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...

This paper studies the extremal behavior of emerging market bonds in relation to equities and bond returns of developed markets. Returns on emerging markets fixed income investments are known to behave like equity returns, yet many studies have used techniques that do not account for their thick...

This paper introduces a measure of extremal correlation. Our measure of tail dependence does not require parametric specification of a copula (or dependence) function. It relies instead on the fact that moments of co-exceedances can be written in terms of tail indices. This simplifies the...

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...