We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test...

We generalize the refinement ordering for well calibrated probability forecasters to the case were the debtors under consideration are not necessarily identical. This ordering is consistent with many well known skill scores used in practice. We also add an illustration using default predictions...

The paper explores the relationship between various orderings among probability forecasts that have been suggested in the literature. It is shown that well calibrated forecasters are in general not comparable according to the domination ordering suggested by Vardeman and Meeden (1983), that the...

The paper considers tests against for autocorrelation among the disturbances in linear regression models that can be expressed as ratios of quadratic forms. It shows that such tests are in general not unbiased and that power can even drop to zero for certain regressors and spatial weight...

The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the...

We show that the weak Pareto law, as used to characterize the tail behaviour of income distributions, implies regularly varying tail probabilities, but that the reverse implication does not hold. We also establish implications among other versions of the weak Pareto law.

Die finanzwirtschaftliche Bedeutung von Kreditausfällen und Kreditausfall- Prognosen bedarf keiner weiteren Begründung. Dieser Bedeutung angemessen, gibt es inzwischen eine Vielzahl von Modellen und Verfahren, die Ausfallwahrscheinlichkeiten von Bankkrediten oder Industrieanleihen zu...