Memory and Anticipation

Last registered on May 13, 2024
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Pre-Trial

Trial Information

General Information

Title
Memory and Anticipation
RCT ID
AEARCTR-0013581
Initial registration date
May 09, 2024

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
May 13, 2024, 12:37 PM EDT

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region

Primary Investigator

Name
Vivek Roy-Chowdhury
Affiliation
University of Cambridge
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2024-05-02
End date
2024-05-14
Keywords
Behavior
Additional Keywords
JEL code(s)
D83
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We explore the role of memory in maintaining optimistic beliefs about the payoff consequences of past choices, consistent with models of anticipatory utility and optimal expectations. We do so in a setting designed to generate anticipatory motives: participants never learn the true consequences of their choices and can therefore distort their beliefs indefinitely. Relative to previous work, we use a design where the causal impact of the payoff-relevance of information is clearly identified: across treatment conditions, we manipulate the relationship between a signal and payoffs without affecting the objective distribution of the signal.
External Link(s)

Registration Citation

Citation
Roy-Chowdhury, Vivek. 2024. "Memory and Anticipation." AEA RCT Registry. May 13. https://doi.org/10.1257/rct.13581-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-05-02
Intervention End Date
2024-05-14

Primary Outcomes

Primary Outcomes (end points)
Beliefs on signal in sessions 1 and 2
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment is split into two sessions, taking place a week apart. Subjects are randomised into two equally sized groups, Treatment and Control. Anticipatory motives to distort beliefs only exist in Treatment: the signal x is generated by the same objective distribution in both treatments but is only relevant to payoffs in Treatment. Since we are interested in the role of anticipatory motives, the challenge is to design an object of beliefs that may be relevant to utility but could remain uncertain indefinitely, maximising the potential for anticipatory motives. We opt to design x such that its only relevance is for to the consequences of subjects' choices for payoffs to a third party they are encouraged to care about.
The essential point is that at the beginning of session 1, subjects in Treatment choose whether to complete a task in session 2 to potentially increase the payment made to an assigned partner in Control. To introduce a guilt motive as well as a possible fairness one, they are informed that their partner will have to complete mandatory tasks in session 2 and receive a lower payment by default, as well as finding out what the subject chose and whether a payment was (or could have been) made.
The full belief treatment is only implemented for those who choose to do the tasks. It is revealed to these subjects that x is directly proportional to the probability p that the payment was made. Since we also measure beliefs on x for other participants, where x has no payoff-relevance (but belief accuracy is incentivised in the same way), our key analysis is of whether the payoff-relevance of x in Treatment causes beliefs to be initially distorted, and whether this distortion changes over time due to memory.
Experimental Design Details
Randomization Method
In JavaScript during survey and R (for participant pairing)
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 individuals
Sample size: planned number of observations
1000 individuals
Sample size (or number of clusters) by treatment arms
50:50 Control:Treatment
50:50 Reveal:NoReveal (within Treatment)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Director of Research, Faculty of Economics, University of Cambridge
IRB Approval Date
2024-05-07
IRB Approval Number
N/A
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