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Do siblings' fertility decisions influence each other?

Torkild Hovde Lyngstad1, Alexia Prskawetz

  • 1Department of Sociology and Human Geography, University of Oslo, Blindern, Oslo, Norway. t.h.lyngstad@sosgeo.uio.no

Demography
|February 11, 2011
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Summary
This summary is machine-generated.

Sibling influences significantly impact first birth decisions but have a weaker effect on second births. This study analyzes fertility choices using Norwegian registry data, highlighting the role of social interaction in family planning.

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Area of Science:

  • Sociology
  • Demography
  • Behavioral Economics

Background:

  • Fertility decisions are influenced by individual factors and social interactions.
  • Disentangling social influences from background variables in fertility choices is challenging.
  • Cross-sibling influences offer a unique measure of social interaction in fertility research.

Purpose of the Study:

  • To quantify the impact of social interaction, specifically cross-sibling influences, on fertility decisions.
  • To differentiate the effect of sibling influences on first versus second birth transitions.
  • To leverage large-scale administrative data for robust analysis of fertility behavior.

Main Methods:

  • Utilized continuous-time hazard models to analyze fertility timing.
  • Incorporated sibling birth events as time-varying covariates.
  • Employed longitudinal population-wide Norwegian administrative registers covering over 110,000 sibling pairs.

Main Results:

  • Cross-sibling influences were found to be substantial for women's first births.
  • Sibling influences demonstrated a weaker effect on the transition to a second birth.
  • Individual socioeconomic and demographic variables also played a role in fertility decisions.

Conclusions:

  • Social interaction, measured through sibling influences, plays a significant role in shaping first birth timing.
  • The impact of social interaction on fertility diminishes for subsequent births.
  • Findings underscore the importance of considering social networks in understanding fertility patterns.