Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. (arXiv:2202.11612v1 [stat.ME])

This paper proposes a new approach for testing Granger non-causality on panel
data. Instead of aggregating panel member statistics, we aggregate their
corresponding p-values and show that the resulting p-value approximately bounds
the type I error by the chosen significance level even if the panel members are
dependent. We compare our approach against the most widely used Granger
causality algorithm on panel data and show that our approach yields lower FDR
at the same power for large sample sizes and …

arxiv causality panels testing