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

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Author Info
Lutz Kilian () (European Central Bank, Kaiserstrasse 29, Postfach 16 03 19, 60066 Frankfurt am Main, Germany.)
Atsushi Inoue () (North Carolina State University, Department of Agricultural and Resource Economics, Box 8109, Raleigh NC 27695-8109, USA.)

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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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Publisher 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
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Handle: RePEc:ecb:ecbwps:20020195

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

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References listed on IDEAS
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