Dissecting Netflix's Self-Preferencing: Evidence from Viewer-Level Data

Tin Cheuk Leung, Shi Qi and Koleman Strumpf
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Tin Cheuk Leung: Wake Forest University
Shi Qi: William & Mary
Koleman Strumpf: Wake Forest University

No 137, Working Papers from Wake Forest University, Economics Department

Abstract: This paper studies self-preferencing in subscription video streaming. We assemble a new dataset linking Netflix's U.S. catalog, Top 10 rankings, Wikipedia page views, and device-level streaming records. Conditional on external popularity and other observables, Netflix Originals are significantly more likely to appear in the Top 10 than comparable non-original titles, especially among series. Using a matched staggered difference-indifferences design around first Top 10 entry, we show that Top 10 placement causally increases subsequent viewership. The effect is weaker among devices with extensive prior Netflix viewing, consistent with personalized recommendations substituting for generic rankings. These findings provide evidence of platform gatekeeping in digital media

Keywords: Self-Preferencing; Netflix; Digital Platforms; Platform Bias (search for similar items in EconPapers)
JEL-codes: D22 K21 L40 L82 M21 (search for similar items in EconPapers)
Pages: 46
Date: 2026-06
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Persistent link: https://EconPapers.repec.org/RePEc:ris:wfuewp:023017

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