Collusion in continuous-time markets

Last registered on November 17, 2025
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Pre-Trial

Trial Information

General Information

Title
Collusion in continuous-time markets
RCT ID
AEARCTR-0017188
Initial registration date
November 13, 2025

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
November 17, 2025, 2:32 PM EST

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

Locations

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Primary Investigator

Name
Mia Tam
Affiliation
University of Melbourne
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Other Primary Investigator(s)

PI Name
Ralph-C Bayer
PI Affiliation
University of Adelaide
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Additional Trial Information

Status
In development
Start date
2025-11-12
End date
2026-12-31
Keywords
Lab
Additional Keywords
collusion, oligopoly, continuous time
JEL code(s)
D43, C92, L13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This research aims to understand the mechanism behind why cooperation in repeated games is higher in real-time environments. Markets where firms set prices are examples of when this mechanism is relevant, as tacit collusion (collusion without explicit communication) is a form of cooperation. As more markets move online, there is increasing concern this could facilitate firms to tacitly collude. Understandingthe mechanism behind higher levels of cooperation in real-time environments can help to inform competition policy.
External Link(s)

Registration Citation

Citation
Bayer, Ralph-C and Mia Tam. 2025. "Collusion in continuous-time markets." AEA RCT Registry. November 17. https://doi.org/10.1257/rct.17188-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Laboratory experiments.
Intervention Start Date
2025-11-12
Intervention End Date
2026-08-31

Primary Outcomes

Primary Outcomes (end points)
Average prices and profits in each market, proportions of markets colluding (or other),
Primary Outcomes (explanation)
In each duopoly market we will have price data that forms a timeseries over 3,600 seconds, at 0.5 second increments. We are interested in collusion levels in each treatment, which can be measured as an average price or total surplus extracted from the market.

The highest level test of treatment differences will be on average prices of independent observations between treatments. Each independent observation is calculated as the average price in a market over the experiment. This is then used to determine the average price in each treatment for the entire experiment.

For each point in time, we can categorise markets by their level of collusiveness based on prices and total surplus in the market.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Three treatments:
Stochastic
Lockin
Stochastic-lockin
Experimental Design Details
Not available
Randomization Method
Participants are invited to sign up to experimental sessions and are not aware of which treatment of the experiment they will participate in.
Randomization Unit
Experimental sessions
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
3 treatments. The exact number of sessions for each treatment will depend on the number of participants that sign up and attend each session, but is expected to be 3-4 per treatment. This is 9-12 sessions in total.
Sample size: planned number of observations
Approx. 20-30 independent observations per treatment. A market, comprising of two participants, is one independent observation. With three treatments, we expect between 60-90 observations
Sample size (or number of clusters) by treatment arms
Three treatments, each with 40-60 participants. Thus, in total between 120-180 participants.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Research Ethics Committee, University of Melbourne
IRB Approval Date
2025-11-13
IRB Approval Number
2025-34345-73202-3
Analysis Plan