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Scale economies, technical change and efficiency in Norwegian electricity distribution, 1998–2010

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  • Subal Kumbhakar
  • Roar Amundsveen
  • Hilde Kvile
  • Gudbrand Lien

Abstract

In this paper, we investigate scale economies, technical change and efficiency in Norwegian electricity distribution companies from 1998 to 2010. The organization and structure of this sector has become an important political question. We use panel data from the Norwegian Water Resources and Energy Directorate to address this issue. Specifically, we use input distance functions to examine scale economies, technical change and technical efficiency in the distribution companies. In modeling technically inefficiency, we separate company-specific effects from inefficiency. Our results show that the potential for scale economies is generally highest among small companies. To some extent, this finding is related to the structure of small companies and is likely to have future policy implications. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Subal Kumbhakar & Roar Amundsveen & Hilde Kvile & Gudbrand Lien, 2015. "Scale economies, technical change and efficiency in Norwegian electricity distribution, 1998–2010," Journal of Productivity Analysis, Springer, vol. 43(3), pages 295-305, June.
  • Handle: RePEc:kap:jproda:v:43:y:2015:i:3:p:295-305
    DOI: 10.1007/s11123-014-0427-6
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    2. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
    3. Vu, Khuong & Hartley, Kris, 2022. "Effects of digital transformation on electricity sector growth and productivity: A study of thirteen industrialized economies," Utilities Policy, Elsevier, vol. 74(C).
    4. Xie, Bai-Chen & Zhang, Zhen-Jiang & Anaya, Karim L., 2021. "Has the unbundling reform improved the service efficiency of China's power grid firms?," Energy Economics, Elsevier, vol. 95(C).
    5. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    6. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    7. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2017. "Specification of merger gains in the Norwegian electricity distribution industry," Energy Policy, Elsevier, vol. 102(C), pages 96-107.
    8. María Molinos-Senante & Alexandros Maziotis, 2019. "Cost Efficiency of English and Welsh Water Companies: a Meta-Stochastic Frontier Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3041-3055, July.
    9. Xie, Bai-Chen & Ni, Kang-Kang & O'Neill, Eoghan & Li, Hong-Zhou, 2021. "The scale effect in China's power grid sector from the perspective of malmquist total factor productivity analysis," Utilities Policy, Elsevier, vol. 69(C).
    10. Walheer, Barnabé, 2018. "Scale efficiency for multi-output cost minimizing producers: The case of the US electricity plants," Energy Economics, Elsevier, vol. 70(C), pages 26-36.
    11. Mydland, Ørjan & Kumbhakar, Subal C. & Lien, Gudbrand & Amundsveen, Roar & Kvile, Hilde Marit, 2020. "Economies of scope and scale in the Norwegian electricity industry," Economic Modelling, Elsevier, vol. 88(C), pages 39-46.
    12. Ørjan Mydland, 2020. "Lost economies of scope and potential merger gains in the Norwegian electricity industry," Empirical Economics, Springer, vol. 58(6), pages 3077-3100, June.
    13. Liu, Xiao-Yan & Pollitt, Michael G. & Xie, Bai-Chen & Liu, Li-Qiu, 2019. "Does environmental heterogeneity affect the productive efficiency of grid utilities in China?," Energy Economics, Elsevier, vol. 83(C), pages 333-344.
    14. Wenche Tobiasson & Manuel Llorca & Tooraj Jamasb, 2021. "Performance Effects of Network Structure and Ownership: The Norwegian Electricity Distribution Sector," Energies, MDPI, vol. 14(21), pages 1-15, November.
    15. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2016. "Specification of merger gains in the Norwegian electricity distribution industry," Discussion Papers 2016/7, Norwegian School of Economics, Department of Business and Management Science.
    16. Zhang, Tao & Li, Hong-Zhou & Xie, Bai-Chen, 2022. "Have renewables and market-oriented reforms constrained the technical efficiency improvement of China's electric grid utilities?," Energy Economics, Elsevier, vol. 114(C).

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    More about this item

    Keywords

    Returns to scale; Stochastic frontier analysis; Input distance function; Heterogeneity; C51; D24; L94;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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