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dc.contributor.authorKittelsen, Sverre A. C.en
dc.date.accessioned2012-09-20T13:15:01Z-
dc.date.available2012-09-20T13:15:01Z-
dc.date.issued1999-
dc.identifier.urihttp://hdl.handle.net/10419/63113-
dc.description.abstractThe statistical properties of the efficiency estimators based on Data Envelopment Analysis (DEA) are largely unknown. Recent work by Simar et al. and Banker has shown the consistency of the DEA estimators under specific assumptions, and Banker proposes asymptotic tests of whether two subsamples have the same efficiency distribution. There are difficulties arising from bias in small samples and lack of independence in nested models. This paper suggest no new tests, but presents results on bias in simulations of nested small sample DEA models, and examines the approximating powers of suggested tests under various specifications of scale and omitted variables.en
dc.language.isoengen
dc.publisher|aUniversity of Oslo, Department of Economics |cOsloen
dc.relation.ispartofseries|aMemorandum |x1999,09en
dc.subject.jelD24en
dc.subject.jelC44en
dc.subject.jelC15en
dc.subject.ddc330en
dc.subject.keywordData Envelopment Analysisen
dc.subject.keywordMonte Carlo simulationsen
dc.subject.keywordHypothesis testsen
dc.subject.keywordNon-parametric efficiency estimationen
dc.subject.stwMonte-Carlo-Methodeen
dc.subject.stwMathematische Optimierungen
dc.subject.stwWirtschaftliche Effizienzen
dc.subject.stwTechnische Effizienzen
dc.subject.stwData-Envelopment-Analyseen
dc.subject.stwTheorieen
dc.titleMonte Carlo simulations of DEA efficiency measures and hypothesis tests-
dc.typeWorking Paperen
dc.identifier.ppn323421636en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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