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Robust estimation of cost efficiency in non-parametric frontier models

Galina Besstremyannaya, Jaak Simm and Sergei Golovan
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Jaak Simm: University of Leuven
Sergei Golovan: New Economic School

No w0244, Working Papers from New Economic School (NES)

Abstract: The paper proposes a bootstrap methodology for robust estimation of cost efficiency in data envelopment analysis. Our algorithm re-samples "naive" input-oriented efficiency scores, rescales original inputs to bring them to the frontier, and then re-estimates cost efficiency scores for the rescaled inputs. We consider the cases with absence and presence of environmental variables. Simulation analyses with multi-input multi-output production function demonstrate consistency of the new algorithm in terms of the coverage of the confidence intervals for true cost efficiency. Finally, we offer real data estimates for Japanese banking industry. Using the nationwide sample of Japanese banks in 2009, we show that the bias of cost efficiency scores may be linked to the bank charter and the presence of the environmental variables in the model. A package `rDEA', developed in the R language, is available from the GitHub and CRAN repository.

Keywords: data envelopment analysis; cost efficiency; bias; bootstrap; banking (search for similar items in EconPapers)
JEL-codes: C44 C61 G21 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2017-12
New Economics Papers: this item is included in nep-ban, nep-eff and nep-ore
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