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Wind of change: Small-scale electricity production and distribution-grid efficiency in Sweden

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  • Vesterberg, Mattias
  • Zhou, Wenchao
  • Lundgren, Tommy

Abstract

In this paper, we measure the technical efficiency for local electricity distribution firms in Sweden, and in particular how small and micro-scale generation affects efficiency scores. Using a two-stage data envelopment analysis to model the technical efficiency and a double bootstrap approach to estimate the determinants of inefficiencies, we show that firms are heterogeneous in terms of inefficiency, but that a large share of small and micro-scale generation is not associated with more inefficient operations.

Suggested Citation

  • Vesterberg, Mattias & Zhou, Wenchao & Lundgren, Tommy, 2021. "Wind of change: Small-scale electricity production and distribution-grid efficiency in Sweden," Utilities Policy, Elsevier, vol. 69(C).
  • Handle: RePEc:eee:juipol:v:69:y:2021:i:c:s0957178721000096
    DOI: 10.1016/j.jup.2021.101175
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    1. Sudhir M. Bobde & Makoto Tanaka, 2018. "Efficiency evaluation of electricity distribution utilities in India: A two-stage DEA with bootstrap estimation," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(9), pages 1423-1434, September.
    2. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non‐parametric, two‐stage models of production," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 170-191, June.
    3. Edvardsen, Dag Fjeld & Forsund, Finn R., 2003. "International benchmarking of electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 25(4), pages 353-371, October.
    4. Daraio, Cinzia & Simar, Leopold & Wilson, Paul, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production," LIDAM Reprints ISBA 2018023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    6. 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.
    7. Léopold Simar & Paul Wilson, 2011. "Two-stage DEA: caveat emptor," Journal of Productivity Analysis, Springer, vol. 36(2), pages 205-218, October.
    8. Filippini, M. & Greene, W. & Masiero, G., 2018. "Persistent and transient productive inefficiency in a regulated industry: electricity distribution," Energy Economics, Elsevier, vol. 69(C), pages 325-334.
    9. Jesse D. Jenkins & Ignacio J. Pérez-Arriaga, 2017. "Improved Regulatory Approaches for the Remuneration of Electricity Distribution Utilities with High Penetrations of Distributed Energy Resources," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    10. Subal C. Kumbhakar & Gudbrand Lien, 2017. "Yardstick Regulation of Electricity Distribution Disentangling Short-run and Long-run Inefficiencies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    11. 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.
    12. Cossent, Rafael & Gómez, Tomás & Frías, Pablo, 2009. "Towards a future with large penetration of distributed generation: Is the current regulation of electricity distribution ready? Regulatory recommendations under a European perspective," Energy Policy, Elsevier, vol. 37(3), pages 1145-1155, March.
    13. Erik Lundin, 2020. "Effects of Privatization on Price and Labor Efficiency: The Swedish Electricity Distribution Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 247-274.
    14. Giannakis, Dimitrios & Jamasb, Tooraj & Pollitt, Michael, 2005. "Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks," Energy Policy, Elsevier, vol. 33(17), pages 2256-2271, November.
    15. Hjalmarsson, Lennart & Veiderpass, Ann, 1992. " Productivity in Swedish Electricity Retail Distribution," Scandinavian Journal of Economics, Wiley Blackwell, vol. 94(0), pages 193-205, Supplemen.
    16. 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.
    17. 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.
    18. Arocena, Pablo, 2008. "Cost and quality gains from diversification and vertical integration in the electricity industry: A DEA approach," Energy Economics, Elsevier, vol. 30(1), pages 39-58, January.
    19. 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.
    20. 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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    Cited by:

    1. Söderberg, Magnus & Vesterberg, Mattias, 2023. "How demand uncertainty influences electricity network prices under revenue-cap regulation: The case of Sweden," Energy Economics, Elsevier, vol. 127(PB).
    2. Ikram, Majid & Rafique, Muhammad Zahid & Mohammed, Kamel Si & Waheed, Rida & Ferraz, Diogo, 2023. "Efficient resource utilization of the electricity distribution sector using nonparametric data envelopment analysis and influential factors," Utilities Policy, Elsevier, vol. 82(C).

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    More about this item

    Keywords

    Data envelopment analysis; Bootstrap; Efficiency;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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