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

Author

Listed:
  • Tin Cheuk Leung

    (Wake Forest University)

  • Shi Qi

    (William & Mary)

  • Koleman Strumpf

    (Wake Forest University)

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

Suggested Citation

  • Tin Cheuk Leung & Shi Qi & Koleman Strumpf, 2026. "Dissecting Netflix's Self-Preferencing: Evidence from Viewer-Level Data," Working Papers 137, Wake Forest University, Economics Department.
    • Handle: RePEc:ris:wfuewp:023017
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    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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