Partitioning input cost efficiency into its allocative and technical components: an empirical DEA application to hospitals

Abstract The study presents an empirical analysis of best practice production and cost frontiers for a sample of 94 acute care hospitals by applying Data Envelopment Analysis (DEA) and a regression model, in a two-stage approach. This paper contributes to the DEA and efficiency measurement literature by adding results from a homogeneous method of partitioning cost efficiency into its allocative (or price) and technical components, and by decomposing technical efficiency into scale, congestion and pure technical efficiency. Allocative efficiency is calculated using a DEA assurance approach. It introduces constraints with lower and upper bounds on the admissible values of weights of the CCD DEA model that computes technical efficiency. We thus obtain scores unbiased by the lack of precise information on input prices. In the second stage, a log-regression model is employed to test a number of hypotheses involving the role of ownership, market structure, and regulation in terms of differences amongst the various efficiency concepts measured. Results highlight the relevance of market concentration and public finance in explaining these differences.