Matthew Botos

I just finished reading Freakonomics, which includes a brief section on how truthfully people represent themselves and make decisions in the online dating world. Like any good researchers, the authors cite their source, a paper that is readily available online. What Makes You Click: An Empirical Analysis of Online Dating is a fully-blown academic paper, but there are some interesting facts to be gleaned from skimming it.

First, everyone lies, at least a little:

Among women, we find that the average stated weight is less than the average weight in the U.S. population. The discrepancy is about 6 lbs among 20-29 year olds, 18 lbs among 30-39 year olds, and 20 lbs among 40-49 year olds. On the other hand, the reported weights of men are generally slightly above yet close to the national averages. The stated height of both men and women is somewhat above the U.S. average. This difference is more pronounced among men, although the numbers are small in size. For example, among 20-29 year olds, the difference is 1.3 inches for men and 1 inch for women.

Looks still matter the most, though:

The median man (in terms of photo attractiveness) can expect to hear back from the median woman with a 40% chance, whereas the median woman can expect to get a reply with a 70% chance.

The utility weight on the looks rating variable differs only little across men (0.277) and women (0.265).

To take advantage of them, though, you’ll have to post a photo, which every site tells you on pretty much the first page:

Having a photo online per se improves the members’ outcomes. Women receive more than twice as many e-mails, and men receive about 50% more e-mails than those users who did not post a photo and describe themselves as having “Average looks”.

After looks comes height:

Height matters for both men and women, but mostly in opposite directions. Women like tall men (figure 5.4). Men in the 6’3”-6’4” range, for example, receive about 60% more first contact e-mails than men in the 5’7”-5’8” range. In contrast, the ideal height for women seems to be in the 5’3”-5’8” range, while taller women experience increasingly worse outcomes. For example, the average 6’3” tall woman receives 40% fewer e-mails than a woman who is 5’5”.

There’s a double standard for education:

With respect to the number of first contact e-mails, there is a college and graduate education premium for men. Relative to high school graduates, a college degree is associated with a 35% increase in the number of first contacts. Grad- uate degrees are associated with a similar premium, but do not improve outcomes further relative to a college degrees. In contrast to these findings for men, the outcomes of women do not improve with their educational attainment. To the contrary, college juniors and se- niors, women in a post-graduate program, and women with a master’s degree incur a slight outcome penalty.

Yet oddly:

The occupation of women, on the other hand, has little influence on their outcomes; in fact, most professions are associated with a slightly lower number of first contacts relative to students.

One of the themes picked up in Freakonomics was that even people who claim no ethnic preference for a mate still reveal one in their actions:

It is evident that both members who declare a preference for their own ethnicity, and those who do not, discriminate against users who belong to different ethnic groups. However, the discrimination size is more pronounced for members of the former group, i.e. these users act consistent with their stated preferences. There is strong evidence, however, that also members of the latter group have ethnic preferences, which is in contradiction to their statement that ethnicity “doesn’t matter” to them.

Another bit called out in the book was how economists can calculate the cost associated with certain trade-offs:

Men generally prefer shorter women, and they particularly try to avoid women who are taller than themselves. Women, on the other hand, prefer men who are taller than themselves, and they have a particularly strong aversion to shorter men. For example, our estimates imply that compared to a man who is five inches taller than a woman and earns $ 50,000 per year, a man who is five inches shorter than a woman would need to earn slightly more than half a million dollars per year to make up for his shortcoming.

Their findings on incomes are a mix of the expected and unexpected:

We confirm that the partner’s income matters to both men and women. Woman, how- ever, place almost twice as much weight on income than men. Contrary to what we ex- pected, men have a statistically significant distaste for women who are poorer than them, while women have a statistically significant distaste for men who are richer than them. The absolute value of these coefficients is small, however, and hence own income appears to matter only little in the evaluation of a partner’s earnings.

Religion also briefly addressed:

Finally, we find that both men and women have a preference for a partner of the same religion.

They also compare how well matches who contacted each other lined up in various traits to people who actually got married, something surely of interest to our friend Dr. Neil Clark Warren.

Another interested concept is that of “search friction”, or the difficulty in meeting people. While this is minimized in an online setting, they acknowledge their data on real-world marriages was likely skewed towards people meeting through the same social circles, neighborhoods, schools, etc.

An interesting follow-up to this research would be to compare with outcomes from sites like eHarmony and Chemistry, where users either have incomplete information on potential partners or receive algorithmic matches without the influence of their own conscious or unconscious biases. And of course, the ultimate question: do any of these dating sites or matching algorithms lead to more successful matches than people just bumping into each other on the street?