Savings and consumption responses to student loan forbearance

Last registered on March 22, 2023

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Pre-Trial

Trial Information

General Information

Title

Savings and consumption responses to student loan forbearance

RCT ID

AEARCTR-0011040

Initial registration date

March 06, 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

March 21, 2023, 1:58 PM EDT

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

Last updated

March 22, 2023, 9:44 PM EDT

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

Justin Katz

Affiliation

Harvard

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

Completed

Start date

2023-03-07

End date

2023-03-22

Keywords

Behavior, Finance & Microfinance

Additional Keywords

JEL code(s)

G50, G51, D14, D91, I22, H3, H81, E21

Secondary IDs

Wharton Credibility Lab #124135

Prior work

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

Abstract

This experimental survey supplements observational analysis in the paper "Savings and consumption responses to student loan forbearance" (link attached). The survey has two purposes. First, in descriptive analysis, it investigates why borrowers with federal student debt continued to make payments a the onset of the opt-out federal student loan payment pause, even though continuing to repay is non-optimal. Second, using an experimental intervention, the survey evaluates whether framing a financial windfall as targeting people with student debt impacts student borrower debt repayment behavior.

External Link(s)

Link to paper draft for observational component of project.

Registration Citation

Citation

Katz, Justin. 2023. "Savings and consumption responses to student loan forbearance." AEA RCT Registry. March 22. https://doi.org/10.1257/rct.11040-1.1

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

See analysis plan.

Intervention Start Date

2023-03-07

Intervention End Date

2023-03-22

Primary Outcomes

Primary Outcomes (end points)

For each participant, the key dependent variables are the amount of total spending allocated towards each category in the intervention described above.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

For heterogeneity in the experiment, I will also collect the following information:
• Whether the person made payments on federal student debt after the federal student loan pause began in March 2020.
• Answers to a financial sophistication instrument. I describe a scenario where participants have two credit cards with interest-bearing balances. One card has a lower balance but higher APR, and the other card has a higher balance but a lower APR. I then ask participants how they would allocate a fixed budget towards repaying each card. I classify borrowers as “making a financial mistake” if they put any of their budget towards the low APR card.

Finally, I will collect demographic information on age, household income, and amount of debt in various categories.

In addition to running the experiment described above, I will also analyze data on whether and why borrowers continued to make payments on their federal student debt after the start of the federal student loan forbearance program. I also include questions to evaluate borrower familiarity with program terms, and subjective explanations for behavior that is not optimal from the perspective of standard lifecycle savings and consumption models.

I will conduct two types of analysis with this additional data. First, I will examine program familiarity, how stimulus checks were spent, and performance on the financial sophistication instrument, splitting the sample based on whether or not borrowers with federal student debt continued to make payments once forbearance began. Second, I will report subjective justifications for continuing to make federal student loan payments after forbearance, as well as subjective justifications for non-optimal behavior, for borrowers who continued to make federal student loan payments after forbearance began.

This analysis is descriptive, so I will not pre-register any specific hypotheses.

Secondary Outcomes (explanation)

Experimental Design

See analysis plan.

Experimental Design Details

There are four treatment groups: (all US households, households with student debt) x (0% interest rate, 7% interest rate). Participants will be assigned to one of these four experimental conditions.

Randomization Method

I will rely on randomization software in the Qualtrics survey platform. Randomization will aim for an equal number of people in each treatment group.

Randomization Unit

Randomization is at the person level. Treatment is not clustered.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

800 people.

Sample size: planned number of observations

800 observations.

Sample size (or number of clusters) by treatment arms

200 people in each treatment condition.

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

I conducted power calculations for versions 1-3 for two outcomes without controls: (i) fraction spent on student loans; and (ii) fraction spent on total spending. Standard deviations are based on pilot results and results in Coibion, Gorodnichenko and Weber (2020). Versions 1 and 2: • Fraction spent on student loan differences: o With control group mean of 0.08 and standard deviation of 0.28, >80% power to detect effects of >6pp. • Fraction spent on total spending: More uncertainty over standard deviations, so conduct sensitivity. o Optimistic case: Control group mean of 0.24, standard deviation of 0.28, >80% power to detect effects of >6pp. o Pessimistic case: Control group mean of 0.24, standard deviation of 0.4, >80% power to detect effects of >8pp. Version 3: • Fraction spent on student loan differences: o With control group mean of 0.08 and standard deviation of 0.28, >80% power to detect effects of >8pp. • Fraction spent on total spending: o Optimistic case: Control group mean of 0.24, standard deviation of 0.28, >80% power to detect effects of >8pp. o Pessimistic case: Control group mean of 0.24, standard deviation of 0.4, >80% power to detect effects of >12pp.

Supporting Documents and Materials

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