A new statistic and practical guidelines for nonparametric Granger causality testing
Upon illustrating how smoothing may cause over-rejection in nonparametric tests for Granger non-causality, we propose a new test statistic for which problems of this type can be avoided. We develop asymptotic theory for the new test statistic, and perform a simulation study to investigate the properties of the new test in comparison with its natural counterpart, the Hiemstra-Jones test. Our simulation results indicate that, if the bandwidth tends to zero at the appropriate rate as the sample size increases, the size of the new test remains close to nominal, while the power remains large. Transforming the time series to uniform marginals improves the behavior of both tests. In applications to Standard and Poor's index volumes and returns, the Hiemstra-Jones test suggests that volume Granger-causes returns. However, the evidence for this gets weaker if we carefully apply the recommendations suggested by our simulation study.
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- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Ma, Yue & Kanas, Angelos, 2000. "Testing for a nonlinear relationship among fundamentals and exchange rates in the ERM," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 135-152, February.
- Okunev, John & Wilson, Patrick & Zurbruegg, Ralf, 2000. "The Causal Relationship between Real Estate and Stock Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 21(3), pages 251-61, November.
- Okunev, John & Wilson, Patrick & Zurbruegg, Ralf, 2002. "Relationships between Australian Real Estate and Stock Market Prices--A Case of Market Inefficiency," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 181-92, April.
- Newey, Whitney K & West, Kenneth D, 1987.
"A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix,"
Econometric Society, vol. 55(3), pages 703-08, May.
- Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
- Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
- Powell, James L. & Stoker, Thomas M., 1996. "Optimal bandwidth choice for density-weighted averages," Journal of Econometrics, Elsevier, vol. 75(2), pages 291-316, December.
- Bell, David & Kay, Jim & Malley, Jim, 1996. "A non-parametric approach to non-linear causality testing," Economics Letters, Elsevier, vol. 51(1), pages 7-18, April.
- Ciner Cetin, 2001. "Energy Shocks and Financial Markets: Nonlinear Linkages," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(3), pages 1-11, October.
- Diks Cees & Panchenko Valentyn, 2005.
"A Note on the Hiemstra-Jones Test for Granger Non-causality,"
Studies in Nonlinear Dynamics & Econometrics,
De Gruyter, vol. 9(2), pages 1-9, June.
- 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.
- An-Sing Chen & James Wuh Lin, 2004. "Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1157-1167.
- Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
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