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Preferences, Homophily, and Social Learning

  • Ilan Lobel

    ()

    (New York University Stern School of Business)

  • Evan Sadler

    ()

    (New York University Stern School of Business)

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    We study a model of social learning in networks where agents have heterogeneous preferences, and neighbors tend to have similar preferences---a phenomenon known as homophily. Using this model, we resolve a puzzle in the literature: theoretical models predict that preference diversity helps learning, and homophily slows learning, while empirical work suggests the opposite. We find that the density of network connections determines the impact of preference diversity and homophily on learning. When connections are sparse, diverse preferences are harmful to learning, and homophily may lead to substantial improvements. In a dense network, preference diversity is beneficial. The conflicting findings in prior work result from a focus on networks with different densities; theory has focused on dense networks, while empirical papers have studied sparse networks. Our results suggest that in complex networks containing both sparse and dense components, diverse preferences and homophily play complementary, beneficial roles.

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    File URL: http://www.netinst.org/Lobel_Sadler_13-01.pdf
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    Paper provided by NET Institute in its series Working Papers with number 13-01.

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    Length: 47 pages
    Date of creation: Sep 2013
    Date of revision:
    Handle: RePEc:net:wpaper:1301
    Contact details of provider: Web page: http://www.NETinst.org/

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    1. Sergio Currarini & Matthew O. Jackson & Paolo Pin, 2009. "An Economic Model of Friendship: Homophily, Minorities, and Segregation," Econometrica, Econometric Society, vol. 77(4), pages 1003-1045, 07.
    2. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
    3. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.
    4. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 797-817, August.
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    6. Antonio Guarino & Antonella Ianni, 2010. "Bayesian Social Learning with Local Interactions," Games, MDPI, Open Access Journal, vol. 1(4), pages 438-458, October.
    7. Bala, V. & Goyal, S., 1995. "Learning from Neighbors," Econometric Institute Research Papers EI 9549-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Daron Acemoglu & Munther A. Dahleh & Ilan Lobel & Asuman Ozdaglar, 2008. "Bayesian Learning in Social Networks," NBER Working Papers 14040, National Bureau of Economic Research, Inc.
    9. 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.
    10. Celen, Bogachan & Kariv, Shachar, 2004. "Observational learning under imperfect information," Games and Economic Behavior, Elsevier, vol. 47(1), pages 72-86, April.
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