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Financial distress in electricity distributors from the perspective of Brazilian regulation

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  • Scalzer, Rodrigo S.
  • Rodrigues, Adriano
  • Macedo, Marcelo Álvaro da S.
  • Wanke, Peter

Abstract

This study investigates which financial indicators can predict financial distress in Brazilian electricity distributors in relation to the targets established by the regulatory body. Specifically, identification of financial distress is possible based on the calculation of firm performance in relation to the regulatory targets, while its ability to predict is enabled by a multimodel inference for the selection of the best financial indicators based on the financial information data provided by the Brazilian regulator (ANEEL) of all existing 60 companies in the period from 2009 to 2015. Return on Assets (ROA) and liquidity measured by IL (Immediate Liquidity) and CL (Current Liquidity) stand out in their power to predict the companies with the worst regulatory performance. These results present valuable contributions to the development of new regulatory legislation in Brazil which resulted from the recent ANEEL public consultation aiming to implement monitoring of the economic and financial sustainability of Brazilian electricity distributors through financial indicators.

Suggested Citation

  • Scalzer, Rodrigo S. & Rodrigues, Adriano & Macedo, Marcelo Álvaro da S. & Wanke, Peter, 2019. "Financial distress in electricity distributors from the perspective of Brazilian regulation," Energy Policy, Elsevier, vol. 125(C), pages 250-259.
    • Handle: RePEc:eee:enepol:v:125:y:2019:i:c:p:250-259
    DOI: 10.1016/j.enpol.2018.10.018
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    as
    1. A. Mendes & R. L. Cardoso & P. C. Mário & A. L. Martinez & F. R. Ferreira, 2014. "Insolvency Prediction In The Presence Of Data Inconsistencies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(3), pages 155-167, July.
    2. Lins, Marcos Pereira Estellita & Sollero, Maria Karla Vervloet & Caloba, Guilherme Marques & da Silva, Angela Cristina Moreira, 2007. "Integrating the regulatory and utility firm perspectives, when measuring the efficiency of electricity distribution," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1413-1424, September.
    3. Arango, Santiago, 2007. "Simulation of alternative regulations in the Colombian electricity market," Socio-Economic Planning Sciences, Elsevier, vol. 41(4), pages 305-319, December.
    4. PER AGRELL & Peter Bogetoft & Jørgen Tind, 2005. "DEA and Dynamic Yardstick Competition in Scandinavian Electricity Distribution," Journal of Productivity Analysis, Springer, vol. 23(2), pages 173-201, May.
    5. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    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. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    8. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    9. Bernstein, Jeffrey I & Sappington, David E M, 1999. "Setting the X Factor in Price-Cap Regulation Plans," Journal of Regulatory Economics, Springer, vol. 16(1), pages 5-25, July.
    10. Perobelli, Fernando Salgueiro & Oliveira, Caio Cézar Calheiros de, 2013. "Energy development potential: An analysis of Brazil," Energy Policy, Elsevier, vol. 59(C), pages 683-701.
    11. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    12. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    13. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    14. El Hage, Fabio S. & Rufín, Carlos, 2016. "Context analysis for a new regulatory model for electric utilities in Brazil," Energy Policy, Elsevier, vol. 97(C), pages 145-154.
    15. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    16. Altoé, Andrey Vinícius & da Costa Jr., Newton & Lopes, Ana Lúcia Miranda & Veloso, Thiago Roberto Magalhães & Saurin, Valter, 2017. "Technical efficiency and financial performance in the Brazilian distribution service operators," Socio-Economic Planning Sciences, Elsevier, vol. 59(C), pages 79-92.
    17. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    18. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    19. Ochoa, Patricia, 2007. "Policy changes in the Swiss electricity market: Analysis of likely market responses," Socio-Economic Planning Sciences, Elsevier, vol. 41(4), pages 336-349, December.
    20. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    21. Johnson, Mark S. & Niles, Marcia S. & Suydam, Stacey L., 1998. "Regulatory changes in the electric utility industry: Investigation of effects on shareholder wealth," Journal of Accounting and Public Policy, Elsevier, vol. 17(4-5), pages 285-309.
    22. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    23. Chang, Hsihui & Chang, Wen-Jing & Das, Somnath & Li, Shu-Hsing, 2004. "Health care regulation and the operating efficiency of hospitals: Evidence from Taiwan," Journal of Accounting and Public Policy, Elsevier, vol. 23(6), pages 483-510.
    24. Liston, Catherine, 1993. "Price-Cap versus Rate-of-Return Regulation," Journal of Regulatory Economics, Springer, vol. 5(1), pages 25-48, March.
    25. Jean-Jacques Laffont & Jean Tirole, 1993. "A Theory of Incentives in Procurement and Regulation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262121743, April.
    26. Baer, Werner & McDonald, Curt, 1998. "A Return to the Past? Brazil's Privatization of Public Utilities: The Case of the Electric Power Sector," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 1), pages 503-523.
    27. Reitenga, Austin L., 2000. "Environmental regulation, capital intensity, and cross-sectional variation in market returns," Journal of Accounting and Public Policy, Elsevier, vol. 19(2), pages 189-198, June.
    28. Nunez, Karen, 2007. "Electric utility deregulation: Stranded costs vs. stranded benefits," Journal of Accounting and Public Policy, Elsevier, vol. 26(2), pages 193-211.
    29. Altman, Edward I., 1984. "The success of business failure prediction models : An international survey," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 171-198, June.
    30. Johnston, Derek, 2005. "An investigation of regulatory and voluntary environmental capital expenditures," Journal of Accounting and Public Policy, Elsevier, vol. 24(3), pages 175-206.
    31. 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.
    32. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    33. Resende, Marcelo, 2002. "Relative efficiency measurement and prospects for yardstick competition in Brazilian electricity distribution," Energy Policy, Elsevier, vol. 30(8), pages 637-647, June.
    34. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    35. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    36. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    37. Pacudan, Romeo & de Guzman, Elaine, 2002. "Impact of energy efficiency policy to productive efficiency of electricity distribution industry in the Philippines," Energy Economics, Elsevier, vol. 24(1), pages 41-54, January.
    38. Sartori, Simone & Witjes, Sjors & Campos, Lucila M.S., 2017. "Sustainability performance for Brazilian electricity power industry: An assessment integrating social, economic and environmental issues," Energy Policy, Elsevier, vol. 111(C), pages 41-51.
    39. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, December.
    40. Førsund, Finn R. & Kittelsen, Sverre A. C., 1998. "Productivity development of Norwegian electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 20(3), pages 207-224, September.
    41. Torrini, Fabiano Castro & Souza, Reinaldo Castro & Cyrino Oliveira, Fernando Luiz & Moreira Pessanha, Jose Francisco, 2016. "Long term electricity consumption forecast in Brazil: A fuzzy logic approach," Socio-Economic Planning Sciences, Elsevier, vol. 54(C), pages 18-27.
    42. Pekka Korhonen & Mikko Syrjänen, 2003. "Evaluation of Cost Efficiency in Finnish Electricity Distribution," Annals of Operations Research, Springer, vol. 121(1), pages 105-122, July.
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