Sampling size and efficiency bias in data envelopment analysis

摘要

In Data Envelopment Analysis, when the number of decision making units is small,the number of units of the dominant or effcient set is relatively large and the average effciency isgenerally high. The high average effciency is the result of assuming that the units in the effcientset are 100% effcient. If this assumption is not valid, this results in an overestimation of theefficiencies, which will be larger for a smaller number of units. Samples of various sizes are usedto find the related bias in the effciency estimation. The samples are drawn from a large scaleapplication of DEA to bank branch efficiency. The effects of different assumptions as to returnsto scale and the number of inputs and outputs are investigated.