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More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation

Aldanondo, Ana M. and Casasnovas, Valero L. (2015): More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation.

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Abstract

The results of an experiment with simulated data show that combining inputs with different criteria (as cost, material inputs aggregates and other) increases the accuracy of the Data Envelopment Analysis (DEA) technical efficiency estimator in data sets with dimensionality problems. The positive impact of this approach surpasses that of reducing the number of variables, since replacement of the original inputs with an equal number of aggregates improves DEA performance in a wide range of cases.

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