Self-Preferencing and Consumer Welfare: Evidence from a Field Experiment

Last registered on October 29, 2025

Pre-Trial

Trial Information

General Information

Title
Self-Preferencing and Consumer Welfare: Evidence from a Field Experiment
RCT ID
AEARCTR-0011370
Initial registration date
June 13, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 23, 2023, 4:39 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
October 29, 2025, 4:11 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Boston University

Other Primary Investigator(s)

PI Affiliation
Harvard Business School
PI Affiliation
Harvard Business School

Additional Trial Information

Status
Completed
Start date
2023-06-13
End date
2023-10-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We seek to study how self-preferencing by digital platforms affects consumer welfare and competition.
External Link(s)

Registration Citation

Citation
Farronato, Chiara , Andrey Fradkin and Alexander MacKay. 2025. "Self-Preferencing and Consumer Welfare: Evidence from a Field Experiment." AEA RCT Registry. October 29. https://doi.org/10.1257/rct.11370-3.0
Experimental Details

Interventions

Intervention(s)
Group 1 is the control group, for which the extension simply monitors participants' behavior. The extension tracks browsing behaviors on Amazon.com, ensuring that confidential information is removed before storing the data. Additionally, the extension tracks URLs visited on other major e-commerce websites, but it does not collect more detailed tracking data or intervene with what the participants see on these websites.
Group 2 is the Amazon treatment group. For this group, the extension hides major Amazon-owned brands from the participants' browsing experience on Amazon.com. This mainly includes removing Amazon-branded products from search and product pages.
Group 3 is the random treatment group. This group is similar to group 2, except that instead of hiding the Amazon-branded products from a web page, the extension hides a random set of products, where the number of hidden products is equal to the number of Amazon-branded products on that web page.

See the included document for details.
Intervention (Hidden)
Intervention Start Date
2023-06-13
Intervention End Date
2023-10-31

Primary Outcomes

Primary Outcomes (end points)
See the pre-registration document and analysis plan.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
See the pre-registration document and analysis plan.
Experimental Design Details
Randomization Method
Simple randomization by computer
Randomization Unit
The unit of randomization is the study participant.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1200 participants, with 1000 minimum if costs of recruitment increase substantially
Sample size: planned number of observations
1200 participants, 6 wishlist task choices per participant
Sample size (or number of clusters) by treatment arms
400 control, 400 amazon brands hide, 400 random hide
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

Documents

Document Name
Survey1 - Eligibility
Document Type
survey_instrument
Document Description
Eligibility survey
File
Survey1 - Eligibility

MD5: 38ea1f567f532fefc7e6d511df166641

SHA1: 3952c40d4a2f7a94e512dbfa9e4fb957b1069479

Uploaded At: June 13, 2023

Document Name
Experiment and pre-analysis plan
Document Type
other
Document Description
File
Experiment and pre-analysis plan

MD5: 432af82ca185a7e0c723ebe51f109639

SHA1: e45448a5f45eb053474712bd7de56b543e153293

Uploaded At: June 13, 2023

Document Name
Survey2 - Intake
Document Type
survey_instrument
Document Description
File
Survey2 - Intake

MD5: 026a7428f78a3e34fd03e80d0c3d7a85

SHA1: 8eff2449f7d65006357b12deb6332810804cb5a7

Uploaded At: June 13, 2023

IRB

Institutional Review Boards (IRBs)

IRB Name
Harvard University Institutional Review Board
IRB Approval Date
2023-06-12
IRB Approval Number
MOD21-1677-11
Analysis Plan

Analysis Plan Documents

Analysis Plan

MD5:

SHA1:

Uploaded At: October 29, 2025

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
Platforms, retailers, and other firms often offer their own products alongside products sold by competitors. We study the effects of this practice by combining a field experiment that hides brands owned by Amazon (i.e., private labels) from shoppers on Amazon.com with model-based counterfactuals and welfare analysis. In the absence of private labels, consumers substitute toward products that are similar along most observable dimensions. Removing Amazon brands does not change consumers' search effort or their propensity to shop at other retail websites. Despite the ample availability of observably similar alternatives, our welfare estimates imply that, for the categories we study, removing Amazon brands would reduce consumer surplus by 5.4 percent in the short run, with approximately 10 percent of the impact due to equilibrium price increases by other sellers. The effects are heterogeneous, with consumer surplus reductions exceeding 10 percent in some categories, while other categories realize much smaller decreases when Amazon brands are removed. Demoting private labels in search results to counteract potential self-preferencing does not lead to gains in consumer surplus. This outcome arises because a subset of consumers derive greater utility from private labels and benefit from their high placement in search results.
Citation
Farronato, Chiara, Andrey Fradkin, and Alexander MacKay. Vertical Integration and Consumer Choice: Evidence from a Field Experiment. No. w34135. National Bureau of Economic Research, 2025.

Reports & Other Materials