This paper explores tests of the hypothesis that the tail thickness of a distribution is constant over time. Using Hill's conditional maximum likelihood estimator for the tail index of a distribution, tests of tail shape constancy are constructed that allow for an unknown breakpoint. The...

This paper introduces a nonparametric estimator for tail dependence in the constant conditional correlation GARCH framework, in contrast to existing estimators that impose the iid assumption. So long as stationarity is satisfied, the difference between the distribution of the tail dependence...

The immense literature and diversity of unit root tests can at times be confusing even to the specialist and presents a truly daunting prospect to the uninitiated. In consequence, much empirical work still makes use of the simplest testing procedures because it is unclear from the literature and...

This paper proposes an approach to testing for coefficient stability in cointegrating regressions in time series models. The test statistic considered is the one-sided version of the Lagrange Multiplier (LM) test. Its limit distribution is non-standard but is nuisance parameter free and can be...

It is shown that the maximum likelihood estimator of a local to unity parameter can be consistently estimated with panel data when the cross-section observations are independent. Consistency applies when there are no deterministic trends or when there is a homogeneous deterministic trend in the...

The author derives some exact finite sample disbibutions and characterizes the tail behavior of maximum likelihood estimators of the cointegrating coefficients in error correction models. The reduced rank regression estimator has a distribution with Cauchy-like tails and no finite moments of...