Abstract
Abstract We apply a suite of models to produce quasi-real-time density forecasts of Norwegian GDP and inflation, and evaluate different combination and selection methods using the Kullback–Leibler information criterion (KLIC). We use linear and logarithmic opinion pools in conjunction with various weighting schemes, and we compare these combinations to two different selection methods. In our application, logarithmic opinion pools were better than linear opinion pools, and score-based weights were generally superior to other weighting schemes. Model selection generally yielded poor density forecasts, as evaluated by KLIC.
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