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dc.contributor.authorSimar, Léopolden
dc.date.accessioned2009-01-29T14:55:06Z-
dc.date.available2009-01-29T14:55:06Z-
dc.date.issued2003-
dc.identifier.piurn:nbn:de:kobv:11-10050382en
dc.identifier.urihttp://hdl.handle.net/10419/22248-
dc.description.abstractIn frontier analysis, most of the nonparametric approaches (DEA, FDH) are based on envelopment ideas which suppose that with probability one, all the observed units belong to the attainable set. In these "deterministic" frontier models, statistical theory is now mostly available. In the presence of noise, this is no more true and envelopment estimators could behave dramatically since they are very sensitive to extreme observations that could result only from noise. DEA/FDH techniques would provide estimators with an error of the order of the standard deviation of the noise. In this paper we propose to adapt some recent results on detecting change points, to improve the performances of the classical DEA/FDH estimators in the presence of noise. We show by simulated examples that the procedure works well when the noise is of moderate size, in term of noise to signal ratio. It turns out that the procedure is also robust to outliers.en
dc.language.isoengen
dc.publisher|aHumboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes |cBerlinen
dc.relation.ispartofseries|aSFB 373 Discussion Paper |x2003,33en
dc.subject.ddc330en
dc.subject.keywordNonparametric frontieren
dc.subject.keywordStochastic DEA/FDHen
dc.subject.keywordRobustness to outliersen
dc.subject.stwNichtparametrisches Verfahrenen
dc.subject.stwData-Envelopment-Analyseen
dc.subject.stwSchätztheorieen
dc.subject.stwTheorieen
dc.titleHow to Improve the Performances of DEA/FDH Estimators in the Presence of Noise?-
dc.typeWorking Paperen
dc.identifier.ppn379165767en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:sfb373:200333en

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