A Note on the Hiemstra-Jones Test for Granger Non-causality
AbstractWe address a consistency problem in the commonly used nonparametric test for Granger causality developed by Hiemstra and Jones (1994). We show that the relationship tested is not implied by the null hypothesis of Granger non-causality. Monte Carlo simulations using processes satisfying the null hypothesis show that, for a given nominal size, the actual rejection rate may tend to one as the sample size increases. Our results imply that evidence for nonlinear Granger causality reported in the applied empirical literature should be re-interpreted.
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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 9 (2005)
Issue (Month): 2 (June)
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Web page: http://www.degruyter.com
Other versions of this item:
- Diks, C.G.H. & Panchenko, V., 2004. "A note on the Hiemstra-Jones test for Granger non-causality," CeNDEF Working Papers 04-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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