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A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies

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  1. Economou, Polychronis & Malefaki, Sonia & Kounetas, Konstantinos, 2019. "Productive Performance and Technology Gaps using a Bayesian Metafrontier Production Function: A cross-country comparison," MPRA Paper 94462, University Library of Munich, Germany.
  2. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
  3. Filippini, M. & Greene, W. & Masiero, G., 2018. "Persistent and transient productive inefficiency in a regulated industry: electricity distribution," Energy Economics, Elsevier, vol. 69(C), pages 325-334.
  4. Albalate, Daniel & Rosell, Jordi, 2019. "On the efficiency of toll motorway companies in Spain," Research in Transportation Economics, Elsevier, vol. 76(C).
  5. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
  6. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
  7. Xin Long Xu & Sen Qiao & Hsing Hung Chen, 2020. "Exploring the efficiency of new energy generation: Evidence from OECD and non-OECD countries," Energy & Environment, , vol. 31(3), pages 389-404, May.
  8. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
  9. Zhang, Ning & Wang, Bing & Chen, Zhongfei, 2016. "Carbon emissions reductions and technology gaps in the world's factory, 1990–2012," Energy Policy, Elsevier, vol. 91(C), pages 28-37.
  10. Cao, Hongjian & Wang, Bizhe & Li, Ke, 2021. "Regulatory policy and misallocation: A new perspective based on the productivity effect of cleaner production standards in China's energy firms," Energy Policy, Elsevier, vol. 152(C).
  11. Elwell, Clifford A. & Biddulph, Phillip & Lowe, Robert & Oreszczyn, Tadj, 2015. "Determining the impact of regulatory policy on UK gas use using Bayesian analysis on publicly available data," Energy Policy, Elsevier, vol. 86(C), pages 770-783.
  12. Massimo Filippini & Thomas Geissmann & William H. Greene, 2018. "Persistent and transient cost efficiency—an application to the Swiss hydropower sector," Journal of Productivity Analysis, Springer, vol. 49(1), pages 65-77, February.
  13. Yongrok Choi & Yunning Ma & Yu Zhao & Hyoungsuk Lee, 2023. "Inequality in Fossil Fuel Power Plants in China: A Perspective of Efficiency and Abatement Cost," Sustainability, MDPI, vol. 15(5), pages 1-15, March.
  14. Daniel Albalate & Jordi Rosell, 2016. "Persistent and transient efficiency on the stochastic production and cost frontiers – an application to the motorway sector," Working Papers XREAP2016-04, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2016.
  15. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
  16. Mingyue Wang & Yu Liu & Yawen Liu & Shunxiang Yang & Lingyu Yang, 2018. "Assessing Multiple Pathways for Achieving China’s National Emissions Reduction Target," Sustainability, MDPI, vol. 10(7), pages 1-16, June.
  17. Lin, Boqiang & Xie, Yongjing, 2023. "Does digital transformation improve the operational efficiency of Chinese power enterprises?," Utilities Policy, Elsevier, vol. 82(C).
  18. Khalili-Damghani, Kaveh & Tavana, Madjid & Santos-Arteaga, Francisco J. & Mohtasham, Sima, 2015. "A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry," Energy Economics, Elsevier, vol. 51(C), pages 320-328.
  19. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
  20. Li, Ke & Lin, Boqiang, 2017. "An application of a double bootstrap to investigate the effects of technological progress on total-factor energy consumption performance in China," Energy, Elsevier, vol. 128(C), pages 575-585.
  21. Shrabana Tripathi, 2025. "Ownership Structure and Technical Efficiency: Evidence from the Indian Utility Sector," SN Operations Research Forum, Springer, vol. 6(1), pages 1-25, March.
  22. Haider, Salman & Mishra, Prajna Paramita, 2021. "Does innovative capability enhance the energy efficiency of Indian Iron and Steel firms? A Bayesian stochastic frontier analysis," Energy Economics, Elsevier, vol. 95(C).
  23. Liu, Xiao & Hang, Ye & Wang, Qunwei & Chiu, Ching-Ren & Zhou, Dequn, 2022. "The role of energy consumption in global carbon intensity change: A meta-frontier-based production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 109(C).
  24. Guangming Rao & Bin Su & Jinlian Li & Yong Wang & Yanhua Zhou & Zhaolin Wang, 2019. "Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China," Sustainability, MDPI, vol. 11(23), pages 1-28, November.
  25. Dong, Hanjiang & Wang, Xiuyuan & Cui, Ziyu & Zhu, Jizhong & Li, Shenglin & Yu, Changyuan, 2025. "Machine learning-enhanced Data Envelopment Analysis via multi-objective variable selection for benchmarking combined electricity distribution performance," Energy Economics, Elsevier, vol. 143(C).
  26. Zhang, H. & Fan, L.W. & Zhou, P., 2020. "Handling heterogeneity in frontier modeling of city-level energy efficiency: The case of China," Applied Energy, Elsevier, vol. 279(C).
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