)00095-8
[24]
Clarke-Sather, A., Qu, J., Wang, Q., Zeng, J. and Li, Y. (2011) Carbon Inequality at the Sub-National Scale: A Case Study of Provincial-Level Inequality in CO2 Emissions in China 1997-2007. Energy Policy, 39, 5420-5428.
https://doi.org/10.1016/j.enpol.2011.05.021
[25]
Padilla, E. and Duro, J.A. (2013) Explanatory Factors of CO2 per Capita Emission Inequality in the European Union. Energy Policy, 62, 1320-1328.
https://doi.org/10.1016/j.enpol.2013.07.018
[26]
Färe, R. and Grosskopf, S. (2004) Modeling Undesirable Factors in Efficiency Evaluation: Comment. European Journal of Operational Research, 157, 242-245.
https://doi.org/10.1016/S0377-2217(03)00191-7
[27]
Shan, Y.L., Guan, D.B., Zheng, H.R., Ou, J.M., Li, Y., Meng, J., Mi, Z.F., Liu, Z. and Zhang, Q. (2018) China CO2 Emission Accounts 1997-2015. Scientific Data, 5, Article No. 170201. https://doi.org/10.1038/sdata.2017.201
