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Congestion effects of energy and its influencing factors: China's transportation sector

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  • Pang, Qinghua
  • Qiu, Man
  • Zhang, Lina
  • Chiu, Yung-ho

Abstract

This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:soceps:v:92:y:2024:i:c:s0038012124000491
    DOI: 10.1016/j.seps.2024.101850
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    as
    1. Bilgen, S., 2014. "Structure and environmental impact of global energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 890-902.
    2. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    3. Song, Yao-yao & Li, Jing-jing & Wang, Jin-li & Yang, Guo-liang & Chen, Zhenling, 2022. "Eco-efficiency of Chinese transportation industry: A DEA approach with non-discretionary input," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Nasreen, Samia & Mbarek, Mounir Ben & Atiq-ur-Rehman, Muhammad, 2020. "Long-run causal relationship between economic growth, transport energy consumption and environmental quality in Asian countries: Evidence from heterogeneous panel methods," Energy, Elsevier, vol. 192(C).
    5. Xia, Yin-Shuang & Sun, Lu-Xuan & Feng, Chao, 2022. "What causes spatial inequalities of low-carbon development in China's transport sector? A newly proposed meta-frontier DEA-based decomposition approach," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    6. Yi Xu & Xiaojuan Li & Daqing Gong, 2021. "Evaluation and Influencing Factors of Transportation Industry Energy Efficiency of Changjiang Economic Zone," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-9, November.
    7. Modarres, Ali, 2013. "Commuting and energy consumption: toward an equitable transportation policy," Journal of Transport Geography, Elsevier, vol. 33(C), pages 240-249.
    8. Zhao, Min & Sun, Tao, 2022. "Dynamic spatial spillover effect of new energy vehicle industry policies on carbon emission of transportation sector in China," Energy Policy, Elsevier, vol. 165(C).
    9. Patrick Puhani, 2000. "The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    10. 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.
    11. Cooper, W. W. & Deng, Honghui & Huang, Zhimin M. & Li, Susan X., 2002. "A one-model approach to congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 36(4), pages 231-238, December.
    12. Liddle, Brantley & Lung, Sidney, 2013. "The long-run causal relationship between transport energy consumption and GDP: Evidence from heterogeneous panel methods robust to cross-sectional dependence," Economics Letters, Elsevier, vol. 121(3), pages 524-527.
    13. Shao, Shuai & Tan, Zhijia & Liu, Zhiyuan & Shang, Wenlong, 2022. "Balancing the GHG emissions and operational costs for a mixed fleet of electric buses and diesel buses," Applied Energy, Elsevier, vol. 328(C).
    14. Arabatzis, G. & Malesios, Ch., 2011. "An econometric analysis of residential consumption of fuelwood in a mountainous prefecture of Northern Greece," Energy Policy, Elsevier, vol. 39(12), pages 8088-8097.
    15. Zhang, Yue-Jun & Jiang, Lin & Shi, Wei, 2020. "Exploring the growth-adjusted energy-emission efficiency of transportation industry in China," Energy Economics, Elsevier, vol. 90(C).
    16. Bao, Zhaoyao & Li, Jiapei & Bai, Xuehan & Xie, Chi & Chen, Zhibin & Xu, Min & Shang, Wen-Long & Li, Hailong, 2023. "An optimal charging scheduling model and algorithm for electric buses," Applied Energy, Elsevier, vol. 332(C).
    17. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    18. Zhang, Yue-Jun & Peng, Hua-Rong & Liu, Zhao & Tan, Weiping, 2015. "Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach," Energy Policy, Elsevier, vol. 87(C), pages 303-313.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions," Energy Economics, Elsevier, vol. 34(3), pages 700-713.
    20. Fare, Rolf & Svensson, Leif, 1980. "Congestion of Production Factors," Econometrica, Econometric Society, vol. 48(7), pages 1745-1753, November.
    21. Wang, Bo & Sun, Yefei & Chen, Qingxiang & Wang, Zhaohua, 2018. "Determinants analysis of carbon dioxide emissions in passenger and freight transportation sectors in China," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 127-132.
    22. Cooper, W. W. & Deng, Honghui & Gu, Bisheng & Li, Shanling & Thrall, R. M., 2001. "Using DEA to improve the management of congestion in Chinese industries (1981-1997)," Socio-Economic Planning Sciences, Elsevier, vol. 35(4), pages 227-242, December.
    23. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    24. Su, Qing, 2011. "The effect of population density, road network density, and congestion on household gasoline consumption in U.S. urban areas," Energy Economics, Elsevier, vol. 33(3), pages 445-452, May.
    25. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries," Energy Economics, Elsevier, vol. 34(3), pages 686-699.
    26. Thapa, Samir & Morrison, Mark & Parton, Kevin A, 2021. "Willingness to pay for domestic biogas plants and distributing carbon revenues to influence their purchase: A case study in Nepal," Energy Policy, Elsevier, vol. 158(C).
    27. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
    28. Sueyoshi, Toshiyuki & Goto, Mika, 2018. "Resource utilization for sustainability enhancement in Japanese industries," Applied Energy, Elsevier, vol. 228(C), pages 2308-2320.
    29. 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.
    30. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
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