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Provincial green economic efficiency of China: A non-separable input–output SBM approach

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  • Tao, Xueping
  • Wang, Ping
  • Zhu, Bangzhu

Abstract

Aiming at the undesirable output (CO2 emission) and non-separable inputs and outputs, we employ a non-separable input/output SBM model to measure China’s provincial green economic efficiency during 1995–2012. Empirical results indicate that (i) there are larger interregional differences in green economic efficiencies. The highest efficiency of 0.7339 is recorded at the southern coastal region, followed by those at the eastern coastal and northern coastal regions. The lowest efficiency only reaches 0.3049 at the northwestern region. (ii) Energy and CO2 emission are the key factors for green economic efficiencies. (iii) Different regions have different energy-saving and CO2 emission reduction potentials. The southern coastal region should at least save energy of 4.7million tons of standard coal. The middle Yellow River, northern coastal and northeast regions should save energy as much as 62, 60, 51million tons of standard coal. CO2 emission excess in the middle Yellow River region reaches 450million tons in 2012, while CO2 emission excess in the southern coastal region is only 12million tons. Finally, we propose some target policies to improve China’s regional green economic efficiencies.

Suggested Citation

  • Tao, Xueping & Wang, Ping & Zhu, Bangzhu, 2016. "Provincial green economic efficiency of China: A non-separable input–output SBM approach," Applied Energy, Elsevier, vol. 171(C), pages 58-66.
  • Handle: RePEc:eee:appene:v:171:y:2016:i:c:p:58-66
    DOI: 10.1016/j.apenergy.2016.02.133
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    References listed on IDEAS

    as
    1. Cheng, Gang & Zervopoulos, Panagiotis D., 2014. "Estimating the technical efficiency of health care systems: A cross-country comparison using the directional distance function," European Journal of Operational Research, Elsevier, vol. 238(3), pages 899-910.
    2. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    3. Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
    4. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    5. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    6. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    7. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    8. Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," European Journal of Operational Research, Elsevier, vol. 80(3), pages 474-499, February.
    9. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    10. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    11. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Mohammadi, Ali, 2011. "Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis," Energy, Elsevier, vol. 36(2), pages 909-916.
    12. Henry Tulkens & Philippe van den Eeckaut, 1993. "Non Parametric Efficiency, Progress and Regress Measures for Panel Data: Methodological Aspects," CESifo Working Paper Series 38, CESifo Group Munich.
    13. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    14. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    15. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    16. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    17. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
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    Cited by:

    1. Na, Joon-Ho & Choi, A-Young & Ji, Jianhua & Zhang, Dali, 2017. "Environmental efficiency analysis of Chinese container ports with CO2 emissions: An inseparable input-output SBM model," Journal of Transport Geography, Elsevier, vol. 65(C), pages 13-24.
    2. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    3. Xin ZHAO & Yong PENG & Yuemei XUE & Shun YUAN, 2016. "Spatial Patterns of Ocean Economic Efficiency and their Influencing Factors in Chinese Coastal Regions," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 35-49, December.
    4. Jadwiga R. Ziolkowska, 2016. "Socio-Economic Implications of Drought in the Agricultural Sector and the State Economy," Economies, MDPI, Open Access Journal, vol. 4(3), pages 1-11, September.
    5. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    6. Wu, Ge & Baležentis, Tomas & Sun, Chuanwang & Xu, Shuhua, 2019. "Source control or end-of-pipe control: Mitigating air pollution at the regional level from the perspective of the Total Factor Productivity change decomposition," Energy Policy, Elsevier, vol. 129(C), pages 1227-1239.

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