Spatial Causal Inference and Neighborhood Effects

Explore the complexities of spatial causal inference and neighborhood effects in this 58-minute talk by Cecile de Bezenac from the Alan Turing Institute. Gain insights into the interference problem arising from social interactions and understand the connection between partial interference assumptions and estimating neighborhood effects in multilevel spatial analyses. Examine a simple agent-based modeling (ABM) framework that challenges the validity of area-level effects and discuss the implications of their causal interpretation. Delve into the intricacies of spatial analysis and its impact on understanding social dynamics and causal relationships within neighborhoods.