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

Quality and Efficiency — A DEA Based Analysis of the Austrian Electricity Distribution Sector

Roland Goerlich, University of Vienna, Austria AND E-Control Austria, Austria, roland.goerlich@univie.ac.at , Ulrich Ruehrnoessl, E-Control Austria, Austria, ulrich.ruehrnoessl@e-control.at
 
Suggested Citation
Roland Goerlich and Ulrich Ruehrnoessl (2017), "Quality and Efficiency — A DEA Based Analysis of the Austrian Electricity Distribution Sector", Data Envelopment Analysis Journal: Vol. 3: No. 1–2, pp 151-195. http://dx.doi.org/10.1561/103.00000019

Publication Date: 15 Nov 2017
© 2017 R. Goerlich and U. Ruehrnoessl
 
Subjects
Performance measurement,  Productivity measurement and analysis,  Semiparametric and nonparametric estimation,  Industrial organization
 
Keywords
EfficiencyQualityBenchmarkingInfrastructureElectricityNetworksRegulation
 

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In this article:
1. Introduction 
2. Current Regime to Regulate Electricity DSOs in Austria 
3. Empirical Analysis — Approach and Results 
4. Conclusions and Recommendations for Regulatory Action 
References 

Abstract

This paper analyses the impact of including quality of supply in a DEA analysis of a sample of Austrian electricity distribution system operators (DSOs). We outline the current Austrian regulatory regime, conduct a DEA-based analysis with various model specifications which is followed by a second stage analysis, carry out a sensitivity analysis regarding the price of quality and determine the shadow price for quality. We conclude that the definition of capital costs (book values versus annuities) exerts a much stronger influence on efficiency scores than the inclusion of quality (outage costs). Shadow prices might not lead to a social optimum if the present quality level is already too low or too high. Quality should be preferably treated as an integral part of the input cost base, i.e. by adding outage costs to network total costs (TOTEX) and not as a separate input. This should be done even if global test statistics suggest that the inclusion of quality has a non-significant impact on the mean of efficiency scores.

DOI:10.1561/103.00000019

Companion

Data Envelopment Analysis Journal, Volume 3, Issue 1-2 DEA and Regulation
See the other articles that are also part of this special issue.