We propose a class of distribution-free rank-based tests for the null hypothesis of a unit root. This class is indexed by the choice of a , which needs not coincide with the unknown actual innovation density . The validity of these tests, in terms of exact finite sample size, is guaranteed,...

Classical estimation techniques for linear models either are inconsistent, or perform rather poorly, under α-stable error densities; most of them are not even rate-optimal. In this paper, we propose an original one-step R-estimation method and investigate its asymptotic performances under...

We consider the problem of detecting unobserved heterogeneity, that is, the problem of testing the absence of random individual effects in an n×T panel. We establish a local asymptotic normality property–with respect to intercept, regression coefficient, the scale parameter σ of the error,...