Abstract
The asymptotic behavior of the Granger-causality test
under stochastic nonstationarity is studied. Our results confirm that the
inference drawn from the test is not reliable when the series are integrated to
the first order. In the presence of deterministic components, the test
statistic diverges, eventually rejecting the null hypothesis, even when the
series are independent of each other. Moreover, controlling for these
deterministic elements (in the auxiliary regressions of the test) does not
preclude the possibility of drawing erroneous inferences. Grangercausality
tests should not be used under stochastic nonstationarity, a property typically
found in many macroeconomic variables.