In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?

34 Pages Posted: 15 Jan 2003

See all articles by Atsushi Inoue

Atsushi Inoue

Southern Methodist University

Lutz Kilian

University of Michigan at Ann Arbor - Department of Economics; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: December 2002

Abstract

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.

Keywords: Data mining, parameter instability, predictability test, reliability of inference

JEL Classification: C12, C22, C52

Suggested Citation

Inoue, Atsushi and Kilian, Lutz, In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use? (December 2002). CEPR Discussion Paper No. 3671. Available at SSRN: https://ssrn.com/abstract=369560

Atsushi Inoue

Southern Methodist University ( email )

Dallas, TX 75275
United States

Lutz Kilian (Contact Author)

University of Michigan at Ann Arbor - Department of Economics ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States
734-764-2320 (Phone)
734-764-2769 (Fax)

Centre for Economic Policy Research (CEPR)

London
United Kingdom

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