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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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    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.
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    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.
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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. repec:hal:journl:halshs-00344780 is not listed on IDEAS

    More about this item

    JEL classification:

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

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