ITERATED BOOTSTRAP WITH APPLICATIONS TO FRONTIER MODELS

The iterated bootstrap may be used to estimate errors which arise from a single pass of the bootstrap and thereby to correct for them. Here the iteration is employed to correct for coverage probability of confi dence intervals obtained by a percentile method in the context of prod uction frontier estimation with panel data. The parameter of interest is the maximum of the intercepts in a fixed firm effect model. The boo tstrap distribution estimators are consistent if and only if there are no ties for this maximum. In the regular case (no ties), poor distrib ution estimators can result when the second largest intercept is close to the maximum. The iterated bootstrap is thus suggested to improve t he accuracy of the obtained distributions. The result is illustrated i n the analysis of labor efficiency of railway companies.