Causal Inference Under Interference on Networks
Rome time
In policy evaluation an important phenomenon to consider is “interference”, where an intervention on one subject may affect another subject’s outcome. Dr Forastiere will illustrate i) estimators spillover effects on networks and ii) a two-stage re-randomization procedure to evaluate strategies to identify key influencers. Dr Forastiere will apply the estimator on the world trade network to investigate how spillover effects shape the optimal level of support in agricultural markets. Dr Forastiere will then present the two-stage method used to design an RCT to foster adoption of iron supplements in Mumbai.
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