Attraction Inequality: Dating Economy Gini Breakdown

Jesus said that the poor would always be with us. Despite the best efforts of philanthropists and redistributionists over the last two millennia, he has been right so far. Every nation in the world has poor and rich, separated by birth and luck and choice. The inequality between rich and poor, and its causes and remedies, are discussed ad nauseam in public policy debates, campaign platforms, and social media screeds.

However, the relentless focus on inequality among politicians is usually quite narrow: they tend to consider inequality only in monetary terms, and to treat “inequality” as basically synonymous with “income inequality.” There are so many other types of inequality that get air time less often or not at all: inequality of talent, height, number of friends, longevity, inner peace, health, charm, gumption, intelligence, and fortitude. And finally, there is a type of inequality that everyone thinks about occasionally and that young single people obsess over almost constantly: inequality of sexual attractiveness.

The economist Robin Hanson has written some fascinating articles that use the cold and inhuman logic economists are famous for to compare inequality of income to inequality of access to sex. If we follow a few steps of his reasoning, we can imagine the world of dating as something like an economy, in which people possess different amounts of attractiveness (the dating economy’s version of dollars) and those with more attractiveness can access more and better romantic experiences (the dating economy’s version of consumer goods). If we think of dating in this way, we can use the analytical tools of economics to reason about romance in the same way we reason about economies.

One of the useful tools that economists use to study inequality is the Gini coefficient. This is simply a number between zero and one that is meant to represent the degree of income inequality in any given nation or group. An egalitarian group in which each individual has the same income would have a Gini coefficient of zero, while an unequal group in which one individual had all the income and the rest had none would have a Gini coefficient close to one. When Jeff Bezos or Warren Buffett walks into a room, the Gini coefficient of the room shoots up.

Some enterprising data nerds have taken on the challenge of estimating Gini coefficients for the dating “economy.” Among heterosexuals, this actually means calculating two Gini coefficients: one for men, and one for women. This is because heterosexual men and heterosexual women essentially occupy two distinct “economies” or “worlds,” with men competing only with each other for women and women competing only with each other for men. The Gini coefficient for men collectively is determined by women’s collective preferences, and vice versa. If women all find every man equally attractive, the male dating economy will have a Gini coefficient of zero. If men all find the same one woman attractive and consider all other women unattractive, the female dating economy will have a Gini coefficient close to one. The two coefficients do not directly influence each other at all, and each sex collectively sets the Gini coefficient—that is, the level of inequality—for the other sex.

A data scientist representing the popular dating app “Hinge” reported on the Gini coefficients he had found in his company’s abundant data, treating “likes” as the equivalent of income. He reported that heterosexual females faced a Gini coefficient of 0.324, while heterosexual males faced a much higher Gini coefficient of 0.542. So neither sex has complete equality: in both cases, there are some “wealthy” people with access to more romantic experiences and some “poor” who have access to few or none. But while the situation for women is something like an economy with some poor, some middle class, and some millionaires, the situation for men is closer to a world with a small number of super-billionaires surrounded by huge masses who possess almost nothing. According to the Hinge analyst: