In-sample tests of predictive ability: a new approach

Todd Clark and Michael McCracken

No RWP 09-10, Research Working Paper from Federal Reserve Bank of Kansas City

Abstract: This paper presents analytical, Monte Carlo, and empirical evidence linking in-sample tests of predictive content and out-of-sample forecast accuracy. Our approach focuses on the negative effect that finite-sample estimation error has on forecast accuracy despite the presence of significant population-level predictive content. Specifically, we derive simple-to-use in-sample tests that test not only whether a particular variable has predictive content but also whether this content is estimated precisely enough to improve forecast accuracy. Our tests are asymptotically non-central chi-square or non-central normal. We provide a convenient bootstrap method for computing the relevant critical values. In the Monte Carlo and empirical analysis, we compare the effectiveness of our testing procedure with more common testing procedures.

Date: 2009
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets and nep-for
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Journal Article: In-sample tests of predictive ability: A new approach (2012)
Working Paper: In-sample tests of predictive ability: a new approach (2009)
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