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Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems

Author

Listed:
  • Per J. Agrell
  • Mehdi Farsi
  • Massimo Filippini
  • Martin Koller
Abstract
The purpose of this study is to analyze the cost efficiency of electricity distribution systems in order to enable regulatory authorities to establish price- or revenue cap regulation regimes. The increasing use of efficiency analysis in the last decades has raised serious concerns among regulators and companies regarding the reliability of efficiency estimates. One important dimension affecting the reliability is the presence of unobserved factors. Since these factors are treated differently in various models, the resulting estimates can vary across methods. Therefore, we decompose the benchmarking process into two steps. In the first step, we identify classes of similar companies with comparable network and structural characteristics using a latent class cost model. We obtain cost best practice within each class in the second step, based on deterministic and stochastic cost frontier models. The results of this analysis show that the decomposition of the benchmarking process into two steps has reduced unobserved heterogeneity within classes and, hence, reduced the unexplained variance previously claimed as inefficiency.

Suggested Citation

  • Per J. Agrell & Mehdi Farsi & Massimo Filippini & Martin Koller, 2013. "Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems," Working Papers 0038, Swiss Economics.
    • Handle: RePEc:chc:wpaper:0038
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    References listed on IDEAS

    as
    1. Fleurbaey,Marc & Maniquet,François, 2011. "A Theory of Fairness and Social Welfare," Cambridge Books, Cambridge University Press, number 9780521715348, September.
    2. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    3. Behr, Andreas, 2010. "Quantile regression for robust bank efficiency score estimation," European Journal of Operational Research, Elsevier, vol. 200(2), pages 568-581, January.
    4. Kumbhakar, Subal C., 1991. "Estimation of technical inefficiency in panel data models with firm- and time-specific effects," Economics Letters, Elsevier, vol. 36(1), pages 43-48, May.
    5. AGRELL, Per J. & BOGETOFT, Peter, 2010. "Harmonizing the Nordic regulation of electricity distribution," LIDAM Reprints CORE 2376, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Andrei Shleifer, 1985. "A Theory of Yardstick Competition," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 319-327, Autumn.
    7. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    8. Mehdi Farsi & Massimo Filippini, 2004. "Regulation and Measuring Cost-Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 25(1), pages 1-19, August.
    9. Haney, Aoife Brophy & Pollitt, Michael G., 2009. "Efficiency analysis of energy networks: An international survey of regulators," Energy Policy, Elsevier, vol. 37(12), pages 5814-5830, December.
    10. Antonio Estache & MartÌn A. Rossi & Christian A. Ruzzier, 2004. "The Case for International Coordination of Electricity Regulation: Evidence from the Measurement of Efficiency in South America," Journal of Regulatory Economics, Springer, vol. 25(3), pages 271-295, May.
    11. 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.
    12. 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.
    13. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    14. 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.
    15. Mehdi Farsi & Massimo Filippini & William Greene, 2006. "Application Of Panel Data Models In Benchmarking Analysis Of The Electricity Distribution Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(3), pages 271-290, September.
    16. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    17. Polachek, Solomon W & Yoon, Bong Joon, 1996. "Panel Estimates of a Two-Tiered Earnings Frontier," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 169-178, March-Apr.
    18. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    19. Uwe Jensen, 2000. "Is it efficient to analyse efficiency rankings?," Empirical Economics, Springer, vol. 25(2), pages 189-208.
    20. repec:cor:louvrp:-2376 is not listed on IDEAS
    21. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    22. Andrew Street, 2003. "How much confidence should we place in efficiency estimates?," Health Economics, John Wiley & Sons, Ltd., vol. 12(11), pages 895-907, November.
    23. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    24. Kris Knox & Eric Blankmeyer & J. Stutzman, 2007. "Technical efficiency in texas nursing facilities: A stochastic production frontier approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 31(1), pages 75-86, March.
    25. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    26. Joanne Evans & Lester C. Hunt (ed.), 2009. "International Handbook on the Economics of Energy," Books, Edward Elgar Publishing, number 12764.
    27. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    28. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    29. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1.
    30. 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.
    31. 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.
    32. 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.
    33. Kalirajan, K P & Obwona, M B, 1994. "Frontier Production Function: The Stochastic Coefficients Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(1), pages 87-96, February.
    34. 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.
    35. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, September.
    36. Gaertner,Wulf & Schokkaert,Erik, 2011. "Empirical Social Choice," Cambridge Books, Cambridge University Press, number 9781107013940, September.
    37. Shuttleworth, Graham, 2005. "Benchmarking of electricity networks: Practical problems with its use for regulation," Utilities Policy, Elsevier, vol. 13(4), pages 310-317, December.
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    Cited by:

    1. Just, Lisa, 2021. "Unobserved technological heterogeneity among German electricity distribution network operators - a latent class analysis," EWI Working Papers 2021-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    2. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    3. Mirza, Faisal Mehmood & Rizvi, Syed Badar-Ul-Husnain & Bergland, Olvar, 2021. "Service quality, technical efficiency and total factor productivity growth in Pakistan's post-reform electricity distribution companies," Utilities Policy, Elsevier, vol. 68(C).
    4. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    5. 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.
    6. Núñez, F. & Arcos-Vargas, A. & Villa, G., 2020. "Efficiency benchmarking and remuneration of Spanish electricity distribution companies," Utilities Policy, Elsevier, vol. 67(C).
    7. Stefano Mainardi, 2021. "Parametric and Semiparametric Efficiency Frontiers in Fishery Analysis: Overview and Case Study on the Falkland Islands," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 169-210, June.
    8. Massimo Filippini & Luis Orea, 2014. "Applications of the stochastic frontier approach in Energy Economics," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 35-42.
    9. Romano, Teresa & Cambini, Carlo & Fumagalli, Elena & Rondi, Laura, 2022. "Setting network tariffs with heterogeneous firms: The case of natural gas distribution," European Journal of Operational Research, Elsevier, vol. 297(1), pages 280-290.
    10. Agrell, P & Brea-Solís, H., 2015. "Stationarity of Heterogeneity in Production Technology using Latent Class Modelling," LIDAM Discussion Papers CORE 2015047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Ronald G. McGarvey & Andreas Thorsen & Maggie L. Thorsen & Rohith Madhi Reddy, 2019. "Measuring efficiency of community health centers: a multi-model approach considering quality of care and heterogeneous operating environments," Health Care Management Science, Springer, vol. 22(3), pages 489-511, September.
    12. Llorca, Manuel & Orea, Luis & Pollit, Michael G., 2013. "Using in the latent class approach as a supervised method to cluster firms in DEA: An application to the US electricity transmission industry," Efficiency Series Papers 2013/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    13. Haney, Aoife Brophy & Pollitt, Michael G., 2013. "International benchmarking of electricity transmission by regulators: A contrast between theory and practice?," Energy Policy, Elsevier, vol. 62(C), pages 267-281.

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    More about this item

    Keywords

    Efficiency analysis; cost function; electricity sector; incentive regulation;
    All these keywords.

    JEL classification:

    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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