Viewing all posts with tag: Savings  

Week of December 6, 2019

1. Trends: Futurism has always come more easily to technologists than policy wonks (probably because it’s easier). But big gatherings are a good chance to look ahead to how the whole inclusive finance ecosystem, getting more complex each year, will evolve. e-MFP’s annual survey of financial inclusion trends – the Financial Inclusion Compass 2019 – was launched during EMW2019, and tries to do just this. If there were a single theme to this paper, it’s the disconnect between, on the one hand, individual stakeholders with their own interests and objectives, and on the other a collective confusion, a ‘soul-searching’ of sorts, for financial inclusion’s purpose amidst the panoply of initiatives and indicators in a sector of now bewildering complexity.

Digital transformation of institutions ranked top, a theme that dominated last year’s European Microfinance Award (EMA) and EMW, with Graham Wright’s keynote call for MFIs to “Digitise or Die!” (and see also the FinDev webinar series on the subject). Client protection remains at the forefront, (second in the rankings, see point 4 below for more going on here) and client-side digital innovations, despite the ubiquitous hype, is only in third overall – and only 7th among practitioners, who actually have to implement FinTech for clients. Do they know something that consultants and investors do not? Among New Areas of Focus (which looks 5-10 years down the track), Agri-Finance is clearly top. The Rural and Agricultural Finance Learning Lab, Mastercard Foundation and ISF Advisors’ Pathways to Prosperity presents the current state-of-the-sector. It’s worth looking at. Finally, Social Performance and/or Impact Measurement is 5th out of 20 trends. There’s too much to choose from here. But the CGAP blog on impact and evidence digs into the subject from a whole range of angles. And check out Tim’s CDC paper [No quid pro quo!--Tim] from earlier this year on the impact of investing in financial systems. Good to see that financial regulators are also giving this the attention it needs.

Finally, finance for refugees and displaced populations generated a lot of comments in the Compass - and was the biggest jumper in the New Area of Focus rankings. It’s been a big part of EMW for the last few years; climate migration was the theme of the excellent conference opening keynote by Tim McDonnell, journalist and National Geographic Explorer, and there’s lots of recent data (here in a World Bank blog) showing refugee numbers at (modern) record levels. Migration of course is inextricably linked to labor conditions. Low paid and low quality work drives migration [maybe we should have more research on migration as a household finance strategy--Tim]. For more on the ‘World of Work’ in the coming century, see below.

2. Climate Change: There may be more evolution in climate change/climate finance than any other area of financial inclusion today. From our side, the European Microfinance Award 2019 on ‘Strengthening Climate Change Resilience’ wrapped up last month, with APA Insurance Ltd of Kenya chosen as the winner for insuring pastoralists against forage deterioration that result in livestock deaths due to droughts . Forage availability is determined by satellite data, via the Normalized Difference Vegetation Index (NDVI). A short video on the program can be seen here.

The severity of climate change and the increasing impact it has on the world’s most vulnerable hardly needs outlining here. Progress has been excruciatingly slow. But a new report by the Global Commission on Adaptation, headed by Bill Gates and former U.N. Secretary-General Ban Ki-moon, aims to change that. Released in September 2019, it mapped out a $1.8 trillion blueprint to ready the world to withstand intensifying climate impacts. The Commission launched the report in a dozen capitals, with the overarching goal of jolting governments and businesses into action.

A bunch of recent publications illustrate the overdue acceleration of responses. The Economist Intelligence Unit’s Climate Change Resilience Index is pretty stark reading. Africa will be hit the hardest by climate change according to the Index – with 4.7% real GDP loss by 2050 (well supported by the rankings in the ND-Gain index from Notre Dame Global Adaptation Initiative (ND-GAIN), which summarizes countries’ vulnerability to (and readiness for) climate change. The EIU index shows that institutional quality matters a lot in minimising the effects. The paper also presents three case studies that highlight the importance of both economic development and policy effectiveness to tackle climate change. It’s worth a (fairly frightening) read. So is AFI’s new paper “Inclusive green finance: a survey of the policy landscape”, which asks and answers why financial regulators are working on climate change, how they have been integrating climate change concerns in their national financial inclusion policies and other financial sector strategies, and how they are collaborating with national agencies or institutions. Blue Orchard has also just published "Rethinking Climate Finance" which points to a US$400 billion shortfall by 2030 in climate finance, just to keep global temperatures within the 1.5 Celsius limit. The authors advocate various blended-finance products to encourage private sector investment, which, their survey reveals, is woefully low considering how significantly those investors perceive climate change risk to their portfolios.

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Week of September 27, 2019

1. Jobs: I've written a good bit here on the "Great Convergence" from the perspective of financial inclusion--that the US and middle-income countries have more in common in that domain than they have ever had--but another version of the "Great Convergence" is the common focus on jobs in countries across the per-capita income spectrum.
It's useful to put the current convergence in historical perspective--the recognition that creating jobs was critical and that "national champion" industrial development was not creating them played a large role in the development of the microfinance movement. The failure of microcredit to produce much beyond self-employment alternatives to casual labor has brought job creation, and especially job creation through SMEs, back to the top of the agenda of international development. At the same time, the failure of richer economies to produce very many "quality" jobs in the 10 years since the Great Recession (and arguably since the 1970s) or for the foreseeable future has put the question of jobs at the top of the list of concerns for policymakers in those countries.
Paddy Carter, the director of research for CDC (UK, not US), and Petr Sedlacek have a new report on how DFIs and social investors should think about job creation that lays out some of the issues (e.g. boosting productivity can both create and destroy jobs) quite nicely. MIT's "Work of the Future Task Force" also has a new report, this more from the perspective of policymakers in wealthier countries, with a call to focus on job quality more than job quantity. Stephen Greenhouse has a new book on dignity at work, which of course has a lot to do with job quality. Here's a talk he gave recently at Aspen's Economic Opportunities Program.
Seema Jayachandran has a new working paper on a specific part of the jobs conversation: how social norms limit women's labor market participation and what might be done about that. For me it also opens the question about microcredit-driven self-employment being a higher "dignity" job for women in many contexts than the jobs that are available to them otherwise. More on that in a moment.

2. Household Finance: I don't have a lot of links here, just some thoughts from conversations in the last few days. But to kick things off, Felix Salmon had a nice gibe at financial literacy this week that had my confirmation bias going. But in hindsight, I actually disagree: teaching financial literacy actually doesn't seem to be that hard based on the many papers that show that running a class leads to passing a financial literacy test. The hard part is making higher financial literacy pay off in terms of changed behavior. But there I agree with Felix's basic point: higher financial literacy doesn't lead to improved decision making for the poor or the wealthy. The wealthy just have more structure and protection (both formal in terms of regulation and practices at private firms who know better than to routinely screw profitable customers, and informal in terms of slack and cushion) from bad choices. On the flip side, Joshua Goodman has a new paper in the Journal of Labor Economics that finds that more compulsory high school math leads African-American students to complete more math coursework and to higher paying jobs (there's a nice little estimate that the return to additional math courses makes up half of the gains from an additional year of school).
Part one of "more on that in a moment" is that Seema with a rockstar list of development economists (Erica Field, Rohini Pande, Natalia Rigol, Simone Schaner and Charity Troyer Moore) has another new paper on whether access to, deposits into and training on using a personal bank account affects women's labor supply and gender norms. They find that it does increase women's labor supply and shifts norms to be more accepting of women working. Here's the indispensible Lyman Stone with a somewhat skeptical take on the interpretation of the data.
Finally, in a conversation with Northern Trust this week about their financial coaching work (see a recent summary here) a really fascinating insight came up: people in the coaching programs seem to have much more success when "saving" is framed as "debt reduction" than when it's framed as "saving." These sort of things always grab my attention because Jonathan's paper Borrowing to Save was a seminal piece for my interest and thinking in financial inclusion. But it also got me thinking: what would happen if retirement savings programs were framed as debt + loss aversion? Specifically, if when you started a job, the employer said: "I'm loaning you $10K, deposited into an IRA and you owe me $x monthly, until you pay it off--and if you don't I take it back." Obviously you couldn't run an experiment like that in the US because of regulations, but is there somewhere you could? Maybe someone has already done it? Let me know if you have any thoughts.

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Week of September 13, 2019

1. Digital Finance: Is a tide turning on digital credit? Old hands in the microfinance world like MicroSave and CGAP have been highlighting concerns about digital credit for the last few years, but the non-specialist community hasn't seemed to notice until recently. In late August Bloomberg had a quick hit piece with an eyebrow-raising headline, "This Nobel-Prize Winning Idea is Instead Piling Debt on Millions," which is likely the way the general public will perceive this despite the protests of insiders that telecoms/fintechs making instant loans at high rates with minimal customer engagement doesn't have much in common with traditional microcredit. A more serious treatment,"Perpetual Debt in the Silicon Savannah" was published in the Boston Review the same week, though it's frustrating in its own ways, notably the lack of engagement with the global/historical context of small dollar lending or with the research from financial diaries.
In both articles there are two additional issues that I wish received more attention. First, the value of liquidity management. The authors of the Boston Review piece, Emma Park and Kevin Donovan (both historian/anthropologists), spend a good deal of time talking about the "zero-balance economy" creating a situation where consumers can be exploited without engaging on the need for services to manage liquidity when you have low and volatile incomes. Second, the kind of default rates being hinted at in these articles raise serious questions about the business models and sustainability of digital lenders. Tala, one of the larger digital credit providers in Kenya (and elsewhere) just raised another $110 million. How much of that money is covering losses? I would love to see some analysis of what sustainable default rates are for digital credit.
Shifting gears a bit, the reason that the Kenya specifically and East Africa more generally remain in the spotlight on digital finance is the ubiquity of access. But ubiquity can't be assumed and in general I would say not enough attention is being paid to what happens when ubiquity fails. Here I don't mean places where everyone knows service is unreliable, but places and times where service is unexpectedly unavailable. Here's a story about the problems that can create in the US with ZipCar customers stranded in the "wilderness" because of a lack of signal leaves them unable to unlock or start the vehicles. More seriously, though, is the concern when access is limited because of political reasons. Here's a story about the rise in government-directed internet shutdowns. Of course there is the big concern of how these shutdowns would affect people who have adopted digital finance and find themselves unable to spend. But I also wonder if Tala investors have priced in the risk to the business model of internet shutdowns.
Internet shutdowns are a blunt tool. We should also be concerned about more fine-grained tools in the hands of governments or private companies. I'm old enough to remember when one of the highlighted "benefits" of digital finance was that it created an audit trail of transactions. Here's a story about how much data about you leaks to unknown parts of the internet when you use the Amazon Prime card and the Apple Card. And finally, here's a new report on cash as a public good from IMTFI, sponsored by the International Currency Association, which I am fascinated to discover exists (though I'm even more fascinated to discover the International Banknote Designers Association, which is one of its members).

2. Our Algorithmic Overlords:
There is of course a lot of overlap between concerns about digital finance and privacy and digital everything and privacy. One of the standard mantras of those gathering and selling data is that much of it is anonymized, so we shouldn't be concerned. But, of course, not so much. That's not just a concern in the US, because digital data-gathering is becoming a thing worldwide. Here's a plea to stop "stop surveillance humanitarianism." And here's a story about how a high-tech surveillance approach to improving disaster response turns out to have not been such a good idea (spoiler: garbage in/garbage out).
One of the major concerns about the use of algorithms in these situations is the garbage in/garbage out problem--combined with the gee-whiz veneer that technology provides obscuring that problem. I'm generally skeptical of that argument as a whole, because my experience is that people are far less likely to trust an algorithm than a human being (In some sense I wrote a whole book about it in a different application: the bogus fears that Toyotas were suddenly accelerating and trying to kill people). But there are other forms that algorithmic discrimination can take. Here's a story about a new US Housing and Urban Development regulation that would exempt landlords from responsibility for the discriminatory results of their screening practices as long as they don't understand the algorithm, which y'know is a given.
Finally, there is a new documentary about the 2016 US election, the Brexit referendum, Facebook/Cambridge Analytica, etc. called The Great Hack. Here's a piece about 7 things the documentary gets wrong which I find pretty convincing.

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Week of March 8, 2019

1. The OGs: I can't think about who influences me without beginning with Esther Duflo, Erica Field, Rohini Pande, Tavneet Suri (special links to two new papers that would have been in the faiV in a normal week--on the impact of digital credit in Kenya, and UBI in developing countries) and Rachel Glennerster.

2. New Views on Microcredit: Because I'm framing this around research that has influenced me and appeared in the faiV, I've organized these into topical buckets that make sense to me. But keep in mind, that may not be the only thing these economists work on. Cynthia Kinnan and Emily Breza have dug into the Spandana RCT to understand heterogeneity of results, and to used the AP repayment crisis and fallout to understand the general equilibrium effects of microcredit. Natalia Rigol with some of the OGs above followed up on the differential returns to capital between men and women from earlier studies finding the differences are largely due to intrahousehold allocation, not gender; she's also looked into how to better target microcredit to high-ability borrowers. Gisella Kagy and Morgan Hardy uncoverbarriers that women-owned microenterprises face. Rachael Meager creatively usesstatistical techniques to better understand heterogeneity in microcredit impact results. Isabelle Guerin provides insight on why microcredit can go wrong.

3. Savings: I will confess that I have a lot of questions about the savings literature. But that's mainly because of the work of these economists. Pascaline Dupas, of course. Silvia Prina tests encouraging savings in Nepal, while Lore Vandewalle tries to build savings habits in India. Jessica Goldberg runs very creative experiments to understand how savings affects decisions. Simone Schaner studies intrahousehold choices around savings.

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Week of December 3, 2018

1. faiVLive Background: The motivation for the faiVLive experiment is discussing what to think about microcredit impact given all the research in recent years. If you can't make it, or if you can, here's your quick cheat sheet to the recent research.
Of course it's starts with the average impact of microcredit being very modest. A Bayesian Hierarchical model look at the data confirms those findings. But there is important heterogeneity hidden within those average effects--"gung-ho" microborrowers do see substantial gains from increased access to credit. It's also true that these are mostly studies of expanding access to formal credit, not introducing it. That's hard to measure, but we can get a cleaner view of the value of credit when it gets taken away from most everyone--and that shows significant benefits, though through a somewhat unexpected channel: casual labor wages. Changes in labor wages can matter a lot for understanding the impact of a program, even entirely masking any benefits of an intervention with evidence that it makes a substantial difference in many contexts. And it's clear that changes in labor supply are quickly passed through into labor rates--in this case, the markets seem to be working fairly well. But it's not just labor markets. When microcredit affects local markets--by increasing or decreasing the supply of tradeable goods--the benefits may be substantial but mostly captured by the people who aren't using microcredit (what economists call general equilibrium effects). Which makes it all the more important to understand local market dynamics, especially when in many cases microenterprises are operating in sectors where supply exceeds demand. That being said, microcredit is a cheap intervention relative to other options. And it's possible we could increase the returns to microcredit for more reluctant microenterprise operators by boosting their aspirations. Or perhaps by doing better targeting of lending. But is it worth targeting? Households do seem to do a pretty good job of allocating access to capital to its most productive use within the household, and the gung-ho entrepreneurs are benefiting even without the expense of targeting.

2. MicroDigitalFinance and Household Finance:
I suppose all of the above would qualify here as well, but here's a bunch of different new stuff, starting with the digital side of things. There are two new papers about the effects of SMEs adopting digital payments. In Kenya, an encouragement intervention led to 78% of treated restaurants and 28% of pharmacies adopting Lipa Na m-Pesa, and consequent increases in access to credit. In Mexico, a different kind of encouragement--the government distributed massive numbers of debit cards as part of the Progresa program--led small retailers to adopt POS terminals. That led to wealthier customers shifting some of their purchasing to these smaller retailers, and increased sales and profits for the retailers, but not an increase in employees or wages paid. On a side note, it's curious that the smaller shock of debit card distribution (pushing debit card ownership to 54% of households) had a large effect on retailers but the larger shock of m-Pesa being adopted by practically everyone has not led to more Lipa Na m-Pesa adoption.
A few weeks ago I featured a puzzle in savings from two savings encouragement experiments--the encouragement worked but savings plateau at a level well below what would seem optimal. Isabelle Guerin sent me a couple of papers that I'm still reviewing that might help explain why, but this week I stumbled across another example. The US CFPB, back in the days when it was allowed to do stuff and wasn't a hollow shell of existential dread, ran an experiment using American Express Serve cards and the "Reserve" functionality. They find that encouraging savings works--people boost their savings--but that the savings plateau after the 12 week encouragement and stay at roughly the same level for 16 months. That's consistent with the results from India and Chile but not with a model of accumulating lump sums or precautionary savings. You would expect among this population that they would experience a shock in that 16 month period and draw down the savings. Participants say they reduce payday loan use, but frankly I don't believe any claims about payday behavior that isn't based on administrative data (and it doesn't make sense if balances were stable).
And finally because I want to encourage this behavior, Maria May sent me an interesting new paper on offering microcredit borrowers flexibility in repayment--customers get two "skip payment" coupons to use during the term of their 12 month loan cycle. Consistent with the much earlier work from Field et al, it yields more investment from borrowers, better outcomes and lower defaults.

3. Evidence-Based Policy: I noted last week that GiveWell, where I have served on the board since it's founding, released it's Top Charity recommendations. One of those is GiveDirectly. GiveWell, as is it's wont, wrote up some details of it's analysis of GiveDirectly, particularly about spillovers from cash transfers. That analysis was significantly informed by a forthcoming paper on general equilibrium effects and spillovers from one of GiveDirectly's programs that GiveWell was given access to even though it is not yet public. Berk Ozler took issue with that. And GiveWell responded. I have nothing whatsoever to do with GiveWell's research process or conclusions, but I was heavily involved advising GiveWell on its response to Berk's questions.

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Week of April 23, 2018

1. Communications: Marc Bellemare has a new post on how to communicate research titled "The Goal of Scientific Communication Is Not to Impress But to Be Understood." To which I say, the goal of human beings is not to be understood but to impress (hence the faiV). But assuming that you aren't as Calvinist as I am, I've been collecting a few things over the last few weeks that broadly fit the theme of better communicating research and ideas. Here's an experiment on disaster relief communications testing negative and positive imagery for their effect on donations and on donors sense of that change was possible. Unfortunately, there are few conclusions to draw; these are hard experiments to run. Here's a piece from ODI on 9 things you are doing, but shouldn't in research communications. I'm guilty of at least five (with mitigating circumstances, e.g. the funders told me I had to).
But let's get specific. Here's something you should definitely not do: produce a set of guidelines for behavior that have no input from the most important people in the equation. You should also not try to write jargony, provocative headlines without really understanding the context, for instance, saying that "40% of Older Americans Will Experience Downward Mobility." Given that the standard models of retirement planning assume that everyone retiring will have a lower income (hello there Lifecycle theory!), and most people aren't close to saving enough for retirement according to those standard models, I'm willing to bet a lot of money that the figure will be a lot higher than 40%. Don't try to find some way to contextualize a massive ritual sacrifice of children. And finally, definitely don't be one of these Manhattanites caught on video expressing revealed preferences for segregation and inequality, but do be like the principal at the end of the video clip and communicate your disgust in no uncertain terms.

2. Global Convergence: But not in a good way. I often think about the divergence in outcomes (or put another way, growing income and wealth inequality, falling mobility) for Americans as a convergence: for the bottom ~40% of the income distribution, the American economy looks a lot more like the economy in, say South Africa or Brazil, than the economy experience by the upper half of the distribution. That clip above is one example of how far out of reach the tools for mobility can be. Justin Fox has a story about fee-based governance in the United States--government agencies funding themselves through fines and fees. Justin makes the connection to the Gilded Age in the US, but it's a mechanism that will be very familiar to people in developing and middle-income countries. For a ray of hope on that front, you can check out Tishuara Jones, Treasurer of St. Louis, who is fighting back against fines and fees as revenue in her city.

3. Household Finance: This week I guest-taught a class at Haverford on US microfinance. In the post-discussion I learned that students prefer off-campus jobs, because Haverford pays student workers only once-a-month, and those who need the paycheck from a job during the semester, need it more frequently. That makes sense. But people on low-incomes also often prefer infrequent payments, so as to get larger lump-sums. Dairy farmers in Kenya do according to this new work from Casaburi and Macchiavello. To the convergence point earlier, this isn't a difference between the US and developing countries. The demand for income spikes among people in the US can be seen in the low take-up rates for monthly EITC payments, and the high take-up of "overwithholding." It's also evident in the fintech Even's pivot away from consumption smoothing. The bottom line is we still have a long way to go to understand optimal income volatility and we should have weak priors about the interest in and benefits of say, on-demand income or a "rainy day EITC."

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First Week of March, 2018

1. Global Development: One of the more encouraging trends in development economics as far as I'm concerned is the growth of long-term studies that report results not just once but on an on-going basis. Obviously long-term tracking like the Young Lives Project or smaller scale work like Robert Townsend's tracking of a Thai village (which continues to yield valuable insights) falls in this category, but it's now also happening with long term follow-up from experimental studies. Sometimes that takes the form of tracking down people affected by earlier studies, as Owen Ozier did with deworming in Kenya. But more often it seems, studies are maintaining contact over longer time frames. A few weeks ago I mentioned a new paper following up on Bloom et. al.'s experiment with Indian textile firms. The first paper found significant effects of management consulting in improving operations and boosting profits. The new paper sees many, but not all, of those gains persist eight years later. Another important example is the on-going follow up of the original Give Directly experiment on unconditional cash transfers. Haushofer and Shapiro have new results from a three year follow-up, finding that as above, many gains persist but not all and the comparisons unsurprisingly get a bit messier.
Although it's not quite the same, I do feel like I should include some new work following up on the Targeting the Ultra Poor studies--in this case not of long-term effects but on varying the packages and comparing different approaches as directly as possible. Here's Sedlmayr, Shah and Sulaiman on a variety of cash-plus interventions in Uganda--the full package of transfers and training, only the transfers, transfers with only a light-touch training and just attempting to boost savings. They find that cash isn't always king: the full package outperforms the alternatives.

2. Our Algorithmic Overlords: If you missed it, yesterday's special edition faiV was a review of Virginia Eubanks Automating Inequality. But there's always a slew of interesting reads on these issues, contra recent editorials that no one is paying attention. Here's NYU's AINow Institute on Algorithmic Impact Assessments as a tool for providing more accountability around the use of algorithms in public agencies. While I tend to focus this section on unintended negative consequences of AI, there is another important consideration: intended negative consequences of AI. I'm not talking about SkyNet but the use of AI to conduct cyberattacks, create fraudulent voice/video, or other criminal activities. Here's a report from a group of AI think tanks including EFF and Open AI on the malicious use of artificial intelligence.

3. Interesting Tales from Economic History: I may make this a regular item as I tend to find these things quite interesting, and based on the link clicks a number of you do too. Here's some history to revise your beliefs about the Dutch Tulip craze, a story it turns out that has been too good to fact check, at least until Anne Goldgar of King's College did so. And here's work from Judy Stephenson of Oxford doing detailed work on working hours and pay for London construction workers during the 1700s. Why is this interesting? Because it's important to understand the interaction of productivity gains, the industrial revolution, wages and welfare--something that we don't know enough about but has implications as we think about the future of work, how it pays and the economic implications for different levels of skills. And in a different vein, but interesting none-the-less, here is an epic thread from Pseudoerasmus on Steven Pinker's new book nominally about the Enlightenment.

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Week of February 12, 2018

1. Banking: In case you missed it, here's that link from last week finding that banks would be better off if they did a lot less. Well, a lot less of the complicated financial stuff that most (large) banks spend a lot of time doing. Matt Levine sees a generalized trend in a positive direction--that is that the financial engineering that financial services companies are engaged in is focused much less on engineering complex financial instruments and a lot more on software and technology engineering. Even the cool project names are being reserved for technology projects rather than hard-to-understand derivatives-of-futures-of-insurance-of-bonds-of-weather-derivatives.
That does raise some questions about the evolution of fintech--if the banks themselves are more focused on the technology of service delivery, what does that mean for the technology firms? I do feel a bit of unease that these are the same banks that don't seem to be able to add value to themselves in their core area of expertise (and it's not just the banks, remember that Morningstar's ratings are negative information). How much should we expect from their wading into technology and advice? More on that below, in item 2.
There's another concern with banks moving in this direction. While it's not always the case, the kind of engineering that banks are doing now tend to increase consolidation: returns to scale tend to be bigger and matter more in software, data and high-volume/low-margin activities. And when consolidation happens it tends to be bad for lower-income customers. Here's a recent paper examining the impact of bank consolidation in the US (particularly large banks acquiring small banks): higher minimum account balances and higher fees, particularly in low-income neighborhoods. Those neighborhoods see deposits flow out of bank accounts (justifying closing branches) and later see increases in check-cashing outlets and decreased resilience to financial shocks. But wait there's more: the current version of the Community Reinvestment Act regulations tend to focus on places where banks have a physical presence. So closing branches and delivering more services through technology means, well, that those banks have less worries about complying with CRA. Hey did you know that the Treasury Department is considering making changes to the CRA regulations? I'm guessing the first priority isn't going to be expanding the CRA mandates.
And just to throw in a little non-US spice, here's a story about massive bank fraud at the Punjab National Bank in India.

2. Our Algorithmic Overlords: I've made jabs in the faiV pretty regularly about fintech algorithms ability to make good recommendations, particularly for lower income households. It turns out I'm not alone in distrusting machine-generated recommendations. Human beings tend to believe pretty strongly that humans make better recommendations than machines particularly when it comes to matter of taste. But we're all wrong. Here's a new paper from Kleinberg, Mullainaithan, Shah and Yeomans testing human versus machine recommendations of jokes(!). The machines do much better. Perhaps I should shift my concern away from machine-learning-driven recommendations and spend more time on a different preoccupation: why humans are so bad at making recommendations. There is perhaps another way: making humans and machines both part of the decision-making loop. A great deal of work in machine learning right now is organized around humans "teaching" a machine to make decisions, and then turning the machine loose. An alternative approach is having the "machine-in-the-loop" without ever turning it loose. That is the approach generally being used in such things as bail decisions. The big outstanding question is where we should allow humans (and which humans) to overrule machine recommendations and when we should allow the machines (and which machines) to overrule the humans.
Key to making such decisions is whether the human is able to understand what the machine is doing, and whether humans should trust the machine. Both are dependent on replicability of the AI. You might think sharing data and code in AI research would be standard. But you'd be as wrong as I was about recommendations. There's a budding replication crisis in AI studies because it is so rare for papers to be accompanied by the training data (about 30%) used in machine-learning efforts, much less the source code for their algorithms (only 6%!). Of note if you click on the paper above about recommendations, on page two  there is note that all of the authors' data and code are available for download.

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The First Week of February 2018: The Morduch Edition

1. Development Economics Superstars: You know by now that NYU economist Paul Romer is heading home to downtown NY, leaving his post as the World Bank Chief Economist. It’s good news for the NYU development economics community. Don’t worry about the World Bank, though – if this list of amazing seminar speakers is any indication, the World Bank continues to be a place to find exciting ideas and research. The first speaker was this week: MIT’s Tavneet Suri talking about digital products and economic lives in Africa (video).

2. Dueling Deatons: It would be embarrassing to let on just how much I’ve learned from reading Angus Deaton over the years. But there are different versions of Deaton. One of them is a careful analyst of income and consumption data with a no-BS attitude toward poverty numbers. Another wrote an op-ed in the New York Times last week.
Deaton’s op-ed argued (1) that there’s quite a lot of extreme poverty in the US, not just in poorer countries, and (2) perhaps we should move budget from anti-poverty efforts abroad to those at home. Development economists & allied cosmopolitans rose up. Princeton ethicist Peter Singer argues that argument #2 clearly fails a cost-benefit test: it’s simply much cheaper to address needs abroad. Charles Kenny and Justin Sandefur of the Center for Global Development reject the idea that spending more in Mississippi should mean spending less in India, and they take a good whack at the US poverty data. But if you’re going to read just one rebuttal, make it Ryan Brigg’s essay in Vox. It’s the rebuttal to “provocative Deaton” that “no-BS Deaton” would have written. The main argument is: no, actually, there isn’t much “extreme poverty” in the US once you look at the data more carefully. Deaton’s basic premise thus falls away.
On a somewhat more personal note: in recent years, I’ve spent time down the back roads of Mississippi with people as poor as you’ll find in the state. I’ve come to know the kinds of Mississippi towns that Kathryn Edin and Luke Shaefer describe in their powerful US book, $2 a Day (one of Deaton’s sources). At the same time, I’ve worked in villages in India and Bangladesh where many households are targeted as “ultrapoor”. So I think I have a sense of what Deaton’s getting at in a more visceral way. He’s right about the essential point: It’s hard not to be angry about our complacency about poverty – both at home and in the US. We should be more aware (and more angry). But Deaton picked the wrong fight (and made it the wrong way) this time. 

3. Risk and Return (Revisited): A big paper published this week. It’s nominally about farmers in Thailand, but it challenges common ways of understanding finance and inequality in general. The study holds important lessons but is fairly technical and not so accessible. The paper is “Risk and Return in Village Economies” by Krislert Samphantharak and Robert Townsend in the American Economic Journal: Microeconomics (ungated).
Why does poverty and slow economic growth persist? A starting point is that banks and other financial institutions often don’t work well in low-income communities. One implication is that small-scale farmers and micro-enterprises can have very high returns to capital -- but (or because) they can’t get hold of enough capital to invest optimally. The entire microfinance sector was founded on that premise, and there’s plenty of (RCT) evidence to back it.
Samphantharak and Townsend use 13 years’ worth of Townsend’s Thai monthly data to dig deeper. The paper gathers many insights, but here are two striking findings: The Thai households indeed have high average returns to capital but they also face much risk. Making things harder, much of that risk affects the entire village or broader economy and cannot be diversified away. As a result, much of the high return to capital is in fact a risk premium and risk-adjusted returns are far, far lower. That means that poorer households may have high returns to capital but they are not necessarily more productive than richer households (counter to the usual microfinance narrative). The action comes from the risk premium.
What is happening (at least in parts of these Thai data) is that poorer farmers are engaged in more risky production modes than richer farmers. Once risk premia are netted out, the picture changes and richer farmers are in fact shown to have higher (risk-adjusted) returns.
A few implications (at least in these data): (1) better-off farmers are both more productive and have more predictable incomes. So inequality in wealth is reinforced by inequality in basic economic security, the kind of argument also at the heart of the US Financial Diaries findings. (2) Poorer farmers face financial constraints, but not of the usual kind addressed by microfinance. The problems largely have to do with coping with risk. That might explain evidence that microfinance isn’t effective in the expected ways. (3) The evidence starkly contrasts with arguments made by people (like me) who argue that rural poverty is bound up with the inability to take on riskier projects.

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