An Axiomatic Test for Regret and Salience Theory

Last registered on July 19, 2023

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Pre-Trial

Trial Information

General Information

Title

An Axiomatic Test for Regret and Salience Test

RCT ID

AEARCTR-0011753

Initial registration date

July 12, 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 19, 2023, 2:04 PM EDT

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

Locations

Country

United States of America

Region

California

Primary Investigator

Name

Songyu He

Affiliation

Royal Holloway, University of London

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2023-07-12

End date

2023-10-31

Keywords

Behavior

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Salience and regret theory are two influential models in economics that capture the impact of correlations between risky choices on individuals’ decisions. In this project, I provide axiomatizations of both theories and conduct a novel experiment to test these axioms.

External Link(s)

Registration Citation

Citation

He, Songyu. 2023. "An Axiomatic Test for Regret and Salience Test." AEA RCT Registry. July 19. https://doi.org/10.1257/rct.11753-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention (Hidden)

Intervention Start Date

2023-07-12

Intervention End Date

2023-10-31

Primary Outcomes

Primary Outcomes (end points)

Measures of choices between two correlated lotteries under different correlations; Measures of choice patterns over small and large outcome differences.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

The proposed experiment last approximately 70 minutes, and it is both a within-subjects and between-subjects design aimed at testing the axioms provided in the study. Subjects will face a total of 28 tasks. Each task requires subjects to make some decisions, and each decision always ask subjects to make a choice between two monetary lotteries. These tasks are designed according to the new axiomatic foundation provided in this project. Subjects complete every task in a laptop provided by EconLab.
In decisions of each task, subjects will be asked to choose between option A and B. In decisions of task 1-6, each option has two possible payments with equal probability. In decisions of task 6-12, each option has four possible payments with equal probability. In decisions of task 12-24, each option has identical possible payments which has different probabilities. Subjects make their decision by clicking ratio buttons shown on the screen.
Data Collection and Analysis:
The experiment is conducted using OTree (Chen et al. 2016), which records subjects’ choices once they make their decision. To protect subjects’ information, upon subjects’ arrival at EconLab, arbitrary numbers will be assigned to them. Through this study, we link this arbitrary participate number with their choices in each task. For instance, if a subject is assigned with number 2, we identify the corresponding choices as decisions of subject 2. Therefore, no private/identifiable information is recorded in this experiment. This study uses these decisions to test the validity of correlation-sensitive preferences.
Compensation Design:
Subjects will be compensated for their participation in two ways. First, all subjects will receive a participation payment of $5. Second, subjects, will be additionally paid their earnings from one decision in one of their tasks. This provides an additional opportunity to earn money. Depending on subject choices, the chosen decision may involve risk. If subject’s chosen decision involves risk, she will be paid according to a randomly picked ball that marked the corresponding event from an urn. Their maximum payments from tasks could be up to $30. Depending on the task that gets chosen for payment, the lowest expected additional payment for a subject who chooses according to expected value is $7.5. The highest expected payment for a subject who chooses according to expected value is $22. Subjects who are very risk averse can ensure they will receive additional earnings with at least 75% chance.

No further information, including questionaries and surveys, will be collected. Subjects will not be audiotaped or videotaped for this study.
All data collected will be used in this study only.
No preliminary studies have been conducted.

Experimental Design Details

Randomization Method

By computer in background code.

Randomization Unit

200 subjects

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

200 subjects

Sample size: planned number of observations

200 subjects

Sample size (or number of clusters) by treatment arms

For within-subject analysis, 200 subjects.
For between-subject analysis: 100 subjects control, 100 subjects with probability and/or correlation manipulations.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

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