Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials

77 Pages Posted: 10 Jun 2014 Last revised: 5 Oct 2018

See all articles by Abhijit V. Banerjee

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics

Arun G. Chandrasekhar

Stanford University - Department of Economics

Esther Duflo

Massachusetts Institute of Technology (MIT) - Department of Economics; Abdul Latif Jameel Poverty Action Lab (J-PAL); National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR); Bureau for Research and Economic Analysis of Development (BREAD)

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute; Canadian Institute for Advanced Research (CIFAR)

Multiple version iconThere are 3 versions of this paper

Date Written: May 6, 2017

Abstract

Can we identify highly central individuals in a network without collecting network data, simply by asking community members? Can seeding information via such nominated individuals lead to significantly wider diffusion than {choosing} randomly chosen people, or even respected ones? In two separate large field experiments in India, we answer both questions in the affirmative. In particular, in 521 villages in Haryana, we provided information on monthly immunization camps to either randomly selected individuals (in some villages) or to individuals nominated by villagers as people who would be good at transmitting information (in other villages). We find that the number of children vaccinated every month is 22% higher in villages in which nominees received the information. We show that people's knowledge of who are highly central individuals and good seeds can be explained by a model in which community members simply track how often they hear gossip about others. Indeed, we find in a third dataset that nominated seeds are central in a network sense, {and are} not just those with many friends or in {powerful} positions.

Keywords: Centrality, Gossip, Networks, Diffusion, Influence, Social Learning

JEL Classification: D85, D13, L14, O12, Z13

Suggested Citation

Banerjee, Abhijit V. and Chandrasekhar, Arun G. and Duflo, Esther and Jackson, Matthew O., Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials (May 6, 2017). MIT Department of Economics Working Paper No. 14-15. Available at SSRN: https://ssrn.com/abstract=2425379 or http://dx.doi.org/10.2139/ssrn.2425379

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

50 Memorial Drive
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Arun G. Chandrasekhar

Stanford University - Department of Economics ( email )

Landau Economics Building
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Stanford, CA 94305-6072
United States

Esther Duflo

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

50 Memorial Drive
Room E52-544
Cambridge, MA 02139
United States
617-258-7013 (Phone)
617-253-6915 (Fax)

Abdul Latif Jameel Poverty Action Lab (J-PAL) ( email )

Cambridge, MA
United States

HOME PAGE: http://www.povertyactionlab.org/

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Bureau for Research and Economic Analysis of Development (BREAD) ( email )

Duke University
Durham, NC 90097
United States

Matthew O. Jackson (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
1-650-723-3544 (Phone)

HOME PAGE: http://www.stanford.edu/~jacksonm

Santa Fe Institute

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Santa Fe, NM 87501
United States

Canadian Institute for Advanced Research (CIFAR) ( email )

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Toronto, Ontario
Canada

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