Morals in multi-unit markets: Study III

Last registered on March 21, 2023


Trial Information

General Information

Morals in multi-unit markets: Study III
Initial registration date
March 20, 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
March 21, 2023, 4:56 PM EDT

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
University of Amsterdam
PI Affiliation
University of Amsterdam

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This study is a follow-up to Ziegler et al. (2022) who found a deterioration of morals in markets where the replacement logic is available (FULL) compared to both individual decision-making and markets with capacity constraints (MULTI), and especially to study II (AEARCTR-0008306). In this study, we provide participants with information from previous sessions to shock their beliefs about the number of other traders that are active. The goal is to study the impact of shocked beliefs on trading behavior.

External Link(s)

Registration Citation

Offerman, Theo, Giorgia Romagnoli and Andreas Ziegler. 2023. "Morals in multi-unit markets: Study III." AEA RCT Registry. March 21.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1) The number of active traders
2) Beliefs about the number of active traders
Primary Outcomes (explanation)
On 1): The main outcome of this study is the comparison, between treatments, of the number of active traders of the first-moving side for unit 13 in market period 1. We will also compare trading for unit 15 and pooling first and second movers. As an additional test, we will pool all periods. If trading stops earlier, the number of active traders is assumed to be 0 for later units.
On 2) We elicit beliefs for the trading of unit 4, 13, and 15. The main outcome is the belief for the number of active traders in market period 1 for unit 13.

Secondary Outcomes

Secondary Outcomes (end points)
a) Margins of offers
b) Quantities traded
Secondary Outcomes (explanation)
On a) We will compare the profit margins of the first offers (as well as of the acceptances of the first movers, for units 13 and 15 as well as for all market periods, as for activity), with a focus on the offer with the lowest profit margin for the responding market side, between treatments.
On b) We will compare the number of traded units between treatments, once for market period 1 and once for all market periods.

Experimental Design

Experimental Design
We will provide participants with information from previous sessions, where participants learn the number of traders that were active at the next unit and whether that next unit was traded.

There are two treatments: in B-FULL-HIGH, this is information from an earlier matching group where many traders were active and trading continued (a matching group of B-FULL). In B-FULL-LOW, this is information from an earlier matching group where few traders were active and trading stopped (a matching group of B-MULTI).

We will perform all test between treatments, using Mann-Whitney U-tests and regressions (clustering standard errors on a matching group level). In addition, we will study the correlation between trading behavior and beliefs, as already done in B-FULL.
Experimental Design Details
After collecting the first half of the data, we will verify that our treatment variation is successful in moving beliefs between B-FULL-HIGH and B-FULL-LOW. A treatment difference in beliefs is the necessary pre-requisite for the data to answer our research question. However, such an effect on beliefs may be attenuated, for example, by the rich information markets participants receive endogenously. If we do not detect a treatment effect in beliefs, we may halt data collection and design alternative treatments to test our conjecture.
Randomization Method
Treatments (B-FULL-LOW and B-FULL-HIGH) are assigned on a session level, the order will be randomly drawn before the start of the experiment.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
20 matching groups, 10 per treatment.
Sample size: planned number of observations
200 participants in 20 matching groups.
Sample size (or number of clusters) by treatment arms
100 participants per treatment, in 10 matching groups.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee Economics and Business (EBEC) University of Amsterdam
IRB Approval Date
IRB Approval Number
EC 20210906110921


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials