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

Chen, Shiu-Sheng; SHIU-SHENG CHEN

doi:10.1002/for.960

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

Resource

Journal of Forecasting, 26(4), 453-464

Journal

Journal of Forecasting

Journal Volume

24

Journal Issue

6

Pages

453-464

Date Issued

2005

Author(s)

Chen, Shiu-Sheng

SHIU-SHENG CHEN

DOI

10.1002/for.960

URI

http://www.scopus.com/inward/record.url?eid=2-s2.0-25444474145&partnerID=MN8TOARS

http://scholars.lib.ntu.edu.tw/handle/123456789/318291

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.

Type

journal article

File(s)

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Format

Adobe PDF

Checksum

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

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