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Measuring Energy Congestion in Chinese Industrial Sectors: A Slacks-Based DEA Approach

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  • F. Wu
  • P. Zhou
  • D. Zhou

Abstract

Measuring the magnitude of energy congestion provides useful information for determining the optimal level of energy input with reference to other inputs. This paper clarifies the concept of energy congestion and adapts a slacks-based DEA method to examine the energy congestion effect in Chinese industrial sectors over time. Our empirical results show that Chinese industrial sectors showed an increasing trend in energy congestion. The size of energy congestion effect varied across different provinces and regions. The central area had a significantly higher amount of energy congestion than that in west area, while the east area registered for the lowest energy congestion inefficiency. On average, 32 % of the energy consumption in Chinese industry was excessively used. A multiple regression analysis within a panel data analysis framework shows that the total energy consumption and industrial value added per capita have a positive while total-factor energy efficiency has a negative effect on energy congestion. Copyright Springer Science+Business Media New York 2015

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  • F. Wu & P. Zhou & D. Zhou, 2015. "Measuring Energy Congestion in Chinese Industrial Sectors: A Slacks-Based DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 479-494, October.
    • Handle: RePEc:kap:compec:v:46:y:2015:i:3:p:479-494
    DOI: 10.1007/s10614-015-9499-2
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    Cited by:

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    7. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    8. Pang, Qinghua & Qiu, Man & Zhang, Lina & Chiu, Yung-ho, 2024. "Congestion effects of energy and its influencing factors: China's transportation sector," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    9. Wu, F. & Zhou, P. & Zhou, D.Q., 2020. "Modeling carbon emission performance under a new joint production technology with energy input," Energy Economics, Elsevier, vol. 92(C).
    10. Hu, Jin-Li & Chang, Ming-Chung & Tsay, Hui-Wen, 2017. "The congestion total-factor energy efficiency of regions in Taiwan," Energy Policy, Elsevier, vol. 110(C), pages 710-718.

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