This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is computed with the Hodrick-Prescott filter...

Weather and temperatures vary in ways that are difficult to explain and predict precisely. In this article we review data on temperature variations in the past as well possible reasons for these variations. Subsequently, we review key properties of global climate models and statistical analyses...

Outlying observations can bias regression estimates, requiring the use of robust estimators. Comparing robust estimates to those obtained using OLS is a common robustness check, however, such comparisons have been mostly informal due to the lack of available tests. Here we introduce a formal...