We study the problem of identifying a forecaster’s loss function from observations on forecasts, realizations, and the forecaster’s information set. Essentially different loss functions can lead to the same forecasts in all situations, though within the class of all continuous loss...

In this paper a new class of tests for parameter stability, the moving-estimates (ME) test, is proposed. It is shown that in the standard situation the ME test asymptotically equivalent to the maximal likelihood ratio test under the alternative of a temporary parameter shift. It is also shown...

We propose a nonparametric test of conditional independence based on the weighted Hellinger distance between the two conditional densities, <italic>f</italic>(<italic>y</italic>|<italic>x</italic>,<italic>z</italic>) and <italic>f</italic>(<italic>y</italic>|<italic>x</italic>), which is identically zero under the null. We use the functional delta method to expand the test statistic around the population value...

This note demonstrates that the conditions of Kotlarski’s (1967, <italic>Pacific Journal of Mathematics</italic> 20(1), 69–76) lemma can be substantially relaxed. In particular, the condition that the characteristic functions of <italic>M</italic>, <italic>U</italic> ₁, and <italic>U</italic> ₂ are nonvanishing can be replaced with much weaker conditions:...

We analyze fast procedures for conducting Monte Carlo experiments involving bootstrap estimators, providing formal results establishing the properties of these methods under general conditions.