Multiple Forecast Model Evaluation

© 2011 by Oxford University Press. All rights reserved.This article focuses on recent developments in the forecasting literature on how to simultaneously control both the overall error rate and the contribution of irrelevant models. As a novel contribution, it derives a general class of superior predictive ability tests, which controls for family-wise error rate (FWER) and the contribution of irrelevant models. The article is organized as follows. Section 2 defines the setup. Section 3 reviews the approaches that control for the conservative FWER. Section 4 considers a general class of tests characterized by multiple joint inequalities. Section 5 presents results allowing for control of the less conservative false discovery rate. Section 6 considers the model confidence set approach and offers a simple alternative that reduces the influence of irrelevant models in the initial set. Section 7 briefly reviews the empirical evidence, while Section 8 concludes