We consider bootstrap inference for estimators which are (asymptotically) biased. We show
that, even when the bias term cannot be consistently estimated, valid inference can be …

We propose methods for constructing regularized mixtures of density forecasts. We explore
a variety of objectives and regularization penalties, and we use them in a substantive …

The purpose of this paper is to show that the effect of the zero-correlation assumption in
combining forecasts can be huge, and that ignoring (positive) correlation can lead to …

In this paper, we use bootstrap approach to test the null hypothesis that all forecasters in the
US Surveys of Professional Forecasters (SPF) have equal ability. Our bootstrap procedure …

Combining forecasts has been widely applied as one of the approaches to increase the
predictive power over the past few decades. With the promising results, it has seen an …

The outbreak of the COVID-19 disease has exerted a deep and extensive influence on the
energy sector. The work modality and lifestyle caused by the confinement policy have …