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Asymptotics And Consistent Bootstraps For Dea Estimators In Nonparametric Frontier Models

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Author Info
Kneip, Alois
Simar, L?opold
Wilson, Paul W.

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Abstract

Nonparametric data envelopment analysis (DEA) estimators based on linear programming methods have been widely applied in analyses of productive efficiency. The distributions of these estimators remain unknown except in the simple case of one input and one output, and previous bootstrap methods proposed for inference have not been proved consistent, making inference doubtful. This paper derives the asymptotic distribution of DEA estimators under variable returns to scale. This result is used to prove consistency of two different bootstrap procedures (one based on subsampling, the other based on smoothing). The smooth bootstrap requires smoothing the irregularly bounded density of inputs and outputs and smoothing the DEA frontier estimate. Both bootstrap procedures allow for dependence of the inefficiency process on output levels and the mix of inputs in the case of input-oriented measures, or on input levels and the mix of outputs in the case of output-oriented measures.

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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 24 (2008)
Issue (Month): 06 (December)
Pages: 1663-1697
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Handle: RePEc:cup:etheor:v:24:y:2008:i:06:p:1663-1697_08

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References listed on IDEAS
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  1. Kneip, A & Park, B-U & Simar, L, 1996. "A Note on the Convergence of Nonparametric DEA Efficiency Measures," Papers 9603, Catholique de Louvain - Institut de statistique.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. David C. Wheelock & Paul Wilson, 2007. "Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations," Working Papers 2005-027, Federal Reserve Bank of St. Louis. [Downloadable!]
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  2. Randall Campbell & Kevin Rogers & Jon Rezek, 2008. "Efficient frontier estimation: a maximum entropy approach," Journal of Productivity Analysis, Springer, vol. 30(3), pages 213-221, December. [Downloadable!] (restricted)
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