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

被引:12
作者
Barros, Carlos Pestana [1 ,2 ]
Chen, Zhongfei [3 ]
Managi, Shunsuke [4 ]
Antunes, Olinda Sequeira [1 ,2 ]
机构
[1] Univ Tecn Lisboa, Inst Super Econ & Gestao, P-1249078 Lisbon, Portugal
[2] UECE Res Unit Complex & Econ, P-1249078 Lisbon, Portugal
[3] Sun Yat Sen Univ, Lingnan Coll, Guangzhou 510275, Guangdong, Peoples R China
[4] Tohoku Univ, Grad Sch Environm Studies, Aoba Ku, Sendai, Miyagi 9808579, Japan
关键词
Efficiency; Electricity utilities; China; STOCHASTIC FRONTIER ANALYSIS; ELECTRICITY DISTRIBUTION; ENERGY EFFICIENCY; UNOBSERVED HETEROGENEITY; EMISSION PERFORMANCE; TECHNICAL EFFICIENCY; EMPIRICAL-ANALYSIS; GENERATING PLANTS; POWER-GENERATION; CO2; EMISSIONS;
D O I
10.1016/j.eneco.2012.10.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:511 / 517
页数:7
相关论文
共 52 条
[31]  
Kumbhakar S. C., 2003, STOCHASTIC FRONTIER
[32]   Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model [J].
Kuosmanen, Timo .
ENERGY ECONOMICS, 2012, 34 (06) :2189-2199
[33]   Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry [J].
Managi, Shunsuke ;
Opaluch, James J. ;
Jin, Di ;
Grigalunas, Thomas A. .
ECOLOGICAL ECONOMICS, 2006, 60 (01) :204-215
[34]   EFFICIENCY ESTIMATION FROM COBB-DOUGLAS PRODUCTION FUNCTIONS WITH COMPOSED ERROR [J].
MEEUSEN, W ;
VANDENBROECK, J .
INTERNATIONAL ECONOMIC REVIEW, 1977, 18 (02) :435-445
[35]   Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry [J].
Nakano, Makiko ;
Managi, Shunsuke .
ENERGY POLICY, 2008, 36 (01) :201-209
[36]  
Orea L., 2004, Empirical Economics, V29, P169, DOI [DOI 10.1007/S00181-003-0184-2, 10.1007/s00181-003-0184-2]
[37]   HOW MUCH DOES INDUSTRY MATTER [J].
RUMELT, RP .
STRATEGIC MANAGEMENT JOURNAL, 1991, 12 (03) :167-185
[38]   An analysis of factors that influence the technical efficiency of Malaysian thermal power plants [J].
See, Kok Fong ;
Coelli, Tim .
ENERGY ECONOMICS, 2012, 34 (03) :677-685
[39]  
Sheppard R.W., 1970, Theory of cost and production
[40]   Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs [J].
Shi, Guang-Ming ;
Bi, Jun ;
Wang, Jin-Nan .
ENERGY POLICY, 2010, 38 (10) :6172-6179