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A general methodology for bootstrapping in non-parametric frontier models

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Simar, Léopold [UCL] Wilson, PW

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 non-parametric 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 & Wilson (1998) by allowing for heterogeneity in the structure of efficiency. A numerical illustration with real data is provided to illustrate the methodology.

Document type Article de périodique (Journal article) – Article de recherche
Publication date 2000
Language Anglais
Journal information "Journal of Applied Statistics" - Vol. 27, no. 6, p. 779-802 (2000)
Peer reviewed yes
Publisher Carfax Publishing (Basingstoke)
issn 0266-4763
e-issn 1360-0532
Publication status Publié
Affiliations UCL - EUEN/STAT - Institut de statistique
UCL - EUEN/CORE - Center for operations research and econometrics
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Bibliographic reference Simar, Léopold ; Wilson, PW. A general methodology for bootstrapping in non-parametric frontier models. In: Journal of Applied Statistics, Vol. 27, no. 6, p. 779-802 (2000)
Permanent URL http://hdl.handle.net/2078.1/43376