Testing for Granger Causality with Mixed Frequency Data
44 Pages Posted: 24 Sep 2013
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Testing for Granger Causality with Mixed Frequency Data
Date Written: September 2013
Abstract
It is well known that temporal aggregation has adverse effects on Granger causality tests. Time series are often sampled at different frequencies. This is typically ignored, and data are merely aggregated to the common lowest frequency. We develop a set of Granger causality tests that explicitly take advantage of data sampled at different frequencies. We show that taking advantage of mixed frequency data allows us to better recover causal relationships when compared to the conventional common low frequency approach. We also show that the mixed frequency causality tests have higher local asymptotic power as well as more power in finite samples compared to conventional tests.
Keywords: Granger causality, mixed data sampling (MIDAS), temporal aggression, vector autoregression (VAR)
JEL Classification: C12, C32
Suggested Citation: Suggested Citation
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