Evidence that Shocks are Managed Better with the Help of Microfinance – Freedom from Hunger Research

Let’s look for shock-coping that is improved by having access to microfinance. Shocks are the more extreme, therefore more easily observed manifestations of the consumption-smoothing capabilities, or resilience, of households. Seasonal shocks are predictable, like scarcity of food in the months before the next harvest or downturn in business activities when local households are focusing on cultivating, planting and weeding the fields. Unexpected shocks, of course, are unpredictable, like illness or death of household income-earners or natural calamity, like drought, storms or floods.

In prior posts here, I have cited the emerging theory of change for microfinance: People from poor households tap microfinance services to smooth consumption and build assets to protect against risks ahead of time and cope with shocks and economic stress events after they occur—leading to widespread poverty alleviation but not widespread poverty reduction. The emphasis in this post is on evidence of coping rather than protection, but let’s take what we can find.

First, how common are such “shocks and economic stress events”? Over the past few years, Freedom from Hunger has been collecting “impact stories” from randomly selected women clients of 10 partner microfinance providers in eight diverse countries: Benin, Burkina Faso and Mali (2 partners) in West Africa; Bolivia, Ecuador and Peru (2 partners) in the Andes; Mexico; and India. My colleague Lynne Jarrell has examined 224 unique, long-term client stories for reports of shocks and how the shocks were managed (or not). That is an average of just over 22 stories per partner provider, ranging from 12 to 35. Of these 224 stories, 44 reported experiencing a financial shock during participation spanning at least three years in the provider’s program of microfinance services (combined with health and/or business/financial education). That is just under 20 percent, or one in five clients experienced a shock (the percentage by partner ranged from 5% to 35%).

Lynne classified the shocks by type (some clients had more than one shock to report):

                    • Death of husband         4
                    • Medical expenses       26
                    • Funeral expenses         4
                    • Natural disaster            6
                    • Theft                             4
                    • Other                            3

Twenty-five of the 44 clients cushioned the shock with program savings and/or loans or some other aspect of the provider’s program of services. That is just under 57 percent who found the microfinance services valuable for dealing with major financial shocks. The distribution of types of shock managed with provider services was very similar to that for all 44 clients.

If we added in the number who were worried about a potential crisis (such as an illness that could force a client and her household to lose everything), the percentage becomes much larger than 44! That larger number would include so many who had experienced crises of various sorts prior to their participation in the program.

Let’s go below this surface view of incidence and response to shocks by looking at the detailed results from two Freedom from Hunger studies.

In the mid-1990s, Freedom from Hunger conducted two parallel randomized controlled trials (RCTs) in Ghana and Bolivia to look for impacts of village banking combined with infant/child nutrition and health education (Credit with Education). Among other dimensions of impact, these studies compared the experience during the “hungry season” of participants and non-participants in the treatment communities and residents of control communities. In Western Region of Ghana, April through June tends to be the period of more prominent food stress, and in the Altiplano of Bolivia, January through February tends to be a period of pronounced food stress. In both areas, these “hungry seasons” come just before the main harvest time for staple food crops. Household food security was measured by whether the respondent’s family had experienced a time in the last 12 months when it was necessary to eat less or less well, and if so, how long this period lasted and how their households had coped.

In Ghana, participant households exhibited a reduced vulnerability to the hungry season relative to the baseline and as compared to the two non-participant samples. The difference was quite dramatic. The percentage of participant families that had experienced a period when they had to eat less or less well during the previous 12 months was cut almost in half. However, virtually no change was evident for either non-participants in program communities or for residents in control communities. For those households that experienced a hungry season, the mean duration of this period was less than one month for participants compared to a mean of almost two months for residents in control communities.

Coping strategies were the same for all three groups. However, participants (5%) were less likely to have borrowed money (at no cost) from family or friends as compared to non-participants (22%) and residents in control communities (24%). No participants, 3% of non-participants and 6% of control residents had also taken informal loans that did have a cost (20–50% of the loan amount). Households that had experienced a “hungry season” typically ate nutritionally inferior, less expensive foods. No participants, 6% of non-participants and 8% of control residents were compelled to deal with food insecurity by selling assets: illiquid savings (jewelry and clothing) and productive assets (land and chickens, the selling of which could have undermined the long-term food and livelihood security of the family). Participants also reported using the cash savings they deposited with the program to buy food and other necessities as needed.

In Bolivia, the Credit with Education program had no significant impact on incidence or duration of the hungry season. Women in all three survey groups reported that the prior year had been a favorable one with especially good harvests. All three groups declined in the percentage of households reporting that they had experienced a period when they had to eat less or less well during the preceding 12 months. While this decline between the baseline and follow-up periods was relatively greatest at 21% for the participant sample as compared to 13% for non-participants and 17% for controls, there were no significant differences between the three groups when controlling for community. The mean duration of the hungry season in the follow-up period was also very similar—on average two months—for each of the three survey sample groups. While again the relative decline in the average length of the hungry season was greatest for participants, there was no significant difference between the years relative to non-participants or residents in control communities.

In contrast to no significant effects on the incidence and duration of a hungry season in Bolivia, the Credit with Education program did seem to affect how participants coped with these periods of difficulty. The participants were less likely to have sold off animals as a coping strategy than residents in control communities. While animals might be considered illiquid savings, they are also typically productive assets, the selling of which undermines the long-term food and livelihood security of the family. Participants were also more likely to have been able to use profits from their business than residents in control communities to help them cope. However, the availability of program loans seemed to have increased the incidence of households assuming debt (most commonly to their fellow village bank members through the process of “internal” lending) to help their family through the hungry season. While a relatively similar percentage of households in each group reported borrowing from family or friends at no cost, participants were much more likely to take a loan from their village bank, which was providing participant households with a new type of “informal” consumption-borrowing but at a cost of approximately 3.5% per month (or 5% if the loan is made from the group’s internal fund).

In sum, the evidence of impacts on incidence and duration of the hungry season was mixed, but the evidence was fairly consistent that Credit with Education helped women and their households cope with food insecurity during their hungry season. Unfortunately, the samples sizes in the three groups in both countries were too small to provide statistical power sufficient to have confidence in these results. What do the recent RCTs tell us about the effects of microfinance on incidence of shocks and how the poor cope with them? I will tackle that question in the next post.


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