Retirement savings - survey experiment

Last registered on January 13, 2021

View Trial History

Pre-Trial

Trial Information

General Information

Title

Retirement savings - survey experiment

RCT ID

AEARCTR-0006995

Initial registration date

January 07, 2021

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

January 08, 2021, 11:39 AM EST

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

Last updated

January 13, 2021, 12:04 AM EST

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

Locations

Country

Australia

Region

Primary Investigator

Name

BETA Team Registration

Affiliation

Behavioural Economics Team of the Australian Government

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Jack Hodge

PI Affiliation

BETA

Contact Investigator

PI Name

Michael Bleasdale

PI Affiliation

BETA

Contact Investigator

PI Name

Harry Greenwell

PI Affiliation

BETA

Contact Investigator

Additional Trial Information

Status

In development

Start date

2021-01-07

End date

2021-01-18

Keywords

Finance & Microfinance

Additional Keywords

retirement, savings, comparison

JEL code(s)

Secondary IDs

Abstract

This study seeks to learn more about how people make choices about their retirement savings products.

External Link(s)

Registration Citation

Citation

Bleasdale, Michael et al. 2021. "Retirement savings - survey experiment." AEA RCT Registry. January 13. https://doi.org/10.1257/rct.6995-1.1

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Three varying displays of retirement savings products will be presented to participants.

Intervention Start Date

2021-01-07

Intervention End Date

2021-01-18

Primary Outcomes

Primary Outcomes (end points)

Choice of fund, Time to complete

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Choice of any fund that is not ‘poor’ performing, Choice of ‘Top’ fund, Ease Rating, Intention to switch

Secondary Outcomes (explanation)

Experimental Design

A three-arm trial, randomised at the individual level.

Experimental Design Details

The experiment will test two primary conditions: the number of categories the participants see, and the sort order of the presented funds. It will be a three-arm trial with differences in the number of categories and sort order. It will include the following groups:
a. Group A: two categories (Good and Poor performance), randomly sorted
b. Group B: three categories (Top, Fair and Poor performance), randomly sorted
c. Group C: three categories, sorted by performance category (then randomly sorted within each category)
Hypothesis 1: On average, respondents in group B will choose a higher rated fund as compared with Group A (Group A < Group B).
Hypothesis 2: On average, respondents in group C will choose a higher rated fund as compared with Group B (Group B < Group C).
Hypothesis 3: On average, respondents in group C will choose a higher rated fund as compared with Group A (Group A < Group C).
Hypothesis 4: On average, respondents in Group C will take less time to make a decision than Group B (Group B > Group C).
Hypothesis 5: On average, respondents in Group B will take less time to make a decision than Group A (Group A > Group B).
Hypothesis 6: On average, respondents in Group C will take less time to make a decision than Group A (Group A > Group C).

Randomization Method

Participants will be randomised to condition within the survey platform, with roughly equal allocation to each condition.

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

2000 individuals

Sample size: planned number of observations

2000 individuals

Sample size (or number of clusters) by treatment arms

667 individuals

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

For the power calculations we set alpha at 0.1 as we are less concerned with a false positive. The sample size is capped at approximately 2,000 participants. We conducted sensitivity analysis to find the minimum detectable effect (MDE). All analyses were conducted in RStudio (R version 4.0.2). For all hypotheses we will conduct one-sided tests. It is unlikely that changing categories or sorting will result in participants selecting a worse performing fund or taking longer to make a decision. Our calculations suggest that with N = 2000, we will have 95% power to detect an effect size of d = 0.16. For fund choice, this equates to approximately 0.3 rank change assuming a pooled standard deviation of around 3 rank scores. For time to complete, this is a difference of less than a second assuming a pooled standard deviation of around 15 seconds.

Supporting Documents and Materials

IRB