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How can we measure the causal effects of social networks using observational data? Evidence from the diffusion of family planning and AIDS worries in South Nyanza District, Kenya

Author

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  • Jere R. Behrman
  • Hans-Peter Kohler

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Susan Cotts Watkins

Abstract

This study presents estimates that social networks exert causal and substantial influences on individuals’ attitudes and behaviors. The study explicitly allows for the possibility that social networks are not chosen randomly, but rather that important characteristics such as unobserved preferences and unobserved community characteristics determine not only the outcomes of interest but also the informal conversational networks in which they are discussed. Longitudinal survey data from rural Kenya on family-planning and AIDS are used to estimate the impact of social networks while controlling for their unobserved determinants. There are four major findings: First, the endogeneity of social networks can substantially distort the usual cross-sectional estimates of network influences. Second, social networks have significant and substantial effects even after controlling for unobserved factors that may determine the nature of the social networks. Third, these network effects generally are nonlinear and asymmetric. In particular, they are relatively large for individuals who have at least one network partner who is perceived to be using contraceptives or or to be at high risk of HIV/AIDS, which is consistent with S-shaped diffusion models that have been emphasized in the literature. Fourth, the effects of networks are not confined to the use of family planning by women, the focus of much of the literature on networks in demography, but appear to be more general, influencing responses to HIV/AIDS, and influencing men as well as women. (AUTHORS)

Suggested Citation

  • Jere R. Behrman & Hans-Peter Kohler & Susan Cotts Watkins, 2001. "How can we measure the causal effects of social networks using observational data? Evidence from the diffusion of family planning and AIDS worries in South Nyanza District, Kenya," MPIDR Working Papers WP-2001-022, Max Planck Institute for Demographic Research, Rostock, Germany.
  • Handle: RePEc:dem:wpaper:wp-2001-022
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    File URL: http://www.demogr.mpg.de/Papers/Working/wp-2001-022.pdf
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Harold Alderman & Jere Behrman & Hans-Peter Kohler & John A. Maluccio & Susan Watkins, 2001. "Attrition in Longitudinal Household Survey Data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(4), pages 79-124, November.
    3. Julia Cordero Coma, 2013. "When the group encourages extramarital sex," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(30), pages 849-880, April.
    4. Santos, Paulo & Barrett, Christopher B., 2004. "Interest And Identity In Network Formation," 2004 Annual meeting, August 1-4, Denver, CO 19920, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Cordero Coma, Julia, 2014. "HIV prevention and marriage: Peer group effects on condom use acceptability in rural Kenya," Social Science & Medicine, Elsevier, vol. 116(C), pages 169-177.

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    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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