Establishes unconfoundedness conditions and proposes matching-based estimators for immediate and carryover causal effects in bipartite interference with time series and random networks.
Time series experiments and causal estimands: Exact randomization tests and trading
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Bipartite causal inference with interference, time series data, and a random network
Establishes unconfoundedness conditions and proposes matching-based estimators for immediate and carryover causal effects in bipartite interference with time series and random networks.