Combining Two Approaches to Efficiency Measurement

Abstract:     
The advent of data envelopment analysis (DEA) enabled the measurement of efficiency to be extended to the case of multiple outputs. Prior to DEA we had the parametric approach based on multiple regression. We highlight some difficulties associated with these two approaches and present a hybrid which overcomes them whilst maintaining the respective advantages of each.

DEA is used to identify the frontier units. A model is then fitted to provide a relationship between the outputs and inputs of these efficient units.Thus our hybrid approach models the efficient frontier in a mathematical form; the resulting smooth representation allows all units to be naturally enveloped and hence slacks to be avoided. (Slacks are potential improvements for inefficient units which are not accounted for in the DEA (radial) score, and so have been problematic for DEA.) The approach identifies the DEA-efficient units and fits a smooth model to them using maximum correlation modeling. This new technique extends the method of multiple regression to the case where there are multiple variables on each side of the model equation (eg outputs and inputs). The resulting expression for the frontier permits managers to estimate the effect on their efficiency score of adjustments in one or more input or output levels.

Number of Pages in PDF File: 7

Keywords: data envelopment analysis, performance measurement, productivity, production theory

JEL Classification: C2, D2

Accepted Paper Series