Abstract
Models of data envelopment analysis DEA , which have been widely used in recent times in operations research for measuring productive efficiency, are essentially based on a set of virtual multipliers, which are optimally solved for in the models. We interpret these multipliers as prices and weights and show that these interpretations allow a more generalized view of the DEA model. Thus the multipliers as weights allow direct use of the canonical correlation theory of statistical data analysis. The price interpretation allows a dynamic view of the intertemporal production frontier, which in some cases yields the static efficiency frontier that is mostly studied in the standard DEA models.
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