Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This study applies non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. Traditional issues in electricity sector benchmarking are addressed, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. Labour, capital, and peak load capacity are used as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) German electricity distribution utilities. A data envelopment analysis (DEA) is applied with constant returns to scale (CRS) as the main productivity analysis technique, whereas stochastic frontier analysis (SFA) with distance function is the 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.