Tests Of Equal Forecast Accuracy For Overlapping Models

This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (1989). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of variables included in the competing forecasting models. The authors consider an out-of-sample version of the two-step testing procedure recommended by Vuong but also show that an exact one-step procedure is sometimes applicable. When the models are overlapping, they provide a simple-to-use fixed regressor wild bootstrap that can be used to conduct valid inference.

Provided by: Federal Reserve Bank of Cleveland Topic: Big Data Date Added: Sep 2011 Format: PDF

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