A Psychological Account of Co-Holding: Why Some Choose to Simultaneously Borrow and Save

Last registered on August 10, 2020

View Trial History

Pre-Trial

Trial Information

General Information

Title

The Co-Holding Puzzle: Why Hold Onto High-Interest Credit When You Have the Savings?

RCT ID

AEARCTR-0005751

Initial registration date

April 22, 2020

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 24, 2020, 3:06 PM EDT

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

Last updated

August 10, 2020, 11:17 AM EDT

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

Locations

Country

Australia

Region

Primary Investigator

Name

Jessica Min

Affiliation

Princeton

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Rafael Batista

PI Affiliation

University of Chicago

Contact Investigator

PI Name

Abigail Sussman

PI Affiliation

University of Chicago

Contact Investigator

PI Name

Neale Mahoney

PI Affiliation

University of Chicago

Contact Investigator

Additional Trial Information

Status

On going

Start date

2019-02-01

End date

2021-01-31

Keywords

Finance & Microfinance

Additional Keywords

behavioral, consumer finance

JEL code(s)

Secondary IDs

Abstract

We seek to understand why individuals “co-hold” high levels of high-interest credit card debt and low-yielding liquid savings, by running a randomized controlled trial (RCT).

External Link(s)

Registration Citation

Citation

Batista, Rafael et al. 2020. "The Co-Holding Puzzle: Why Hold Onto High-Interest Credit When You Have the Savings?." AEA RCT Registry. August 10. https://doi.org/10.1257/rct.5751-1.3

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2020-02-01

Intervention End Date

2020-03-31

Primary Outcomes

Primary Outcomes (end points)

Credit card repayment amount

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

1. Engagement domain:
a. Indicator for saw T1
b. Indicator for interacted with T1
c. Indicator for saw T2
d. Indicator for interacted with T2
2. Credit card repayment domain:
a. Indictor for repaid more than pre-intervention 3-month average
b. Indicator for repaid more than minimum due
c. Indicator for repaid the full amount due
3. Credit card borrowing domain
a. Revolving balance
b. Indicator for balance higher than pre-intervention 3-month average
c. Interest charges
4. Savings domain
a. Savings balance
b. Indicator for balance higher than pre-intervention 3-month average
c. Interest earnings
5. Net financial benefit domain
a. Net interest (savings interest earnings – credit card interest charges)

Secondary Outcomes (explanation)

Experimental Design

We run a randomized controlled trial, messaging people who have revolving credit card debt incurring interest and who have savings over a extended time period. We randomize individuals into one control and two treatment groups. The control group receive no messaging. The first treatment group is shown a message to inform them about their available funds. The second treatment group is shown a message with informs them of their available funds, as well as making salient the cost of co-holding.

Experimental Design Details

Randomization Method

Randomization by app

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Sample size: planned number of observations

125,328 individuals

Sample size (or number of clusters) by treatment arms

41,776 in control, 41,776 in treatment 1, 41,776 in treatment 2.

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

We conducted power analysis to determine minimum detectable effects (MDEs) with α=0.05 and power of 1-β=0.80. We assume the control group sample size is 41,776 and the treatment group is 83,552, pooling together treatment 1 and 2. We run a two-tailed comparison of means, assuming control and treatment groups have the same standard deviations. Based on the analysis, the minimum detectable effect size of credit card repayment amount is $39 on a base of $1,361, or 3% of the mean, and standard deviation of $2,312. Section 4.3 of the pre-analysis plan describes the power analysis in further detail, and table 1 of the pre-analysis plan reports the minimum effect sizes for primary and secondary outcomes. We note when we account for multiple testing, adjusted p-values for a given effect size are roughly twice as large as unadjusted p-values. Any adjustments are made within outcome variable domains (outlined in section 3.3).

Supporting Documents and Materials

IRB