Peer effects and women's demand for financial services in Peru

This study will develop two experiments using nudges to increase the use of financial services by Peruvian women microentrepreneurs who are currently clients of two financial institutions. The delivery channel for the messages to these clients takes advantage of peer effects which seem important for these entrepreneurs; a fictional character with characteristics that resonate with the entrepreneurs will deliver personalized communication to promote saving and use of credit.

For the trial, Whatsapp text messages and audios, based on a fictional character, will be sent to randomly-selected clients over a two-month period, while a control group will receive innocuous, placebo messages.

Primary and secondary outcome measures will be measured one month after the intervention was completed.

2024-02-26

2024-04-22

For Institution A, primary outcomes include the percentage of women who have a savings account and the amount saved.

For Institution B, primary outcome measure is the percentage of clients (also disaggregated by gender) who take out pre approved second loans.

For Institution B,

These primary outcome measures will come from administrative data from the financial institutions.

For Institution A, secondary outcome measures include: i) intention to save, ii) whether or not women have a saving target; and whether a saving plan was shared with another individual.

The secondary outcome measures for Institution A will be collected by a survey conducted at endline.
No secondary outcome measures will be examined for Institution B because there are not resources to conduct an endline survey that would allow additional outcomes to be analyzed.

The experimental design for the two financial institutions will be quite similar.

First, the sample will be stratified by region to ensure representativity across Peru.

For both financial institutions, the unit of randomization is the financial advisor. Advisors will be randomly assigned to either the treatment or control groups.

For Institution A, financial advisors organize their clients into groups ranging in size from 10 to 25 members; advisors communicate with these groups via Whatsapp. The universe of advisors eligible for the experiment will have: i) at least 20 groups of clients, and ii) a minimum of two years working for Institution A.

Given the relatively small size of groups, our strategy will be to include all members of a group in the sample; as noted above, since advisors are randomly assigned to either the treatment or control group, there is no possibility of one group of a given advisor being in the treatment group and another group from this same advisor being in the control group. (This avoids the potential of contamination of the control groups via information accidently leaked by the advisor.)

From this universe, a sample of approximately 588 financial advisors will be randomly selected to participate in the experiment. Of these, half will be randomly assigned to the treatment group and half to the control group.

For Financial Institution B, the unit of randomization is also the financial advisor. Group size is larger than in the case of Institution A. Groups may have up to 250 members, and the average group size is about 150. From the universe of financial advisors, approximately 108 will be selected to participate in the experiment, with half being randomly assigned to the treatment group and half to the control group. Given the large group size, not all group members from a given advisor will be included in the treatment or control group; this participation will be capped at 30 individuals in order to ensure the participation of a sufficiently large group of advisors.

Not available

Randomization done in office by computer.

Financial advisor (see description of experimental design above)

Yes

For Financial Institution A, there will be 588 clusters.

For Financial Institution B, there will be 108 clusters.

For Financial Institution A, there will be 10,000 observations. For Financial Institution B, there will be 16,000 observations.

For each financial institution, there will be only one treatment arm.

For Institution A, minimum detectable effect size is an absolute increase in savings of 2 percentage points, from 4% to 6% This is a 50% increase. For Institution B, minimum detectable effect size is an absolute increase in use of credit of 5 percentage points, from 50 to 55%. This is a 10% increase.