DP3671 In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?
|Author(s):||Atsushi Inoue, Lutz Kilian|
|Publication Date:||December 2002|
|Keyword(s):||data mining, parameter instability, predictability test, reliability of inference|
|JEL(s):||C12, C22, C52|
|Programme Areas:||International Macroeconomics|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=3671|
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.