Abstract
A dynamic version of data envelopment analysis (DEA) is developed in the present paper. Our model introduces investment in traditional DEA and imposes intertemporal cost minimization. Adding an intertemporal adjustment constraint into the cost minimization problem, we derive the relation between the DEA variables of the variable cost function and those of the primary production frontiers’ coefficients. The augmented DEA model can be solved using standard linear programming. This dynamic framework enables computing the production frontiers, measuring the productive efficiencies and evaluating the potential economies all in the presence of adjustment costs.
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