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

Autor:	Aldanondo, Ana M., Casasnovas, Valero L.
Rok vydání:	2015
Předmět:	jel:C61 jel:D20 jel:C14 Technical efficiency Aggregation bias Monte Carlo DEA Estimator accuracy
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=od_______645::9afb2a9921fcd2a8961d4ae76ea24a7b https://mpra.ub.uni-muenchen.de/64120/1/MPRA_paper_64120.pdf Zobrazit plný text záznamu