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

Atsushi Inoue and Lutz Kilian

No 195, Working Paper Series from European Central Bank

Abstract: It is widely known that significant in-sample evidence of predictability does not garantuee significant out-of-sample predictability. This is often interpreted as an indiciation 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-smaple 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

Keywords: Data mining; Out-of-sample inference.; Predictability text; structural change (search for similar items in EconPapers)
Date: 2002-11
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Citations: View citations in EconPapers (64)

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Related works:
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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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:2002195

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