FEAR: A software package for frontier efficiency analysis with R

By Paul Wilson. 2008

563 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/58cc0169ac2e48a60e9ee8205c1baa37badb461c

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In Economics and Econometrics

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Citations in the corpus

Inference by the m out of n bootstrap in nonparametric frontier models (2011, methodology): “These methods would be easy for the applied researcher to implement using the FEAR software library developed by Wilson (2008) or perhaps other software, and therefore should be useful.”
Hypothesis testing in nonparametric models of production using multiple sample splits (2020, methodology): “The tests, together with the new bootstrap method introduced here, will soon be added to a future version of the FEAR software package described by Wilson (2008).”
WHEN BIAS KILLS THE VARIANCE: CENTRAL LIMIT THEOREMS FOR DEA AND FDH EFFICIENCY SCORES (2014, background): “…about the asymptotic properties of DEA and FDH estimators of efficiency for a fixed point (e.g., see Kneip, Park, and Simar, 1998; Kneip, Simar, and Wilson, 2008; Park, Jeong, and Simar, 2010; Park, Simar, and Weiner, 2000), and bootstrap methods are now available for making inference about the…”
When, where and how to perform efficiency estimation (2011, methodology): “For the estimator of Kneip et al. (2008) we use the FEAR (Wilson, 2008) package.”
Estimation and Inference in Nonparametric Frontier Models: Recent Developments and Perspectives (2013, methodology): “2The FEAR package (Wilson, 2008) uses a simplex method described by Hadley (1962).”
Does industrial upgrading promote eco-efficiency? ─A panel space estimation based on Chinese evidence (2021, methodology): “To address the weakness brought by the DEA model, we employ the Bootstrap-DEA method proposed by Wilson (2008) to measure the eco-efficiency of 30 provinces in China, which is a significant improvement compared to the traditional method.”
Probabilistic characterization of directional distances and their robust versions (2012, methodology): “These asymptotic properties have been extended to the hyperbolic α-quantile estimator in Wheelock and Wilson (2008) which we need here.”