STOCHASTIC-MODELS AND VARIABLE RETURNS TO SCALES IN DATA ENVELOPMENT ANALYSIS

Stochastic Data Envelopment Analysis (DEA) models were developed by ta king random disturbances into account for the possibility of variation s in input-output data structure. The stochastic efficiency measure of a Decision Making Unit (DMU) is defined via joint probabilistic compa risons of inputs and outputs with other DMUs, and can be characterized by solving a chance constrained programming problem. Deterministic eq uivalents are derived for both situations of multivariate symmetric ra ndom disturbances and a single random factor in the production relatio nships. An analysis of stochastic variable returns to scale is develop ed. (C) Elsevier Science B.V.