Microcredit Impacts: Evidence from a Randomized Microcredit Program Placement Experiment by Compartamos Banco

North America

Mexico

Labour Market

Microcredit

Manuela Angelucci, Dean Karlan and Jonathan Zinman

2015

Angelucci, Manuela, Dean Karlan, and Jonathan Zinman. “Microcredit Impacts: Evidence from a Randomized Microcredit Program Placement Experiment by Compartamos Banco.” American Economic Journal. Applied Economics 7.1 (2015): 151–182.
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Dataset and codes are available at the journal’s website

2016

Compartamos

April 2010-March 2012 (baseline-endline surveys)

The study aims to estimate impacts at the community level from a group lending expansion at 110 percent APR (annual percentage rate) by the largest microlender in Mexico. Compartamos Banco (Compartamos) has been both praised (for expanding access to group credit for millions of people) and criticized (for being for-profit and publicly traded, and for charging higher interest rates than similar lenders do in other countries).

Women between the ages of 18 and 60 answered yes to any of 3 questions: (i) “Do you have an economic activity or a business? This can be, for example, the sale of a product like cosmetics, clothes, or food, either through a catalog, from a physical location or from your home, or any activity for which you receive some kind of income;” (ii) “If you had money to start an economic activity or a business, would you do so in the next year?;” (iii) “If an institution were to offer you credit, would you consider taking it?”

The authors worked with Compartamos to identify an area of Mexico that it planned to enter but had not yet done so. The bank selected the north-central part of the State of Sonora, which includes Nogales, Caborca, Agua Prieta, and their surrounding towns. The study area borders Arizona to the north, and its largest city, Nogales (on the US border), has a population of roughly 200,000 people. The area contains urban, peri-urban, and rural settlements. The research team divided the study area into 250 geographic clusters, with each cluster being a unit of randomization. In rural areas, a cluster is typically a well-defined community (e.g., a municipality). In urban areas, the authors mapped clusters based on formal and informal neighborhood boundaries. We then grouped the urban clusters (each of which is located within the municipal boundaries of Nogales, Caborca, or Agua Prieta) into “superclusters” of four adjacent clusters each. Half the clusters were randomly assigned to receive direct promotion and access to Crédito Mujer, while the other half would not receive any loan promotion or access until study data collection was completed. This randomization was stratified into superclusters for urban areas and branch offices in rural areas (one of three offices had primary responsibility for each cluster).

• Fraction of 4–17-year-old children working + outcomes related to micro-entrepreneurship, income, labor supply, expenditures, social status, and subjective well-being.

RCT

Study design: the analysis uses a randomized cluster encouragement design, with randomization of access to credit assigned by neighborhood (for urban areas) or by the community (for rural areas). The sample is composed of two frames: the “panel” sample frame contains 33 clusters in the outlying areas of Nogales and has both baseline and end-line surveys, and the “endline-only” sample frame contains 205 clusters and has only endline surveys.
Sample: the sample is composed of two frames: the “panel” sample

frame contains 33 clusters in the outlying areas of Nogales and has both baseline and end-line surveys, and the “endline-only” sample frame contains 205 clusters and has only endline surveys.
Survey Instrument: Both baseline and end-line surveys were administered to potential borrowers the question detailed in “Eligibility” above. The endline survey was administered to 16,560 respondents, approximately 2–3 years after Compartamos’ entry. The authors make only limited use of the baseline survey in this paper, using it to check whether baseline characteristics are orthogonal to treatment assignment and attrition, and to control for baseline outcomes when data is available (while controlling for missing values of the baseline outcome variable).

No evidence of transformative impacts on 37 outcomes measured at a mean of 27 months post-expansion, across 6 domains: micro-entrepreneurship, income, labor supply, expenditures, social status, and subjective well-being. This includes no evidence of the impact of the program on child labor (children 4-17 years old). No strong evidence of heterogeneity when examining distributional impacts.

Child Labour

Households

Local

There is no evidence of the impact of the program on child labour (children 4-17 years old) in Mexico. No strong evidence of heterogeneity when examining distributional impacts.

No evidence of transformative impacts on 37 outcomes measured at a mean of 27 months post-expansion, across 6 domains: micro-entrepreneurship, income, labour supply, expenditures, social status, and subjective well-being.

The results come with several caveats. Many of the null intent-to-treat results have confidence intervals that include economically meaningful effect sizes, particularly if one were to scale up our intent-to-treat estimates to infer treatment-on-the-treated effects. The lack of highly precise nulls, despite the relatively large sample size (compared to many evaluations), is likely due to some combination of the modest take-up differential between treatment and control areas, heterogeneous treatment effects, and high variance and measurement error in outcomes.