Chance‐constrained data envelopment analysis

Abstract

Abstract Data envelopment analysis (DEA) is extended to the case of stochastic inputs and outputs through the use of chance‐constrained programming. The chance‐constrained frontier envelops a given set of observations ‘most of the time’. As an empirical illustration, we re‐examine the pioneering 1981 study of Program Follow Through by Charnes, Cooper and Rhodes.