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Disentangling Costs of Persistent and Transient Technical Inefficiency and Input Misallocation: The Case of Norwegian Electricity Distribution Firms

Author

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  • Subal C. Kumbhakar
  • Ørjan Mydland
  • Andrew Musau
  • Gudbrand Lien

Abstract

Numerous studies have focused on estimating technical inefficiency in electricity distribution firms. However, most of these studies did not distinguish between persistent and transient technical inefficiency. Furthermore, almost none of the studies estimated the cost of input misallocation arising from non-optimal use of inputs. One reason is that the cost function (input distance function) typically used in the literature does not allow for the separation of technical inefficiency and allocative inefficiency. In this study, we estimate both the persistent and transient components of technical inefficiency and input misallocation of Norwegian electricity distribution firms, using panel data from 2000 to 2016. Our modeling and estimation strategy is to use a system approach, consisting of the production function and the first-order conditions of cost minimization. Input misallocation for each pair of inputs is modeled via the first-order conditions of cost minimization. We also estimate the costs of each component of technical inefficiency and input misallocation by deriving the cost function for a multi-output separable production technology. Our modeling and estimation strategy handles endogeneity of inputs. Finally, we allow for inclusion of determinants of persistent and transient technical inefficiency. Our results show that the costs of input misallocation of Norwegian electricity distribution firms are non-negligible.

Suggested Citation

  • Subal C. Kumbhakar & Ørjan Mydland & Andrew Musau & Gudbrand Lien, 2020. "Disentangling Costs of Persistent and Transient Technical Inefficiency and Input Misallocation: The Case of Norwegian Electricity Distribution Firms," The Energy Journal, , vol. 41(3), pages 143-160, May.
    • Handle: RePEc:sae:enejou:v:41:y:2020:i:3:p:143-160
    DOI: 10.5547/01956574.41.3.skum
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    References listed on IDEAS

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    Cited by:

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    7. Christopher F. Parmeter & Subal C. Kumbhakar, 2025. "The generalized panel data stochastic frontier model: A review and nonparametric estimation," Journal of Productivity Analysis, Springer, vol. 64(3), pages 321-339, December.
    8. Badunenko, Oleg & Cullmann, Astrid & Nieswand, Maria, 2025. "Integrating renewable energy resources in electricity distribution systems—A firm-level efficiency analysis for Sweden controlling for weather conditions," Energy Economics, Elsevier, vol. 142(C).

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