Data Envelopment Analysis Journal > Vol 3 > Issue 1–2

Use of Data Envelopment Analysis for Incentive Regulation of Electric Distribution Firms

Rajiv Banker, Temple University, USA, Finn R. Førsund, University of Oslo, Norway, Daqun Zhang, Texas A&M University — Corpus Christi, USA,
Suggested Citation
Rajiv Banker, Finn R. Førsund and Daqun Zhang (2017), "Use of Data Envelopment Analysis for Incentive Regulation of Electric Distribution Firms", Data Envelopment Analysis Journal: Vol. 3: No. 1–2, pp 1-47.

Published: 15 Nov 2017
© 2017 R. Banker, F. R. Førsund and D. Zhang
Management control,  Performance measurement,  Econometric models: identification,  Econometric models: model choice and specification analysis,  Productivity measurement and analysis,  Industrial organization: regulatory economics
Incentive regulationElectricity distributionData envelopment analysis

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In this article:
1. Introduction
2. Specification of Inputs and Outputs
3. What Costs to Compare
4. Imposing Structure on Benchmarking Models
5. Treatment of Contextual Variables
6. Incentive Regulation in Norway
7. Incentive Regulation in Finland
8. Incentive Regulation in Brazil
9. Conclusion


Regulators worldwide increasingly use data envelopment analysis (DEA) for the incentive regulation of electric distribution firms. Although the production/cost frontiers estimated by DEA models provide valuable information for electricity rate setting, the benefit of DEA benchmarking in regulatory practice would be limited due to specification errors of DEA models. In this paper, we summarize and discuss existing issues of using DEA models for efficiency benchmarking from four aspects: 1. Specification of inputs and outputs, 2. Selection of costs for benchmarking, 3. Imposition of structure on benchmarking models, and 4. Treatment of contextual variables. We also give suggestions for improving the use of DEA models.



Data Envelopment Analysis Journal, Volume 3, Issue 1-2 DEA and Regulation
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