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A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway

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  • Luis Orea
  • Inmaculada C. Alvarez
  • Tooraj Jamasb

Abstract

An important methodological issue in efficiency analysis for incentive regulation of utilities is how to account for the effect of unobserved cost drivers such as environmental factors. We combine a spatial econometric approach with stochastic frontier analysis to control for unobserved environmental conditions when measuring efficiency of electricity distribution utilities. Our empirical strategy relies on the geographic location of firms as a source of information that has previously not been explored in the literature. The underlying idea is to utilise data from neighbouring firms that can be spatially correlated as proxies for unobserved cost drivers. We illustrate this approach using a dataset of Norwegian distribution utilities for the 2004-2011 period. We show that the lack of information on weather and geographic conditions can be compensated with data from surrounding firms. The methodology can be used in efficiency analysis and regulation of other utilities sectors where unobservable cost drivers are important, e.g. gas, water, agriculture, fishing.

Suggested Citation

  • Luis Orea & Inmaculada C. Alvarez & Tooraj Jamasb, 2018. "A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway," The Energy Journal, , vol. 39(3), pages 93-116, May.
    • Handle: RePEc:sae:enejou:v:39:y:2018:i:3:p:93-116
    DOI: 10.5547/01956574.39.3.lore
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    1. Toru Hattori & Tooraj Jamasb & Michael Pollitt, 2005. "Electricity Distribution in the UK and Japan: A Comparative Efficiency Analysis 1985-1998," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-48.
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    5. Haney, Aoife Brophy & Pollitt, Michael G., 2013. "International benchmarking of electricity transmission by regulators: A contrast between theory and practice?," Energy Policy, Elsevier, vol. 62(C), pages 267-281.
    6. 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.
    7. Growitsch, Christian & Jamasb, Tooraj & Wetzel, Heike, 2012. "Efficiency effects of observed and unobserved heterogeneity: Evidence from Norwegian electricity distribution networks," Energy Economics, Elsevier, vol. 34(2), pages 542-548.
    8. Wang, Hung-Jen, 2003. "A Stochastic Frontier Analysis of Financing Constraints on Investment: The Case of Financial Liberalization in Taiwan," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 406-419, July.
    9. 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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    Cited by:

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    2. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Glass, Anthony J. & Kenjegalieva, Karligash & Douch, Mustapha, 2020. "Uncovering spatial productivity centers using asymmetric bidirectional spillovers," European Journal of Operational Research, Elsevier, vol. 285(2), pages 767-788.
    4. Zhang, Qizheng & Qian, Zesen & Wang, Shuo & Yuan, Lingran & Gong, Binlei, 2022. "Productivity drain or productivity gain? The effect of new technology adoption in the oilfield market," Energy Economics, Elsevier, vol. 108(C).
    5. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim J.S., 2024. "Can operational efficiency in the Portuguese electricity sector be improved? Yes, but..," Energy Policy, Elsevier, vol. 190(C).
    6. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    7. Anthony J. Glass & Karligash Kenjegalieva, 2023. "Dynamic returns to scale and geography in U.S. banking," Papers in Regional Science, Wiley Blackwell, vol. 102(1), pages 53-85, February.
    8. Álvarez, Inmaculada C. & Gude, Alberto & Orea, Luis, 2019. "Effects of inter-industry and spatial spillovers on regional productivity: Evidence from Spanish panel data," Efficiency Series Papers 2019/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    9. Anthony J. Glass & Karligash Kenjegalieva, 2024. "Returns to scale, spillovers and persistence: A network perspective of U.S. bank size," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2049-2076, April.
    10. 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.
    11. Kerui Du & Luis Orea & Inmaculada C. Álvarez, 2024. "Fitting spatial stochastic frontier models in Stata," Stata Journal, StataCorp LP, vol. 24(3), pages 402-426, September.
    12. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    13. Glass, Anthony J. & Kenjegalieva, Karligash, 2019. "A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992–2015," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1165-1179.
    14. 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

    spatial econometrics; stochastic frontier models; environmental; conditions; electricity distribution networks;
    All these keywords.

    JEL classification:

    • F0 - International Economics - - General

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