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Welfare Effects of Self-Preferencing by a Platform: Empirical Evidence from Airbnb

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  • Kaede Hanazawa

Abstract

This paper studies the welfare effects of self-preferencing by Airbnb, a practice where Airbnb utilizes its pricing algorithm to prioritize maximizing platform-wide commission revenue rather than optimizing individual host revenues. To examine this welfare implication, I construct a Bertrand competition model with differentiated products between Airbnb hosts and hotels. Using unique data from Tokyo's 23 wards, I estimate the model and conduct counterfactual simulations to evaluate the welfare effects of self-preferencing. Counterfactual simulations reveal that self-preferencing reduces social welfare by 5.08% on average, equivalent to an annual loss of about 14.90% of Tokyo's vacation rental market size in 2023 while increasing Airbnb's commission revenue by an average of 37.73%. These findings highlight the significant trade-offs between platform-driven revenue optimization and market efficiency, emphasizing the urgent need for competition policy reforms and greater transparency and accountability in platform practices.

Suggested Citation

  • Kaede Hanazawa, 2025. "Welfare Effects of Self-Preferencing by a Platform: Empirical Evidence from Airbnb," Papers 2503.04489, arXiv.org.
    • Handle: RePEc:arx:papers:2503.04489
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