Assortative Mating and the Reversal of Gender Inequality in Education in Europe: An Agent-Based Model
Authored by Andre Grow, Bavel Jan Van
Date Published: 2015
DOI: 10.1371/journal.pone.0127806
Sponsors:
European Union
Platforms:
NetLogo
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/HPUQ1Y
Abstract
While men have always received more education than women in the past, this gender imbalance in education has turned around in large parts of
the world. In many countries, women now excel men in terms of
participation and success in higher education. This implies that, for
the first time in history, there are more highly educated women than men
reaching the reproductive ages and looking for a partner. We develop an
agent-based computational model that explicates the mechanisms that may
have linked the reversal of gender inequality in education with observed
changes in educational assortative mating. Our model builds on the
notion that individuals search for spouses in a marriage market and
evaluate potential candidates based on preferences. Based on insights
from earlier research, we assume that men and women prefer partners with
similar educational attainment and high earnings prospects, that women
tend to prefer men who are somewhat older than themselves, and that men
prefer women who are in their mid-twenties. We also incorporate the
insight that the educational system structures meeting opportunities on
the marriage market. We assess the explanatory power of our model with
systematic computational experiments, in which we simulate marriage
market dynamics in 12 European countries among individuals born between
1921 and 2012. In these experiments, we make use of realistic agent
populations in terms of educational attainment and earnings prospects
and validate model outcomes with data from the European Social Survey.
We demonstrate that the observed changes in educational assortative
mating can be explained without any change in male or female
preferences. We argue that our model provides a useful computational
laboratory to explore and quantify the implications of scenarios for the
future.
Tags
selection
Demography
patterns
preferences
homogamy
Mate Choice
Marriage markets
Sex-differences
Wedding-ring
37
cultures