Alejandro Sanchez Becerra

Alejandro Sanchez Becerra
Job Market Paper

Spillovers, Homophily and Selection into Treatment: The Network Propensity Score

Propensity score matching (PSM) is a well-known method to estimate treatment effects when there is selection on observables. PSM fails to identify any relevant causal effects, however, when there are spillovers amongst friends and individuals befriend similar people (homophily). I propose a novel network propensity score matching (NPS) approach that identifies both treatment effects and spillovers amongst friends when there is selection on observables and homophily on observables. I show that the proposed NPS -a three dimensional vector of probabilities- can be used to identify causal effects for individuals with similar observables, analogous to the propensity score. I then propose estimators that are consistent and asymptotically normal for settings with multiple large networks. I evaluate my methodology on an information intervention to increase microfinance adoption in Southern India, where selection and homophily are particularly salient, finding positive treatment effects but limited spillover effects. In the extensions I show how to conduct robustness checks, extend the NPS to settings with relationships intensity, and how interpret the NPS in stratified multi-stage experiments.


Econometrics, Applied Microeconomics, Networks, Causal Inference


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Xu Cheng

Petra Todd

Francis J. DiTraglia

Job Market Candidate Status
I am a Ph.D. candidate at the Economics Department of the University of Pennsylvania. I am from Colombia, where I studied my undergraduate and masters' degrees. My research is dedicated to updating the modern program evaluation toolkit to incorporate network data and spillover effects. I develop new methods for applied econometrics and development. I am on the job market and will be available for interviews at the 2021 Meetings.