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The impact of transmission auctions on Brazilian electric power companies

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  • Brandão, Lucas G.L.
  • Ehrl, Philipp

Abstract

This paper estimates the impact of electricity transmission line auctions on the stock prices of Brazilian companies. We combine the endogenous switching regression model with flexible copula functions to account for the dependency between a firm's choice to participate in an auction and the impact of the auction's result on the firm's stock price. Both processes are thus modeled as a function of firm-specific and macroeconomic variables while accounting explicitly for their dependence. We show that a lower number of participants, being a state-owned company, and having synergies positively affect the chance of winning an auction. According to the estimated average treatment effect, a new transmission line increases firms' stock prices by 3.7%.

Suggested Citation

  • Brandão, Lucas G.L. & Ehrl, Philipp, 2022. "The impact of transmission auctions on Brazilian electric power companies," Utilities Policy, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:juipol:v:78:y:2022:i:c:s0957178722000777
    DOI: 10.1016/j.jup.2022.101412
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    1. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 71, Elsevier.
    2. Dakshina G. De Silva, 2005. "Synergies in Recurring Procurement Auctions: An Empirical Investigation," Economic Inquiry, Western Economic Association International, vol. 43(1), pages 55-66, January.
    3. Paul Klemperer, 2002. "What Really Matters in Auction Design," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 169-189, Winter.
    4. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    5. Dutra, Joisa & Menezes, Flavio, 2005. "Lessons from the Electricity Auctions in Brazil," The Electricity Journal, Elsevier, vol. 18(10), pages 11-21, December.
    6. Rego, Erik Eduardo & Parente, Virginia, 2013. "Brazilian experience in electricity auctions: Comparing outcomes from new and old energy auctions as well as the application of the hybrid Anglo-Dutch design," Energy Policy, Elsevier, vol. 55(C), pages 511-520.
    7. Adamson, Seabron & Noe, Thomas & Parker, Geoffrey, 2010. "Efficiency of financial transmission rights markets in centrally coordinated periodic auctions," Energy Economics, Elsevier, vol. 32(4), pages 771-778, July.
    8. Washington Martins Silva & Osvaldo Candido, 2020. "Assessing Brazilian electric power transmission auctions," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(1), pages 182-199, February.
    9. Vega, Clara, 2006. "Stock price reaction to public and private information," Journal of Financial Economics, Elsevier, vol. 82(1), pages 103-133, October.
    10. Takuya Hasebe, 2013. "Copula-based maximum-likelihood estimation of sample-selection models," Stata Journal, StataCorp LP, vol. 13(3), pages 547-573, September.
    11. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    12. El in Ayka Alp, 2016. "Energy Consumption and Economic Growth in OECD Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 6(4), pages 753-759.
    13. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    14. Rocha, Katia & Moreira, Ajax & Limp, Rodrigo, 2013. "Determinantes dos altos deságios nos leilões de transmissão de energia elétrica no Brasil entre 1999-2010," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(2), June.
    15. Murray D. Smith, 2003. "Modelling sample selection using Archimedean copulas," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 99-123, June.
    16. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    17. Reboredo, Juan C., 2015. "Is there dependence and systemic risk between oil and renewable energy stock prices?," Energy Economics, Elsevier, vol. 48(C), pages 32-45.
    18. Kishore, T.S. & Singal, S.K., 2014. "Optimal economic planning of power transmission lines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 949-974.
    19. Laffont, Jean-Jacques & Vuong, Quang, 1996. "Structural Analysis of Auction Data," American Economic Review, American Economic Association, vol. 86(2), pages 414-420, May.
    20. Luiz T. A. Maurer & Luiz A. Barroso, 2011. "Electricity Auctions : An Overview of Efficient Practices," World Bank Publications - Books, The World Bank Group, number 2346, December.
    21. Stiglitz, Joseph E, 1969. "A Re-Examination of the Modigliani-Miller Theorem," American Economic Review, American Economic Association, vol. 59(5), pages 784-793, December.
    22. Hunt., Julian David & Stilpen, Daniel & de Freitas, Marcos Aurélio Vasconcelos, 2018. "A review of the causes, impacts and solutions for electricity supply crises in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 208-222.
    23. Blázquez de Paz, Mario, 2018. "Electricity auctions in the presence of transmission constraints and transmission costs," Energy Economics, Elsevier, vol. 74(C), pages 605-627.
    24. Philipp Ehrl, 2021. "Live large or die young: subsidized loans and firm survival in Brazil," Empirical Economics, Springer, vol. 61(6), pages 3479-3503, December.
    25. Yanqin Fan & Andrew J. Patton, 2014. "Copulas in Econometrics," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 179-200, August.
    26. Steven N. Kaplan & Luigi Zingales, 1997. "Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 169-215.
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    More about this item

    Keywords

    Electric power transmission; Stock prices; Copulas;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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