In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?
North Carolina State University - Department of Agricultural & Resource Economics
University of Michigan at Ann Arbor - Department of Economics; Centre for Economic Policy Research (CEPR)
ECB Working Paper No. 195
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.
Number of Pages in PDF File: 43
Keywords: Predictability test, data mining, structural change, out-of-sample inference
JEL Classification: C12, C22, C52working papers series
Date posted: February 27, 2003
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