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Revenue decoupling, energy demand, and energy efficiency: Empirical evidence from the U.S. electricity sector

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  • von Loessl, Victor
  • Wetzel, Heike

Abstract

This paper investigates the relationship between the regulatory policy revenue decoupling, which separates utilities’ revenue from sales fluctuations, and electricity customers’ energy demand and efficiency in the U.S. electricity sector. To this end, we use recent Stochastic Frontier Analysis estimation techniques that account for both persistent and transient energy efficiency. The results show a significant negative correlation between decoupling and electricity consumption. However, the implementation year, which serves as a reference for price adjustments, is associated with increasing electricity demand and decreasing transient energy efficiency. Therefore, utilities seem to anticipate the implementation of decoupling, which partially offsets the benefits.

Suggested Citation

  • von Loessl, Victor & Wetzel, Heike, 2022. "Revenue decoupling, energy demand, and energy efficiency: Empirical evidence from the U.S. electricity sector," Utilities Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:juipol:v:79:y:2022:i:c:s0957178722000807
    DOI: 10.1016/j.jup.2022.101416
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    References listed on IDEAS

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    1. Jenya Kahn-Lang, 2016. "The Effects of Electric Utility Decoupling on Energy Efficiency," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Michelfelder, Richard A. & Ahern, Pauline & D'Ascendis, Dylan, 2019. "Decoupling impact and public utility conservation investment," Energy Policy, Elsevier, vol. 130(C), pages 311-319.
    3. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    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. Eto, Joseph & Stoft, Steven & Belden, Timothy, 1997. "The theory and practice of decoupling utility revenues from sales," Utilities Policy, Elsevier, vol. 6(1), pages 43-55, March.
    6. repec:hal:spmain:info:hdl:2441/2vteelu0n785l82j764n6ul273 is not listed on IDEAS
    7. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    8. Giovanni Marin & Francesco Vona, 2017. "The Impact of Energy Prices on Employment and Environmental Performance: Evidence from French Manufacturing Establishments," Working Papers 2017.53, Fondazione Eni Enrico Mattei.
    9. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    10. Marin, Giovanni & Vona, Francesco, 2019. "Climate policies and skill-biased employment dynamics: Evidence from EU countries," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    11. Paul Carrillo & Dina Pomeranz & Monica Singhal, 2017. "Dodging the Taxman: Firm Misreporting and Limits to Tax Enforcement," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 144-164, April.
    12. Kennedy, Peter E, 1981. "Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations [The Interpretation of Dummy Variables in Semilogarithmic Equations]," American Economic Review, American Economic Association, vol. 71(4), pages 801-801, September.
    13. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    14. Timothy Brennan, 2010. "Decoupling in electric utilities," Journal of Regulatory Economics, Springer, vol. 38(1), pages 49-69, August.
    15. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    16. Datta, Souvik, 2019. "Decoupling and demand-side management: Evidence from the US electric industry," Energy Policy, Elsevier, vol. 132(C), pages 175-184.
    17. 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.
    18. Penelope Buckley, 2020. "Prices, information and nudges for residential electricity conservation : A meta-analysis," Post-Print hal-02500507, HAL.
    19. Brucal, Arlan & Tarui, Nori, 2021. "The effects of utility revenue decoupling on electricity prices," Energy Economics, Elsevier, vol. 101(C).
    20. Marin, Giovanni & Vona, Francesco, 2021. "The impact of energy prices on socioeconomic and environmental performance: Evidence from French manufacturing establishments, 1997–2015," European Economic Review, Elsevier, vol. 135(C).
    21. 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.
    22. 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.
    23. Giles, David E. A., 1982. "The interpretation of dummy variables in semilogarithmic equations : Unbiased estimation," Economics Letters, Elsevier, vol. 10(1-2), pages 77-79.
    24. 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.
    25. David G. Victor & Keigo Akimoto & Yoichi Kaya & Mitsutsune Yamaguchi & Danny Cullenward & Cameron Hepburn, 2017. "Prove Paris was more than paper promises," Nature, Nature, vol. 548(7665), pages 25-27, August.
    26. Kihm, Steven, 2009. "When Revenue Decoupling Will Work ... And When It Won't," The Electricity Journal, Elsevier, vol. 22(8), pages 19-28, October.
    27. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    28. Buckley, Penelope, 2020. "Prices, information and nudges for residential electricity conservation: A meta-analysis," Ecological Economics, Elsevier, vol. 172(C).
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    More about this item

    Keywords

    Revenue decoupling; Energy demand; Energy efficiency;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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