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dc.contributor.authorKittelsen, Sverre A. C.en_US
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_US
dc.publisherDep. of Economics, Univ. of Oslo Osloen_US
dc.relation.ispartofseriesMemorandum, Department of Economics, University of Oslo 1999,09en_US
dc.subject.keywordData Envelopment Analysisen_US
dc.subject.keywordMonte Carlo simulationsen_US
dc.subject.keywordHypothesis testsen_US
dc.subject.keywordNon-parametric efficiency estimationen_US
dc.subject.stwMathematische Optimierungen_US
dc.subject.stwWirtschaftliche Effizienzen_US
dc.subject.stwTechnische Effizienzen_US
dc.titleMonte Carlo simulations of DEA efficiency measures and hypothesis testsen_US
dc.typeWorking Paperen_US
Appears in Collections:Memorandum, Department of Economics, University of Oslo

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