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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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    Cited by:

    1. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    2. 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.
    3. 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).
    4. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    5. 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.
    6. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. Puerta-Cuartas, Alejandro & Ramírez-Hassan, Andrés, 2025. "A spatial one-sided error model to identify where unarrested criminals live," Economic Modelling, Elsevier, vol. 142(C).
    8. 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.
    9. 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).
    10. 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).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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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