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Frontier estimation in the presence of measurement error with unknown variance

Banff International Research Station for Mathematical Innovation and Discovery

We consider the problem of estimating a stochastic frontier, i.e. a frontier that is subject to (additive) measurement error. Contrary to other papers in the literature who work with unknown frontiers and normal noise variables, we consider the case where the variance of the noise is unknown. We show that under weak model assumptions this variance is identifiable, and we propose three ways to estimate this variance. The first proposal is given in Kneip, Simar and Van Keilegom (2015), who study the asymptotic theory and finite sample behavior in detail. The two other proposals are currently under investigation. Preliminary results will be given showing their excellent finite sample behavior. All three methods will first be studied in the univariate case (i.e. in the case where the boundary of the support of a univariate variable is of interest). The extension to (two- or more-dimensional) frontier models will be given in a second step.

Mathematics; Statistics; Probability theory and stochastic processes

video/mp4

Author affiliation: Université catholique de Louvain

2017-02-16

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/60605

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/