Population heterogeneity and individual differences in an agent-based marriage and divorce model (MADAM) using search with relaxing expectations

While many models have investigated the role of competitive mate selection processes in human marriage, few have addressed the potential for assortative processes to explain the observed demographics, as well as simultaneously investigating divorce. To explore the possibility that assortative mate selection processes may explain patterns of both marriage and divorce, we developed an agent-based model, MADAM (Marriage and Divorce Annealing Model), based on homophilic trait matching, in which individuals search for mates similar to themselves, but relax these expectations as they age. MADAM assumes individuals live in a world with N mate-relevant traits, where each individual chooses a set of k traits from those N to represent his or her identity. Individuals seek marriage partners with some number of identical traits, but over time relax their expectations for this desired threshold number of matching traits. Divorce is allowed when individuals find a partner who shares more traits with them than their current partner. With this implementation, we explored how population heterogeneity and individual differences affect population-level demographic trends, finding that increasing population heterogeneity and a reduction in the rate of relaxing expectations can both increase the mean age at first marriage. MADAM also accurately predicts demographic marriage and divorce data across cultures, with quantitatively accurate predictions for length of first marriage, likelihood of first marriage ending in divorce, and percent of population married by the end of the lifespan.