Frontier estimation and extreme value theory
Copyright policy )Frontier estimation and extreme value theory
In this paper, we investigate the problem of nonparametric monotone frontier estimation from the perspective of extreme value theory. This enables us to revisit the asymptotic theory of the popular free disposal hull estimator in a more general setting, to derive new and asymptotically Gaussian estimators and to provide useful asymptotic confidence bands for the monotone boundary function. The finite-sample behavior of the suggested estimators is explored via Monte Carlo experiments. We also apply our approach to a real data set based on the production activity of the French postal services.
Published in at http://dx.doi.org/10.3150/10-BEJ256 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)
monotone boundaries, 330, Asymptotic distribution theory in statistics, Statistics of extreme values; tail inference, Monte Carlo methods, Mathematics - Statistics Theory, nonparametric estimation, Statistics Theory (math.ST), extreme values, conditional quantile, conditional quantiles, Asymptotic properties of nonparametric inference, production frontier, FOS: Mathematics, Nonparametric estimation, monotone boundary, B- ECONOMIE ET FINANCE
monotone boundaries, 330, Asymptotic distribution theory in statistics, Statistics of extreme values; tail inference, Monte Carlo methods, Mathematics - Statistics Theory, nonparametric estimation, Statistics Theory (math.ST), extreme values, conditional quantile, conditional quantiles, Asymptotic properties of nonparametric inference, production frontier, FOS: Mathematics, Nonparametric estimation, monotone boundary, B- ECONOMIE ET FINANCE
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