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The Examination of Diffusion Effects on Modern Contraceptive Use in Nigeria

Author

Listed:
  • David K. Guilkey

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

  • Veronica Escamilla

    (University of North Carolina at Chapel Hill)

  • Lisa M. Calhoun

    (University of North Carolina at Chapel Hill)

  • Ilene S. Speizer

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

Abstract

This study uses data gathered for an evaluation of a Bill & Melinda Gates Foundation–funded initiative designed to increase modern contraceptive use in select urban areas of Nigeria. When the initiative was conceived, the hope was that any positive momentum in the cities would diffuse to surrounding areas. Using a variety of statistical methods, we study three aspects of diffusion and their effects on modern contraceptive use: spread through mass communications, social learning, and social influence. Using a dynamic causal model, we find strong evidence of social multiplier effects through social learning. The results for social influence and spread through mass communications are promising, but we are unable to identify definitive causal impacts.

Suggested Citation

  • David K. Guilkey & Veronica Escamilla & Lisa M. Calhoun & Ilene S. Speizer, 2020. "The Examination of Diffusion Effects on Modern Contraceptive Use in Nigeria," Demography, Springer;Population Association of America (PAA), vol. 57(3), pages 873-898, June.
  • Handle: RePEc:spr:demogr:v:57:y:2020:i:3:d:10.1007_s13524-020-00884-6
    DOI: 10.1007/s13524-020-00884-6
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    References listed on IDEAS

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    1. Mroz, Thomas A., 1999. "Discrete factor approximations in simultaneous equation models: Estimating the impact of a dummy endogenous variable on a continuous outcome," Journal of Econometrics, Elsevier, vol. 92(2), pages 233-274, October.
    2. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    3. Jere Behrman & Hans-Peter Kohler & Susan Watkins, 2002. "Social networks and changes in contraceptive use over time: Evidence from a longitudinal study in rural Kenya," Demography, Springer;Population Association of America (PAA), vol. 39(4), pages 713-738, November.
    4. Hans-Peter Kohler & Jere Behrman & Susan Watkins, 2000. "Empirical Assessments of Social Networks, Fertility and Family Planning Programs," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 3(7).
    5. Reinhard Schunck, 2013. "Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models," Stata Journal, StataCorp LP, vol. 13(1), pages 65-76, March.
    6. Alok Bhargava, 2006. "Identification and Panel Data Models with Endogenous Regressors," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 3, pages 49-60, World Scientific Publishing Co. Pte. Ltd..
    7. Reinhard Schunck & Francisco Perales, 2017. "Within- and between-cluster effects in generalized linear mixed models: A discussion of approaches and the xthybrid command," Stata Journal, StataCorp LP, vol. 17(1), pages 89-115, March.
    8. Hans-Peter Kohler & Jere Behrman & Susan Watkins, 2001. "The density of social networks and fertility decisions: evidence from south nyanza district, kenya," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 43-58, February.
    9. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    10. repec:bla:obuest:v:63:y:2001:i:4:p:437-57 is not listed on IDEAS
    11. Joanna K. Swaffield, 2001. "Does Measurement Error Bias Fixed‐effects Estimates of the Union Wage Effect?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(4), pages 437-457, September.
    12. Chowdhury, Gopa & Nickell, Stephen, 1985. "Hourly Earnings in the United States: Another Look at Unionization, Schooling, Sickness, and Unemployment Using PSID Data," Journal of Labor Economics, University of Chicago Press, vol. 3(1), pages 38-69, January.
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