From https://papers.ssrn.com/sol3/papers.cfm?abstract_id=895442 :

https://i.imgur.com/okVd1n2.png

Authors' comments:

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 65% more first-contact e-mails than men in the 5’7 - 5’8 range. In contrast, the ideal height for women is in the 5’3 - 5’8 range, while taller women experience increasingly worse outcomes. For example, the average 6’3 tall woman receives 42% fewer e-mails than a woman who is 5’5.




Caveats

This graph is from the unpublished 2006 draft version of the “What Makes You Click” paper by Hitsch, Hortaçsu and Ariely. By the time the paper was actually published, 4 years later, in a SJR ~2 & IF ~1 journal, it had jettisoned all of the blackpills contained within (including the figure pictured). One suspects this had more to do with the more “political” aspects of the editorial and peer-review process than the actual legitimacy of the data. Nevertheless, it should still be acknowledged that, in the published version, the authors have a statement distancing themselves from their earlier drafts:

Note that previous versions of this paper (“What Makes You Click? – Mate Preferences and Matching Outcomes in Online Dating”) were circulated between 2004 and 2006. Any previously reported results not contained in this paper or in the companion piece Hitsch et al. (2010) did not prove to be robust and were dropped from the final paper versions.

http://faculty.chicagobooth.edu/guenter.hitsch/papers/Mate-Preferences.pdf

Methodology

Unnamed online dating service with the following features:

After registering, the users can browse, search, and interact with the other members of the dating service. Typically, users start their search by indicating in a database query form a preferred age range and geographic location for their partners. The query returns a list of “short profiles” indicating the user name, age, a brief description, and, if available, a thumbnail version of the photo of a potential mate. By clicking on one of the short profiles, the searcher can view the full user profile, which contains socioeconomic and demographic information, a larger version of the profile photo (and possibly additional photos), and answers to several essay questions. Upon reviewing this detailed profile, the searcher decides whether to send an e-mail to the user. Our data contain a detailed, second-by-second account of all these user activities. In particular, we know if and when a user browses another user, views his or her photo(s), and sends an e-mail to another user. In order to initiate a contact by e-mail, a user has to become a paying member of the dating service. Once the subscription fee is paid, there is no limit to the number of e-mails a user can send.

Sample description

  • Full Sample Size: 22,000
  • Location: Boston and San Diego
  • Dates: Online activity observations took place over a 3.5 month period in 2003
  • targeted long-term partner-seeking daters
  • average number of first-contact emails received by gender: 2.3 for men, 11.4 for women
  • % of users who did not receive any email: 56.4% of men, 21.1% of women

Mate preference model: Outcome regression approach

https://i.imgur.com/7dkIxlg.png

Where:

  • Y = number of unsolicited emails that a user received
  • x=vector of categorical user attributes
  • 𝜃j = regression coefficient associated with a specific attribute unique to user A that user B, the selected “baseline” user, lacks, holding all other attributes constant
  • exp(𝜃j) measures premium (or penalty) from the specific attribute in terms of the outcome difference (i.e., number of emails) expressed as a percent

Operating assumptions (limitations) of the model:

  • assumes that all users have homogenous preferences by default, unless preference heterogeneity is accounted for a priori
  • assumes all profiles are equally likely to be sampled during the search process