A Comprehensive Analysis of the Subproportionality and Risk-Tolerance/Risk-Aversion Properties

Last registered on April 10, 2025

Pre-Trial

Trial Information

General Information

Title
A Comprehensive Analysis of the Subproportionality and Risk-Tolerance/Risk-Aversion Properties
RCT ID
AEARCTR-0015734
Initial registration date
April 03, 2025

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
April 10, 2025, 7:22 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
Caltech

Other Primary Investigator(s)

PI Affiliation
Cornell
PI Affiliation
Caltech

Additional Trial Information

Status
In development
Start date
2025-04-07
End date
2025-05-05
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project proposes to systematically study two key properties central to non-Expected Utility (EU) decisionmaking models: subproportionality and changing patterns of risk tolerance with probabilities. Subproportionality reflects evidence that when facing a choice between a relatively high probability of a moderate prize and relatively low probability of a high prize, individuals are more likely to choose the latter alternative as both probabilities are scaled down. Changing patterns of risk tolerance reflects the classic finding that in choices between a certain amount and a risky lottery, choices often appear risk tolerant at low probabilities, and risk averse at high probabilities of winning in the risky lottery. Existing evidence on these two phenomena are largely derived from separate data sets with incomplete coverage of the relevant space of parameters. This project proposes to systematically investigate the entire space to deliver a more complete empirical foundation for theories of non-EU decisionmaking.
External Link(s)

Registration Citation

Citation
Farres, Camila, Ted O'Donoghue and Charles Sprenger. 2025. "A Comprehensive Analysis of the Subproportionality and Risk-Tolerance/Risk-Aversion Properties." AEA RCT Registry. April 10. https://doi.org/10.1257/rct.15734-1.0
Experimental Details

Interventions

Intervention(s)
Decisions under uncertainty will be completed under various parameterizations for the probabilities of prizes. A total of 189 probability combinations are considered, constituting 189 different treatment conditions. Subjects will be randomly assigned to a subset of conditions (30 in total) and comparison of valuations across conditions will be conducted.
Intervention (Hidden)
See document
Intervention Start Date
2025-04-07
Intervention End Date
2025-05-05

Primary Outcomes

Primary Outcomes (end points)
Valuations of lotteries to be compared across parameter combinations (treatments)
Primary Outcomes (explanation)
See document

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experimental design establishes the relevant space of parameters for simultaneously studying subproportionality and changing risk tolerance over probabilities. 800 subjects will each complete 30 tasks at different, randomly-assigned locations in the parameter space.
Experimental Design Details
See document
Randomization Method
Randomization of parameters done by computer. Different subjects will face problems from different locations in the parameter space. Subjects are randomly assigned to complete 30 of 189 possible tasks.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
800
Sample size: planned number of observations
800*30 = 24000 total observations
Sample size (or number of clusters) by treatment arms
A total of 189 points in the parameter space are proposed leading to ~126 per location. 1/6 of observations are direct repeats, leaving ~ 105 independent observations per location. As noted above, different parameters constitute different conditions and are randomly assigned.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For evaluation differences in valuations across two locations: a MDE of around $2.75 (around 18% of expected average valuation, $15, with s.d. of 7) is calculated.
IRB

Institutional Review Boards (IRBs)

IRB Name
Caltech
IRB Approval Date
2024-09-13
IRB Approval Number
IR24-1475
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

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