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Determinants of Investment under Incentive Regulation: The Case of Norwegian Electricity Distribution Networks

Author

Listed:
  • Rahmatallah Poudineh

    (Durham University Business School, Durham, UK)

  • Tooraj Jamasb

    (Durham University Business School, Durham, UK)

Abstract

Investment in electricity networks, as regulated natural monopolies, is among the highest regulatory and energy policy priorities. The electricity sector regulators adopt different incentive mechanisms to ensure that the firms undertake sufficient investment to maintain and modernise the grid. Thus, an effective regulatory treatment of investment requires understanding the response of companies to the regulatory incentives. This study analyses the determinants of investment in electricity distribution networks using a panel dataset of 129 Norwegian companies observed from 2004 to 2010. A Bayesian Model Averaging approach is used to provide a robust statistical inference by taking into account the uncertainties around model selection and estimation. The results show that three factors drive nearly all network investments: investment rate in previous period, socio-economic costs of energy not supplied and finally useful life of assets. The results indicate that Norwegian companies have, to some degree, responded to the investment incentives provided by the regulatory framework. However, some of the incentives do not appear to be effective in driving the investments.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Rahmatallah Poudineh & Tooraj Jamasb, 2013. "Determinants of Investment under Incentive Regulation: The Case of Norwegian Electricity Distribution Networks," Working Papers EPRG 1312, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1312
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    Citations

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    Cited by:

    1. Rahmatallah Poudineh & Grigorios Emvalomatis & Tooraj Jamasb, 2014. "Dynamic Efficiency and Incentive Regulation: An Application to Electricity Distribution Networks," Working Papers EPRG 1402, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    2. Poudineh, Rahmatallah & Jamasb, Tooraj, 2016. "Determinants of investment under incentive regulation: The case of the Norwegian electricity distribution networks," Energy Economics, Elsevier, vol. 53(C), pages 193-202.
    3. Dengjun Zhang & Jinghua Xie, 2017. "Investment and revenue cap under incentive regulation: The case study of the Norwegian electricity distributors," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1400900-140, January.
    4. Hao Chen, Chi Kong Chyong, Zhifu Mi, and Yi-Ming Wei, 2020. "Reforming the Operation Mechanism of Chinese Electricity System: Benefits, Challenges and Possible Solutions," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 219-246.
    5. Cullmann, Astrid & Nieswand, Maria, 2016. "Regulation and investment incentives in electricity distribution: An empirical assessment," Energy Economics, Elsevier, vol. 57(C), pages 192-203.
    6. Michael Schmidthaler & Jed Cohen & Johannes Reichl & Stefan Schmidinger, 2015. "The effects of network regulation on electricity supply security: a European analysis," Journal of Regulatory Economics, Springer, vol. 48(3), pages 285-316, December.
    7. Carlo Cambini & Raffaele Congiu & Golnoush Soroush, 2020. "Regulation, Innovation, and Systems Integration: Evidence from the EU," Energies, MDPI, vol. 13(7), pages 1-18, April.
    8. Astrid Cullmann & Maria Nieswand, 2015. "Regulierung und Investitionen in der leitungsgebundenen Energieversorgung," DIW Roundup: Politik im Fokus 54, DIW Berlin, German Institute for Economic Research.
    9. Carlo Cambini & Elena Fumagalli & Laura Rondi, 2016. "Incentives to quality and investment: evidence from electricity distribution in Italy," Journal of Regulatory Economics, Springer, vol. 49(1), pages 1-32, February.
    10. Hinz, Fabian & Schmidt, Matthew & Möst, Dominik, 2018. "Regional distribution effects of different electricity network tariff designs with a distributed generation structure: The case of Germany," Energy Policy, Elsevier, vol. 113(C), pages 97-111.
    11. Anna Pechan, 2014. "Which Incentives Does Regulation Give to Adapt Network Infrastructure to Climate Change? - A German Case Study," Working Papers V-365-14, University of Oldenburg, Department of Economics, revised May 2014.
    12. Cullmann, Astrid & Nieswand, Maria, 2015. "Regulation and Investment Incentives in Electricity Distribution," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113090, Verein für Socialpolitik / German Economic Association.
    13. Remy Tehero & Emmanuel Brou Aka & Murat Cokgezen, 2020. "Drivers of the Quality of Electricity Supply," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 183-195.
    14. Pereira, Guillermo Ivan & Pereira da Silva, Patrícia & Cerqueira, Pedro André, 2020. "Electricity distribution incumbents' adaptation toward decarbonized and smarter grids: Evidence on the role market, regulatory, investment, and firm-level factors," Energy Policy, Elsevier, vol. 142(C).
    15. Dong, Hanjiang & Wang, Xiuyuan & Cui, Ziyu & Zhu, Jizhong & Li, Shenglin & Yu, Changyuan, 2025. "Machine learning-enhanced Data Envelopment Analysis via multi-objective variable selection for benchmarking combined electricity distribution performance," Energy Economics, Elsevier, vol. 143(C).
    16. repec:cam:camdae:1324 is not listed on IDEAS

    More about this item

    Keywords

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    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • L43 - Industrial Organization - - Antitrust Issues and Policies - - - Legal Monopolies and Regulation or Deregulation
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L52 - Industrial Organization - - Regulation and Industrial Policy - - - Industrial Policy; Sectoral Planning Methods
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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