The Effects of For-Profit Microloans

In recent years, the effects of microcredit, particularly the high-interest loans offered by for-profit lenders, have been hotly debated.  New research (abstract; PDF) from Dean Karlan and two co-authors, which Karlan discussed on this blog as the project was getting underway, addresses the impacts of the for-profit loans offered by Compartamos Banco, Mexico's largest micro lender.  Their findings:

Our results suggest modest but generally positive average effects on our sample of borrowers and prospective borrowers. We make five broad inferences. First, increasing access to microcredit increases borrowing and does not crowd-out other loans. Second, loans seem to be used for both investment—in particular for expanding previously existing businesses—and risk management (through a reduction in asset fire sales). Third, there is evidence of positive average impacts on business size, reliance on/need for aid, lack of depression, trust, and female decision making. Fourth, there is little evidence of negative average impacts: the only “negative” impacts are reductions in asset purchases and temptation goods, and these results have normatively positive or neutral interpretations as well. Fifth, the positive effects are not sweeping or transformative. Although some of the AIT effects are economically large, and all of the statistically significant effects are likely large in treatment-on-the-treated terms, we find statistically significant effects on only 12 of the 35 more-ultimate outcomes we evaluate, and no positive effects on household/business income, consumption, or wealth. 

How a Microfinance Program Encouraged School Dropouts

A new working paper (abstractPDF) by Britta Augsburg, Ralph De Haas, Heike Harmgart, and Costas Meghir uses a randomized trial to assess a microcredit program in Bosnia:

[W]e randomly allocated loans to a subset of applicants considered too risky and “unreliable” to be offered loans as regular borrowers of a well established MFI [micro-finance institution] in Bosnia. Our group is poorer and generally more disadvantaged than regular borrowers. What is particularly interesting is that they have applied for the loan and thus believe they have a profitable investment opportunity; however, they were turned down. This is exactly the group we need to analyze if we are to understand whether alleviating liquidity constraints in this way can be an effective anti-poverty tool.

Hypotheses for an Impact Study on a For-Profit Microlender

Through Innovations for Poverty Action, I am co-Principal Investigator on a randomized trial of the impact of Compartamos, a for-profit microlender in Mexico. Compartamos was the first microcredit organization to go public, and at IPO time had a market capitalization of US$1.5 billion.  Needless to say, that created a lot of buzz.  Several years later, we will soon be finishing a randomized trial to measure the impact on communities in the Nogales area in northern Mexico.We will be posting our hypothesis before we do the analysis, and encourage readers to do the same, for three reasons:

A Nudge Photo Contest

What is this photo about? It came to me courtesy of Jan Chipchase, a design guru who spoke at a great meeting last week on how to help microfinance meet the needs of clients better. As an aside, the most poignant question posed at this meeting of donors, investors, policymakers and researchers on microfinance: Why oh why did it take so long for "client needs" to be the topic of conversation? And the most important question posed: How can we go beyond understanding something about client behavior and choices and translate that knowledge to scalable policies for banking to the poor?

Anyhow, I digress, back to the contest.

What Percentage of Microfinance Loans Actually Go to Business Investment?

If someone with a clipboard came up to you in the street and asked you if you secretly harbor racist views, have stolen things in the past, had unprotected sex, or some other illicit behavior, how likely would you be to tell the truth?

Probably not very. This causes havoc for any researcher who wants to study behavior that may deviate from social norms in some way. A survey technique called "list randomization" allows researchers to calculate the average response to a question in a population, without being able to identify the response of any one individual. In theory this gives people the freedom to answer truthfully, knowing that even the interviewer won't be able to tell what they answered.

This method has indeed been used to measure hidden racism and sexism among American voters, as well as all sorts of bad behavior by American teens.

In a paper, forthcoming in the Journal of Development Economics, Jonathan Zinman and I apply this approach to the question of how the poor spend their microfinance loans.