A note on in-sample and out-of-sample tests for Granger causality

Shiu-Sheng Chen

Journal of Forecasting, 2005, vol. 24, issue 6, 453-464

Abstract: This paper studies in-sample and out-of-sample tests for Granger causality using Monte Carlo simulation. The results show that the out-of-sample tests may be more powerful than the in-sample tests when discrete structural breaks appear in time series data. Further, an empirical example investigating Taiwan's investment-saving relationship shows that Taiwan's domestic savings may be helpful in predicting domestic investments. It further illustrates that a possible Granger causal relationship is detected by out-of-sample tests while the in-sample test fails to reject the null of non-causality. Copyright © 2005 John Wiley & Sons, Ltd.

Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:24:y:2005:i:6:p:453-464

DOI: 10.1002/for.960

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