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Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model

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  • Barros, Carlos Pestana
  • Chen, Zhongfei
  • Managi, Shunsuke
  • Antunes, Olinda Sequeira

Abstract

This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000–2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed.

Suggested Citation

  • Barros, Carlos Pestana & Chen, Zhongfei & Managi, Shunsuke & Antunes, Olinda Sequeira, 2013. "Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model," Energy Economics, Elsevier, vol. 36(C), pages 511-517.
    • Handle: RePEc:eee:eneeco:v:36:y:2013:i:c:p:511-517
    DOI: 10.1016/j.eneco.2012.10.007
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    Cited by:

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    4. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    5. 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.
    6. Shunsuke Managi & George Halkos, 2015. "Production analysis in environmental, resource, and infrastructure evaluation," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 4(1), pages 1-4, December.
    7. Du, Limin & He, Yanan & Yan, Jianye, 2013. "The effects of electricity reforms on productivity and efficiency of China's fossil-fired power plants: An empirical analysis," Energy Economics, Elsevier, vol. 40(C), pages 804-812.
    8. Barros, C.P. & Wanke, Peter & Dumbo, Silvestre & Manso, Jose Pires, 2017. "Efficiency in angolan hydro-electric power station: A two-stage virtual frontier dynamic DEA and simplex regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 588-596.
    9. 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.

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    More about this item

    Keywords

    Efficiency; Electricity utilities; China;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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