6 citations · 7 across the 6 of their papers we have counts for
6 papers
Design-Based Weighted Regression Estimators for Average and Conditional Spillover Effects
Fei Fang, Laura Forastiere
When individuals engage in social or physical interactions, a unit's outcome may depend on the treatments received by others. In such interference environments, we provide a unifie…
Effective treatment allocation strategies under partial interference
Samantha G Dean, Georgia Papadogeorgou, Laura Forastiere
Interference occurs when the potential outcomes of a unit depend on the treatment of others. Interference can be highly heterogeneous, where treating certain individuals might have…
Regression Discontinuity Designs Under Interference
Elena Dal Torrione, Tiziano Arduini, Laura Forastiere
We extend the continuity-based framework to Regression Discontinuity Designs (RDDs) to identify and estimate causal effects under interference when units are connected through a ne…
Heterogeneous Treatment and Spillover Effects under Clustered Network Interference
Falco J. Bargagli-Stoffi, Costanza Tortù, Laura Forastiere
The bulk of causal inference studies rule out the presence of interference between units. However, in many real-world scenarios, units are interconnected by social, physical, or vi…
Causal Inference on Networks under Continuous Treatment Interference
Laura Forastiere, Davide Del Prete, Valerio Leone Sciabolazza
This paper investigates the case of interference, when a unit's treatment also affects other units' outcome. When interference is at work, policy evaluation mostly relies on the us…
Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates
C. Tortù, I. Crimaldi, F. Mealli +1
Policy evaluation studies, which intend to assess the effect of an intervention, face some statistical challenges: in real-world settings treatments are not randomly assigned and t…