The Effect of Sport in Online Dating: Evidence from Causal Machine Learning - Daniel Boller; Michael Lechner; Gabriel Okasa (Institute of Labor Economics (IZA), 2021)
Online dating emerged as a key platform for human mating. Previous research focused on socio-demographic characteristics to explain human mating in online dating environments, neglecting the commonly recognized relevance of sport. This research investigates the effect of sport activity on human mating by exploiting a unique data set from an online dating platform. Thereby, we leverage recent advances in the causal machine learning literature to estimate the causal effect of sport frequency on the contact chances. We find that for male users, doing sport on a weekly basis increases the probability to receive a first message from a woman by 50%, relatively to not doing sport at all. For female users, we do not find evidence for such an effect. In addition, for male users the effect increases with higher income.
Keywords: J12; Z29; C21; C45; 330; online dating; sports economics; big data; causal machine learning; effect heterogeneity; Modified Causal Forest