A Study of Payday Loan Borrower Behavior

Last registered on November 23, 2019
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Pre-Trial

Trial Information

General Information

Title
A Study of Payday Loan Borrower Behavior
RCT ID
AEARCTR-0003043
Initial registration date
October 20, 2018

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
October 22, 2018, 1:03 AM EDT

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

Last updated
November 23, 2019, 11:01 AM EST

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

Locations

Country
United States of America
Region
Indiana

Primary Investigator

Name
Hunt Allcott
Affiliation
Microsoft Research
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Other Primary Investigator(s)

PI Name
Joshua Kim
PI Affiliation
Stanford
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PI Name
Dmitry Taubinsky
PI Affiliation
Berkeley
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PI Name
Jonathan Zinman
PI Affiliation
Dartmouth College
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Additional Trial Information

Status
Completed
Start date
2018-10-22
End date
2019-07-15
Keywords
Finance & Microfinance
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
It is often argued that payday lending regulations can increase welfare, because people with self-control problems might borrow more than they expect or would like to in the long run. To test this, we ran a field experiment with a large payday lender to elicit borrowers' predictions of their future borrowing and willingness-to-pay for an incentive to avoid future borrowing. We combine the experimental results with a novel sufficient statistic-based approach to estimate a model of partially naive present focus.
External Link(s)

Registration Citation

Citation
Allcott, Hunt et al. 2019. "A Study of Payday Loan Borrower Behavior." AEA RCT Registry. November 23. https://doi.org/10.1257/rct.3043-2.2
Former Citation
Allcott, Hunt et al. 2019. "A Study of Payday Loan Borrower Behavior." AEA RCT Registry. November 23. https://www.socialscienceregistry.org/trials/3043/history/57663
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Do payday loans harm borrowers by exploiting behavioral biases? We examine whether and why borrowers fall into “debt traps” -- failing to anticipate future borrowing and its costs -- by eliciting forecasts and commitment valuations from current borrowers in partnership with a large payday lender and then tracking borrowing behavior with administrative data. Our baseline survey asks borrowers to forecast their borrowing behavior over the next several months, and also gives them incentivized between an unconditional cash transfer and one that is contingent on not taking out a loan.

Intervention Start Date
2018-10-22
Intervention End Date
2019-07-15

Primary Outcomes

Primary Outcomes (end points)
See pa
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
To avoid the possibility of experimenter demand effects, we are not disclosing further information about the study until data collection is complete.
Experimental Design Details
Do payday loans harm borrowers by exploiting behavioral biases? We examine whether and why borrowers fall into “debt traps” -- failing to anticipate future borrowing and its costs -- by eliciting forecasts and commitment valuations from current borrowers in partnership with a large payday lender and then tracking borrowing behavior with administrative data. Our baseline survey asks borrowers to forecast their borrowing behavior over the next several months, and also gives them incentivized between an unconditional cash transfer and one that is contingent on not taking out a loan.
We plan to use the data in several ways. First, we will estimate borrower forecast biases and commitment valuations. Second, we will use the randomized incentives to estimate the price elasticity of demand for payday loans. Third, we will estimate present-bias and sophistication parameters from a beta-delta model. Fourth, we plan to input those parameter estimates into a calibrated model of consumption, savings, and borrowing and use it to simulate the welfare effects of popular regulatory approaches.
Randomization Method
Randomization done by computer survey software.
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
Uncertain; depends on business conditions.
Sample size (or number of clusters) by treatment arms
Uncertain; depends on business conditions.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford Panel on Non-Medical Human Subjects
IRB Approval Date
2018-10-15
IRB Approval Number
46136
Analysis Plan

Analysis Plan Documents

Exclusion Criteria 1-22-2019

MD5: 423feeaa2bd637726067a0d5858bd3f5

SHA1: 319b2e90eb57dab94f9f659caf08dc40f80e57e2

Uploaded At: January 22, 2019

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
July 15, 2019, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
July 15, 2019, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?
No

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Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials