Testing for Productive Efficiency with Errors-in-Variables: with an application to the Dutch electricity sesctor

We develop a nonparametric test of productive efficiency that accounts for the possibility of errors-in-variables. The test allows for statistical inference based on the extreme value distribution of the L?? norm. In contrast to the test proposed by Varian, H (1985): 'Nonparametric Analysis of Optimising Behaviour with Measurement Error, Journal of Econometrics 30, 445-458, our test can be computed using simple enumeration algorithms or linear programming. An empirical application for the Dutch electricity sector illustrates the proposed test procedure

Non-Parametric Tests for Firm Efficiency in Case of Errors-in-Variables

This paper develops a novel statistic for firm efficiency called efficiency depth that allows for statistical inference in case of errors-in-variables. We derive statistical tests that require minimal statistical assumptions; neither the sample distribution nor the noise level is required. An empirical illustration for European banks illustrates that - despite the minimal assumptions- the tests can have substantial discriminating power in practical applications