Sampling for Others in a Principal-Agent Setting

Last registered on February 29, 2024


Trial Information

General Information

Sampling for Others in a Principal-Agent Setting
Initial registration date
July 27, 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
July 28, 2023, 2:06 PM EDT

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

Last updated
February 29, 2024, 10:13 AM EST

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


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Primary Investigator

Heidelberg University

Other Primary Investigator(s)

PI Affiliation
Heidelberg University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
When making a choice in real-world situations such as investing or making larger purchases, decision makers often trust others’ experience. Commonly, such as in financial advice, there is a principal-agent relationship between decision maker and advisor, with the advisor collecting information by experience for one or multiple clients. Literature on decisions from experience so far has focused mostly on individual decision making, i.e. situations where decision makers gather information for themselves and then make a choice. We aim to provide insights into the linkage between information gathering and actual decision making, when both processes are handled by different persons. We test the fundamentals of such processes in a controlled laboratory setting. We vary the degree of responsibility agents have to collect information by having them either i) just gather information, ii) also provide a recommendation, or iii) also make a choice for the client. We contrast these results to decision makers collecting information and making decisions for themselves.
External Link(s)

Registration Citation

Becker, Christoph and Stefan Trautmann. 2024. "Sampling for Others in a Principal-Agent Setting." AEA RCT Registry. February 29.
Experimental Details


Different modes of collecting information for self or for others.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
(i) Number of samples drawn in each task.
(ii) Which lottery (out of two possibilities) was chosen in ach task.
Primary Outcomes (explanation)
(i) Participants draw samples from two lotteries. The samples either inform themselves or another participant (depending on the treatment) on which lottery to choose.
(ii) We then record the final choice participants either make for themselves or others.

Secondary Outcomes

Secondary Outcomes (end points)
(i) Demographics (age, gender, field of study, risk attitude)
Secondary Outcomes (explanation)
(i) Answers will be used as control variables.

Experimental Design

Experimental Design
Participants in the experiment are faced with five tasks that each consist of a choice between two risky lotteries. Participants initially have no information bout the outcomes and probabilities of the lotteries, but can acquire additional information, depending on their specific treatment. Collection information is done by clicking one two buttons, each representing on of the lotteries. Participants will either sample for themselves or for others.
Experimental Design Details
Not available
Randomization Method
Randomization of treatments done by the experimental software.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
500 Laboratory participants
Sample size: planned number of observations
500 Laboratory participants
Sample size (or number of clusters) by treatment arms
100 participants per treatment: 100 participants in Self, 100 participants in Sample, 100 participants in Recommendation and 100 in the Client condition. Participants in the Client condition see data from 3 participants of the Sample, Recommendation, and Decision treatment respectively (hence 3:1 agents to clients).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
There is no clear theoretical prediction how many samples should be drawn. In order to identify differences of 5 Samples between the different conditions (assuming a standard deviation of 12.5 based on previous research for participants sampling for themselves), we would need around 100 participants to achieve 80% Power at an alpha=0.05.
Supporting Documents and Materials


Document Name
Document Type
Document Description

MD5: 18e0d56ec637536b533ab8818f9b9c91

SHA1: 6f9b3b9f97d942626f6826def0ce6938411e6e2f

Uploaded At: July 27, 2023

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Institutional Review Boards (IRBs)

IRB Name
IRB of the Alfred-Weber-Institute for Economics, Heidelberg University
IRB Approval Date
IRB Approval Number