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The effect of sport in online dating: evidence from causal machine learning

Author

Listed:
  • Daniel Boller

    (World Bank
    University of St. Gallen)

  • Michael Lechner

    (University of St. Gallen
    CEPR
    CESifo
    IAB)

  • Gabriel Okasa

    (University of St. Gallen
    Swiss National Science Foundation)

Abstract

Online dating emerged as a key instrument for human mating. This research investigates the effect of sports activity on human mating by exploiting a unique data set from an online dating platform. We leverage advances in causal machine learning to estimate the causal effect of sports frequency on contact chances. We find that for male users, sport on a weekly basis increases the probability of receiving a first message from another user by 50%, relative to not doing sport. For female users, we do not find evidence for such an effect. In addition, for male users, the effect increases with higher income.

Suggested Citation

  • Daniel Boller & Michael Lechner & Gabriel Okasa, 2025. "The effect of sport in online dating: evidence from causal machine learning," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-04566-9
    DOI: 10.1057/s41599-025-04566-9
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    More about this item

    JEL classification:

    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • Z29 - Other Special Topics - - Sports Economics - - - Other
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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