Data and Code for: Self-Preferencing at Amazon: Evidence from Search Rankings
Principal Investigator(s): View help for Principal Investigator(s) Chiara Farronato, Harvard University; Andrey Fradkin, Boston University; Alexander MacKay, Harvard University
Version: View help for Version V1
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Project Citation:
Farronato, Chiara, Fradkin, Andrey, and MacKay, Alexander. Data and Code for: Self-Preferencing at Amazon: Evidence from Search Rankings. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-05-22. https://doi.org/10.3886/E189942V1
Project Description
Summary:
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We study whether Amazon engages in self-preferencing on its marketplace by favoring its own brands (e.g., Amazon Basics) in search. To address this question, we collect new micro-level consumer search data using a custom browser extension installed by a panel of study participants. Using this methodology, we observe search positions, search behavior, and product characteristics. We find that Amazon branded products are indeed ranked higher than observably similar products in consumer search results. The prominence given to Amazon brands is 30% to 60% of the prominence granted to sponsored products.
Scope of Project
Subject Terms:
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Self-preferencing;
e-commerce;
digital platforms;
antitrust;
vertical integration
JEL Classification:
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D12 Consumer Economics: Empirical Analysis
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
L13 Oligopoly and Other Imperfect Markets
L15 Information and Product Quality; Standardization and Compatibility
L81 Retail and Wholesale Trade; e-Commerce
D12 Consumer Economics: Empirical Analysis
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
L13 Oligopoly and Other Imperfect Markets
L15 Information and Product Quality; Standardization and Compatibility
L81 Retail and Wholesale Trade; e-Commerce
Geographic Coverage:
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United States
Time Period(s):
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6/2022 – 1/2023
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