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Efficiency Analysis of German Electricity Distribution Utilities - Non-Parametric and Parametric Tests

[journal article]

Hirschhausen, Christian von
Cullmann, Astrid
Kappeler, Andreas

Abstract

This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence speci... view more

This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) German electricity distribution utilities. We apply a data envelopment analysis (DEA) with constant returns to scale (CRS) as the main productivity analysis technique, whereas stochastic frontier analysis (SFA) with distance function is our verification method. The results suggest that returns to scale play but a minor role; only very small utilities have a significant cost advantage. Low customer density is found to affect the efficiency score significantly, in particular in the lower third of all observations. Surprisingly, East German utilities feature a higher average efficiency than their West German counterparts. The correlation tests imply a high coherence of the results.... view less

Free Keywords
efficiency analysis; econometric methods; electricity distribution; benchmarking; Germany

Document language
English

Publication Year
2006

Page/Pages
p. 2553-2566

Journal
Applied Economics, 38 (2006) 21

DOI
https://doi.org/10.1080/00036840500427650

Status
Postprint; peer reviewed

Licence
PEER Licence Agreement (applicable only to documents from PEER project)


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.