Causal inference with interfering units for cluster and population level intervention programs

Neyman Seminar
Nov 8, 2017 4:00pm to 5:00pm
Location: 
1011 Evans Hall
Status: 
Happening As Scheduled
Interference arises when an individual's potential outcome depends on the individual treatment and also on the treatment of others. A common assumption in the causal inference literature in the presence of interference is partial interference, implying that the population can be partitioned in clusters of units whose potential outcomes only depend on the treatment of other units within the...
Fabrizia Mealli, University of Florence