IDEAS home Printed from https://ideas.repec.org/p/hrv/hksfac/9804490.html
   My bibliography  Save this paper

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

Author

Listed:
  • Hanna, Rema N.
  • Alatas, Vivi
  • Banerjee, Abhijit
  • Chandrasekhar, Arun G.
  • Olken, Benjamin A.

Abstract

We use a unique data-set from Indonesia on what individuals know about the income distribution in their village to test theories such as Jackson and Rogers (2007) that link information aggregation in networks to the structure of the network. The observed patterns are consistent with a basic diffusion model: more central individuals are better informed, and individuals are able to better evaluate the poverty status of those to whom they are more socially proximate. To understand what the theory predicts for cross-village patterns, we estimate a simple diffusion model using within-village variation, simulate network-level diffusion under this model for the over 600 different networks in our data, and use this simulated data to gauge what the simple diffusion model predicts for the cross-village relationship between information diffusion and network characteristics (e.g. clustering, density). The coefficients in these simulated regressions are generally consistent with relationships suggested in previous theoretical work, even though in our setting formal analytical predictions have not been derived. We then show that the qualitative predictions from the simulated model largely match the actual data in the sense that we obtain similar results both when the dependent variable is an empirical measure of the accuracy of a village’s aggregate information and when it is the simulation outcome. Finally, we consider a real-world application to community based targeting, where villagers chose which households should receive an anti-poverty program, and show that networks with better diffusive properties (as predicted by our model) differentially benefit from community based targeting policies.

Suggested Citation

  • Hanna, Rema N. & Alatas, Vivi & Banerjee, Abhijit & Chandrasekhar, Arun G. & Olken, Benjamin A., 2012. "Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia," Scholarly Articles 9804490, Harvard Kennedy School of Government.
  • Handle: RePEc:hrv:hksfac:9804490
    as

    Download full text from publisher

    File URL: http://dash.harvard.edu/bitstream/handle/1/9804490/RWP12-043_Hanna.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:cep:stieop:43 is not listed on IDEAS
    2. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
    3. Andrea Galeotti & Fernando Vega‐Redondo, 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, March.
    4. Michael Kremer & Edward Miguel, 2007. "The Illusion of Sustainability," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1007-1065.
    5. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    6. Oriana Bandiera & Iwan Barankay & Imran Rasul, 2009. "Social Connections and Incentives in the Workplace: Evidence From Personnel Data," Econometrica, Econometric Society, vol. 77(4), pages 1047-1094, July.
    7. Matthew O. Jackson & Leeat Yariv, 2007. "Diffusion of Behavior and Equilibrium Properties in Network Games," American Economic Review, American Economic Association, vol. 97(2), pages 92-98, May.
    8. Vivi Alatas & Abhijit Banerjee & Rema Hanna & Benjamin A. Olken & Julia Tobias, 2012. "Targeting the Poor: Evidence from a Field Experiment in Indonesia," American Economic Review, American Economic Association, vol. 102(4), pages 1206-1240, June.
    9. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    10. Banerjee, Abhijit & Chandrasekhar, Arun G & Duflo, Esther & Jackson, Matthew O., 2012. "The Diffusion of Microfinance," CEPR Discussion Papers 8770, C.E.P.R. Discussion Papers.
    11. Daron Acemoglu & Munther A. Dahleh & Ilan Lobel & Asuman Ozdaglar, 2011. "Bayesian Learning in Social Networks," Review of Economic Studies, Oxford University Press, vol. 78(4), pages 1201-1236.
    12. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    13. Alderman, Harold & Haque, Trina, 2006. "Countercyclical safety nets for the poor and vulnerable," Food Policy, Elsevier, vol. 31(4), pages 372-383, August.
    14. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
    15. Oriana Bandiera & Robin Burgess & Narayan Das & Selim Gulesci & Imran Rasul & Munshi Sulaiman, 2013. "Can Basic Entrepreneurship Transform the Economic Lives of the Poor?," STICERD - Economic Organisation and Public Policy Discussion Papers Series 043, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
    17. Matthew O. Jackson & Tomas Rodriguez-Barraquer & Xu Tan, 2012. "Social Capital and Social Quilts: Network Patterns of Favor Exchange," American Economic Review, American Economic Association, vol. 102(5), pages 1857-1897, August.
    18. Galasso, Emanuela & Ravallion, Martin, 2005. "Decentralized targeting of an antipoverty program," Journal of Public Economics, Elsevier, vol. 89(4), pages 705-727, April.
    19. Jackson Matthew O. & Rogers Brian W., 2007. "Relating Network Structure to Diffusion Properties through Stochastic Dominance," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-16, February.
    20. Kaivan Munshi, 2003. "Networks in the Modern Economy: Mexican Migrants in the U. S. Labor Market," The Quarterly Journal of Economics, Oxford University Press, vol. 118(2), pages 549-599.
    21. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    22. Mueller-Frank, Manuel, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jacopo Bonan & Pietro Battiston & Jaimie Bleck & Philippe LeMay-Boucher & Stefano Pareglio & Bassirou Sarr & Massimo Tavoni, 2017. "Social Interaction and Technology Adoption: Experimental Evidence from Improved Cookstoves in Mali," Working Papers 2017.47, Fondazione Eni Enrico Mattei.
    2. Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
    3. Tisorn Songsermsawas & Kathy Baylis & Ashwini Chhatre & Hope Michelson, 2014. "Can Peers Improve Agricultural Productivity?," CESifo Working Paper Series 4958, CESifo.
    4. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Sciences Po publications info:hdl:2441/78vacv4udu9, Sciences Po.
    5. Xiong, Hang & Payne, Diane & Kinsella, Stephen, 2016. "Peer effects in the diffusion of innovations: Theory and simulation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 1-13.
    6. Kaustia, Markku & Rantala, Ville, 2015. "Social learning and corporate peer effects," Journal of Financial Economics, Elsevier, vol. 117(3), pages 653-669.
    7. Bennett, Daniel & Chiang, Chun-Fang & Malani, Anup, 2015. "Learning during a crisis: The SARS epidemic in Taiwan," Journal of Development Economics, Elsevier, vol. 112(C), pages 1-18.
    8. Pan He & Marcella Veronesi, 2015. "The Diffusion of Information and Behavior in Social Networks: Renewable Energy Technology Adoption in Rural China," Working Papers 06/2015, University of Verona, Department of Economics.
    9. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2016. "Networks: An Economic Perspective," Papers 1608.07901, arXiv.org.
    10. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    11. A. Stefano Caria & Marcel Fafchamps, 2015. "Can Farmers Create Efficient Information Networks? Experimental Evidence from Rural India," CSAE Working Paper Series 2015-07, Centre for the Study of African Economies, University of Oxford.
    12. Mekonnen, Daniel Ayalew & Gerber, Nicolas & Matz, Julia Anna, 2018. "Gendered Social Networks, Agricultural Innovations, and Farm Productivity in Ethiopia," World Development, Elsevier, vol. 105(C), pages 321-335.
    13. Raphaël Soubeyran, 2019. "Technology adoption and pro-social preferences," CEE-M Working Papers halshs-02291905, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.
    14. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    15. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    16. SHIMAMOTO Daichi & Yu Ri KIM & TODO Yasuyuki, 2019. "The Effect of Social Interactions on Exporting Activities: Evidence from Micro, Small, and Medium-Sized Enterprises in rural Vietnam," Discussion papers 19020, Research Institute of Economy, Trade and Industry (RIETI).
    17. Ariel BenYishay & A. Mushfiq Mobarak, 2014. "Social Learning and Communication," NBER Working Papers 20139, National Bureau of Economic Research, Inc.
    18. Magnan, Nicholas & Spielman, David J. & Lybbert, Travis J. & Gulati, Kajal, 2015. "Leveling with friends: Social networks and Indian farmers' demand for a technology with heterogeneous benefits," Journal of Development Economics, Elsevier, vol. 116(C), pages 223-251.
    19. Nicholas Magnan & David J Spielman & Travis J. Lybbert & Kajal Gulati, 2013. "Leveling with Friends: Social Networks and Indian Farmers’ Demand for Agricultural Custom Hire Services," Working Papers id:5591, eSocialSciences.
    20. Kondylis, Florence & Mueller, Valerie, 2012. "Seeing is Believing? Evidence from a Demonstration Plot Experiment in Mozambique:," MSSP working papers 1, International Food Policy Research Institute (IFPRI).

    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hrv:hksfac:9804490. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Office for Scholarly Communication). General contact details of provider: http://edirc.repec.org/data/ksharus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.