In-sample or out-of-sample tests of predictability: which one should we use? - Atsushi Inoue; Lutz Kilian (European Central Bank (ECB), 2002)
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.
Keywords: C12; C22; C52; 330; Data mining; Out-of-sample inference; Predictability text; Structural change