期刊
JOURNAL OF ECONOMETRICS
卷 124, 期 1, 页码 1-31出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2003.12.011
关键词
power; forecast evaluation; Granger causality; model selection
This paper presents analytical, Monte Carlo, and empirical evidence on the effects of structural breaks on tests for equal forecast accuracy and encompassing. We show that out-of-sample predictive content can be hard to find because out-of-sample tests are highly dependent on the timing of the predictive ability. Moreover, predictive content is harder to find with some tests than others: in power, F-type tests of equal forecast accuracy and encompassing often dominate t-type alternatives. Based on these results and evidence from an empirical application, we conclude that structural breaks under the alternative may explain why researchers often find evidence of in-sample, but not out-of-sample, predictive content. (C) 2003 Elsevier B.V. All rights reserved.
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