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A Note on the Hiemstra-Jones Test for Granger Non-causality
Open accessAbstract
We 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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Citations
Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Cited by
A new statistic and practical guidelines for nonparametric Granger causality testing
Diks, C., & Panchenko, V. (2006) · Journal of Economic Dynamics and Control · doi:10.1016/j.jedc.2005.08.008 · Cited by 962
Self-citationCausality detection based on information-theoretic approaches in time series analysis
HLAVACKOVASCHINDLER, K., PALUS, M., VEJMELKA, M., & BHATTACHARYA, J. (2007) · Physics Reports · doi:10.1016/j.physrep.2006.12.004 · Cited by 800
Geopolitical risks and stock market dynamics of the BRICS
Balcilar, M., Bonato, M., Demirer, R., & Gupta, R. (2018) · Economic Systems · doi:10.1016/j.ecosys.2017.05.008 · Cited by 477
Metadata
- Authors
- Diks, C., & Panchenko, V.
- Venue
- Studies in Nonlinear Dynamics & Econometrics
- Publisher
- Walter de Gruyter GmbH
- Published
- 2005-01-06
- Volume
- 9
- Issue
- 2
- ISSN
- 1081-1826 (ISSN-L)
- 1558-3708
- OpenAlex
- W2045865139
- Cited by
- 242
- References
- 1
- FWCI
- 11.93
- Type
- journal article
- Language
- en
- Open access
- green
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