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

✍ Scribed by Shiu-Sheng Chen

Publisher: John Wiley and Sons
Year: 2005
Tongue: English
Weight: 90 KB
Volume: 24
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.960

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✦ Synopsis

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 insample test fails to reject the null of non-causality.

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