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Oral Communications<br />
CO2<br />
Tuesday, September 3rd<br />
19:45<br />
Nonparametric short- and long-run<br />
Granger-causality testing in the frequency<br />
domain<br />
Cleiton Guollo Taufemback<br />
UFRGS<br />
We propose on this paper a novel nonparametric frequency Granger-causality test. Before testing<br />
for causality absence of one series on to another, we apply a filtering process, removing any<br />
presence of reverse causality. Then, performing a local kernel regression for each frequency, we<br />
can test the hypothesis of non-causality from the distance between each estimate to zero. We<br />
provide asymptotic results for strict stationary series respecting α-mixing conditions. Monte Carlo<br />
experiments illustrate that our method has comparable performance with other alternative methods<br />
present in the literature and superior performance whenever the tested model presents smooth<br />
transition coefficients in the frequency domain. Finally, we test causality of term spread and money<br />
stock (M2) on real economic growth, as well as, between Monetary Policy Variables and Stock<br />
Prices.<br />
Keywords: Granger-causality; Frequency-domain; Nonparametric test; Alpha-mixing<br />
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