DEA does not like positive discrimination : a comparison of alternative models based on empirical data

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Type
Report: a report published by a school or other institution, usually numbered within a series.
Publication sub-type
Working paper: Working papers contain results presented by the author. Working papers aim to stimulate discussions between scientists with interested parties, they can also be the basis to publish articles in specialized journals
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Title
DEA does not like positive discrimination : a comparison of alternative models based on empirical data
Author(s)
Huguenin J.-M.
Institution details
Swiss Graduate School of Public Administration
Address
Lausanne
Issued date
2014
Number
7/2014
Genre
Working paper de l'IDHEAP
Language
english
Number of pages
92
Abstract
Due to the existence of free software and pedagogical guides, the use of data envelopment analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run themselves their own efficiency analysis. Within DEA, several alternative models allow for an environment adjustment. Five alternative models, each of them easily accessible to and achievable by practitioners and decision makers, are performed using the empirical case of the 90 primary schools of the State of Geneva, Switzerland. As the State of Geneva practices an upstream positive discrimination policy towards schools, this empirical case is particularly appropriate for an environment adjustment. The alternative of the majority of DEA models deliver divergent results. It is a matter of concern for applied researchers and a matter of confusion for practitioners and decision makers. From a political standpoint, these diverging results could lead to potentially opposite decisions.
Grâce à l'existence de logiciels en libre accès et de guides pédagogiques, la méthode data envelopment analysis (DEA) s'est démocratisée ces dernières années. Aujourd'hui, il n'est pas rare que les décideurs avec peu ou pas de connaissances en recherche opérationnelle réalisent eux-mêmes leur propre analyse d'efficience. A l'intérieur de la méthode DEA, plusieurs modèles permettent de tenir compte des conditions plus ou moins favorables de l'environnement. Cinq de ces modèles, facilement accessibles et applicables par les décideurs, sont utilisés pour mesurer l'efficience des 90 écoles primaires du canton de Genève, Suisse. Le canton de Genève pratiquant une politique de discrimination positive envers les écoles défavorisées, ce cas pratique est particulièrement adapté pour un ajustement à l'environnement. La majorité des modèles DEA génèrent des résultats divergents. Ce constat est préoccupant pour les chercheurs appliqués et perturbant pour les décideurs. D'un point de vue politique, ces résultats divergents conduisent à des prises de décision différentes selon le modèle sur lequel elles sont fondées.
Keywords
Data Envelopment Analysis, environmental models, positive discrimination, priority education policy
Create date
27/01/2014 15:06
Last modification date
20/08/2019 16:14
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