Partial frontier efficiency analysis for Stata

Abstract

Despite its frequent use in applied work, nonparametric approaches to efficiency analysis, namely data envelopment analysis (DEA) and free disposal hull (FDH), have bad reputations among econometricians. This is mainly due to DEA and FDH representing deterministic approaches that are highly sensitive to outliers and measurement errors. However, recently, so-called partial frontier approaches namely order-m and order-alpha have been developed. They generalize FDH by allowing for super-efficient observations to be located beyond the estimated production-possibility frontier. Although these methods are purely nonparametric too, sensitivity to outliers is substantially reduced by partial frontier approaches enveloping just a sub-sample of observations. We introduce the new Stata commands orderm and orderalpha that implement order-m, order-alpha, and FDH efficiency analysis in Stata. The commands allow for several options, such as statistical inference based on sub-sampling bootstrap.