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

43 Pages Posted: 27 Feb 2003  

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: November 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: Predictability test, data mining, structural change, out-of-sample 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? (November 2002). ECB Working Paper No. 195. Available at SSRN: https://ssrn.com/abstract=358500

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)

77 Bastwick Street
London, EC1V 3PZ
United Kingdom

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