x

We are happy to announce that all trial registrations will now be issued DOIs (digital object identifiers). For more information, see here.
Measuring Trust in Peruvian Shantytowns
Last registered on July 26, 2016

Pre-Trial

Trial Information
General Information
Title
Measuring Trust in Peruvian Shantytowns
RCT ID
AEARCTR-0001240
Initial registration date
July 26, 2016
Last updated
July 26, 2016 2:56 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Northwestern University
Other Primary Investigator(s)
PI Affiliation
Microsoft
PI Affiliation
University of Michigan
PI Affiliation
Central European University
Additional Trial Information
Status
Completed
Start date
2005-01-01
End date
2005-12-31
Secondary IDs
Abstract
This paper uses a microfinance field experiment in two Lima shantytowns to measure the relative importance of social networks and prices for borrowing. Our design randomizes the interest rate on loans provided by a microfinance agency, as a function of the social distance between the borrower and the cosigner. This design effectively varies the relative price (interest rate differential) of having a direct friend versus an indirect friend as a cosigner. After loans are processed, a second randomization relieves some cosigners from their responsibility. These experiments yield three main results. (1) As emphasized by sociologists, connections are highly valuable: having a friend cosigner is equivalent to 18 per cent of the face value of a 6-month loan. (2) While networks are important, agents do respond to price incentives and switch to a non-friend cosigner when the interest differential is large. (3) Relieving responsibility of the cosigner reduces repayment for direct friends but has no effect otherwise, suggesting that different social mechanisms operate between friends and strangers: Non-friends cosign known high types, while friends also accept low types because of social collateral or altruism.
Registration Citation
Citation
Karlan, Dean et al. 2016. "Measuring Trust in Peruvian Shantytowns." AEA RCT Registry. July 26. https://doi.org/10.1257/rct.1240-1.0.
Former Citation
Karlan, Dean et al. 2016. "Measuring Trust in Peruvian Shantytowns." AEA RCT Registry. July 26. https://www.socialscienceregistry.org/trials/1240/history/9678.
Sponsors & Partners

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information
Experimental Details
Interventions
Intervention(s)
In collaboration with PRISMA, a Peruvian NGO offering credit through village banks, we designed and implemented a new loan product to measure the relative importance of social networks and prices for borrowing. Diverging from the traditional group lending model, this program sought to use social connections to screen for responsible clients. We required new clients to match up with sponsors who were already bank clients in order to obtain a loan.

Social network surveys conducted in the communities before the implementation of the loan program allowed us to map the relationships between clients and sponsors. Existing communal bank members acted as a pool of potential sponsors who could cosign small, individual loans for residents of the community who were not already bank members. The sponsor was responsible for repaying a loan if the client defaulted, and thus they were incentivized to cosign with more responsible individuals whom they could easily monitor. Each adult household member in the village received a card, which outlined the rules of the program and included a list of all sponsors in the community as well as a map of the community showing sponsor location. Both spouses of a sponsoring household and a borrowing household had to act as co-signers.

We choose an interest rate randomization, which is geared to estimate the tradeoff between choosing a socially close sponsor and a more distant sponsor with lower interest rate. Every client is randomly assigned one of 4 ‘slopes’: slope 1 decreases the interest rate by 0.125 percent per month for a 1-step increase in social distance. Slopes 2 to 4 imply 0.25, 0.5 and 0.75 decrements. Therefore, close friends generally provide the highest interest rate and distant acquaintances the lowest, but the decrease depends on the slope.
Intervention Start Date
2005-01-01
Intervention End Date
2005-12-31
Primary Outcomes
Primary Outcomes (end points)
- Having a friend cosigner (binary variable)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Our micro-finance program was implemented in communities that are as self-contained as possible. Since we implemented the program in Lima, which is a city of almost 8 million people we chose identifiable neighborhoods with about 250 to 300 households and a community leadership that helps to organize the community and represent it in front of municipal authorities. For example, in both communities the leadership had lobbied for the construction of running water lines.

The survey work was implemented in two rounds. The first round (Baseline I) was a household level census of the community. The most important aspect of the survey was the collection of a list of all household members, but it also included basic socioeconomic indicators, information on leaders in the community, detailed income and occupation information, information on household assets, and information on household businesses. The community roster, or list of people living in the community, was derived from this survey.

The second round of survey work (Baseline II) was implemented in two modules. Module A was a household level survey that collected information about contacts the family had had in the community before moving there, and savings and loans held by family members. Module B was an individual level social network survey, which was conducted with both the head of household and his or her spouse. It asked respondents to name the people in the community outside of their home that they spent the most time with and who they trusted the most. Respondents were also asked to name family members who lived in the community but not in their household, and list people with whom they were members of Roscas and village banks. For each link we inquired whether respondents had borrowed money or objects from that contact or lent money or objects to that contact. We also asked a number of hypothetical questions, such as “Would you leave this person in charge of your home?”, “Would you ask this person to assist in the construction of your home?”, “Would you start a business with this person?” Baseline II surveys were done with sponsor households, any household they had named as well as any household those households had named. Clients of our loan program who had not received a baseline II survey were surveyed after the start of the loan program.

About 25 sponsors were recruited based on their responses to Baseline I. An attempt was made to identify sponsors that had been named as community leaders and who were in the top half of the socioeconomic spectrum, but some interested people who did not fit these characteristics were accepted. Sponsors were evaluated by a credit officer and were assigned a credit line based on their capacity to pay. They were allowed to use 30 percent of this credit line for personal loans or loans to other members of their household at a preferential interest rate. They participated in a training session held by the credit officer, explaining the program, how to sponsor clients, and what to look for in responsible clients. Each sponsor was told that they would participate in three lotteries over the course of the first six months of the program as an incentive for sponsoring loans. The number of points that they received was based both on the number of loans that they had sponsored and the percentage of their credit line that they had used sponsoring.

The loan program was advertised to community members through a door-to-door promotion. Each household received a customized laminated card explaining the program and listing all the sponsors and the interest rate at which the client could take out a loan if that sponsor agreed to co-sign the client’s loan. The back of the card contained a map of the community indicating the homes of all the sponsors to make it easy for clients to find the sponsors. An effort was made to explain the program personally to someone in each household but if no one was found at home after two or three visits, the card was left under the door. The same cards were distributed again in both communities three months after the initial promotion to remind community members of the program.

The credit officer made weekly visits to each community at a pre-specified time and location. Those who wanted a loan would go to the meeting with their sponsor to verify his or her willingness to co-sign the loan contract. Loan information was then collected through a Pocket PC, which assigned the correct interest rate based on the selected client/sponsor pair. Both the client and the sponsor returned to the meeting the next week and the credit officer handed out the check and both signed the contract. Both the client and the sponsor were given a copy of the payment schedule. If the loan had been assigned 50 percent sponsor responsibility, the sponsor and client would both later receive letters informing them that the sponsor was legally responsible for only half of the loan she had sponsored.

All loans were taken out for periods of six months with both capital and interest paid every month. The payments were made at a local bank, a 10 to 15 minute distance from the communities. Sponsors had initial responsibility for controlling default and ensuring that payments were made on time. If clients were more than a month late in their payments they would receive letters at their homes and the credit officer would visit the sponsors and eventually the clients themselves. Recuperation procedures were somewhat complicated by cumbersome record-keeping procedures of the NGO.
Experimental Design Details
Randomization Method
randomization done in office by a computer
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
299 households
Sample size: planned number of observations
299 households
Sample size (or number of clusters) by treatment arms
it's complicated
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
December 31, 2005, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
December 31, 2005, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
299 households
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
299 households
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers
Abstract
This paper uses a microfinance field experiment in two Lima shantytowns to measure the relative importance of social networks and prices for borrowing. Our design randomizes the interest rate on loans provided by a microfinance agency, as a function of the social distance between the borrower and the cosigner. This design effectively varies the relative price (interest rate differential) of having a direct friend versus an indirect friend as a cosigner. After loans are processed, a second randomization relieves some cosigners from their responsibility. These experiments yield three main results. (1) As emphasized by sociologists, connections are highly valuable: having a friend cosigner is equivalent to 18 per cent of the face value of a 6-month loan. (2) While networks are important, agents do respond to price incentives and switch to a non-friend cosigner when the interest differential is large. (3) Relieving responsibility of the cosigner reduces repayment for direct friends but has no effect otherwise, suggesting that different social mechanisms operate between friends and strangers: Non-friends cosign known high types, while friends also accept low types because of social collateral or altruism.
Citation
Karlan, Dean, Markus Mobius, Tanya Rosenblat, and Adam Szeidl. "Measuring Trust in Peruvian Shantytowns." Working Paper, Yale University, July 2009.