4 papers
Estimating peer effects in noisy, low-rank networks via network smoothing
Alex Hayes, Keith Levin
Peer effect estimation requires precise network measurement, yet most empirical networks are noisy, rendering standard estimators inconsistent. To address measurement error in netw…
Minimax rates for the linear-in-means model reveal an identifiability-estimability gap
Alex Hayes, Keith Levin
The linear-in-means model is widely used to study peer influence in social networks. We consider estimation in the linear-in-means model when a randomized treatment is applied to n…
Co-factor analysis of citation networks
Alex Hayes, Karl Rohe
One compelling use of citation networks is to characterize papers by their relationships to the surrounding literature. We propose a method to characterize papers by embedding them…
Estimating network-mediated causal effects via principal components network regression
Alex Hayes, Mark M. Fredrickson, Keith Levin
We develop a method to decompose causal effects on a social network into an indirect effect mediated by the network, and a direct effect independent of the social network. To handl…