Boundedly rational information demand

Last registered on November 30, 2022
View Trial History

Pre-Trial

Trial Information

General Information

Title
Boundedly rational information demand
RCT ID
AEARCTR-0010543
Initial registration date
November 29, 2022

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 30, 2022, 4:59 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
Yucheng Liang
Affiliation
Carnegie Mellon University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-11-30
End date
2023-03-31
Keywords
Behavior
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This experiment will study how information demand is affected by the decision an individual is about to make.
External Link(s)

Registration Citation

Citation
Liang, Yucheng. 2022. "Boundedly rational information demand." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.10543-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-11-30
Intervention End Date
2023-01-31

Primary Outcomes

Primary Outcomes (end points)
Demand for information
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment varies the decision participants will make and measures their demand for information before the decision.
Experimental Design Details
Not available
Randomization Method
randomization done through Qualtrics
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
825 individuals
Sample size: planned number of observations
825 individuals
Sample size (or number of clusters) by treatment arms
D-Information treatment: 150
O-Information treatment: 150
Inconclusive good news treatment: 75
Willingness-to-pay treatment: 75
Strategy method treatment: 75
O-backs-up-D treatment: 150
D-backs-up-O treatment: 150
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Carnegie Mellon University IRB
IRB Approval Date
2022-07-12
IRB Approval Number
00000603
Analysis Plan