2 citations · 2 across the 4 of their papers we have counts for
4 papers
Consensus and Disagreement: Information Aggregation under (not so) Naive Learning
Abhijit Banerjee, Olivier Compte
We explore a model of non-Bayesian information aggregation in networks. Agents non-cooperatively choose among Friedkin-Johnsen type aggregation rules to maximize payoffs. The DeGro…
Doctors and Nurses Social Media Ads Reduced Holiday Travel and COVID-19 infections: A cluster randomized controlled trial in 13 States
Emily Breza, Fatima Cody Stanford, Marcela Alsan +18
During the COVID-19 epidemic, many health professionals started using mass communication on social media to relay critical information and persuade individuals to adopt preventativ…
Selecting the Most Effective Nudge: Evidence from a Large-Scale Experiment on Immunization
Abhijit Banerjee, Arun G. Chandrasekhar, Suresh Dalpath +8
Policymakers often choose a policy bundle that is a combination of different interventions in different dosages. We develop a new technique -- treatment variant aggregation (TVA) -…
Using Gossips to Spread Information: Theory and Evidence from a Randomized Controlled Trial
Abhijit Banerjee, Arun G. Chandrasekhar, Esther Duflo +1
Is it possible to identify individuals who are highly central in a community without gathering any network information, simply by asking a few people? If we use people's nominees a…