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Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
This paper proposes a new approach for testing Granger non-causality on panel data.
Why did the distribution change?
We describe a formal approach based on graphical causal models to identify the "root causes" of the change in the probability distribution of variables.
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