The density of social networks and fertility decisions: evidence from south nyanza district, kenya

Abstract

Demographers have argued increasingly that social interaction is an important mechanism for understanding fertility behavior. Yet it is still quite uncertain whether social learning or social influence is the dominant mechanism through which social networks affect individuals’ contraceptive decisions. In this paper we argue that these mechanisms can be distinguished by analyzing the density of the social network and its interaction with the proportion of contraceptive users among network partners. Our analyses indicate that social learning is most relevant with high market activity; in regions with only modest market activity, however, social influence is the dominant means by which social networks affect women’s contraceptive use.

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W.R. Kenan Jr. Professor of Economics University of Pennsylvania

We are indebted to Barbara Entwisle and two anonymous referees for many comments, which helped us to improve this paper. We are also grateful for comments by Christoph Bühler, Laura Bernardi, Martina Morris, Ina Warriner, Ester Wilder, and the participants in the session on social networks and fertility change in less developed countries, held at the 1999 annual meetings of the Population Association of America. The data used in this paper were collected with a grant from USAIDs Evaluation Project to Susan Watkins and Naomi Rutenberg for the first phase of the data collection, and with a grant from the Rockefeller Foundation to Watkins for the second phase. The analysis was undertaken in part through support from NIH Grant RO1 HD37276-01, the Rockefeller Foundation, and TransCoop Program of the German-American Academic Council.

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Kohler, H., Behrman, J.R. & Watkins, S.C. The density of social networks and fertility decisions: evidence from south nyanza district, kenya. Demography 38, 43–58 (2001). https://doi.org/10.1353/dem.2001.0005

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Keywords

  • Family Planning
  • Social Influence
  • Market Activity
  • Contraceptive User
  • Sparse Network