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Performance benchmarking models for electricity transmission regulation: Caveats concerning the Brazilian case

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  • da Silva, Aline Veronese
  • Costa, Marcelo Azevedo
  • Ahn, Heinz
  • Lopes, Ana Lúcia Miranda

Abstract

Regulation plays an important role under natural monopoly markets, such as energy electricity distribution and transmission. In recent years, abrupt changes in the regulation of the Brazilian Transmission System Operators (TSOs) has increased the risk perceived by investors, harming the economic stability of the sector. In this paper, we present a review of the benchmarking model used to regulate Brazilian TSOs' operational costs. The objective of the paper is to suggest improvements in the Data Envelopment Analysis (DEA) model proposed by the regulator in 2018. The suggested changes would help to ensure a robust and reliable regulatory process.

Suggested Citation

  • da Silva, Aline Veronese & Costa, Marcelo Azevedo & Ahn, Heinz & Lopes, Ana Lúcia Miranda, 2019. "Performance benchmarking models for electricity transmission regulation: Caveats concerning the Brazilian case," Utilities Policy, Elsevier, vol. 60(C), pages 1-1.
  • Handle: RePEc:eee:juipol:v:60:y:2019:i:c:12
    DOI: 10.1016/j.jup.2019.100960
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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, April.
    2. V V Podinovski, 2004. "Production trade-offs and weight restrictions in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1311-1322, December.
    3. Atici, Kazim Baris & Podinovski, Victor V., 2015. "Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture," Omega, Elsevier, vol. 54(C), pages 72-83.
    4. Braeutigam, Ronald R & Panzar, John C, 1993. "Effects of the Change from Rate-of-Return to Price-Cap Regulation," American Economic Review, American Economic Association, vol. 83(2), pages 191-198, May.
    5. Jesús T. Pastor & José L. Ruiz, 2007. "Variables With Negative Values In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 63-84, Springer.
    6. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    7. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    8. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, October.
    9. Victor Podinovski & Emmanuel Thanassoulis, 2007. "Improving discrimination in data envelopment analysis: some practical suggestions," Journal of Productivity Analysis, Springer, vol. 28(1), pages 117-126, October.
    10. da Silva, Aline Veronese & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & do Carmo, Gabriela Miranda, 2019. "A close look at second stage data envelopment analysis using compound error models and the Tobit model," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 111-126.
    11. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    12. Finn Førsund, 2013. "Weight restrictions in DEA: misplaced emphasis?," Journal of Productivity Analysis, Springer, vol. 40(3), pages 271-283, December.
    13. 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.
    14. Arcos-Vargas, A. & Núñez-Hernández, F. & Villa-Caro, Gabriel, 2017. "A DEA analysis of electricity distribution in Spain: An industrial policy recommendation," Energy Policy, Elsevier, vol. 102(C), pages 583-592.
    15. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    16. V V Podinovski, 2007. "Improving data envelopment analysis by the use of production trade-offs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1261-1270, October.
    17. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    18. 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.
    19. Mendonca, Augusto F. & Dahl, Carol, 1999. "The Brazilian electrical system reform," Energy Policy, Elsevier, vol. 27(2), pages 73-83, February.
    20. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    21. 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.
    22. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    23. 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.
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    1. Veronese da Silva, Aline & Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia, 2022. "Accounting multiple environmental variables in DEA energy transmission benchmarking modelling: The 2019 Brazilian case," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    2. Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia & Kilger, Alexander de Carvalho & Micas, Artur Fontenelle, 2023. "Limitations of weight restrictions in data envelopment analysis for benchmarking Brazilian electricity distribution system operators," Utilities Policy, Elsevier, vol. 82(C).

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