Student Loan Debt and Risk Preferences on the Job Market

Last registered on June 23, 2023

Pre-Trial

Trial Information

General Information

Title
Student Loan Debt and Risk Preferences on the Job Market
RCT ID
AEARCTR-0011612
Initial registration date
June 20, 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
June 23, 2023, 5:04 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Michigan

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-11-01
End date
2023-08-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Rising concerns about the size and scope of student loan debt balances in the United States have generated interest in studying how these debt balances impact borrowers' economic decision-making after leaving school. I test how student loan debt holdings impact the ways that individuals weigh risk-related tradeoffs on the job market. I aim to determine whether the need to service fixed monthly student loan payments through a loan servicer might induce borrowers to select jobs that are more stable in terms of risk factors like layoff risk and pay variability, and whether this effect increases with the size of one’s total student loan debt holdings and their required monthly payment. I test this using a novel survey experiment on U.S. 4-year degree recipients ages 22-30. In my survey experiment, I first test respondents’ baseline risk preferences in job choice using their actual student debt levels and actual monthly required payment (if any) by providing them with menus of job choices that vary in risk and pay, and by using these job choice menu questions to iteratively narrow down their willingness to pay to avoid risk. I then induce experimental variation by providing the respondent with new hypothetical scenarios in which their student loan debt level is artificially higher (i.e., through unexpected tuition hikes while they were enrolled), where the shock size varies across participants, to test whether this changes their job preferences. I also study the likelihood with which they anticipate experiencing major life choices involving risk (buying a house, pursuing further education, investing, etc.) before and after the shock to debt level. Initial pilot results suggest that as I increase the size of the shock to total debt level by \$1,000, respondents are willing to pay \$18.50/month more to avoid a fixed increase in job layoff risk ($p=0.023$) and \$10.66/month more to avoid a fixed increase in pay variation ($p=0.003$). Respondents also report significantly lower likelihoods of making life choices that require them to bear risk when their debt level is artificially increased.
External Link(s)

Registration Citation

Citation
Abourezk-Pinkstone, Hayley. 2023. "Student Loan Debt and Risk Preferences on the Job Market." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.11612-1.0
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2022-11-01
Intervention End Date
2023-08-31

Primary Outcomes

Primary Outcomes (end points)
Observed hypothetical job choices, willingness to pay measures, risk parameters
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
I employ a stated preference survey methodology and add randomized shocks to hypothetical student loan debt balances to measure the impact of debt on job choices.
Experimental Design Details
Randomization Method
Survey treatment arm randomization (computer-generated randomization)
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 Individuals
Sample size: planned number of observations
1000 Individuals
Sample size (or number of clusters) by treatment arms
All individuals randomly assigned to one of three treatment arms (resulting in 333-334 individuals per treatment arm).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Michigan IRB-HSBS
IRB Approval Date
2022-01-27
IRB Approval Number
HUM00211542

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials