The effect of cartel-fine structure on cartel pricing and cartel stability

Last registered on September 15, 2023
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Pre-Trial

Trial Information

General Information

Title
The effect of cartel-fine structure on cartel pricing and cartel stability
RCT ID
AEARCTR-0012043
Initial registration date
September 07, 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
September 15, 2023, 8:49 AM EDT

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

Locations

Country
Netherlands
Region
Amterdam

Primary Investigator

Name
Sindri Engilbertsson
Affiliation
University of Amsterdam
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Other Primary Investigator(s)

PI Name
Leonard Treuren
PI Affiliation
KU Leuven
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PI Name
Sander Onderstal
PI Affiliation
University of Amsterdam
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Additional Trial Information

Status
In development
Start date
2023-09-11
End date
2023-12-31
Keywords
Crime, Violence, & Conflict, Firms & Productivity, Lab
Additional Keywords
Antitrust, Competition, Cartels
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This paper considers the policy question of how cartels should be fined, building on a recent theoretical literature. We compare three different designs for cartel fines on the formation and pricing behavior of cartels theoretically and using a laboratory experiment. The three fining regimes are based on i) profits, ii) revenue, and iii) overcharge. The theoretical findings suggest that the revenue-regime will result in prices above the monopoly level, while the overcharge-regime will keep cartel prices below the monopoly level. Additionally, we expect deterrence to be the greatest under the overcharge regime, and equal under the profit and revenue regimes. We design an experiment that provides a test of our predictions.
External Link(s)

Registration Citation

Citation
Engilbertsson, Sindri, Sander Onderstal and Leonard Treuren. 2023. "The effect of cartel-fine structure on cartel pricing and cartel stability." AEA RCT Registry. September 15. https://doi.org/10.1257/rct.12043-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-09-11
Intervention End Date
2023-09-21

Primary Outcomes

Primary Outcomes (end points)
Market prices and prices set by firms, also broken down by cartel status. Cartel (re-)formation, cartel agreements, and stability of collusive agreements.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our experiment tests the pricing and cartel deterrence effects of three different cartel fining regimes: fines based on cartel profits, cartel revenues, and cartel overcharge. Subjects play an infinitely repeated Bertrand triopoly game. In each period, subjects first engage in optional communication and then set their price unilaterally. Next, the market clears, and communication is detected and punished with a fixed probability of 0.2. We vary fines across different treatments by basing them either on a firm’s revenue, profit, or overcharge. Finally, subjects receive feedback on the prices, fines, and profits. With probability 0.9, the three matched subjects play another period, while with probability 0.1, each subject is re-matched with two new subjects before playing the next period.
Experimental Design Details
We plan to test the following hypotheses:
H1: The treatments rank as follows in terms of market price:
p_REVENUE > p_PROFIT > p_OVERCHARGE

While probability of another round in each supergame (0.9) should theoretically lead to perfect deterrence in each treatment, the critical discount factor is greatest in the OVERCHARGE regime (0.81), and equal in the PROFIT and REVENUE regimes (2/3). For cartel stability, we thus expect to observe:
H2: The treatments rank as follows in terms of cartel stability:
C_REVENUE=C_PROFIT>C_OVERCHARGE

For both hypotheses, we first employ F-tests for testing that the outcome variables are not all equal.
Between-treatment differences are tested with regressions where we account for within-matching group dependency by clustering the standard errors at the matching group level.
Randomization Method
Participants register for sessions without information on the treatment.
Within the lab, the computers are set up such that two participants in the same matching group will never sit next to one another. Participants are then randomly placed at computers to randomize matching groups within sessions.
Randomization Unit
Experimental sessions.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
30 matching groups.
Each experimental session has 18 participants that are split into matching groups of 9. During the experiment, participants are grouped into new 'markets' of three for each of the four supergames. To make sure no participants are ever in the same group twice, we rematch within matching groups of 9.
Sample size: planned number of observations
1080 groups of 3 participants. In total we will have 270 participants and each participant is a member of four different groups (or 'markets') during a session.
Sample size (or number of clusters) by treatment arms
360 groups in profit regime, 360 groups in revenue regime, and 360 groups in overcharge regime.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
EB Research Management Services
IRB Approval Date
2023-03-16
IRB Approval Number
EB-1145
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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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
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials