Is it time to write off group loans?
October 1, 2012 | 6 min read
The ability of microcredit to combat poverty remains hotly debated. After years of rapid growth, various microfinance institutions (MFIs) are currently struggling with repayment problems and, in some cases, a political backlash. Skepticism has been further fuelled by several randomized field experiments which show that the capacity of microcredit to lift people out of poverty might be smaller than previously thought. In a nutshell, the evidence suggests that microcredit may reduce liquidity constraints, help families cope with shocks, and encourage entrepreneurship. The ultimate impact on poverty indicators such as income and consumption nevertheless remains ambiguous. Impacts on health and education are difficult to substantiate too.
Learning about the impact of microcredit is also important because the microfinance industry itself is changing. A number of leading MFIs have moved from joint-liability lending, as pioneered by Grameen bank in the 1970s, to individual lending. Under joint liability, small groups of borrowers are responsible for the repayment of each other’s loans. Group members are treated as being in default when at least one of them does not repay and all members are denied subsequent loans. Group lending often involves committing to repayment meetings and can exploit social pressure, making it onerous for borrowers. This is a key reason why MFIs are moving from joint to individual lending.
Somewhat surprisingly, there exists very limited evidence on the relative merits of individual and group lending in terms of borrower impact. Armendáriz and Morduch (2005, p. 101-102)[1] note that: “In a perfect world, empirical researchers would be able to directly compare situations under group-lending contracts with comparable situations under traditional banking contracts. (…). The best evidence would come from well-designed deliberate experiments in which loan contracts are varied but everything else is kept the same.” The working paper “Group lending or individual lending?” (Attanasio, Augsburg et al., 2011)[2] also discusses such evidence.
The experiment
Mongolia is the most sparsely populated country in the world and this makes disbursing, monitoring, and collecting small loans very costly. The aim of our experiment, conducted in cooperation with Mongolia’s XacBank, was to analyze whether group lending can be an effective and efficient way to lend. Mongolian microcredit has traditionally been provided as individual loans, reflecting concerns that the nomadic lifestyle of indigenous Mongolians had impeded the buildup of social capital.
Our experiment took place in 40 villages. XacBank was interested in expanding access to poor and female borrowers, an underserved market segment. A total of 1,148 women from the poorest parts of the population participated and a detailed face-to-face survey was administered to each of them during March-April 2008. We measured variables that reflect households’ living standards and that could in principle be affected by the intervention during a 1.5 year interval: income, consumption, and savings; entrepreneurial activity and labor supply; asset ownership and debt; and informal transfers. After the baseline survey, we randomized at the village level: women in 15 villages received access to individual loans, to group loans in another 15 villages, while in 10 control villages XacBank did not lend to the women during the experiment. The randomization removed selection bias, allowing us to attribute post-treatment differences in outcomes to the two lending programs.
The ‘treatment period’ during which XacBank disbursed loans lasted 1.5 years — from April 2008 to September 2009 — with some variation across villages. During this period, 57 (50) per cent of the respondents in the group (individual) lending villages borrowed from XacBank. The probability of receiving a microloan during the experiment was 24 percentage points higher in treatment than in control villages. In October-November 2009 we conducted a follow-up survey to measure the poverty status and economic activity of all women again. We use the data of both survey rounds to measure the impact of the programs on poverty by comparing all women who initially signed up in treatment villages, irrespective of whether they borrowed or not, with those who signed up in control villages.
Group lending versus individual lending: similarities…
Although XacBank’s loans were intended to finance business creation; about half of all credit was used for household rather than business purposes in both the group- and individual-lending villages. For instance, we find that at the end of the experiment the probability of owning a VCR or radio was 17 and 14 per cent higher in the group- and individual-lending villages, respectively (compared to control villages). For large household appliances the corresponding figures are 9 and 7 per cent.
A second finding that holds for both treatment programs is that women with lower education seem to benefit more. We take education as a proxy for long-term poverty, more reliable than a wealth indicator as it is easier to measure and more stable over time. The results suggest that it is the poorer part of the targeted population that benefits most from microcredit, regardless of how it is delivered. Third, we find no differences in repayment behavior between both lending programs. Giné and Karlan (2009)[3] also compare repayment rates between group and individual lending — both with mandatory weekly repayment meetings — and find no significant differences. In our case neither loan program included mandatory repayment meetings.
… and differences
We also find important differences between the impact of group and individual loans, to suggest that the former were more effective. For group loans we find a positive impact on female entrepreneurship, one of the main intermediate objectives of the programs. This is largely driven by less-educated women who at the end of the experiment had a 29 per cent higher chance of operating a business compared to similar women in control villages. This difference is 10 per cent for highly educated women. Enterprise profits increase over time as well.
Did increased entrepreneurial activity feed through to improved household well-being? To answer this question we use detailed information on household consumption elicited in the surveys. We find a significant and robust increase, relative to control villages, in food consumption in group-lending villages.Access to group loans led to more and healthier food consumption, in particular of fresh items such as fruit, vegetables and dairy products. Total food consumption was 17 percentage points higher. Over time we also see an increase in the use of combustibles and felt for the isolation of gers — traditional Mongolian felt tents — as well as other non-durable and total consumption.
Our findings for individual lending suggest that this form of lending was simply not as effective. We find no impact on female entrepreneurship or on consumption, not even with increased exposure to credit. We do find, however, that over time there is an increase in the probability that women operate a business jointly with their spouse — and that these joint enterprises gradually also become more profitable. Nevertheless, it is not clear whether these longer-term effects translate in the same way into higher consumption as they do for group borrowers. We find no evidence that food consumption goes up with exposure in individual-lending villages.
There is at this stage no evidence of changes in income as a result of either of the programs, though it may simply be too early to observe such effects. The more sustained and more generalized increase in consumption in group-lending villages seems to indicate that these loans are more effective at increasing permanent income. Why?
One possibility is that joint-liability ensures better discipline. Group discipline may not only prevent the selection of overly risky investment projects, it may also ensure that a substantial part of the loans is actually invested in the first place. We document results on informal transfers that seem to support this hypothesis: women in group-lending villages decrease their transfer activities with families and friends, the opposite to what we find in individual-lending villages. This could reflect that groups replace some of their informal financial networks but further analysis is needed to explore this.
Our weaker results for individual loans may also reflect that borrowing at baseline (i.e. pre-program) was somewhat higher in individual compared to group-lending villages. Moreover, since group-lending was an innovation in Mongolia, the unmet demand for this product — and its marginal impact — may have been larger. Loan take-up was indeed higher in group-lending villages. This could indicate that some women, in particular the less-educated, had not been comfortable with borrowing alone but were willing to borrow as part of a group. This would imply that group and individual lending are complementary services for which the demand differs across borrower types. The process of liability individualization by MFIs may therefore run the risk that certain borrowers, those who are not able or willing to borrow on their own, may gradually lose access to finance. It is too early to write off group lending just yet.
References
- Armendáriz,B., and J. Morduch. “The Economics of Microfinance.” MIT Press, (2005).
- Attanasio, Orazio, Britta Augsburg, Ralph De Haas, Emla Fitzsimons, and Heike Harmgart. “Group lending or individual lending? Evidence from a randomised field experiment in Mongolia.” ERDB Working Paper No.136, (2011).
- Giné, Xavier, and Dean S. Karlan. “Group Versus Individual Liability: Long Term Evidence from Philippine Microcredit Lending Groups.” SSRN eLibrary (May 20, 2009).
This article may be reproduced according to our terms of use with attribution (and link, if online) to www.tias.edu. To be cited as: “Is it time to write off group loans?”, Ralph De Haas, www.tias.edu, October 1, 2012.
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Author(s)
Ralph de Haas
Deputy Director of Research, ERDB