DATA ENVELOPMENT ANALYSIS and Confident-DEA

This work contributes to the Data Envelopment Analysis (DEA) literature at three ways. First it extends the roots of DEA by providing an analytical approach deriving the basic Charnes-Cooper-Rhodes (1978) model from the Weak Axiom of Profit Maximization (WAPM) of Firm Theory. Second this work provides a systematic way for classifying the existing DEA literature by offering a taxonomy. Finally a theoretical contribution to the literature Confident-DEA approach is proposed involving a bilevel convex optimization model to which a Genetic-Algorithm-based solution method is suggested. Complementing previous DEA methodologies which provides single valued efficiency measures Confident-DEA provides a range of values for the efficiency measures an efficiency confidence interval and hence the name reflecting the imprecision in data. Monte-Carlo simulation is used to determine the distribution of the efficiency measures taking into account the distribution of the bounded imprecise data over their corresponding intervals. Confident-DEA is applied to predict the efficiency of banking systems in OECD countries.