Does TikTok promote or cannibalize music streaming? Estimands and identification with heavy-tailed outcomes

Abstract We study how TikTok affects demand for music on paid streaming platforms in the context of Universal Music Group’s (UMG) global withdrawal of its catalog from TikTok. Recent studies using this quasi-natural experiment have reached different conclusions about whether TikTok promotes or cannibalizes streaming demand. We show that these differences arise in part because the estimand changes with the specification. With heavy-tailed outcomes, common difference-in-differences implementations in levels, logs, and Poisson place weight on different parts of the distribution and therefore answer different economic questions. In our data, the top 10% of songs account for 96% of TikTok creations and 76% of Spotify streams, making the distinction between the typical song and the economically consequential song central. We find that removing TikTok access lowers aggregate Spotify demand for UMG titles. The losses are concentrated among viral songs, while the long tail shows little economically meaningful change. Evidence from the 2025 U.S. TikTok outage, which disrupted TikTok access across labels rather than for UMG alone, points in the same direction. Finally, we show that lost TikTok exposure reduces playlist inclusion, compounding the initial demand shock into longer-term declines in streaming demand. We also provide a practitioner’s companion that guides the choice of DiD estimands, estimators, and diagnostics in heavy-tailed outcome settings, along with an interactive tool at DiDestimands.app .