Testing Referrals for Peer Screening and Influencing Repayment
Last registered on July 26, 2016

Pre-Trial

Trial Information
General Information
Title
Testing Referrals for Peer Screening and Influencing Repayment
RCT ID
AEARCTR-0000327
Initial registration date
July 26, 2016
Last updated
July 26, 2016 3:03 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Northwestern University
Other Primary Investigator(s)
PI Affiliation
London School of Economics
PI Affiliation
Dartmouth College
Additional Trial Information
Status
Completed
Start date
2008-01-01
End date
2013-04-29
Secondary IDs
Abstract
Empirical evidence on peer intermediation lags behind many years of lending practice and a large body of theory in which lenders use peers to mitigate adverse selection and moral hazard. Using a simple referral incentive mechanism under individual liability, we develop and implement a two-stage field experiment that permits separate identification of peer screening and enforcement effects. We allow for borrower heterogeneity in both ex-ante repayment type and ex-post susceptibility to social pressure. Our key contribution is how we deal with the interaction between these two sources of asymmetric information. Our method allows us to cleanly identify selection on the likelihood of repayment, selection on the susceptibility to social pressure, and loan enforcement. We estimate peer effects on loan repayment in our setting, and find no evidence of screening (albeit with an imprecisely estimated zero) and large effects on enforcement. We then discuss the potential utility and portability of the methodological innovation, for both science and for practice.
External Link(s)
Registration Citation
Citation
Bryan, Gharad, Dean Karlan and Jonathan Zinman. 2016. "Testing Referrals for Peer Screening and Influencing Repayment." AEA RCT Registry. July 26. https://www.socialscienceregistry.org/trials/327/history/9717
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Experimental Details
Interventions
Intervention(s)
1. Screening Incentive Group: Referrers in the first group received a bonus if the person they referred was approved for a loan. As a result, they had an incentive to screen for candidates who were likely to get approved for a loan based on observable characteristics.
2. Screening and Enforcement Incentive Group: Referrers in the second group received a bonus if the person they referred was approved and subsequently repaid the loan on time. They had an incentive to both screen for creditworthiness and encourage repayment.
Once the referrals were approved, researchers introduced a second stage of randomization, which changed the initial set of incentives that referrers faced.

1.a. After loan approval, no change. 1.b. After loan approval, enforcement incentive added (ie. offered an additional bonus of US$12 if the person they referred repaid the loan)

2.a. After loan approval, enforcement incentive removed, (ie. received a bonus as soon as their referee’s loan was approved.) 2.b. After loan approval, no change.
Intervention Start Date
2008-02-01
Intervention End Date
2009-07-01
Primary Outcomes
Primary Outcomes (end points)
Incentives for peer enforcement, peer selection
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Researchers partnered with Opportunity Finance South Africa to test its Refer-A-Friend program, which offered existing clients the opportunity to receive a bonus for referring a friend who met particular criteria. In order to test whether people have information about the reliability of their peers and can enforce loan repayment, referrers were randomly divided into two groups, each of which received a different set of incentives. Researchers measured screening and enforcement effects by comparing repayment performance and default rates of loans referred by people facing different incentive structures.
Experimental Design Details
Randomization Method
Randomization was done by computer at Opportunity Finance South Africa (Opportunity) who handed out referral cards.
Randomization Unit
Individual level (borrowers)
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
N/A no cluster
Sample size: planned number of observations
4,408 borrowers. Of the 4,408 cards that were handed out, 430 were returned and 245 of these referred clients were approved for a loan.
Sample size (or number of clusters) by treatment arms
(a) Penalty Interest Charged by Lender (N=245)
(b) Positive Balance Owing at Maturity (N=240)
(c) Portion of Loan Value Owing at Maturity (N=240)
(d) Loan Charged off By Lender (N=239)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
July 01, 2009, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
July 01, 2009, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
N/A, no cluster.
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
No attrition as we use administrative data.
Final Sample Size (or Number of Clusters) by Treatment Arms
(a) Penalty Interest Charged by Lender (N=245) (b) Positive Balance Owing at Maturity (N=240) (c) Portion of Loan Value Owing at Maturity (N=240) (d) Loan Charged off By Lender (N=239)
Data Publication
Data Publication
Is public data available?
Yes
Program Files
Program Files
Yes
Reports and Papers
Preliminary Reports
Relevant Papers
Abstract
Empirical evidence on peer intermediation lags behind many years of lending practice and a large body of theory in which lenders use peers to mitigate adverse selection and moral haz- ard. Using a simple referral incentive mechanism under individual liability, we develop and implement a two-stage field experiment that permits separate identification of peer screening and enforcement effects. We allow for borrower heterogeneity in both ex-ante repayment type and ex-post susceptibility to social pressure. Our key contribution is how we deal with the interaction between these two sources of asymmetric information. Our method allows us to cleanly identify selection on the likelihood of repayment, selection on the susceptibility to so- cial pressure, and loan enforcement. We estimate peer effects on loan repayment in our setting, and find no evidence of screening (albeit with an imprecisely estimated zero) and large effects on enforcement. We then discuss the potential utility and portability of the methodological innovation, for both science and for practice.
Citation
Gharad Bryan, Dean Karlan, and Jonathan Zinman. 2014. “Referrals: Peer Screening and Enforcement in a Consumer Credit Field Experiment.” American Economic Journal: Microeconomics, Forthcoming.