Gender Pay Gap Among Content Creators

Monday, 7 July 2025: 15:30
Location: SJES007 (Faculty of Legal, Economic, and Social Sciences (JES))
Oral Presentation
Sarah WEISSMANN ANNA, University of Potsdam, Germany
Aaron PHILIPP, University of Potsdam, Germany
Claudia BUDER, Université Paris 1 Panthéon-Sorbonne, France
Roland VERWIEBE, University of Potsdam, Germany
Chiara OSORIO KRAUTER, University of Potsdam, Germany
Licia BOBZIEN, University of Potsdam, Germany
Despite improvements in pay equity between men and women in recent decades, the gender pay gap (GPG) persists. Research suggest several explanations for these differences: occupational segregation (Busch, 2020), job position in the life course (Meara et al., 2020), and workforce interruptions (Blau & Kahn, 2017). We know, however, little about the extent of GPG and the mechanisms contributing to the GPG in the digital sphere, particularly regarding the new group of algorithm-dependent occupations on digital platforms.

Evidence suggests that the GPG for digital work on some platforms (e.g., Twitch, Instagram, Uber) is smaller than in many established ”offline” occupations but cannot fully be mitigated through increased job flexibility or algorithmic curation (Cook et al., 2020; Gaenssle, 2024). However, there has been no systematic GPG study among content creators (CCs) on YouTube, the first platform to offer monetization for digital workers. This paper fills this gap by answering the following research question: Is there a GPG among content creators on YouTube across topics? What are the decisive factors enforcing or diminishing the GPG on that platform?

The study employs the Duncan-Duncan segregation index as well as multivariate regressions and matching analyses (Meara et al., 2020). Empirically, we use a random sample of N=4,000 CCs from German-speaking countries and add socio-structural characteristics using a standardized classification survey (Seewann et al., 2022). The average monthly earnings from the YouTube Partner Program (using AdSense rates and view counts) is our dependent variable. First results show a strong inequality of earnings on YouTube (Gini: 86,6). Nonetheless, regression and matching analyses indicate a reversed GPG in the overall sample which is driven by favorable earnings of women in topics like gaming. That reversed GPG completely disappears when looking at the top 20% of CCs.