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

Author

Listed:
  • 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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    References listed on IDEAS

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    3. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.

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