DEA efficiency for the benchmarking of Iranian electric distribution utilities

During recent years, Iranian authorities have tried to make competitive condition and to grant distribution companies to private sectors. The aim of Iranian authorities is not only to prevent the misuse of the monopoly position, but also to provide companies with efficiency incentives. In this paper, a new algorithm is presented to assess the efficiency of Iranian electric companies using data envelopment analysis (DEA) with principle component analysis (PCA). One of the important steps in the design of the benchmarking model is selecting input and output variables. PCA is used to reduce the number of input and output variables. DEA efficiency is highly sensitive to errors in the data, so a bootstrap method is used to assess this uncertainty by estimating bias and confidence intervals. The results of benchmarking include DEA efficiency score (overall, technical and scale efficiency) and bootstrap technique.