Archive for: Rich Rosenberg

Watching this year’s Global Microcredit Summit in Spain come to an end, I am glad to see that many in the industry are ready to face the challenges that have emerged in microfinance over the last years.  A plenary session on Tuesday morning with Anton Simanowitz from IDS, Tilman Ehrbeck of CGAP, Rosheneh Zafar from Kashf Foundation and Fabiola Cespedes from FOROLACFR was titled “Challenges to the Field and Solutions: Over-Indebtedness, Client Drop-Outs, Unethical Collection Practices, Exorbitant Interest Rates, Mission Drift, Poor Governance Structures and More.”  Read the rest of this page »

It is my privilege to close out this blog series which has been a wonderfully rich exploration of one of the most complex and consequential topics in microfinance.  I’m tempted just to sit back and say – I like what Rich wrote about the challenge of definitions and how Jessica illustrated the difficulty of drawing the line of “acceptable sacrifice” and the way Jacco laid out the responsibilities of various stakeholders. In fact, that’s largely what I propose to do, while taking up the overall theme of learning from research.

This series demonstrates the wide field of research emerging on overindebtedness. Several of the contributors to the series are the first movers who have established tentative hypotheses and tested research methodologies.  We need more such studies to inform product design and policy making. Milton is skeptical that more knowledge will lead to better outcomes, and he does have a point.  It’s quite possible that the only way to learn and take the steps necessary to produce a better outcome is to plunge a market into a crisis.  Even better, however, would be to use the results of research. Although the studies profiled here are a huge step forward, it is still early to use them for making decisions: it is not yet clear how their findings will hold up in other countries and different settings. Read the rest of this page »

Earlier this year Rich Rosenberg started this series with a blog which made the point that for most markets we simply don’t know how serious the issue of over-indebtedness is: we are flying blind in the face of a clear and present danger. What we need especially are early warning tools to identify problems.

On 17 January this year, a study* was published which presents an important first step to establish an early warning index to help prevent future over-indebtedness crises in microfinance markets. Read the rest of this page »

What has repeatedly astonished me about the discussion of over-indebtedness during the last couple of months is that people tend to treat the topic as if we only discovered it most recently.

To say so may reveal me as a microfinance dinosaur.

But didn’t we discuss over-indebtedness from every angle already back in 1998/99, when the Bolivia crisis loomed? Didn’t we conclude to strengthen information sharing significantly, to force all major players to participate and to even build in financial incentives to make MFIs take a more cautious approach? Didn’t we also set strong incentives for MFIs to transform into formal entities, with strong supervision from the superintendency and also forcing them to be as transparent as possible?

I say “we” as I have been involved as a consultant to the superintendency for many years, during which many of these steps have been implemented. Did this deliver the expected result?  It did.  That’s why the Bolivian microfinance market although certainly showing in many regions a high level of penetration does not seem to show dramatic overshooting.

What about Peru, which also has implemented all of those measures, doesn’t it show signs of over-indebtedness? If we take an elevated portfolio at risk (PAR), high rescheduling and write-off levels as indicators, I would say it does. But is there anything fundamentally wrong? No. To the contrary, all the necessary mechanisms are in place to counterbalance the risk of over indebtedness and those mechanism show results.

The basic recipe to counterbalance the risk of over indebtedness is known. It is made with the following ingredients: formalisation of MFIs, strong supervision, high financial incentives not to overshoot through strict provisioning requirements, full compulsory information sharing, broad product range with more and more individual lenders who can much more easily fine tune their reaction in case of problems and who carry out a more detailed cash flow analysis compared to group lenders, and strong supervision of internal control mechanism–to name the most essential ones.

Unfortunately, if we compare our basic recipe with the current regulation frameworks in many countries, we find that too small a number of countries use the basic ingredients described above.  Regulators, only too often influenced by politicians and sometimes lacking specific know-how or experience, cook by their own recipes. Most countries barely support the core principles of a sound financial sector development policy, which is by far the most efficient tool to at least adequately control the risk of over-indebtedness.

Moreover, there is a real danger that politicians and regulators, alarmed by media coverage of over-indebtedness, become over ambitious chefs, i.e. they undertake measures that are ineffective or outright harmful. Instead of building a regulatory framework that fosters development of the market while including elements that counterbalance overheating, instead they constrain market development. The inevitable result is reduced services, and poor people have less choice, or lose access to finance completely. The Malegam recommendations in India are a case in point.

Over-indebtedness is as old as lending itself. A growing credit market will always bring about cases of client over-indebtedness. To put consumer protection measures in place is an essential part of good practice. However, this protection must not stifle market development itself. Avoiding over-indebtedness at any price is not desirable, as the overriding goal of building inclusive financial markets will not be achieved.

Rich brought up the question in his post: “how do we know if sacrifices without loans wouldn’t have been even worse?” And – I hope I understand correctly – this is a question that has to be asked on an individual level but also on an aggregated level. Whatever the answer might be, to justify the restriction of choice for the poor would not be an acceptable outcome. Access to finance is part of people’s economic freedom. To restrict it on grounds of consumer protection and thus exclude thousands of people from the opportunities credit markets offer is patronizing the poor, not helping them.

What we can and must do is learn from past crises that have caused wide-spread over-indebtedness. We can identify the signals that appeared prior to breaking out of crises. This can help us anticipate and prevent future crises and their repercussions. An important step in this regard is the research project we have undertaken together with the University of Zurich and in partnership with Triodos and CMEF in order to develop an over-indebtedness early warning index and discuss preliminary results.

–Rochus Mommartz, responsAbility

This post is the next in the blog series on over-indebtedness. In the coming weeks we’ll be featuring a variety of voices from across the globe on this topic. We welcome your participation in this discussion through comments.

What a pleasure to see this discussion evolve – I believe that a broad discussion is what this over-indebtedness question needs. By involving everyone’s needs and concerns we will first of all learn that it is not “one” solution we are looking for. It is instead a set of responses to the various needs to understand over-indebtedness, track it with easily measurable indicators, or to determine its boundaries for legal purposes.

A sacrifice-based definition will be useless for the latter two due do its subjectivity, its cultural dependence, it’s vulnerability to dishonesty, and the amount of work required to measure it. If my interest for the time being focuses on the first, that is because I believe that a sound understanding of the concept in its abstract, hardly measurable form, is what will guide us to choose the right indicators for other purposes. The same will be true for the different perspectives of protecting customers, managing MFI portfolio risk, and improving business through customer satisfaction.

So with regards to this conceptual definition, holding up the priority of protecting clients from harm, Rich has raised an important challenge: how do we know if sacrifices without loans wouldn’t have been even worse? I hope to be able to soon share results from our empirical work in Ghana, in cooperation with the Smart Campaign and KfW: With all the downsides of subjective information, the borrowers seem again to be the best judges if difficulties are or are not related to their loans. And changes in sacrifices over time may be another indicator.

As tempting as it is, the tendency to mix the over-indebtedness question with the impact question may also be risky. Is it a loan that makes the borrower worse off that makes him over-indebted? No legal definition would ask if the loan was the origin of the borrower’s troubles. If borrowing does not cause the sacrifices but makes people more vulnerable to the shocks that they have always experienced – isn’t that important when we argue for microfinance as a form of vulnerability reduction? If it is just the lending terms (e.g. the lack of a grace period as argued in V.Rengarajan’s comment), not the amount of debt that makes the borrower struggle, is that not the type of debt problems we want to protect borrowers from?

We should not expect the over-indebtedness definition to solve the impact debate just in passing by. And testing the causal relationships in an econometrically valid way, observing how many sacrifices we can cause for people with different treatments has some serious ethical challenges. But what if each impact study, each Randomized Control Trial that was done in the future asked about the sacrifices people made before and after taking loans? How about if we included this potential downside in our standard approaches to thinking about impact? It will certainly enhance our understanding of what microfinance does and does not do for poor people and how its products and services can be improved. I am looking forward to others taking over and turning this blog series more towards the operational questions of tackling over-indebtedness and developing solutions. There are a million ways to go about it. By creating the transparency and the literacy for empowered consumers to make informed choices, we are likely to go a long way.

–Jessica Schicks

Jessica Shicks’s post in this series argues that from a consumer protection perspective–I assume that’s the most relevant perspective for development practitioners–the notion of over-indebtedness should include not just situations where the borrower can’t repay, but also situations where the borrower can repay but only at the cost of “unacceptable” sacrifices. Adrian Gonzalez made much the same point in his doctoral dissertation; likewise Beth Rhyne in a blog post a few months ago. I think that they’re right, and that it makes sense to incorporate this sacrifice dimension into a definition of over-indebtedness for research purposes.

But there’s a knotty problem here.  When we talk about “over-indebtedness,” we usually assume that it’s something that ought to happen pretty rarely if credit is being delivered responsibly.  But take Jessica’s example of a woman who is “over-indebted” in the sense that she has to go hungry in order to make a loan payment.  Suppose she goes without food for three days to pay off a loan: at first blush, this probably sounds like an unacceptable sacrifice. But further suppose that she borrowed the money in the first place to avoid going without food for three weeks.  This is a loan that resulted in over-indebtedness as we’ve defined it, even though the loan may have been a good deal for the borrower, and we’d want the same deal to be available to plenty of other borrowers if they’re in similar circumstances.

Paying off a loan is just one among many payments that poor people have to make. The fact that they’re poor implies that coming up with cash for any  purpose can be associated with serious sacrifices—someone may, for instance, have to go hungry or sell productive assets to pay school fees or medical expenses.  With this in mind, maybe we should expect  to find substantial levels of over-indebtedness (thus defined) among poor microborrowers, even if the lending is responsible.

Of course, a lot depends on how high we set the bar in defining which sacrifices are “unacceptable.”  This is really a tough one. It’s hard to argue with Jessica’s position that the answer has to come from the borrowers themselves. But like everything else about over-indebtedness, this involves complications too. Do we wind up defining over-indebtedness as loans the borrowers wish they hadn’t taken?  I’ll be very interested to see how this is operationalized in Jessica’s forthcoming paper on her Ghana research.

(Adrian Gonzalez’s dissertation avoided the question of what was “unacceptable,” and focused instead on whether a sacrifice was “unanticipated.” This may be easier to determine in a field interview, but it further weakens the link between “over-indebtedness” thus defined and a conclusion about whether the lending operation is a responsible one.)

–Rich Rosenberg

In a video-taped interview seven months ago, I expressed a degree of optimism that, historically at least, we had not been over-indebting unacceptable numbers of poor microborrowers, based on an admittedly tenuous inference from high repayment levels in most of the world. Since then, various conversations and data points have left me less comfortable with that inference.

• My guess was that most large, sophisticated MFIs had gotten pretty good at the reporting collection performance accurately. This may have been naïve: for instance, Sanjay Sinha says that recent portfolio testing by M-CRIL in a range of leading Indian MFIs revealed unsustainably high loan losses, notwithstanding published financial reports saying all was well. (Assuming this is true, is the problem data systems that still can’t do the job, or is it a deliberate pre-IPO window dressing by management?)
• But let’s assume that reports of high repayment in most markets are true. If, as many practitioners think, the preponderant motivation to repay uncollateralized loans is the borrowers’ desire to keep future access to a valued service, then high repayment would seem to suggest that few of those borrowers think that they’re getting too deeply in debt. But conversations with David Roodman, Esther Duflo, and Abhijit Banerjee have forced me to recognize that we don’t really know how much of the loan repayment is driven by other factors, including pressure from groups or loan officers. If these latter motivations are widespread, borrowers may be repaying even if they haven’t experienced their loans as helpful.
• Most importantly, microcredit markets are becoming saturated in more and more places. (This can happen at penetration levels that seem low: we microfinance enthusiasts tend to overestimate the percentage of the eligible population that will want a loan at any given time.) Gabriel Davel, South Africa’s former consumer credit regulator, observes that when competitive retail credit markets approach saturation, problems with over-indebtedness are almost inevitable: One probably shouldn’t expect microcredit to be an exception, given that few microcredit markets have good credit bureaus that allow a lender to check a loan applicant’s repayment of loans from other providers.

The point is not to assert that we have a generalized problem with over-indebted microborrowers. The point is that for most markets we simply don’t know.  We’re flying blind in the face of a clear and present danger.  Fortunately, more researchers are starting to look at levels of debt stress. But we’re still a long way from having solid, practical tools—especially early-warning tools—to identify problems.  High default levels sometimes (not always) can tell us, after the fact, that a lot of clients have gotten over-indebted. But low default levels don’t mean that everything has been OK, even if the reporting is competent and honest. Borrowers might be repaying only at the cost of unacceptable sacrifices.

The obvious question here is what “unacceptable” means. That turns out to be an annoyingly complex topic that I don’t have time to write about, and you probably don’t have the time to read about, just now. I’m sure the question will rear its head in connection with later blogs in this series.

–Rich Rosenberg

This post is the next in the blog series on over-indebtedness. In the coming weeks we’ll be featuring a variety of voices from across the globe on this topic. We welcome your participation in this discussion through comments.

Rich Rosenberg blogged yesterday about an Atlantic article that profiled John Ioannidis’s critique of medical research. The article reminded me of a meeting held in Washington a few years ago.  Consumers and producers of microfinance impact studies were brought together to discuss the research agenda.  One participant, who is not a researcher, concluded dolefully that microfinance research lags far behind medical research.

My immediate thought was that that claim was probably false: not because microfinance research is so far ahead, but because much medical research seems full of problems.  If you read beyond the newspaper headlines, it’s usual to see simple correlations between health conditions and a given diet/activity/lifestyle quickly – and falsely — assumed to be causally determined.  Sample sizes are small.  Lots of hypotheses get tested, but just a few get published.

According to Ioannidis, it doesn’t get better when you scour the academic medical literature.  The willingness to broadcast that fact has made John Ioannidis a rock star in the health statistics world.  Health researchers routinely test many, many hypotheses; often rely on small samples; and face fierce competition to get published in top journals.  One result, Ioannidis argues, is that the pressure to publish, combined with editors’ penchants for publishing striking (often counter-intuitive) results, means that a lot of results get published that wouldn’t hold up if the sample had been larger or the tests more robust.  Ioannidis’s analysis holds especially strongly in non-experimental studies (his simulations suggest that 80% of “results” from non-randomized studies are in fact wrong).  Another big result is that randomized controlled trials do much better (25% of health RCTs are wrong, according to Ioannidis).

Of course, being wrong just one-quarter of the time is no cause for celebration.  But it does point to a real strength of RCTs – which is even more true of RCTs in microfinance .

The RCTs do better because they are designed from the ground up to test a particular (and narrow) set of hypotheses.  That greatly curtails the opportunity for “fishing expeditions” and the chance that one of your 57 hypotheses happens to be statistically significant by a fluke.  The questions tend to be far more focused in the microfinance context.  Does access to microfinance increase business profit?  Business investment?  Household consumption? Those microfinance  hypotheses usually stem from a clear theoretical model and should show up in clear patterns.

That’s far different from many medical studies, in which a much greater range of plausible hypotheses exist (along with a greater range of incorrect hypotheses).  The situation persists because the specific pathways that link diet/activity/lifestyle to health conditions remain poorly understood.  So lots of stuff gets tested in the medical literature, and “effects” may emerge that pass standard levels of statistical significance but which are caused by odd outliers or other features common to small data sets – and which turn out to be wrong.

So, on this score, Ioannidis’s criticisms are far less of a concern when it comes to microfinance.  We have tighter theoretical understandings, a smaller set of hypotheses, and, usually, bigger samples.
But don’t relax completely.  Microfinance research has its own set of concerns.  Here are a few:

1) Replication.  We don’t (and can’t) replicate studies in the sense that medical researchers can.  Medical researchers replicate by trying a similar test again with a different, similar sample.  It can be a big help in determining the robustness of the initial finding, over-riding results that do not hold when repeatedly replicated. But in microfinance, to the extent that we replicate, we do it to test the same idea in very different settings. Sure, it worked in Bosnia, but will it work in East Timor?  Argentina?  What we get is a mapping of the landscape, learning how financial mechanisms work in different contexts.  That’s helpful to understand, but because contexts vary so greatly, a positive finding in one place rarely has power to knock out a negative result elsewhere.  Replication is crucial, but not for the reasons that replication is crucial in the medical context.

2) External validity.  The problem of replication above is tied to a more general problem in extrapolating from one context to another.  This is hardly a problem unique to RCTs: it is a generic problem of evaluation.  On this, researchers could do a better job of explaining who’s in their samples and how the populations relate to communities in other regions or countries.

3) But is it an interesting parameter?  When there’s a debate about RCT results, it’s usually not about whether the finding is wrong or right, but about whether it’s interesting.  Did the experimental design yield an estimate of an aspect of microfinance impact that matters most?  Researchers deserve much credit for measuring the short-term impact of new urban microfinance branches, say, but if we had magical powers we’d really like to measure the impact of established branches in more typical settings, and we’d want to see longer-term impacts.  It’s not fair to downplay the findings that we have just because we lust after an idealized (and unmeasurable) set of parameters.  Still, we need to accept that a given study might not give us everything we want to know.

The problem with imperfect studies is that you don’t know how big the bias is (but you know the bias could be really big).  RCTs have taken us a huge step forward, and promise to deliver clean estimates of various slices of microfinance impact.  In the end, the big question is not the one Ioannidis asks (are the results apt to be right or wrong?).  The big questions concern how the particular results matter to our understanding of microfinance broadly.
—- Jonathan Morduch

David Freedman in the November issue of The Atlantic  profiles John Ioannidis, one of the world’s most respected and sought-after experts on the credibility of medical research.

Ioannidis argues that much of what biomedical researchers conclude in published studies is misleading, exaggerated, and often flat-out wrong. “Gold-standard” randomized controlled trials (RCTs) are not immune: 25 percent of published RCT results are subsequently convincingly refuted. When Ioannidis narrowed the focus to the very pinnacle of the research pyramid—49 of the most highly regarded medical research findings of the past 13 years—he found the same problems.

The causes are varied and complex, including researcher bias (and sometimes even outright fraud), publication bias that highlights certain types of findings and buries others, inadequate statistical procedures, and of course financial conflicts of interest when pharmaceuticals are tested.

“Medical research is not especially plagued with wrongness,” says Freeman. “Other meta-research experts have confirmed that similar issues distort research in all fields of science, from physics to economics (where the highly regarded economists J. Bradford DeLong and Kevin Lang once showed how a remarkably consistent paucity of strong evidence in published economics studies made it unlikely that any of them were right).”

Does any of this bear on the credibility of microfinance RCTs? I could speculate about some differences.  For instance, I wouldn’t expect financial conflicts of interest to very much of a problem in current microfinance RCTs. And publication bias may be lesser; after all, a major reason that Dean Karlan and his buddies started IPA was to carry out research that academics would have a hard time getting published.

But I’m a statistical illiterate with no business opining on these issues.  Watch this space tomorrow for Jonathan Morduch’s much more informed reflections on the matter.

In an August 22 post on DevFinance Dale Adams opined that my CGAP paper on impact “dismissed” expressed demand (also called “revealed preference”) as a way to find out if microcredit helps borrowers:

“In an otherwise excellent note [thanks, Dale!], Rosenberg dismisses expressed-demand as an indicator of the usefulness of microloans: (CGAP, Focus Note No. 59, “Does Microcredit Really Help Poor People?”). This leads him to conclude that more rigorous (and costly) studies are needed to measure the benefits of microloans…. 

My first concern is with the comparison he uses to justify dismissing the votes-people-make-with-their-feet as a measure of the usefulness of loans to borrowers.   To support his claim he says that ‘…repeated use does not by itself prove that a service is benefiting users.  No one would make this argument about repeated use of heroin, for example.’  He goes on to mention that borrowers might be caught in a debt trap and seek loans to keep their heads above water.

Using comparisons, analogies, and parables can be useful (and tricky) in making a point, but equating loans to a habit-forming drug is a stretch.  Does CGAP really want to take the position that microloans are habit forming and therefore dangerous to the health of borrowers?   Even if a tiny percentage of borrowers do fall into debt traps, is it useful to extend the habit-forming analogy to cover all microborrowers? Should we think of the millions of women who take loans from the Grameen Bank as addicts?”

That’s how Dale read it. On the other hand, a May 17 New Yorker article quoted prominent researcher Esther Duflo as saying that our position was “moronic” precisely because it embraced (!) the expressed-demand argument. 

(Were Drs. Adams and Duflos both reading the same paper?) 

I thought the paper expressed a middle position. On the one hand, I used the admittedly extreme example of addictive substances to make the point (a correct one, I think) that you cannot automatically assume that repeated use means something is good for someone.  However, the whole discussion both before and after the sentences that worried Dale was a series of arguments about why we should take the revealed preferences of micro-borrowers (and especially micro-repayers) seriously as evidence that they benefit from their loans. I ended with the point (also correct, I think) that the revealed-preference arguments I was making do not conclusively settle the matter. And that therefore further research would be a good idea.

Rigorous impact studies are fairly expensive–the only on whose price tag I know was high six figures. But I find it a little hard to take this seriously as an argument against more studies.  As a percentage of the mutiple billions that donors and socially-oriented investors have already spent on microfinance, the cost of impact studies is inconsequential. Given how much we still don’t know about what kind of impact all this investment is producing, I think further research makes pretty good sense.

What’s the moral of this little story?  That impact is a really complicated topic? Or maybe just that I should work at writing more clearly?

Richard Rosenberg