Testing for causality in the presence of leading variables


  • Theologos Pantelidis




This paper provides useful guidelines to practitioners who investigate causality-in-mean and/or causality-in-variance within a system of more than two variables by means of the two-step procedure proposed by Cheung and Ng (Journal of Econometrics, 1996) and modified by Hong (Journal of Econometrics, 2001). Specifically, this study highlights cases that can mislead the researcher into reporting false causal relations among the variables under scrutiny. The results of Monte Carlo simulations reveal the seriousness of the problem.


Bhar, R. and S. Hamori (2005). Causality in Variance and the Type of Traders in Crude Oil Futures. Energy Economics 27, 527-539.

Cheung, Y.M. and L.K. Ng (1996). A Causality-in-Variance Test and Its Application to Financial Market Prices. Journal of Econometrics 72, 33-48.

Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrica, 37, 424-438.

Hong, Y., (2001). A Test for Volatility Spillover with Application to Exchange Rates. Journal of Econometrics 103, 183-224.

Inagaki, K. (2007). Testing for Volatility Spillover between the British Pound and the Euro. Research in International Business and Finance 21 (2), 161-174.

Speight, A.E.H and D.G. McMillan (2001). Volatility Spillovers in East European Black-market Exchange Rates. Journal of International Money and Finance 20, 367-378.

Van Dijk, D, D.R. Osborn and M. Sensier (2005). Testing for Causality in Variance in the Presence of Breaks. Economics Letters 89, 193-199.




How to Cite

Pantelidis, T. (2015). Testing for causality in the presence of leading variables. Economics and Business Letters, 4(1), 17-29. https://doi.org/10.17811/ebl.4.1.2015.17-29