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In-Sample or out-of-sample tests of predictability: which one should we use?

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Abstract

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. JEL Classification: C12; C22; C52;

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 195.

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Length: 43 pages
Date of creation: Nov 2002
Date of revision:
Handle: RePEc:ecb:ecbwps:20020195

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Keywords: Predictability test; data mining; structural change; out-of-sample inference.;

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