In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?

Lutz Kilian and Atsushi Inoue

No 3671, CEPR Discussion Papers from C.E.P.R. Discussion Papers

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.

Keywords: Data mining; Parameter instability; Predictability test; Reliability of inference (search for similar items in EconPapers)
JEL-codes: C12 C22 C52 (search for similar items in EconPapers)
Date: 2002-12
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
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Citations: View citations in EconPapers (113)

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Journal Article: In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use? (2005)
Working Paper: In-sample or out-of-sample tests of predictability: which one should we use? (2002)
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