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

Christian R. von Hirschhausen and Astrid Cullmann

No 06/05, Dresden Discussion Paper Series in Economics from Technische Universität Dresden, Faculty of Business and Economics, Department of Economics

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 specific to the situation in Germany This paper applies parametric and non-parametric and parametric tests to asses the efficiency of electricity distribution companies in Germany. We use labor, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data covers 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 a minor role; only very small utilities have a significant cost advantage. Low customer density is found to affect the efficiency score significantly 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.

Keywords: Efficiency analysis; econometric methods; electricity distribution; benchmarking; Germany (search for similar items in EconPapers)
JEL-codes: C14 L43 L51 L94 (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Journal Article: Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests (2006)
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