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Weather Factors and Performance of Network Utilities: A Methodology and Application to Electricity Distribution

Author

Listed:
  • Tooraj Jamasb

    (Department of Economics, Heriot-Watt University)

  • Luis Orea

    (Faculty of Economics, University of Cambridge Department of Economics, University of Oviedo)

  • Michael G. Pollitt

    (EPRG, Electricity Policy Research Group Judge Business School, University of Cambridge)

Abstract

Incentive regulation and efficiency analysis of network utilities often need to take the effect of important external factors, such as the weather conditions, into account. This paper presents a method for estimating the effect of weather conditions on the costs of electricity distribution networks using parametric techniques. It examines whether the use of popular statistical variable reduction techniques is conceptually and econometrically sound for analyzing the effect of weather on the network costs. In this paper we estimate cost functions with the whole set of weather variables, identifying, when necessary, a subset of variables that can accurately reflect the effects of weather conditions. We show that weather conditions significantly affect distribution costs and the absence of weather variables has a downward biased impact on the effect of quality on costs. Also, the performance of statistical weather composites to capture this effect is poor. Finally, we show that there is a distinction between the effects of persistent and time varying weather conditions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Tooraj Jamasb & Luis Orea & Michael G. Pollitt, 2010. "Weather Factors and Performance of Network Utilities: A Methodology and Application to Electricity Distribution," Working Papers EPRG 1020, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1020
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    References listed on IDEAS

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    1. repec:cup:cbooks:9780521623940 is not listed on IDEAS
    2. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    3. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    4. P. Nillesen & M. Pollitt, 2010. "Using Regulatory Benchmarking Techniques to Set Company Performance Targets: The Case of Us Electricity," Competition and Regulation in Network Industries, Intersentia, vol. 11(1), pages 50-85, March.
    5. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    6. Lewin, Arie Y & Morey, Richard C & Cook, Thomas J, 1982. "Evaluating the administrative efficiency of courts," Omega, Elsevier, vol. 10(4), pages 401-411.
    7. Wagner, Janet M. & Shimshak, Daniel G., 2007. "Stepwise selection of variables in data envelopment analysis: Procedures and managerial perspectives," European Journal of Operational Research, Elsevier, vol. 180(1), pages 57-67, July.
    8. Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
    9. William Yu & Tooraj Jamasb & Michael Pollitt, 2009. "Willingness-to-Pay for Quality of Service: An Application to Efficiency Analysis of the UK Electricity Distribution Utilities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-48.
    10. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    11. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    12. Yu, William & Jamasb, Tooraj & Pollitt, Michael, 2009. "Does weather explain cost and quality performance? An analysis of UK electricity distribution companies," Energy Policy, Elsevier, vol. 37(11), pages 4177-4188, November.
    13. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    14. Kim, Moshe, 1986. "Banking technology and the existence of a consistent output aggregate," Journal of Monetary Economics, Elsevier, vol. 18(2), pages 181-195, September.
    15. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    16. Denny, Michael & Fuss, Melvyn A, 1977. "The Use of Approximation Analysis to Test for Separability and the Existence of Consistent Aggregates," American Economic Review, American Economic Association, vol. 67(3), pages 404-418, June.
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    Cited by:

    1. Rahmatallah Poudineh & Tooraj Jamasb, 2013. "Investment and Efficiency under Incentive Regulation: The Case of the Norwegian Electricity Distribution Networks," Cambridge Working Papers in Economics 1310, Faculty of Economics, University of Cambridge.
    2. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    3. Karim L. Anaya & Michael G. Pollitt, 2014. "Does Weather Have an Impact on Electricity Distribution Efficiency? Evidence from South America," Cambridge Working Papers in Economics 1424, Faculty of Economics, University of Cambridge.
    4. Andaluz-Alcazar, Alvaro, 2012. "Choix d'investissement sous incertitude des gestionnaires des réseaux de distribution (GRD) en Europe à l'horizon 2030," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/10862 edited by Keppler, Jan Horst.
    5. Greene, William & Orea, Luis & Wall, Alan, 2011. "A one-stage random effect counterpart of the fixed-effect vector decomposition model with an application to UK electricity distribution utilities," Efficiency Series Papers 2011/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).

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    More about this item

    Keywords

    Electricity distribution cost; separability; weather composites; instrumental variable estimator.;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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