Abstract
Data envelopment analysis (DEA), introduced in Charnes, Cooper, and Rhodes (1978), provides a new approach to the estimation of relative efficiencies of decision making units (DMUs). As described by Banker (1980b) and Banker, Charnes, and Cooper (1984), DEA also encompasses estimation of production frontiers making minimal assumptions—such as convexity—about the production possibility set. DEA may be employed to estimate technical and scale efficiencies as in Banker, Charnes, and Cooper, rates of substitution between inputs as in Banker, Charnes, and Cooper and Charnes, Cooper, and Rhodes (1978), and returns to scale and most productive scale sizes as in Banker (1984) and Banker, Charnes, and Cooper (1984). These estimates of different production characteristics pertain to the efficient production surface, unlike the commonly employed regression techniques which estimate the average production correspondence. In this chapter, we report on the results of a simulation study in which DEA was employed to estimate the production frontier from input and output data randomly generated from a known technology.
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Banker, R.D., Charnes, A., Cooper, W.W., Maindiratta, A. (1988). A Comparison of DEA and Translog Estimates of Production Frontiers Using Simulated Observations from a Known Technology. In: Dogramaci, A., Färe, R. (eds) Applications of Modern Production Theory: Efficiency and Productivity. Studies in Productivity Analysis, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3253-1_2
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DOI: https://doi.org/10.1007/978-94-009-3253-1_2
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