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Social Networks and the Aggregation on Individual Decisions

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  • D. Lee Heavner
  • Lance Lochner

Abstract

This paper analyzes individual decisions to participate in an activity and the aggregation of those decisions when individuals gather information about the outcomes and choices of (a few) others in their social network. In this environment, aggregate participation rates are generally inefficient. Increasing the size of social networks does not necessarily increase efficiency and can lead to less efficient long-run outcomes. Both subsidies for participation and penalties for non-participation can increase participation rates, though not necessarily by the same amount. Punishing non-participation has much greater effects on participation rates than rewarding participation when current rates are very low. A program that provides youth with mentors who have participated themselves can increase participation rates, especially when those rates are low. Finally, communities plagued by the flight of successful participants will experience lower short- and long-run participation rates.

Suggested Citation

  • D. Lee Heavner & Lance Lochner, 2002. "Social Networks and the Aggregation on Individual Decisions," NBER Working Papers 8979, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:8979
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    References listed on IDEAS

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    1. Edward L. Glaeser & Bruce Sacerdote & José A. Scheinkman, 1996. "Crime and Social Interactions," The Quarterly Journal of Economics, Oxford University Press, vol. 111(2), pages 507-548.
    2. Timothy Conley & Udry Christopher, 2001. "Social Learning Through Networks: The Adoption of New Agricultural Technologies in Ghana," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 668-673.
    3. Glenn Ellison & Drew Fudenberg, 1995. "Word-of-Mouth Communication and Social Learning," The Quarterly Journal of Economics, Oxford University Press, vol. 110(1), pages 93-125.
    4. 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.
    5. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    6. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2001. "Social Interaction and Stock-Market Participation," NBER Working Papers 8358, National Bureau of Economic Research, Inc.
    7. Marianne Bertrand & Erzo F. P. Luttmer & Sendhil Mullainathan, 2000. "Network Effects and Welfare Cultures," The Quarterly Journal of Economics, Oxford University Press, vol. 115(3), pages 1019-1055.
    8. Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 612-643, August.
    9. Banerjee, Abhijit & Fudenberg, Drew, 2004. "Word-of-mouth learning," Games and Economic Behavior, Elsevier, vol. 46(1), pages 1-22, January.
    10. Duflo, Esther & Saez, Emmanuel, 2002. "Participation and investment decisions in a retirement plan: the influence of colleagues' choices," Journal of Public Economics, Elsevier, vol. 85(1), pages 121-148, July.
    11. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
    12. Jeff Dominitz & Charles F. Manski, 1996. "Eliciting Student Expectations of the Returns to Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 31(1), pages 1-26.
    13. Lance Lochner, 2001. "A Theoretical and Empirical Study of Individual Perceptions of the Criminal Justice System," RCER Working Papers 483, University of Rochester - Center for Economic Research (RCER).
    14. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
    15. Manski, Charles F., 1993. "Dynamic choice in social settings : Learning from the experiences of others," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 121-136, July.
    16. Julian R. Betts, 1996. "What Do Students Know about Wages? Evidence from a Survey of Undergraduates," Journal of Human Resources, University of Wisconsin Press, vol. 31(1), pages 27-56.
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    Cited by:

    1. Bjerk, David, 2010. "Thieves, thugs, and neighborhood poverty," Journal of Urban Economics, Elsevier, vol. 68(3), pages 231-246, November.
    2. Yannis M. Ioannides & Linda Datcher Loury, 2004. "Job Information Networks, Neighborhood Effects, and Inequality," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1056-1093, December.
    3. Lance Lochner, 2007. "Individual Perceptions of the Criminal Justice System," American Economic Review, American Economic Association, vol. 97(1), pages 444-460, March.
    4. Fabien Moizeau & Jean-Philippe Tropeano & Jean-Christophe Vergnaud, 2010. "Effets de voisinage et localisation. La ségrégation urbaine est-elle inéluctable ?," Revue économique, Presses de Sciences-Po, vol. 61(4), pages 723-750.
    5. Sandro de Freitas Ferreira & Suzana Quinet de Andrade Bastos & Admir Antonio Betarelli Junior, 2019. "The role of social control in Brazilian homicide rates," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(6), pages 2695-2717, November.

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    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • H0 - Public Economics - - General

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