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Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia

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  • Vivi Alatas
  • Abhijit Banerjee
  • Arun G. Chandrasekhar
  • Rema Hanna
  • Benjamin A. Olken

Abstract

We use unique data from 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 different network structures, which we show are borne out in the data. We apply our findings to a community-based targeting program, where villagers chose which households should receive aid, and show that networks the model predicts to be more diffusive differentially benefit from community targeting.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18351.

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Date of creation: Aug 2012
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Handle: RePEc:nbr:nberwo:18351

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  1. Conley, T.G. & Udry, C.R., 2000. "Learning about a New Technology: Pineapple in Ghana," Papers 817, Yale - Economic Growth Center.
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  12. Vivi Alatas & Abhijit Banerjee & Rema Hanna & Benjamin A. Olken & Julia Tobias, 2010. "Targeting the Poor: Evidence from a Field Experiment in Indonesia," NBER Working Papers 15980, National Bureau of Economic Research, Inc.
  13. Mueller-Frank, Manuel, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
  14. Andrea Galeotti & Fernando Vega‚ÄźRedondo, 2011. "Complex networks and local externalities: A strategic approach," International Journal of Economic Theory, The International Society for Economic Theory, vol. 7(1), pages 77-92, 03.
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Cited by:
  1. Michael Clemens & Erwin Tiongson, 2012. "Split Decisions: Family finance when a policy discontinuity allocates overseas work," CReAM Discussion Paper Series 1234, Centre for Research and Analysis of Migration (CReAM), Department of Economics, University College London.
  2. Mastrobuoni, Giovanni, 2014. "The Value of Connections: Evidence from the Italian-American Mafia," IZA Discussion Papers 7925, Institute for the Study of Labor (IZA).

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