The Effect of the Spillover on the Granger Causality Test

• In this paper, we investigate the properties of the Granger causality test in stationary and stable vector autoregressive models under the presence of spillover effects, i.e., causality in variance. The Wald test and the WW test (the Wald test with White’s proposed heteroskedasticity-consistent covariance matrix estimator imposed) are analyzed. The investigation is undertaken by using Monte Carlo simulation in which two different sample sizes and six different kinds of data generating process are used. The results show that the Wald test overrejects the null hypothesis both with and without the spillover effect, and that the overrejection in the latter case is more severe in larger samples. The size properties of the WW test are satisfactory when there is spillover between the variables. Only when there is feedback in the variance is the size of the WW test slightly affected. The Wald test is shown to have higher power than the WW test when the errors follow a GARCH(1,1) process without a spillover effect. When there is spillover, the power of both tests deteriorates, which implies that the spillover has a negative effect on the causality tests.

Ämnesord

SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv -- Nationalekonomi (hsv//swe)

SOCIAL SCIENCES  -- Economics and Business -- Economics (hsv//eng)

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Nyckelord

causality in variance

GARCH

Granger causality

volatility spillover

Econometrics

Ekonometri

Statistics/Econometrics

Statistik

Statistik

Granger causality

causality in variance

GARCH

volatility spillover

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