43 Pages Posted: 27 Feb 2003
Date Written: November 2002
It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this paper we question this conventional wisdom. Our analysis shows that neither data mining nor parameter instability is a plausible explanation of the observed tendency of in-sample tests to reject the no predictability null more often than out-of-sample tests. We provide an alternative explanation based on the higher power of in-sample tests of predictability. We conclude that results of in-sample tests of predictability will typically be more credible than results of out-of-sample tests.
Keywords: Predictability test, data mining, structural change, out-of-sample inference
JEL Classification: C12, C22, C52
Suggested Citation: Suggested Citation
Inoue, Atsushi and Kilian, Lutz, In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use? (November 2002). ECB Working Paper No. 195. Available at SSRN: https://ssrn.com/abstract=358500