Social Networks and Long-Term Fertility Trends: An Agent-Based Modeling Approach

Eli Nomes, University of Leuven
Andre Grow , University of Leuven (KU Leuven)
Jan Van Bavel, Katholieke Universiteit Leuven

The notion that people’s fertility behavior is affected by others in their social networks has found strong empirical support, but assessing the role that such influence played in shaping long-term fertility trends is difficult. Several studies have had promising results employing an agent-based computational modelling approach, but it remains unclear whether these models can also explain more long-term fertility change, characterized by several trend reversals. In this paper, we examine to what extent social influence could explain such long-term, non-monotonic fertility trends. We focus on the mid-twentieth century baby boom in Belgium. Preliminary results show that social influence potentially explains part of the fertility dynamics of the baby boom, as our basic model is broadly capturing the observed non-monotonous changes. We will investigate whether extending the model can improve the results. Subsequently, we will apply the model to the recent reversal of the educational gradient in fertility observed in Scandinavia.

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 Presented in Session 208. Computational Demography