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Relative Performance of U.S. and Japanese Electricity Distribution: An Application of Stochastic Frontier Analysis

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  • Toru Hattori

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Abstract

This paper estimates and compares the technical efficiency of the U.S. and Japanese electric utilities during the period 1982–1997 using a stochastic frontier analysis. Our focus is on electricity distribution services of major investor-owned utilities. We employ translog input distance functions to represent the technology of electricity distribution. Empirical results show that after controlling for environmental variables, on average, the Japanese electric utilities are more efficient. It is shown, however, that some U.S. utilities are as efficient as the most efficient Japanese utilities, indicating that the estimated frontier is not necessarily dominated by Japanese utilities. Copyright Kluwer Academic Publishers 2002

Suggested Citation

  • Toru Hattori, 2002. "Relative Performance of U.S. and Japanese Electricity Distribution: An Application of Stochastic Frontier Analysis," Journal of Productivity Analysis, Springer, vol. 18(3), pages 269-284, November.
  • Handle: RePEc:kap:jproda:v:18:y:2002:i:3:p:269-284 DOI: 10.1023/A:1020695709797
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    References listed on IDEAS

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    1. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    2. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, pages 325-332.
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    4. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    5. 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.
    6. Martín Rossi, 2015. "Using Labor Productivity Change Estimates as an Input for X-Factors in Price-Cap Regulation," Working Papers 118, Universidad de San Andres, Departamento de Economia, revised Feb 2015.
    7. Vaninsky, Alexander, 2010. "Prospective national and regional environmental performance: Boundary estimations using a combined data envelopment – stochastic frontier analysis approach," Energy, Elsevier, vol. 35(9), pages 3657-3665.
    8. Dong, Feng & Li, Xiaohui & Long, Ruyin & Liu, Xiaoyan, 2013. "Regional carbon emission performance in China according to a stochastic frontier model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 525-530.
    9. Li, Ming-Jia & Tao, Wen-Quan, 2017. "Review of methodologies and polices for evaluation of energy efficiency in high energy-consuming industry," Applied Energy, Elsevier, pages 203-215.
    10. 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.
    11. Darío Ezequiel Díaz, 2013. "La Distribución Eléctrica en Argentina y su Eficiencia Técnica:Una Aplicación del Análisis de Fronteras Estocásticas (SFA) Utilizando Funciones Distancia," Revista de Economía y Estadística, Universidad Nacional de Córdoba, Facultad de Ciencias Económicas, Instituto de Economía y Finanzas, vol. 0(1), pages 85-118, January.
    12. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    13. Yeinni Andrea Patiño Moya & Gustavo Adolfo Gómez Flórez & Emma Osorio Medina, 2010. "Evaluación del desempeño del sector de distribución de electricidad en Colombia: una aplicación del análisis de frontera estocástica," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE, vol. 28(62), pages 70-123, June.
    14. Gonzalez, Maria A & Lopez, Rigoberto A, 2007. "Political Violence and Farm Household Efficiency in Colombia," Economic Development and Cultural Change, University of Chicago Press, pages 367-392.
    15. Zhang, Yinfang & Parker, David & Kirkpatrick, Colin, 2005. "Competition, regulation and privatisation of electricity generation in developing countries: does the sequencing of the reforms matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(2-3), pages 358-379, May.
    16. Huang, Yi-Ju & Chen, Ku-Hsieh & Yang, Chih-Hai, 2010. "Cost efficiency and optimal scale of electricity distribution firms in Taiwan: An application of metafrontier analysis," Energy Economics, Elsevier, vol. 32(1), pages 15-23, January.
    17. Tone, Kaoru & Tsutsui, Miki, 2007. "Decomposition of cost efficiency and its application to Japanese-US electric utility comparisons," Socio-Economic Planning Sciences, Elsevier, vol. 41(2), pages 91-106, June.
    18. Goto, Mika & Tsutsui, Miki, 2008. "Technical efficiency and impacts of deregulation: An analysis of three functions in U.S. electric power utilities during the period from 1992 through 2000," Energy Economics, Elsevier, vol. 30(1), pages 15-38, January.
    19. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Cambridge Working Papers in Economics 1423, Faculty of Economics, University of Cambridge.

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