– by Rob Brooks, Khandis Blake & Lutz Fromhage
Choosing a mate involves a vast number of considerations. Personalities, looks, kindness, and attentiveness all come into play. So do status, wealth and material resources because mating partnerships are – at least in part – economic arrangements.
A couple shares much of their time, labour, and wealth, often investing in their joint social mobility and in raising children. Wherever and whenever money and status matter in heterosexual mating decisions, it is far more common for women to partner upward (a pattern called hypergyny) than it is for men. Across cultures and eras, hypergyny is common but its opposite (hyperandry) is vanishingly rare.
If economic considerations influence mating decisions, then it seems reasonable to expect the distribution of wealth to have important effects on mating patterns. For example, gaps in average income or wealth between women and men will likely alter the number of suitable partners a person might encounter. When women have few means of their own, then a majority of men could provide at least some upward mobility to any one of a majority of women.
That’s an argument we have encountered in verbal form, but when we wanted to make the argument in our work on the mating market consequences of inequality, we found a surprising lack of modelling. Moreover, thinking about the effects of income inequality within the sexes was even more sparse. If economic conditions like gender- and income inequality affect mating prospects, then that’s one more reason for them to also affect individual well-being, happiness, and political attitudes. So, in a recent Evolution and Human Behaviour paper, we modelled how inequalities between women and men, and inequalities within the sexes, might influence fitness prospects under hypergyny.
We created a population of individuals (a million of each sex), assigning them ‘wealth’ according to specified sex-dependent distributions. Their ‘status’ is their rank-order in wealth within their sex, so we can compare what happens under various wealth distributions. Individuals go through a series of one-to-one encounters with random unpaired members of the opposite sex. If, in an encounter, the two individuals’ preference rules are met, they form a pair and don’t participate in any further encounters. The result that interested us was how sex and status influenced the chances of an individual pairing up within 100 encounters.
The simplest preference rule – Choice Rule 1 – considered an encounter a match if the man’s wealth was the same as or greater than the woman’s. Some might find men’s lack of agency and women’s hard-edged preferences somewhat affronting, so we tried a few other rules. Rule 2 only allowed a match if the man’s wealth exceeded the women’s but by no more than a specified ‘cap’. Rule 3 added a second trait (which we imaginatively called ‘X’) that men cared about in that they only paired with a woman whose X exceeded their own. And Rule 4 gave women and men both preferences for wealth and ‘X’. Rules 2 to 4 made the results of our modelling a little less stark, as one might expect, but not fundamentally different, so our paper focuses really on the original preference rule 1.
Inequality between the sexes
If the wealth distribution for women doesn’t differ from that for men, the result is simple and easily anticipated. Men of above average wealth always find a match, the poorest never do, and the success of those in between depends on where they fit in terms of ranked wealth (i.e. ‘status’). In the same way, women of below average wealth always find a man who meets their preference and the wealthiest never do. The result is so obvious it probably doesn’t need modelling, and the intuition is common among evolutionary scientists, at least as far back as Trivers and Willard’s 1973 paper about adaptive offspring sex ratio adjustment.
Things get a bit more interesting when we introduce a small sex difference in mean wealth. If men average one standard deviation more wealth than women, the chance of mating improves dramatically for below-average status men and above-average status women (remember the above-average men and below-average women were already successful in pairing).
We modelled the effects of sex differences in mean wealth for up to four standard deviations in each direction, and showed that the more men’s wealth exceeded women’s, the more likely poorer men and wealthier women were to find a mate. When women’s wealth exceeded men’s on average, it was the above-average men and the below-average women whose mating prospects declined.
These results provide some insight into the mating market consequences of gender gaps. Those consequences might alter how people approach mating, gender relations, and even voting. For example, Incel (involuntary celibate) men, many of whom are young and below average income, blame narrowing gender gaps for undermining their marriage and mating prospects. They are infamous for their often violent, misogynistic rage, much of it directed at movements like feminism and laws that limit gender inequities.
Next we turned our attention to within-sex income inequality by altering the standard deviation of the distribution of wealth within each sex. We began by manipulating inequality in the same way for women and men simultaneously. Reducing inequality improved the pairing success of the two groups that struggle most finding a partner under hypergyny: the poorest men and wealthiest women. These results match with the intuition that – under hypergyny – inequality leaves a larger number of poor men unable to find a mate, and likewise that very wealthy women will be unable to find a partner whose income exceeds theirs.
An increase in inequality, however, did not hit the poorest men and wealthiest women as hard as it hit those men who were just below average in wealth and those women who were just a bit wealthier than average. If our modelling holds up in real mating markets, it would suggest that mating markets might respond to inequality in ways that entail more than merely comparisons between wealthy and poor.
That becomes even more true when we manipulate the inequality in one sex alone, while keeping it constant in the other. Those details are probably beyond a readable blog post, but the most intriguing finding is that a small shift in status can make a big difference between whether inequality suits or harms one’s mating interests..
Where to from here?
Evolutionary behavioural scientists have long understood that mating markets can have profound effects on a variety of behaviours. This enterprise has been most successful, to date, in the study of biased sex ratios and their flow-on effects. Nonetheless, economic inequalities are known to be associated with behaviours that are related to mating, as documented in Martin Daly and Margo Wilson’s extensive research on homicide rates. Indeed, our recent studies of self-sexualisation on social media, and the incidence of Incels posting on Twitter, drew to our attention the need to model how inequalities affect mating markets.
Our model shows that the effects of inequalities on mating interests are never as simple as favouring one sex at the expense of the other. It is our hope that our paper stimulates both theoretic and empirical exploration of how economic inequalities between and within the sexes shape mating markets and a variety of human behaviours.
Brooks, R.C., Blake, K., & Fromhage, L. (2022). Effects of gender inequality and wealth inequality on within-sex mating competition under hypergyny. Evolution and Human Behavior, 43(6), 501-509.