Monte Carlo simulations of DEA efficiency measures and hypothesis tests

Arbeitspapier

The 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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Memorandum ; No. 1999,09

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity ; Operations Research; Statistical Decision Theory ; Statistical Simulation Methods: General
• Thema: Data Envelopment Analysis ; Monte Carlo simulations ; Hypothesis tests ; Non-parametric efficiency estimation ; Monte-Carlo-Methode ; Mathematische Optimierung ; Wirtschaftliche Effizienz ; Technische Effizienz ; Data-Envelopment-Analyse ; Theorie

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Kittelsen, Sverre A. C.
• Ereignis: Veröffentlichung
• (wer): University of Oslo, Department of Economics
• (wo): Oslo
• (wann): 1999

Weitere Informationen

• Handle: http://hdl.handle.net/10419/63113
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ