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Does environmental heterogeneity affect the productive efficiency of grid utilities in China?

Author

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  • Xiao-Yan Liu

    (College of Management and Economics, Tianjin University, Tianjin, China)

  • Li-Qiu Liu

    (College of Management and Economics, Tianjin University, Tianjin, China)

  • Bai-Chen Xie

    (College of Management and Economics, Tianjin University, Tianjin, China - Energy Policy Research Group (EPRG), Judge Business School, University of Cambridge)

  • Michael G. Pollitt

    (Energy Policy Research Group (EPRG), Judge Business School, University of Cambridge)

Abstract

China’s electricity industry has experienced a reform whereby the generation sector is being opened up to competition but the transmission and distribution sectors are still regulated. Efficiency and benchmarking analyses are widely used for improving the performance of regulated segments, and the impact on efficiency of observable environmental factors, together with unobservable characteristics, has gained increasing attention in recent years. This study uses alternative stochastic frontier models combined with input distance functions to study the productive efficiency of 29 grid firms of China over the period 1993–2014 and investigates the effect of observed environmental factors and unobserved heterogeneity. The results indicate that efficiency is sensitive to model specification and illustrates the presence of observed and unobserved heterogeneity. The number of customers, power delivered and network length are demonstrated to have positive impacts on the utilities’ efficiency while adverse environmental conditions harm the operation of grid utilities, but policy regulations may offset the negative impact. Finally, we suggest that there is room for efficiency improvement in the distribution grid, which could be encouraged by incentive regulation, even taking due account of environmental heterogeneity.
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  • Xiao-Yan Liu & Li-Qiu Liu & Bai-Chen Xie & Michael G. Pollitt, 2018. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Working Papers EPRG 1820, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1820
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    1. Pollitt, M. & Yang, C-H. & Chen, H., 2017. "Reforming the Chinese Electricity Supply Sector: Lessons from International Experience," Cambridge Working Papers in Economics 1713, Faculty of Economics, University of Cambridge.
    2. Christian von Hirschhausen & Astrid Cullmann & Andreas Kappeler, 2006. "Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2553-2566.
    3. Yeoh, Boon-Siew & Rajaraman, Rajesh, 2004. "Electricity in China: The Latest Reforms," The Electricity Journal, Elsevier, vol. 17(3), pages 60-69, April.
    4. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    5. Kopsakangas-Savolainen, Maria & Svento, Rauli, 2011. "Observed and unobserved heterogeneity in stochastic frontier models: An application to the electricity distribution industry," Energy Economics, Elsevier, vol. 33(2), pages 304-310, March.
    6. Paul L. Joskow, 2014. "Incentive Regulation in Theory and Practice: Electricity Distribution and Transmission Networks," NBER Chapters, in: Economic Regulation and Its Reform: What Have We Learned?, pages 291-344, National Bureau of Economic Research, Inc.
    7. 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.
    8. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    9. Mehdi Farsi & Massimo Filippini, 2006. "An Analysis of Efficiency and Productivity in Swiss Hospitals," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(I), pages 1-37, March.
    10. Zhao, Xiaoli & Ma, Chunbo, 2013. "Deregulation, vertical unbundling and the performance of China's large coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 474-483.
    11. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Lau, Sim-Yee, 2017. "Have regulatory reforms improved the efficiency levels of the Japanese electricity distribution sector? A cost metafrontier-based analysis," Energy Policy, Elsevier, vol. 108(C), pages 606-616.
    12. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
    13. Filippini, Massimo & Wetzel, Heike, 2014. "The impact of ownership unbundling on cost efficiency: Empirical evidence from the New Zealand electricity distribution sector," Energy Economics, Elsevier, vol. 45(C), pages 412-418.
    14. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    15. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    16. Paul Nillesen & Michael Pollitt, 2011. "Ownership Unbundling in Electricity Distribution: Empirical Evidence from New Zealand," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 38(1), pages 61-93, January.
    17. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    18. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2017. "Endogenous environmental variables in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 199(2), pages 131-140.
    19. Sun, Kai & Kumbhakar, Subal C. & Tveterås, Ragnar, 2015. "Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 194-202.
    20. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    21. Cambini, Carlo & Croce, Annalisa & Fumagalli, Elena, 2014. "Output-based incentive regulation in electricity distribution: Evidence from Italy," Energy Economics, Elsevier, vol. 45(C), pages 205-216.
    22. Raymond W. Goldsmith, 1951. "A Perpetual Inventory of National Wealth," NBER Chapters, in: Studies in Income and Wealth, Volume 14, pages 5-73, National Bureau of Economic Research, Inc.
    23. Subal Kumbhakar & Efthymios Tsionas, 2008. "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks," Empirical Economics, Springer, vol. 34(3), pages 585-602, June.
    24. Astrid Cullmann, 2012. "Benchmarking and firm heterogeneity: a latent class analysis for German electricity distribution companies," Empirical Economics, Springer, vol. 42(1), pages 147-169, February.
    25. Anna Ter-Martirosyan & John Kwoka, 2010. "Incentive regulation, service quality, and standards in U.S. electricity distribution," Journal of Regulatory Economics, Springer, vol. 38(3), pages 258-273, December.
    26. Battese, George E., 1992. "Frontier production functions and technical efficiency: a survey of empirical applications in agricultural economics," Agricultural Economics, Blackwell, vol. 7(3-4), pages 185-208, October.
    27. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    28. Wang, Qiang & Chen, Xi, 2012. "China's electricity market-oriented reform: From an absolute to a relative monopoly," Energy Policy, Elsevier, vol. 51(C), pages 143-148.
    29. 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, vol. 20(2), pages 325-332.
    30. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    31. Yu, William & Jamasb, Tooraj & Pollitt, Michael, 2009. "Does weather explain cost and quality performance? An analysis of UK electricity distribution companies," Energy Policy, Elsevier, vol. 37(11), pages 4177-4188, November.
    32. Xun Li & Rigoberto A. Lopez, 2016. "Food environment and weight outcomes: a stochastic frontier approach," Applied Economics, Taylor & Francis Journals, vol. 48(47), pages 4526-4537, October.
    33. 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.
    34. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    35. 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.
    36. MA Hossain & ND Karunaratne, 2004. "Trade Liberalisation and Technical Efficiency: Evidence from Bangladesh Manufacturing Industries," Journal of Development Studies, Taylor & Francis Journals, vol. 40(3), pages 87-114.
    37. Tovar, Beatriz & Javier Ramos-Real, Francisco & de Almeida, Edmar Fagundes, 2011. "Firm size and productivity. Evidence from the electricity distribution industry in Brazil," Energy Policy, Elsevier, vol. 39(2), pages 826-833, February.
    38. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    39. Subal Kumbhakar & Roar Amundsveen & Hilde Kvile & Gudbrand Lien, 2015. "Scale economies, technical change and efficiency in Norwegian electricity distribution, 1998–2010," Journal of Productivity Analysis, Springer, vol. 43(3), pages 295-305, June.
    40. Luis Alberiko Gil-Alana & Carlos Barros & Dercio Mandlaze, 2017. "A performance assessment of Mozambique banks: a Bayesian stochastic frontier," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4579-4587, September.
    41. C. P. Barros & G. Rossi, 2014. "A Bayesian stochastic frontier of Italian football," Applied Economics, Taylor & Francis Journals, vol. 46(20), pages 2398-2407, July.
    42. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    43. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    44. Leland Gerson Neuberg, 1977. "Two Issues in the Municipal Ownership of Electric Power Distribution," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 303-323, Spring.
    45. Jiro Nemoto & Mika Goto, 2006. "Measurement of technical and allocative efficiencies using a CES cost frontier: a benchmarking study of Japanese transmission-distribution electricity," Empirical Economics, Springer, vol. 31(1), pages 31-48, March.
    46. 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.
    47. Efthymios G. Tsionas & Subal C. Kumbhakar, 2014. "FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY: A GENERALIZED TRUE RANDOM‐EFFECTS model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 110-132, January.
    48. Anaya, Karim L. & Pollitt, Michael G., 2017. "Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1078-1094.
    49. Griffiths, William E. & Hajargasht, Gholamreza, 2016. "Some models for stochastic frontiers with endogeneity," Journal of Econometrics, Elsevier, vol. 190(2), pages 341-348.
    50. Nancy L. Rose, 2014. "Economic Regulation and Its Reform: What Have We Learned?," NBER Books, National Bureau of Economic Research, Inc, number rose05-1, March.
    51. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    52. See, Kok Fong & Coelli, Tim, 2013. "Estimating and decomposing productivity growth of the electricity generation industry in Malaysia: A stochastic frontier analysis," Energy Policy, Elsevier, vol. 62(C), pages 207-214.
    53. Duman, Yavuz Selman & Kasman, Adnan, 2018. "Environmental technical efficiency in EU member and candidate countries: A parametric hyperbolic distance function approach," Energy, Elsevier, vol. 147(C), pages 297-307.
    54. Kumbhakar, Subal C. & Hjalmarsson, Lennart, 1998. "Relative performance of public and private ownership under yardstick competition: electricity retail distribution," European Economic Review, Elsevier, vol. 42(1), pages 97-122, January.
    55. Growitsch, Christian & Jamasb, Tooraj & Wetzel, Heike, 2012. "Efficiency effects of observed and unobserved heterogeneity: Evidence from Norwegian electricity distribution networks," Energy Economics, Elsevier, vol. 34(2), pages 542-548.
    56. Lai, Hung-pin & Kumbhakar, Subal C., 2018. "Endogeneity in panel data stochastic frontier model with determinants of persistent and transient inefficiency," Economics Letters, Elsevier, vol. 162(C), pages 5-9.
    57. Pérez-Reyes, Raúl & Tovar, Beatriz, 2009. "Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms," Energy Policy, Elsevier, vol. 37(6), pages 2249-2261, June.
    58. Jamasb, Tooraj & Pollitt, Michael, 2003. "International benchmarking and regulation: an application to European electricity distribution utilities," Energy Policy, Elsevier, vol. 31(15), pages 1609-1622, December.
    59. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    More about this item

    Keywords

    Grid industry; Efficiency estimation; Stochastic frontier analysis; Environmental heterogeneity; China;
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    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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