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Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for social sustainability in China

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  • Sueyoshi, Toshiyuki
  • Yuan, Yan

Abstract

This study discusses the concept of natural and managerial disposability from their economic and methodological implications on social sustainability development. Then, it explores their analytical linkages to a concept on “congestion.” The concept is classified into Undesirable Congestion (UC) under natural disposability and Desirable Congestion (DC) under managerial disposability. Considering the two disposability concepts, this study compares between Returns to Damage (RTD) under UC and Damages to Return (DTR) under DC. Conceptually, UC and DC are conceptually different from RTD and DTR although they are closely related to each other group. An occurrence of the former measures is identified by a single negative multiplier (i.e. dual variable). In contrast, the latter measures are associated with multiple negative multipliers and an intercept of a supporting hyperplane on a production and pollution possibility set. Thus, an occurrence of UC and DC is a necessary condition, but not a sufficient condition on RTD and DTR, respectively, in terms of the number of negative multipliers on production factors. To document the practicality of the proposed approach, this study applies it to Chinese economic and environmental assessment for its economic and energy planning for social sustainability development. This study identifies four important findings: First, the Chinese government has historically paid attention to the economic prosperity, but not paying serious attention on the environmental pollution (e.g., air pollution). Second, there was an increasing trend in improving the two components (i.e., economic and environmental performance measures) regarding social sustainability. Third, China's economic and energy policy concerns have been focused upon well-developed municipalities (e.g., Beijing and Shanghai) and large provinces. Therefore, it is an important strategy for the government to allocate economic and energy resources to other provinces so that China can reduce the industrial and regional imbalances. As a result, China can enhance the level of social sustainability. Finally, the municipalities need strict regulation on traffic control in these metropolitan areas and a fuel mix shift from coal combustion to natural gas and renewable energies (e.g., solar, water, and nuclear generations). The fuel mix strategy, along with the structure change (e.g., from manufacturing to service and from public to private energy firms), will be a major industrial policy issue for China in near future.

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  • Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
  • Handle: RePEc:eee:eneeco:v:56:y:2016:i:c:p:288-309
    DOI: 10.1016/j.eneco.2016.02.014
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    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Toshiyuki Sueyoshi & Yan Yuan & Aijun Li & Daoping Wang, 2017. "Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    3. Wenhui Zhao & Ye Qiu & Wei Lu & Puyu Yuan, 2022. "Input–Output Efficiency of Chinese Power Generation Enterprises and Its Improvement Direction-Based on Three-Stage DEA Model," Sustainability, MDPI, vol. 14(12), pages 1-14, June.
    4. Jie Liu & Chunhui Yuan & Xiaolong Li, 2019. "The Environmental Assessment on Chinese Logistics Enterprises Based on Non-Radial DEA," Energies, MDPI, vol. 12(24), pages 1-18, December.
    5. Ren, Xian-tong & Fukuyama, Hirofumi & Yang, Guo-liang, 2022. "Eliminating congestion by increasing inputs in R&D activities of Chinese universities," Omega, Elsevier, vol. 110(C).
    6. Toshiyuki Sueyoshi & Ruchuan Zhang & Aijun Li, 2023. "Measuring and Analyzing Operational Efficiency and Returns to Scale in a Time Horizon: Assessment of China’s Electricity Generation & Transmission at Provincial Levels," Energies, MDPI, vol. 16(2), pages 1-23, January.
    7. Jinchao Li & Yuwei Xiang & Huanyu Jia & Lin Chen, 2018. "Analysis of Total Factor Energy Efficiency and Its Influencing Factors on Key Energy-Intensive Industries in the Beijing-Tianjin-Hebei Region," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
    8. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    9. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    10. Sueyoshi, Toshiyuki & Wang, Derek, 2018. "DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon," Energy Economics, Elsevier, vol. 72(C), pages 276-289.
    11. Sueyoshi, Toshiyuki & Goto, Mika, 2019. "The intermediate approach to sustainability enhancement and scale-related measures in environmental assessment," European Journal of Operational Research, Elsevier, vol. 276(2), pages 744-756.
    12. Sun, Chuanwang & Liu, Xiaohong & Li, Aijun, 2018. "Measuring unified efficiency of Chinese fossil fuel power plants: Intermediate approach combined with group heterogeneity and window analysis," Energy Policy, Elsevier, vol. 123(C), pages 8-18.
    13. Aizhen Zhang & Aijun Li & Yaping Gao, 2018. "Social Sustainability Assessment across Provinces in China: An Analysis of Combining Intermediate Approach with Data Envelopment Analysis (DEA) Window Analysis," Sustainability, MDPI, vol. 10(3), pages 1-24, March.
    14. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    15. Sueyoshi, Toshiyuki & Yuan, Yan & Li, Aijun & Wang, Daoping, 2017. "Methodological comparison among radial, non-radial and intermediate approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 67(C), pages 439-453.
    16. Sueyoshi, Toshiyuki & Wang, Derek, 2017. "Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California," Energy Economics, Elsevier, vol. 65(C), pages 389-398.
    17. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations," Energy Economics, Elsevier, vol. 56(C), pages 270-287.
    18. Meiqiang Wang & Yingwen Chen & Zhixiang Zhou, 2020. "A Novel Stochastic Two-Stage DEA Model for Evaluating Industrial Production and Waste Gas Treatment Systems," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    19. Li, Aijun & Zhang, Aizhen & Huang, Huijie & Yao, Xin, 2018. "Measuring unified efficiency of fossil fuel power plants across provinces in China: An analysis based on non-radial directional distance functions," Energy, Elsevier, vol. 152(C), pages 549-561.
    20. Zhang, Yue-Jun & Liu, Jing-Yue & Su, Bin, 2020. "Carbon congestion effects in China's industry: Evidence from provincial and sectoral levels," Energy Economics, Elsevier, vol. 86(C).
    21. Xiaoyang Zhou & Hao Chen & Hao Wang & Benjamin Lev & Lifang Quan, 2019. "Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment," Energies, MDPI, vol. 12(18), pages 1-20, September.

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    Keywords

    Energy; Congestion; Returns to damage; Damages to return; Industrial policy;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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