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Identifying fertility contagion using random fertility shocks

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Fertility contagion through social networks increasingly attracts the interest of demographers. While these theories propose a causal mechanism, they are rarely put to test in a plausibly causal statistical design. This study applies quasi-experimental techniques to distinguish network effects from selection. Using contagion between siblings as an empirical example, we draw data from Norwegian administrative registers (N approx.170 000 men and women). We use twin births and the sex composition of children as random fertility shocks. We find no consistent significant effects of random shocks to a sibling's fertility on ego's fertility. First born women have larger families over time if a younger sibling chooses to have three children, as captured by the same sex instrument. We find no evidence that similarity strengthens contagion.

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  • Rannveig Kaldager Hart & Sara Cools, 2017. "Identifying fertility contagion using random fertility shocks," Discussion Papers 861, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:861
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    File URL: https://www.ssb.no/en/forskning/discussion-papers/_attachment/311690
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    Cited by:

    1. Rannveig Hart & Sara Cools, 2019. "Identifying interaction effects using random fertility shocks," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(10), pages 261-278.
    2. Zafer Buyukkececi & Thomas Leopold & Ruben Gaalen & Henriette Engelhardt, 2020. "Family, Firms, and Fertility: A Study of Social Interaction Effects," Demography, Springer;Population Association of America (PAA), vol. 57(1), pages 243-266, February.

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    More about this item

    Keywords

    Fertility; Social networks; Social contagion; Instrumental Variables;
    All these keywords.

    JEL classification:

    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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