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How Homophily Affects the Speed of Learning and Best-Response Dynamics

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  • Benjamin Golub
  • Matthew O. Jackson

Abstract

We examine how the speed of learning and best-response processes depends on homophily: the tendency of agents to associate disproportionately with those having similar traits. When agents' beliefs or behaviors are developed by averaging what they see among their neighbors, then convergence to a consensus is slowed by the presence of homophily but is not influenced by network density (in contrast to other network processes that depend on shortest paths). In deriving these results, we propose a new, general measure of homophily based on the relative frequencies of interactions among different groups. An application to communication in a society before a vote shows how the time it takes for the vote to correctly aggregate information depends on the homophily and the initial information distribution. JEL Codes: D83, D85, I21, J15, Z13 Copyright 2012, Oxford University Press.

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Bibliographic Info

Article provided by Oxford University Press in its journal The Quarterly Journal of Economics.

Volume (Year): 127 (2012)
Issue (Month): 3 ()
Pages: 1287-1338

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Handle: RePEc:oup:qjecon:v:127:y:2012:i:3:p:1287-1338

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Cited by:
  1. Tim Hellmann & Mathias Staudigl, 2012. "Evolution of social networks," Working Papers, Bielefeld University, Center for Mathematical Economics 470, Bielefeld University, Center for Mathematical Economics.
  2. Daron Acemoglu & Azarakhsh Malekian & Asuman E. Ozdaglar, 2013. "Network Security and Contagion," Levine's Working Paper Archive 786969000000000797, David K. Levine.
  3. Leguizamon, Sebastian & Leguizamon, Susane & Christafore, David, 2013. "Education, race and revealed attitudes towards homosexual couples," MPRA Paper 47068, University Library of Munich, Germany.
  4. FORSTER, Manuel & MAULEON, Ana & VANNETELBOSCH, Vincent, 2013. "Trust and manipulation in social networks," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2013050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Liangjie Zhao & Wenqi Duan, 2014. "Simulating the Evolution of Market Shares: The Effects of Customer Learning and Local Network Externalities," Computational Economics, Society for Computational Economics, Society for Computational Economics, vol. 43(1), pages 53-70, January.
  6. Elsner, Benjamin & Narciso, Gaia & Thijssen, Jacco J. J., 2013. "Migrant Networks and the Spread of Misinformation," IZA Discussion Papers 7863, Institute for the Study of Labor (IZA).

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