A microsimulation model of fertility shows that preferences cannot explain why highly educated women remain childless more often

Education is a strong driver of whether and when women become mothers. Many different and contradicting mechanisms have been proposed to explain why highly educated women are more likely to remain childless and become mothers at higher ages than less educated women. The demands on data to disentangle these mechanisms are extraordinary, and no dataset exists that allows for this. Microsimulation models can help in this situation by explicitly modelling the mechanisms and comparing the outcomes of the models to real-world outcomes. The simulation models presented here simulate fertility outcomes over the life courses of agents based on behavioural factors, such preferences and partnership trajectories, and biological factors that determine the ability to have children, such as the age at sterility, fecundability, and intrauterine mortality. To parametrise the models, we use administrative data from Social Statistics Netherlands, survey data from the LISS panel for the behavioural factors, and findings from reproductive medicine for the biological parameters. Our models show that unintended childlessness strongly differs between women with different educational levels. Despite higher educated women preferring to have children at a later age, our simulations showed that these preferences hardly played a role in explaining childlessness. The higher age at cohabitation was the main explanation for the higher unintended childlessness among highly educated women. We discuss the advantages and drawbacks of our simulation approach and how it can contribute to family sociology.

Summary

     Dag van de Sociologie

     Groningen, the Netherlands

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Description

Education is a strong driver of whether and when women become mothers. Many different and contradicting mechanisms have been proposed to explain why highly educated women are more likely to remain childless and become mothers at higher ages than less educated women. The demands on data to disentangle these mechanisms are extraordinary, and no dataset exists that allows for this. Microsimulation models can help in this situation by explicitly modelling the mechanisms and comparing the outcomes of the models to real-world outcomes. The simulation models presented here simulate fertility outcomes over the life courses of agents based on behavioural factors, such preferences and partnership trajectories, and biological factors that determine the ability to have children, such as the age at sterility, fecundability, and intrauterine mortality. To parametrise the models, we use administrative data from Social Statistics Netherlands, survey data from the LISS panel for the behavioural factors, and findings from reproductive medicine for the biological parameters. Our models show that unintended childlessness strongly differs between women with different educational levels. Despite higher educated women preferring to have children at a later age, our simulations showed that these preferences hardly played a role in explaining childlessness. The higher age at cohabitation was the main explanation for the higher unintended childlessness among highly educated women. We discuss the advantages and drawbacks of our simulation approach and how it can contribute to family sociology.