Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia
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Olken_Network structure.pdf
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Author(s)
Alatas, Vivi
Banerjee, Abhijit
Chandrasekhar, Arun Gautham
Hanna, Rema N.
Olken, Benjamin
Date Issued
July 2016
Journal
American Economic Review
Publisher
American Economic Association
Citation
Alatas, Vivi; Banerjee, Abhijit; Chandrasekhar, Arun G.; Hanna, Rema and Olken, Benjamin A. “Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia†.” American Economic Review 106, no. 7 (July 2016): 1663–1704. © 2016 American Economic Association
Version
Final published version
Abstract
We use unique data from over 600 Indonesian communities on what individuals know about the poverty status of others to study how network structure influences information aggregation. We develop a model of semi-Bayesian learning on networks, which we structurally estimate using within-village data. The model generates qualitative predictions about how cross-village patterns of learning relate to network structure, which we show are borne out in the data. We apply our findings to a community-based targeting program, where citizens chose households to receive aid, and show that the networks that the model predicts to be more diffusive differentially benefit from community targeting.
MIT Department
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1257/aer.20140705
