The limits of microcredit

I always thought the whole fuss over microcredit as the panacea of development, back in 2005, was a bit silly – there’s never a silver bullet for something as complex as economic development. It’s remarkable how much some people want to believe in such cure-all interventions anyway. We as a species are pretty clever, but we’re not very wise, nor are we particularly good at thinking in terms of complex systems and interactions over distance or between multiple parties. But I digress.

Sometimes I also think that people who wish to design economic empowerment programs for the poor have a poor track record of picking historical or cross-cultural examples to learn from. So many programs are erroneously predicated on fundamentally Western beliefs about social structures – say, the persistent thought in community development programs a few years that a local mayor or group of elders could accurately represent the rest of the people in a town, which seems to draw on traditions of democratic representation in local government that exist in the West, but don’t always hold true in developing countries. (Of course it does in some places, but there are plenty of counterfactual examples as well.) And yet, when it came to microfinance, so many providers seem to have made exactly the opposite mistake, and ignored the fact that in Western systems of credit, some people are outright judged too “vulnerable” (i.e. uncreditworthy) to take out a loan, for fear that they won’t be able to repay. I certainly understand that it’s hard to judge someone’s creditworthiness in a low-income situation, and microfinance does indeed benefit many people who may have been unfairly excluded from traditional credit on the basis of their existing poverty. But that’s the point: just because microfinance is “for the poor,” doesn’t mean that it’s for everyone who’s poor.

Indeed, it’s been shown that the benefits of microcredit tend to accrue to borrowers who live right around the $1-a-day poverty line – not to the poorest of the poor, such as those who are too sick or old to work, or who are somehow kept outside of the cash economy for other reasons. This may seem like a rather cruel paradox – that people who may be most in need of additional capital are least likely to benefit from a microfinance intervention – but instead I think it speaks to the fact that it’s unusual to use market-based solutions, such as microcredit, for social protection. Hence the kerfuffle about Bush’s social security investment accounts around the same time. This seems like a broader and more accurate analogy than any belief that local government must inherently be representative, and it’s interesting that the dialogue around microfinance as the best economic solution for the poor (as a unified body) seemed to miss the nuances of credit’s function in more developed economies.  (Of course this is also a generalization, as there are surely some microfinance institutions who take these things into account, but the number of academic accounts that I’ve seen of microfinance’s shortcomings suggest that there are plenty which don’t.)

Occupational categories

basketsBaskets woven by co-op members, Mayange, Rwanda

I was struck recently by the New Times‘ “good news” that the rate of non-agricultural employment in Rwanda has doubled in the last 10 years!  That is, it’s apparently gone from 5% of the population to 10%.  Kigali is such a bubble; it’s easy to forget that there are many Rwandese people who will live out their days without ever seeing a multiple-story building or a paved road.

That said, this official stat about 10% non-ag employment/90% subsistence ag seems like at best a crude measure of people’s actual livelihood strategies.  I haven’t seen a specification of how much non-ag employment is formal or informal (or even what you’d consider to be “informal” around here), and in a similar sense, I’m sure that many rural residents participate in at least some non-ag activities as part of their income-smoothing plans.  I’d love to see a better measure of this data – to get a sense of how many people are exclusively dependent on agriculture (though perhaps with different types of income-generating activities within the sector), and how many are principally dependent on ag, with a significant amount of income still coming from other activities (carpentry, say, or teaching, or day labor on other farms…).  I also know a small subset of co-op members in Nyamata who grow most of their own food, even though they make a majority of their income from basket-weaving – I wonder how they’d be classified.

Transportation infrastructure

Walking a bicycle taxi up the newly paved road

I’ve been trying diligently to imagine Nyamata as it must have been in the peri-genocidal period, and it’s an interesting thought.  I keep coming back to Hatzfeld’s research, and one of the genocidaires’ statement that the looting that was so common during the genocide allowed the impoverished farmers to go into shops in Nyamata “where farmers had never been before.”  I also keep thinking of the night when the 6 mzungus apparently bought all of the beer in Mbyo.  If the economic situation along the Kigali-Bugesera-Burundi road has picked up since it was paved last year, its baseline must have been awfully low, which offers further commentary on the poverty of the farmer-genocidaires.

Improved transportation infrastructure is obviously going to be more beneficial to people who already have the wherewithall to use it – the wealthier shopkeepers in Nyamata, I’m guessing.  The picture of pre-genocide Bugesera that Hatzfeld develops seems predicated on local production to a much greater degree than it is today, where you can find Primus & packaged foods way the hell off the main road, like in Ngeruka.  (I’m pretty sure Ngeruka is still waiting for the water pipeline to come its way.)  So transport of heavy & imported items, like bottled beer and maize flour, would be privileged.   It extends the reach of existing markets.

I suppose what I’m wondering about is its effect on the incomes of people inside and outside of Nyamata, then.  It seems reasonable that their incomes must have gone up to some degree in order to be able to afford such things; was this because of trade with Kigali, or because new markets developed with truckers and construction workers passing through town?  I’d also love to know how this affected the market access of rural Bugesera residents.  The weekly market at Nyamata strikes me as decently large; did a paved road make it easier for outlying farmers to come to town?  Or does pavement only really make a difference for people who can afford wheeled transport?  The rain here rarely makes roads totally unwalkable after it’s finished, so perhaps pavement would only be a marginal improvement for people who were just walking anyway.  Institutional memory in Rwanda seems remarkably short sometimes, in large part because of the enormous upheaval and movement in the several years following the genocide; I’m not sure that anyone in Nyamata, literally, has been there long enough to know.

Healthcare access & equity

When I was researching microinsurance and maternal mortality last year, I was struck by some of the observations that other researchers felt it necessary to include in their results.  One of them was the finding that distance to a health center affects people’s access to care.  In other news, water quenches thirst!  I had to wonder if this was a relic of the general lack of forethought that must be put into procuring transport in the global North, where it’s more or less equally simple to reach a doctor one kilometer from one’s home as thirty kilometers.  I otherwise fail to see how it’s notable that people who live farther from a clinic may use it less often.

This does highlight the fact that there are fundamental issues of healthcare access that aren’t purely microeconomic in nature.  Distance is one, but the challenge of retaining skilled doctors in a low-wage environment is a second, and difficulties in obtaining and maintaining quality equipment and medication stocks (non-counterfeit medications!) are a third.  The attitudes of healthcare workers also appeared extremely important to low-income patients, who seemed understandably sensitive about their social status, and hesitant to use centers where they would be treated disrespectfully because of their poverty.

The other thing I’ve been thinking of, however, was a little-discussed (at least in the papers that I read) corollary to the observations that microinsurance increases healthcare access, and health centers are favorably inclined towards patients who can actually pay for their care. My immediate concern upon reading these statements was, if access to microinsurance is still uneven, isn’t there a real possibility that patients who are even slightly better off will crowd out those who are too poor to afford $2-a-year insurance at all? If the resource base of health centers is fixed (and it may not be – I don’t have info on that), dramatic increases in patients covered by microinsurance could very well make the poorest of the poor even more vulnerable. I wonder how you’d best be able to test that.  I imagine you’d have to look at the effects of a growing resource base (if the increased payments are used at the local level) or the improved quality of care referenced in the last post, and sort out what effects those have on the healthcare uptake rates of the poorest.  Perhaps the question actually is, does extending microinsurance to some harm the uninsured by crowding them out, or does it improve their situation by letting them get a bit of a free ride on some improvements brought about by the insurance payments?  Interesting.


Microinsurance is one of the most fascinating and tricky types of pro-poor financial services that I’ve encountered.  The basic concept of insurance (be it for health, crops or life) is an incredibly powerful one in the face of exogenously varying incomes and the strong need for income smoothing and predictability, but it seems to suffer from the same problem as savings vs. microfinance – an existing emergency is a stronger incentive to ex-post savings than a predicted or potential emergency is to ex-ante savings.  Thus there seems to be a very real moral hazard of people joining insurance programs shortly before a planned medical expenditure or crop failure, in order to receive all of the benefits of membership without the burdensome advance saving that long-term membership would require.  Given that insurance, savings accounts, and microloans all represents systems of savings & disbursement, it seems possible to incentivize all of them similarly to promote ex-ante savings.  I wonder if there are any microinsurance agencies that pay their clients to sign up, which has been effective for encouraging regular savings accounts.

Income variability & emergency saving

Income variability is hugely important.  The salient factor about the incomes of poor people isn’t just that they’re low; it’s that they vary seasonally and daily, which makes regular payments for anything difficult.  Commitment savings devices are even better worth pursuing in this circumstance, because the combination of poverty and a variable income can be tragic when it comes to large welfare-related expenses, such as school fees or healthcare.  Pursuing “opt-in” savings strategies (such as paying people to open accounts) is a good option.   So is designing loan repayment systems with A) realistic assumptions of the timeframe of income generation, and B) flexible payment options.

In a sense, “emergency” microloans are just a more expensive form of saving for the poor.  Rather than saving in advance and earning interest, they have to save after the fact and pay interest.  The incentives of the poor (not reducing current consumption for future expenditures) and the banks (taking in interest instead of paying it out) are currently aligned on this issue, but it results in a suboptimal equilibrium.  Or, actually, I wonder how these incentives might vary between formal banks, and microfinance organizations (often non-profits) which may acquire their capital from different sources.