Financial Decision Making

Last registered on December 01, 2022

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Pre-Trial

Trial Information

General Information

Title

Financial Decision Making

RCT ID

AEARCTR-0009138

Initial registration date

April 14, 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

April 20, 2022, 7:48 AM EDT

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

Last updated

December 01, 2022, 7:57 PM EST

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

Locations

Country

United States of America

Region

Primary Investigator

Name

Elif Incekara Hafalir

Affiliation

University of Technology Sydney

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Robert Slonim

PI Affiliation

UTS-CBA

Contact Investigator

PI Name

Hanlin Lou

PI Affiliation

UTS-CBA

Contact Investigator

PI Name

Lionel Page

PI Affiliation

Contact Investigator

Additional Trial Information

Status

In development

Start date

2022-04-14

End date

2022-12-31

Keywords

Behavior

Additional Keywords

financial decision making, credit cards

JEL code(s)

D04, D14, D31

Secondary IDs

Prior work

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

Abstract

We aim to understand whether providing different types of information on credit card debt affect repayment behaviour. Specifically, we will examine the effect of reporting the minimum required payment and the effect of reporting information on the length of time and the amount of total interest accrued based on the participants' chosen credit card payment.

External Link(s)

Registration Citation

Citation

Incekara Hafalir, Elif et al. 2022. "Financial Decision Making." AEA RCT Registry. December 01. https://doi.org/10.1257/rct.9138-4.0

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Experimental Details

Interventions

Intervention(s)

Intervention is the content of the information received by the participants. Information manipulation will be in two categories: 1) minimum payment information and 2) the length of time and the amount of total interest accrued based on the payment amount chosen by the participant.

STUDY 2: We will look at varying the presentation of the information (months, interest) which will be either numerical or with graphical representation.

STUDY 3: We will look at varying a set of menu options that vary on the number of months to pay off the entire balance. They will range from 2 to 8 eight menu options. The options vary the number of additional months: 1, 2, 4, 6 or 8 options that expand each time on the number of months.
update: We used the following menu options in addition to the controls: 1m, 1m+2m+3m, 1m+2m+3m+6m+12m, 1m+2m+3m+6m+12m+24m+36m.

STUDY 4:
We will additionally test different ways of entering the payment info.

Intervention Start Date

2022-04-14

Intervention End Date

2022-12-31

Primary Outcomes

Primary Outcomes (end points)

Our outcome variables are mean repayment amounts, the likelihood of paying the minimum, the likelihood of paying the minimum and less, and the likelihood of paying the maximum.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will also look at the different options that the decision maker clicked on before coming to the final decision.

Secondary Outcomes (explanation)

Experimental Design

It is a 2x2 design with manipulation of the minimum required payment and the manipulation of the information about the length of time and the amount of interest accrued based on payment amounts.

STUDY 2:
We aim to test the effect of providing the info in graphically and numerically in payment amounts, in months to finish the debt, and the interest to be paid. This creates 8 different conditions. The main comparison we aim to make is between four conditions: (1)no graphs; (2)graphs on Payments only; (3)graphs on Months only; and (4) graphs on Interest only .

STUDY 3:
we will have two control and multiple (six) treatment layouts.
update: we have 11 conditions (see above for the details)

STUDY 4:
This will test the effect of different ways of entering the payment info on outcomes.

Experimental Design Details

Experimental design is written in detail above.

Randomization Method

Randomization is done by Qualtrics survey platform.

Randomization Unit

The unit of randomization is individuals.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

500

study 2:
800

study 3:
700
update (560)

Sample size: planned number of observations

500 study 2: 800 STUDY 3: 700 update (560) STUDY 4:

Sample size (or number of clusters) by treatment arms

125 in each condition

study 2:
100 in each cell for a total of 8 cells.

study 3:
80 in conditions of #1, #2, and #7.
40 in the rest of the conditions

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

We updated the power calculations based on the pilot data we collected. With the following inputs Effect size |ρ| = 0.2 α err prob = 0.05 Power (1-β err prob) = 0.9 We plan to collect 125 in each cell, giving us 250 in each cell in our 2x2 design experiment. we determined the sample sized in the subsequent studies similarly.

Supporting Documents and Materials

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