Photos from around Rwanda:
Tea fields near Nyungwe National Park
Decorative shields at the National Museum, Butare
I’ve seen some interestingly conflicting reports lately on the impacts of microfinance upon education. Someone directed me to one which showed that microcredit clients were more likely to pull their children out of school to do the domestic work which parents gave up in order to run their microcredit-supported businesses, but I’ve also seen another which found that the children of microcredit clients were actually more likely to be in school, as their parents could more easily pay their school fees. I can think of several different ways in which these elements of small businesses, children’s labor, and schooling could interact:
On an unrelated note, I came across a sentence I totally loved whilst rereading Understanding Poverty recently – “these essays presage what we feel is an important new trend in the economics of poverty: a willingness to take the social and psychological environment of the poor seriously.” This is probably the most fruitful interaction possible between qualitative and quantitative disciplines in the study of development – a genuine respect for the psychosocial lives of the poor.
A bit of a rant, so feel free to find the egress if that’s not what you’re here for. But: beyond the standard stereotypes (either “savage tribal wars” or “happy villagers living in harmony with nature”), there are several slightly more complex cliches about Africa that make me want to grind my teeth. In fact, one could create a taxonomy of the African Cliche (genus Africanus) as follows:
Ok, taxonomic rant finished. (Although I guess the entrepreneurius and the polisci are more stock characters than cliches.) The common thread among many of these tropes is my impatience with people who don’t make an effort to move past their Western points of reference when studying/discussing/visiting/speaking with/working with Africans. And I am saying “Africans” and not “Africa” very intentionally. There’s a large lexical difference between thinking of a place primarily in terms of the people who live there, and thinking of it almost as an anthropomorphized piece of suffering land. Consider sentences like, “Africa is unlikely to achieve the MDGs,” or “Africa suffers disproportionately from AIDS.” They don’t make any sense unless one interpolates some people in there to do the suffering, but this type of statement – endowing the continent as a whole with sentience and linguistically skipping over the people who actually live there – is usually taken at face value.
Anyway, I mention the perils of not questioning Western frames of reference not because I believe Western capitalist culture is evil, but because it’s at the least misguided and at the most dangerous to view everything in the world through the lenses of one’s own national affiliation. Misguided is assuming that Western actions are the only important actions in the world, as though non-Western political leaders or private individuals can’t impact a situation as well. (C.f. the movement for American companies to boycott Congolese minerals, which I guarantee will accomplish nothing besides making a bunch of Chinese manufacturers happy about their increased access to the mines.) Dangerous is failing to move beyond assumptions in situations where one’s actions actually may have a large impact – and where one is working in the midst of great power disparities to boot. (C.f. the assumption that structural adjustment would provide sufficient trickle-down benefits for the poor to counterbalance the loss of government-funded social services in the short run.) The fact that cross-cultural work is difficult doesn’t mean it shouldn’t be done. But cross-cultural work in the face of extremely uneven power relations demands that one actually take the time to thoroughly learn the environment in which and the demands of the people with whom one will be working, instead of resting on cliches.
Lending group sizes: Read something recently stating that repayment rates were highest among a studied selection of lending groups when the group had 14 people in it. I find this fascinating – is it something like Dunbar’s number for close friends, instead of general social connections? What I don’t totally understand is why the number would be as large as 14. It seems to me that the social pressure exerted by any one individual on others would decrease linearly with the number of group members – that is, I can put more pressure on 5 other people to repay their loans than on 14, because of my own time constraints. Or perhaps the limits on social pressure are outweighed by the implicit pressure of having 13 other examples of people successfully repaying their loans, instead of just 4? Freakonomics mentioned some research recently about the power of implicit social pressure (or sanction) in guiding behavior, with regard to people seeing examples or merely believing that a majority of others were acting in a certain way. Perhaps one could think of living up to an example (of loan repayment, in this case) as a way of earning social capital, instead of actively spending it by pressuring other group members to repay their loans.
Social determinants of lending group access: Another predictable but still interesting fact is that self-selecting lending groups are sometimes reluctant to take on members who are too poor – lacking social capital as well as financial (and isn’t that a metaphor for poverty in general?). It does make sense to view current poverty as deterministic of future entrepreneurial success, from the POV of another lending group member, but I also wonder if group members would view occasional poverty (i.e. brought on by a recent illness) differently than chronic poverty. How long does someone have to be abjectly poor before a lending group is more likely to reject them? That’s an interesting question. [NB: Can’t find citation for this, although I think it may have come from Understanding Poverty.)
Monthly vs. weekly repayment schedules: This was a wonderful study – an analysis of whether Indian MFI clients were more likely to repay their loans if they made weekly repayments, monthly repayments, or monthly repayments with weekly group meetings regardless. Repayments didn’t actually vary in a statistically significant manner across any of the three repayment schemes, although the monthly group actually had the lowest rate of missed payments according to the raw data. I say “wonderful” because this knowledge is a great step towards designing lending programs that are better suited to the variable and unpredictable incomes of the poor – it’s quite valuable to understand that time-consuming weekly repayments aren’t necessary to pressure clients into repaying, which may give them more flexibility with their repayments (and use of loans).
Just a quick note on the research on agricultural supply chains that I’m doing right now – I’m finding it fascinating that one can guess at the nutritional status of households based on their income elasticity of food expenditures. Poorer households tend to have an elasticity of demand close to one, suggesting that people who are far from getting their nutritional needs met will spend almost all additional income on food. Wealthier households in developing countries, on the other hand, are more likely to have an elasticity of close to zero, suggesting that people who are well-nourished will spend little additional income on food. Of course, it’s also been found that some wealthier households have an elasticity of caloric intake close to 0.5, hinting that as income goes up, consumption of packaged foods that are more expensive and less healthy may crowd out some cheaper and more nutritious foods. This is so cool – graphical representations of the complex social & economic realities that govern food choices.
I’ve been reading a great deal recently about the linkages between food availability, intra-household resource allocation, and nutritional status, and it’s made me wonder about time-specific determinants of resource allocation. That is, it’s clear that there are some systematic, long-term differences in allocation connected to overall education levels, overall income, and gender. What I’m curious about are short-term, potentially more idiosyncratic effects: for instance, are women more or less likely to command adequate nutrition if they fall ill? Are there differences between the amount of food received at home by, say, a young child in school (potentially also benefiting from a school lunch program) and an older child who drops out to care for younger ones or help in the fields? How much would one discount future education (for the young child) versus immediate ability to do work in that case, and how might one be able to change that calculus if it weren’t a long-term beneficial one?
The obvious connection to pro-poor financial services lies in the oft-noted social “shock” of women suddenly receiving access to credit when they previously had none, which disrupts existing allocation schemes and may result in tension or violence between women and their relatively disempowered husbands. I can think of a few specific predictors of violence or generally negative reactions in this case – a history of prior violence being the most obvious one, or a husband’s unemployment, or a cultural injunction against women handling money – but I wonder if there are other traits that could be used to predict whether men might react poorly to women’s credit, and perhaps develop plans to defuse this scenario. I’ll have to think some more about this. The intersection between culture and credit is a fraught and fascinating one.