Benchmarking with uncertain data: a simulation study comparing alternative methods
Jens Hougaard (),
Pieter Jan Kerstens () and
Kurt Nielsen ()
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Pieter Jan Kerstens: Department of Food and Resource Economics, University of Copenhagen
Kurt Nielsen: Department of Food and Resource Economics, University of Copenhagen
No 2019/05, IFRO Working Paper from University of Copenhagen, Department of Food and Resource Economics
We consider efficiency measurement methods in the presence of uncertain input and output data, and without the (empirically problematic) assumption of convexity of the production technology. In particular, we perform a simulation study in order to contrast two well-established methods, IDEA and Fuzzy DEA, with a recently suggested extension of Fuzzy DEA in the literature (dubbed the HB method). We demonstrate that the HB method has important advantages over the conventional methods, resulting in more accurate efficiency estimates and narrower bounds for the efficiency scores of individual Decision Making Units (DMUs): thereby providing more informative results that may lead to more effective decisions. The price is computational complexity. Although we show how to significantly speed up computational time compared to the original suggestion, the HB method remains the most computationally heavy method among those considered. This may limit the use of the method in cases where efficiency estimates have to be computed on the fly, as in interactive decision support systems based on large data sets.
Keywords: data envelopment analysis; data uncertainty; fuzzy; imprecise data envelopment analysis; simulation (search for similar items in EconPapers)
JEL-codes: C61 D24 (search for similar items in EconPapers)
Pages: 27 pages
New Economics Papers: this item is included in nep-cmp and nep-eff
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Persistent link: https://EconPapers.repec.org/RePEc:foi:wpaper:2019_05
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