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date: 19 November 2019

Abstract and Keywords

This article discusses out-of-sample evaluation based on assessing the conditional predictive ability of forecasting models, which stands in contrast to the notion of unconditional predictive ability testing. Here the word “conditional” refers to any approach in the literature that has gone beyond assessing the forecasting performance of models on average. The common thread which unites the papers discussed in this article is the argument that focusing solely on the average, or global, performance of a model may result in a loss of information and possibly lead to incorrect forecast selection decisions. Most of the discussion focuses on the problem of comparing the performance of two competing forecasts, but some extensions to different testing environments are also pointed out.

Keywords: forecasting models, economic forecasting, conditional predictive ability

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