A General Methodology for Bootstraping in Nonparametric Frontier Models

The Data Envelopment Analysis method has been extensively used in the literature to provide measures of firms’ technical efficiency. These measures allow rankings of firms by their apparent performance. The underlying frontier model is nonparametric since no particular functional form is assumed for the frontier model. Since the observations result from some data-generating process, the statistical properties of the estimated efficiency measures are essential for their interpretations. In the general multi-output, multi-input framework, the bootstrap seems to offer the only means of inferring these properties (i.e. to estimate the bias and variance, and to construct confidence intervals). This paper proposes a general methodology for bootstrapping in frontier models, extending the more restrictive method proposed in Simar and Wilson (1998a) by allowing for heterogeneity in the structure of efficiency. A numerical illustration with real data is provided to illustrate the methodology.

• metadata
• relations

Document type	Document de travail (Working Paper)
Access type	Accès libre
Publication date	1998
Language	Anglais
Number of pages	33 pages
Collection	STAT Discussion Papers - 9811
Affiliations	UCL - EUEN/STAT - Institut de statistique UCL - EUEN/CORE - Center for operations research and econometrics University of Texas - Department of Economics
Keywords	DEA ; Bootstrapping ; Nonparametric estimation ; Efficiency ; Frontier models
Links	http://sites.uclouvain.be/IAP-Stat-Phase-V-VI/ISBApub/ISBAdp.html#1998 http://hdl.handle.net/2078.1/123568[Handle]

See also
	[boreal:43376]	A general methodology for bootstrapping in non-parametric frontier models