Abstract
The main contribution in this paper is a presentation and discussion of issues that arise in the practical application of a regulatory benchmarking model. We describe the regulatory benchmarking model for electricity distribution companies in Norway, and we focus on how different choices influence different incentives for the companies. These choices cover methodology, modelling assumptions and variables, but also how the benchmarking results are applied in the regulatory model. The benchmarking model is only one part of the regulatory model for setting revenue caps. This discussion shows some of the trade-offs that have to be considered in this process, and sheds some light on why regulators may deviate from optimal text-book solutions.
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Notes
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These are property taxes and costs incurred in higher network levels. In addition the companies are allowed to cover some of their R&D costs directly in the allowed revenue. In this way NVE gives incentives for R&D among companies.
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In the input of the DEA we also include capital that have been financed through contributions. This is because these outputs are included in the companies’ data, therefore we need to add the costs as well.
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We use the same WACC model as in the cost base.
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NVE has assumed the need for investments (for distribution companies) to be five billion NOK per year the next 10 years. In 2012 the total book value in the distribution level for the industry is 46 billion NOK.
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Low voltage grid is highly correlated with both customers and network stations and is not needed in the model.
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If λ ij denotes the weight of DSO j on the reference set of DSO i. Then \( {\phi}_{ij} = {\lambda}_{ij}{x}_j/{\lambda}_i{x}_i \) is DSO j’s share of the inputs for the target unit of DSO i.
References
Amundsveen R, Kvile HM, Kordahl OP, Langset T (2014) Second stage adjustment for firm heterogeneity in DEA: a novel approach used in regulation of Norwegian electricity DSOs. In: Emrouznejad A, Banker R, Doraisamy SM, Arabi B (eds) Recent developments in data envelopment analysis and its applications, Proceedings of the 12th International Conference of DEA, Kuala Lumpur, April 2014
Coelli TJ, Rao DSP, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis, 2nd edn. Springer, New York
Edvardsen DF (2004) Efficiency of Norwegian construction firms, four essays on the measurement of productive efficiency. Doctoral thesis, University of Gothenburg
Haney AB, Pollit MG (2012) International benchmarking of electricity transmission by regulators: theory and practice. EPRG working paper 1226
Kittelsen SAC (1994) Effektivitet og regulering i norsk elektrisitetsdistribusjon. SNF-report 3/1994
Kuosmanen T (2012) Stochastic semi-nonparametric frontier estimation of electricity distribution networks: application of the StoNED method in the Finnish regulatory model. Energy Econ 34:2189–2199. doi:10.1016/j.eneco.2012.03.005
Langset T, Syvertsen SC (2013) A new WACC model in the regulation of the Norwegian electricity network operators. Paper presented at the 1st Conference of the RCEM & ICSTF, ESCP Europe Business School, London
Ministry of Petroleum and Energy (2014) Et bedre organisert strømnett. Report from an expert commission, Oslo
NVE (2009) Endringer i normkostnadsmodellen for distribusjonsnettet. Memorandum from 22 October 2009
NVE (2011) Alderseffekter i NVEs kostnadsnormer—evaluering og analyser. NVE-report 21/2011
Shleifer A (1985) A theory of yardstick competition. Rand J Econ 16(3, autumn):319–332
Simar L, Wilson PW (2007) Estimation and inference in two-stage, semi-parametric models of production processes. J Econ 136(1):31–64. doi:10.1016/j.jeconom.2005.07.009
Waddams C (2000) Efficiency and productivity studies in incentive regulation of UK utilities. Revista de Economia del Rosario 3(2)
Weyman‐Jones T (2006) Efficiency and productivity analysis in regulation and governance. 4th NAPW Plenary Paper, New York
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Amundsveen, R., Kvile, H.M. (2016). Balancing Incentives: The Development and Application of a Regulatory Benchmarking Model. In: Greene, W., Khalaf, L., Sickles, R., Veall, M., Voia, MC. (eds) Productivity and Efficiency Analysis. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-23228-7_14
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DOI: https://doi.org/10.1007/978-3-319-23228-7_14
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