ASPECTS OF STATISTICAL-ANALYSIS IN DEA-TYPE FRONTIER MODELS

In Grosskopf (1995) and Banker (1995) different approaches and problem s of statistical inference in DEA frontier models are presented. This paper focuses on the basic characteristics of DEA models from a statis tical point of view. It arose from comments and discussions on both pa pers above. The framework of DEA models is deterministic (all the obse rved points lie on the same side of the frontier), nevertheless a stoc hastic model can be constructed once a data generating process is defi ned. So statistical analysis may be performed and sampling properties of DEA estimators can be established. However, practical statistical i nference (such as test of hypothesis, confidence intervals) still need s artifacts like the bootstrap to be performed. A consistent bootstrap relies also on a clear definition of the data generating process and on a consistent estimator of it: The approach of Simar and Wilson (199 5) is described. Finally, some trails are proposed for introducing sto chastic noise in DEA models, in the spirit of the Kneip-Simar (1995) a pproach.