Chapter 15: Causal Machine Learning
Interference, Spillovers, and SUTVA Violations in Financial Markets intermediate
In markets, one unit's treatment rarely stays politely confined to that unit.
In markets, one unit's treatment rarely stays politely confined to that unit.
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References
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
Guido W. Imbens
(2020)
— Journal of Economic Literature
The seven tools of causal inference, with reflections on machine learning
Judea Pearl
(2019)
— Communications of the ACM
Commonality in liquidity
Tarun Chordia, Richard Roll, Avanidhar Subrahmanyam
(2000)
— Journal of Financial Economics