BIRS Workshop Lecture Videos
Frontier estimation in the presence of measurement error with unknown variance Van Keilegom, Ingrid
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.
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