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A general methodology for bootstrapping in non-parametric frontier models

Simar, Léopold, Wilson, Paul W.·2000·Journal of Applied Statistics

Abstract

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.

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Metadata

Authors
Simar, L., & Wilson, P. W.
Venue
Journal of Applied Statistics
Published
2000-08
Volume
27
Issue
6
Pages
779-802
ISSN
  • 0266-4763 (ISSN-L)
  • 1360-0532
OpenAlex
W1975935631
Cited by
1,149
References
2
FWCI
14.05
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A general methodology for bootstrapping in non-parametric frontier models. https://app.cochat.ai/papers/10.1080/02664760050081951
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Simar, L., & Wilson, P. W. (2000). A general methodology for bootstrapping in non-parametric frontier models. Journal of Applied Statistics. https://doi.org/10.1080/02664760050081951

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