Comparing structural efficiency of unbalanced subsamples: A resampling adaptation of data envelopment analysis

This paper investigates the performance of a bootstrapping enhanced DEA to measure the relative structural efficiency of unbalanced subsamples. Although this issue plays an important role in applied DEA, it is often ignored, resulting in misleading conclusions concerning relative efficiency. It is shown, that a reasampling approach to DEA can cope with this problem and also allows the use of pooled samples. The distribution of a statistic to test the hypotheses of equal structural efficiency is derived from Monte Carlo simulations and compared with the corresponding statistic calculated from standard DEA results. While the resampling variant of DEA justifies the use of the normal approximation, this is not the case for standard DEA.