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Viewing all FaiV posts with topic: Savings  

Week of March 8, 2019

The IWD Edition

1. The OGs: I can't think about who influences me without beginning with Esther DufloErica FieldRohini PandeTavneet 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 microcreditNatalia 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 borrowersGisella Kagy and Morgan Hardy uncoverbarriers that women-owned microenterprises faceRachael Meager creatively usesstatistical techniques to better understand heterogeneity in microcredit impact resultsIsabelle 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 IndiaJessica Goldberg runs very creative experiments to understand how savings affects decisionsSimone Schaner studies intrahousehold choices around savings.  

4. Related Development Topics: I feel a special burden here to point out the non-comprehensiveness of this item. These are economists whose work comes to mind often as I try to puzzle through evidence. Dina Pomeranz could have been in the savings items above, but she also does lots of interesting things on taxation in developing countriesSeema Jayachandran on cash transfers and changing behavior via payments. Pam Jakiela's work on intrahousehold bargaining and on occupational choicesOriana Bandiera's work on labor markets.  

5. US Household and Micro- Finance: A different kind of caveat here. These are women I work with closely who aren't economists, but whose work is important to understanding household and microfinance in the United States. Joyce Klein is the expert on US microfinance in practice as far as I'm concerned. Ida Rademacher,Joanna Smith-RamaniGenevieve Melford and Katherine McKay are doing great work delving into US household finance, particularly through the Expanding Prosperity Impact Collaborative on topics like income volatility and consumer debt.

From  Tatyana Derugina , via  Annette Brown . Though in my experience the trend line is similar to publishing in every other domain I've been a part of.

From Tatyana Derugina, via Annette Brown. Though in my experience the trend line is similar to publishing in every other domain I've been a part of.

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.
All of that is interesting, but I wanted to quickly draw attention to the Evidence-Based Policy subtext: internal and external validity. As Berk noted there are a number of papers that show negative spillovers from cash transfers in other contexts, and he makes the implicit argument that those papers are more internally valid because of public scrutiny and peer review. But are they externally valid--do their findings apply in other contexts? And more specifically, how should one weight research that has not had it's internal validity "boosted" by public scrutiny but is presumably more internally valid for being a study of the actual program being considered? GiveWell is putting a lot of weight on the non-public study because it has a large sample, is randomized and is pre-registered. Of course, one of the co-authors is a co-founder of GiveDirectly, which obviously presents some conflict-of-interest concerns. But one of the other co-authors might be called a godfather of the research transparency movement (OK, I'm doing it; I'm calling Ted Miguel a godfather of the research transparency movement).
Evidence-based policy is hard.
And that's before we factor in any of the complications of working with government and trying to incorporate community voice and self-determination. Susannah Hares reviews some lessons on "how, why and when to evaluate government-led reforms" through the lens of three impact evaluations of education policy reforms, from Delhi, Madhya Pradesh and Liberia. And since I'm speaking with Karthik Muralidharan later today, here's a throwback to a discussion he kicked off with comments at a recent RISE conference on evaluating policy reforms.  

4. Methods: I suppose that last link might belong more in a methods category, let's go right there. Well, let's go back to those internal validity questions. There's no shortage of discussion on the internet of whether peer review makes a difference or not. But it's much more rare to be told that "robustness checks are a joke." Double faiV points if you guess who wrote that before clicking. Quadruple points if you can guess who it links to. 
On the other hand, sometimes the rigors of peer review, robustness checks and working to have your research finding integrated into policy are just too much. It would all be much easier if your findings were suitably dramatic, surprising and large, even if that's not consistent with the data you've gathered. Here are ten simple rules for faking your research and getting it published (and not retracted).

5. Global Development : Please don't interpret that last link as having anything to do with what is in this item. Esther Duflo famously has noted that an advantage of RCTs is they have the ability to surprise. For my part, I'm frequently surprised by what expermenters manage to convince people to randomize. For instance, how about randomizing the religious content of a poverty intervention delivered by a Christian charity? That happened, in the Philippines, and here's a Freakonomics podcast about it. The results indicate that the evangelical Protestant content does increase effort and earnings. That's consistent with historical work in Germany, and by the way with the wave of work on the role of aspirations and hope. 
Speaking of aspirations and hope, those two characteristics would seem to be disproportionately held by migrants. Here's Michael Clemens and Katelyn Gough on the "best ideas for making migration work.
Finally, I've had a few links on updated work on the impact of the Green Revolution, which remains surprisingly controversial, hanging around waiting for the right faiV to include them, and well, I'm going to include them today. Here's a paper exploiting time variation in the development of high yielding crop varieties and their diffusion that finds that a 10% increase in use of HYVs increases GDP per capita by 15% (within a sample of 84 countries). Alternatively, here's work that finds that HYVs delayed industrialization and urbanization in India, and thereby limited GDP growth. But here's another new paper that finds that while HYV may have kept people in rural areas, it did decrease infant mortality. So if you weren't feeling bad enough about the difficulty of evidence-based policy and evaluating policy reforms as they happen, keep in mind that 30 years later people will still be arguing over whether the reform was good or bad.

Whether you survey husbands or wives about household assets matters, and can have a substantial effect on poverty measures. Via  Development Impact Blog , Source:  Adnan Silverio-Murillo .    

Whether you survey husbands or wives about household assets matters, and can have a substantial effect on poverty measures. Via Development Impact Blog, Source: Adnan Silverio-Murillo.    

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."

4. The Ridiculous: Perhaps a new category for the faiV. Presented without further comment: "Soon Blockchain Will Let Armies of Free Agents Run Companies" and the "leading expert" on student loans was just a front for a student loan consolidation company. . Oops.

5. US Poverty and Inequality: When William Julius Wilson writes, it's probably a good idea to read. And here's the best review of The Financial Diaries (and of The Unbanking of America) that I've seen.   

A very cool video (snippet) of the week, visualizing data on the learning gap. Via  Lee Crawfurd ,  Quartz , and from  Luis Crouch .

A very cool video (snippet) of the week, visualizing data on the learning gap. Via Lee Crawfurd, Quartz, and from Luis Crouch.

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.

4. Household Finance: I want you to look at two pieces that are about household finance, one from the US and one Ghana and tell me if you react to them the same or differently and whether that reaction is positive or negative. I feel like these two stories are one of the most effective rohrshach tests you could imagine to get at people's feelings about financial services for poor households. First we have a blog post from CGAP about PayGo Water--in other words, rather than paying a monthly water service bill retroactively, using digital payments to enforce payment before the water is delivered. Second, this blog post from Aaron Klein about hidden price discrimination based on what payment methods consumers use--in other words the poor pay more.

5. Social Investment: Here are a few other pieces that similarly may spark conflicting responses. Ross Douthat has an editorial on the trade-offs in the behavior of corporate America as it seems to more explicitly blend socially liberal but economic-inequality-boosting policies. Fast Company reviews the state of Social Impact Bonds, a facet of social investment that seems to have fallen out of the spotlight as people realize how complicated they (and the world) are. I'm a long-term critic of the idea that social investing has "no trade-offs." If you're getting market-rate returns you're just investing as far as I'm concerned, not social investing. But this longform critique of the "doing well by doing good" rhetoric seems to me to really be talking about making grants not investments. And finally this piece doesn't truly fit here unless you really squint and cock your head to the side, but it does induce conflicting feelings. It's about continuing large-scale discrimination against borrowers of color by US banks (and in that sense it fits fairly well with the piece above), and the stories they tell will likely leave you seething. But the evidence isn't that strong since they can only see a small portion of the data you would need to really determine creditworthiness. Don't get me wrong, I'm not saying there isn't discrimination. But it seems much more likely to me that the source of the discrimination is the pre-existing racial wealth gap and biases in credit scoring, not purposeful discrimination by the banks or loan officers.

Week of February 12, 2018

Editor's Note: I'm obviously not anti-bank (at least I hope that's obvious!), but in the wake of last week's piece on how hard it is to figure out the value of most of what banks do, I've been accumulating a number of pieces on bank behavior that are less than flattering. I've been struggling to come up with any other service that is so vital and that society so commonly holds in contempt. It's a reminder, again, of what an enormous accomplishment it was for microfinance's pioneers to get people to view banks and bankers as heroes. If there are any sociologists in the house who would like to school me on the literature of social perceptions of banking, please do!--Tim Ogden

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.

3. Risk: Last week I promised some more thoughts on risk and aspirations. To summarize for those who haven't been following along: there is strong evidence of large returns on investment for poor farmers and even some microenterprises, there are similarly large returns for rural farmers investing in migrating to urban areas, those folks tend to avoid making such investments, and interventions that reduce risk or allow pre-commitment tend to increase such investments. More recently, several other pieces of evidence seem to be falling into place. First, those large returns on investment are not so large once you adjust them for risk (that's from the recent Townsend paper that Jonathan first linked two weeks ago). Second, urban migration might be riskier than we have appreciated. Third, people who migrate may be systematically different and more capable (and thus have less risk) than those who don't. And fourth, as I talked about last week, another way to get people to make more investment is to raise their aspirations or sense of personal efficacy, which could be interpreted as increasing their risk tolerance. 
There are a number of things that strike me given this set of stylized (and not yet fully proven) facts:
1) There are big reasons to be concerned about general equilibrium effects of increasing the risk tolerance of people who are risk averse. It's very plausible that early experiments in this domain would show large gains for participants but those gains would not only fade, but substantially reverse at scale. If this pattern is true, it makes a very, very strong case for investing in insurance that protects people from risk rather than changing their risk tolerance.
2) The pattern of risk-adjusted returns in the Townsend data looks a lot like the entrepreneurial equilibrium in developed countries, as described by Amar Bhide in his book The Origin and Evolution of New Businesses. The short version: established businesses take all of the less risky investments, leaving the truly high risk ones to entrepreneurs. Those entrepreneurs take them not only because they are less risk averse, but because they are the only options available--which is consistent with general findings that successful entrepreneurs are just as risk averse as corporate managers. But we only ever see the risks which pay off, leaving us with a profoundly distorted view of entrepreneurism.
3) A book I spent some time reading while on break was James Scott's Against the Grain. One of the main claims of the book is that, contrary to the traditional narrative, the hunter-gatherer lifestyle is far less risky than the sedentary agricultural lifestyle. He makes a very convincing case using all sorts of evidence, but it raises the big question of why risk-averse agriculturalists haven't continually reverted back to hunter-gatherer lifestyles. I find the arguments there less convincing, but I'm not sure what to think about that or the implications. 

4. Inequality: OK, late in the day. Time for some rapid fire links. An argument for income redistribution to address growing inequality from an unexpected source: Bain & Company. A new paper looks at whether one of the methods for income redistribution, a Universal Basic Income, discourages work by examining Alaska's citizen oil dividend and finds that it mostly doesn't, though with some effects in tradeable sectors. Overlooked in many discussions of inequality is the largest disparity in college-going: rural kids are the ones most left behind.
And a lengthy piece on the hidden inequality in how people in the US make payments. The rich use credit cards and get lots of rewards (like cash back or airline miles, mostly paid for by merchants, and don't carry balances) and the poor use debit cards or cash and get nothing--making for a very regressive system. Just another way the poor are different than you and me: they pay more.

5. Microfinance Is Just Banking: And to tie the whole thing together, I'm going to close with two pieces about microfinance. First on the motivations and impact of an MFI in Bangladesh dropping its group meetings in favor of mobile money transactions. Second on what's wrong in Sri Lanka's microfinance industry. Is it a Straussian reading if I tell you to read this item like a Straussian? Here let me make the sub-text text: you should read these pieces only after looking at the pieces above what is wrong with banking and be amazed at how quickly microfinance seems to be re-learning all the lessons of modern consumer banking that are evident in developed countries or even in other countries with more mature microfinance.

Mechanical Turk is a common source of 'warm bodies' for social scientists but it's hard to know to just who the workers who participate are, and even how many there really are--and the answers are highly dependent on how you define who is a "regular" participant. It's a complicated question to answer, and the chart below is interesting but wrong,  for interesting reasons . Source:  Panos Ipeirotis .

Mechanical Turk is a common source of 'warm bodies' for social scientists but it's hard to know to just who the workers who participate are, and even how many there really are--and the answers are highly dependent on how you define who is a "regular" participant. It's a complicated question to answer, and the chart below is interesting but wrong, for interesting reasons. Source: Panos Ipeirotis.

The First Week of February 2018: The Morduch Edition

Editor's Note: this week’s faiV is guest-edited by none other than Jonathan Morduch. I'll be back on regular faiV duty next week. --Tim Ogden

Guest Editor Jonathan Morduch's Note:
Thanks, Tim Ogden, for letting me take the wheel for this week’s faiV. Sean Higgins did a great job with last week’s faiV, and I’m feeling a bit of pressure to meet their high standards. Here we go:

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 abroad 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.

4. Our Algorithmic Overlords:
 Political scientist Virginia Eubanks has a new book, Automating Inequality, [Tim will have a review in next week's faiV] about poverty in the digital age. Eubanks argues that we’re creating “digital poorhouses” akin to the poorhouses of old. The basic story is that data-driven policy approaches hurt the most disadvantaged – but seem hard to understand and thus hard to criticize. Eubanks, though, says they’re not in fact so complicated. Eubanks is featured in an interesting interview in MIT’s Technology Review. One snippet on politics and activism:I do think it’s really interesting, the way we tend to math-wash these systems, that we have a tendency to think they're more complicated and harder to understand than they actually are. I suspect that there's a little bit of technological hocus-pocus that happens when these systems come online and people often feel like they don't understand them well enough to comment on them. But it’s just not true.” 
Bonus: Just learned the phrase “math-wash”. 

5. Paychecks as Commitment Devices: If you’re like me, you’re probably paid monthly by your employer. A 2016 working paper by Lorenzo Casaburi and Rocco Macchiavello (which I just saw Lorenzo present – I’m very late to the party) argues that – for members of a Kenyan dairy cooperative at least – being paid monthly has an advantage that is easy to take for granted: It helps overcome saving constraints. In effect, the cooperative is saving weekly earnings so the members don’t have to. What’s most striking is that members are willing to pay (by foregoing earnings) for the chance to be paid monthly. The result lines up with other (surprising) evidence that people are willing to pay for saving mechanisms that transform small cash inflows into meaningfully large sums (to take a phrase from Stuart Rutherford).

CEGA Special Edition: A bit more from AEA

Editor's Note: this week’s faiV highlights more research on financial inclusion and machine learning from the American Economic Association annual meetings, guest-edited by Sean Higgins, a Post-Doctoral Fellow at the Center for Effective Global Action at UC Berkeley, whose research focuses on financial inclusion.

Next week, I'm hoping Jonathan Morduch will fill in for me before I resume normal service the week of February 5th--Tim Ogden

1. Financial Inclusion: I [Sean] organized a session on savings and financial inclusion that looked at the impact of various savings interventions such as commitment devices, opt-out savings plans, and mobile money. Continuing last week’s theme on similarities between developed and developing countries, a savings intervention that has greatly increased savings in the US is opt-out savings plans or “default assignment,” such as being automatically enrolled in a 401(k) plan. In an experiment in Afghanistan, Joshua Blumenstock, Michael Callen, and Tarek Ghani explore why defaults affect behavior: some employees are defaulted into a savings program where 5% of their salaries are automatically deposited in a mobile money savings account, but they can opt out at any time. Those who were defaulted in were 40 percentage points more likely to contribute to the savings account, which is comparable to the effect of the employer matching 50% of employees’ savings contributions

Commitment savings accounts have also been tested in the US and in many other countries. In a study by Emily Breza, Martin Kanz, and Leora Klapper, employees in Bangladesh were offered a commitment savings account, with a twist: depending on the treatment arm, employers sometimes endorsed the product, and employees were sometimes told that their decision would be disclosed to the employer. Only the treatment arm that had both employer endorsement and disclosure of the employee’s choice led to higher take-up, suggesting that workplace signaling motivated employees to save. Another study by Simone Schaner et al. (covered in last week’s faiV) offered employees in Ghana a commitment savings product with the goal of building up enough savings to stop incurring overdraft fees, which are common. Take-up was high, but baseline overdrafters were more likely to draw down their savings before the commitment period ended -- meaning they benefited less from the intervention.
Two important barriers to financial inclusion in the US and around the world are transaction costs and low trust in banks. In a paper I coauthored with Pierre Bachas, Paul Gertler, and Enrique Seira, we study the impact of providing debit cards to government cash transfer recipients who were already receiving their benefits directly deposited into a bank account. Debit cards lower the indirect transaction costs -- such as time and travel costs -- of both accessing money in a bank account and monitoring the bank to build trust. Once they receive debit cards, beneficiaries check their balances frequently, and the number of checks decreases over time as their reported trust in the bank and savings increase"


2. Household Finance: Digital credit is a financial service that is rapidly spreading around the world; it uses non-traditional data (such as mobile phone data) to evaluate creditworthiness and provide instant and remote small loans, often through mobile money accounts. One of the concerns about digital credit is that customers’ credit scores can be negatively impacted, even for the failure to repay a few dollars. In turn, this can leave them financially excluded in the future. Andres Liberman, Daniel Paravisini, and Vikram Pathania find a similar result for “high-cost loans” in the UK (which we would call payday loans in the US). They use a natural experiment and compare applicants who receive loans with similar applicants who do not receive loans to study the impact of the loans on financial outcomes. For the average applicant, taking up a high-cost loan causes an immediate decrease in the credit score, and as a result the applicant has less access to credit in the future.  

3. Our Algorithmic Overlords: There were a number of sessions at the AEA meetings on big data and machine learning. My favorite of these showcased a variety of economic applications of machine learning, three of which use big data from mobile phones. Susan Athey et al. use high-frequency location data from mobile phones to estimate a consumer choice model over restaurants and travel time. There are a large number of variables going into each individual’s decision of where to go for lunch, and each individual is different; the benefit of using machine learning is that they can incorporate a large number of variables on both restaurants and consumer preferences into the model. Susan also has an excellent overview of applications of machine learning in economics here.


Mobile phone data can also be used to predict creditworthiness: in a middle-income Latin American country, Daniel Björkegren and Darrell Grissen find that mobile phone call detail records perform just as well at predicting creditworthiness as traditional credit bureau scores (although neither perform particularly well in this sample). The mobile phone data appears to be picking up useful information to predict creditworthiness, and could be especially useful for consumers with no formal credit history or traditional credit score. These data sources and models could also help low-income women, who face a bias in the amount lenders are willing to provide, higher interest rates, and legal frameworks which can make it more difficult for them to access credit.

4. More Machine Learning: After the meetings each year, the AEA offers two-day continuing education courses on a changing variety of topics. This year, one of the courses was Machine Learning and Econometrics taught by Susan Athey and Guido Imbens. The webcasts and slides from the course can be accessed here. As economics increasingly adopts methods from machine learning in the coming years, this class’s combination of practical tools, R code, intuition, and theory make it more than worth your time to watch the webcasts and peruse the course materials.

One of the gems was the intuitive descriptions of various machine learning techniques. I feel like I finally have an intuitive understanding of what stochastic gradient descent and neural nets do (and I had to explain it to a friend yesterday which is always a good test). For example, here’s Susan’s description of the “incredibly powerful” method of stochastic gradient descent (in minute 58 of this video). What we usually do: “Estimating a model is climbing a mountain. In economics the way we approached that problem historically, is if you were climbing up that mountain trying to find the parameters that maximize an objective function, at a particular point in climbing that hill there’s a gradient that tells you in which direction should I change my parameters to get up to the top of the hill and find the parameters that best fit my data. We might spend fifteen minutes of our computation computing the gradient at one point, and then climb up the hill a little bit and work really hard at computing the gradient at the next point.” 
The magic of stochastic gradient descent: “At each point in climbing the hill, you evaluate the gradient using just one data point from your data set…you just pick one data point and compute where you should go as if that data point was your only data point. It’s an unbiased estimate of the gradient but it’s incredibly noisy. But instead of doing 10,000 computations to figure out how to make one tiny step, instead 10,000 times you go up and down your hill, up-down-up-down, over here over there, but you’re always kind of going in the right direction. And 10,000 points later you’re almost at the top, while with our old methods you would have gone much more in the right direction but you would have just made one tiny step and you’re nowhere near the top of the mountain.” 

5. Inequality:
The World Wealth & Income Database group led by Thomas Piketty, Facundo Alvaredo, and Lucas Chancel at the Paris School of Economics and Emmanual Saez and Gabriel Zucman at UC Berkeley presented on global inequality and policy. Recently, the group has been combining data from household surveys, national accounts, and tax records to create more comprehensive measures of income and wealth inequality. One interesting finding they presented was that Brazil’s large reduction in inequality since 2001 -- which is based on income measured in household surveys -- goes away if we instead use a measure that combines data from household surveys, national accounts, and tax records. With the more comprehensive measure, income inequality in Brazil has been flat. They also reported that inequality is increasing in almost every region of the world, and the global top 1% have about 20% of global income. A webcast of this session is available here.

Default assignment into an opt-out automatic savings plan leads to a large increase in take-up of the savings account, comparable to the effect of a 50% savings match (from  Blumenstock, Callen, and Ghani ).

Default assignment into an opt-out automatic savings plan leads to a large increase in take-up of the savings account, comparable to the effect of a 50% savings match (from Blumenstock, Callen, and Ghani).

Week of January 8, 2018

Editor's Note: I took some time off from my time off to attend what is officially the Annual Convention of the Allied Social Sciences Associations, but I prefer to be transparent for people outside the economics profession and just call it the American Economic Association annual meeting. Herewith are some papers I encountered in the three days of the meeting, along with related thoughts and a few other items thrown in for good measure.

Next week, Sean Higgins of CEGA will be guest editing the faiV--Tim Ogden


1. The Economics Production Function: Over the last few years, papers on microenterprises generally shared a couple of remarkable--given the general narrative--findings: microenterprises (on average) didn't grow no matter what you did to try to boost them, and women-owned microenterprises performed worse than male-owned ones. Those findings led to plenty of yowls from practitioners whose work, livelihoods and in some cases core beliefs were based on the opposite. In many conversations I had, I got the impression that people outside the profession believed that economists would publish these findings and then move on. But that perception really misunderstands the motivations of economists and the way the field works. Economists don't leave puzzles alone once they find them--the field pursues them relentlessly.
The best session I attended this weekend was based on the particular puzzle of why female-owned microenterprises are less profitable. Natalia Rigol presented work following up on an earlier studies that documented the profitability gender gap, finding that the source of the gap is mostly due to lower returns from female-owned enterprises where there was another (male-owned) enterprise in the household. Those male-owned enterprises were in more profitable industries (something documented in the original studies), so the households were making quite rational decisions to allocate additional funds to the more profitable business (and making it look as if the female-owned business had 0 or negative returns). In households where there was only a female-owned business there is no gap in returns to capital. Leonardo Iacovone and David McKenzie presented on efforts in Mexico and Togo, respectively, to provide training to help women entrepreneurs improve their businesses with positive results--in both cases seemingly based on personal initiative training rather than business skills. And Gisella Nagy presented results (unfortunately there's nothing yet to point to on this one) that women tailors in Ghana show lower profitability than male tailors because there are more women tailors which drives down prices they can get in the market. This last finding is particularly important because it suggests that part of the way forward for microcredit aimed at building women's businesses is to do a much better job targeting, or as I've called it elsewhere, abandoning the vaccine (everyone gets one!) model of microcredit for an antibiotic (only people who really need it get one!) model.
And all of that is just a very small sample of work being done on the puzzle of heterogeneity of returns to microenterprises and what can be done about it. I'm now sorely tempted to write an overview on all these studies, but dammit I really want to get to "subsistence retail."


2. Causal Inference is Hard: Those two topics aren't orthogonal to each other of course. One way they are joined together is my common theme about how hard causal inference is for the average person, and in particular for the subsistence (or just above) operator of a microentrprise (whether farming or retail). That's what I kept thinking about when reading this new post from David McKenzie on "Statistical Power and the Funnel of Attribution". David is writing for economists trying to write convincing papers, but this point "Failure to see impacts on your ultimate outcome need not mean the program has no effect, just that the funnel of attribution is long and narrows" is equally important for the people being treated. If the funnel of attribution is long and narrows, then its approaching impossible for the individual (not gifted with a large sample size or a deep understanding of statistics) to figure out which of their actions actually matter.
There is a connection to AEA here. As I was perusing the poster displays (also known as "the saddest place on earth") I kept hearing people arguing with Jacob Cosman, the creator of a poster about how the opening of new restaurants in a neighborhood affects the behavior of existing restaurants. The answer: a very precisely estimated no effect at all. (Here's a link to an old version of the paper with somewhat different results) Economists walking by simply couldn't believe this and were constantly suggesting to the author things he must have done wrong. I was amused. My strong prior is that a person would not open one of these restaurants unless they believed that their restaurant was unique (otherwise, you would believe that your restaurant would quickly fail like the 90+% of other small restaurants and you wouldn't open in the first place). So when another new restaurant arrives, you don't actually see it as a threat that needs a response. You are, after all, different! But even if you did think you needed to respond, how would you possibly know what the right response was? Do prices matter? Menus? Advertising? Item descriptions? Coupons? The funnel of attribution on all of these is so long and imprecise we should assume that individual entrepreneurs have no idea what to do even if they wanted to do something. Which ultimately brings us back to why it's so hard to get microentrepreneurs to change their behavior in a lasting way, and why personal initiative training may work much better than business skills. Personal initiative training teaches you that what you do matters, even if you can't tell, while business skills training teaches you to do something even though you can't tell that it matters.  

3. More from the Saddest Place on Earth: There's more than a whiff of desperation about the poster display area at AEA, where you often find young economists-in-training doing their best impression of a street-corner evangelist/panhandler hybrid. The possibility of being accosted by a well-meaning but overly eager job-seeker seems to keep most attendees away from the area, which is a shame because I always find some quite interesting posters. Two of note this year were about microfinance loan officer behavior. Marup Hossain looked at the behavior of BRAC loan officers after the famous (at least in these parts) TUP experiment and found that they were using TUP participants relative performance in livestock husbandry in that program to determine who to approve for microcredit loans--and that this was a good way of targeting the loans to those most likely to achieve high returns. Sarah Wolfolds had a poster on performance pay in non-profit microfinance institutions in Latin America finding MFIs making smaller loans have smaller pay-for-performance payouts but more targets--I can't find a paper behind it but I always like to highlight work looking at principal-agent issues within MFIs since I don't think that gets nearly enough attention. 
Other "fun" posters amidst the sadness: Declining investment in infrastructure led to rebellions against the Qing dynasty; There's a lot less excess sensitivity to income than most measures suggest; eliminating a small debt account improves cognitive function of the poor more than paying off a larger amount of debt (but not fully paying it off); and digital (non-tangible) innovations tend to contribute more to income inequality than tangible innovations.

4. Our Algorithmic Overlords:  Due to a series of regrettable automotive incidents I missed several of the machine learning/AI/FinTech sessions at AEA on Friday morning that I was really looking forward to. Links to sessions here, here and here. To compensate, here are some completely different algorithmic overlords pieces to contemplate. Wired has a lengthy story about the growth of China's digital panopticon and social ratings. You should click on that and read it before coming back here to click on this link to an excerpt of Virginia Eubanks' forthcoming book Automating Inequality, so that you'll especially feel the bite of discovering how much Americans in poverty already live in an automated panopticon. I've just gotten a review copy of the book, so there will be more on this when I come back from vacation (which will be partially spent reading it). 

5. It's a Small World After All: There's another of my regular themes connecting those last two links: there's not so much difference between here and there. Want another example? At a session at AEA on savings and financial inclusion Simone Schaner presented research on a commitment savings account for serial checking account overdrafters in Ghana (hey, they have them in Ghana too!). The commitment account had shockingly high take-up (over 70% if I remember correctly) and savings in the accounts accumulated at an impressive rate. But decomposing the sample, and looking at savings outside the account, Schaner et. al. find that above median overdrafters drew down there other savings and took on debt, while below-median overdrafters actually built up savings. Oh, and here's Beshears et. al. taking a similar look at the big picture for people defaulted into the commitment savings account we in the US call 401(k)s. Defaulting people in raises the amount they save in the 401(k)substantially. But it also increases the amount of debt those people have 4 years later (though at least it's auto and mortgage loans and not revolving debt). 
There are of course some differences. Compare/Contrast these two pieces on solar home systems in Myanmar and the United States. First, here's a complaint that government subsidies ruined the business of a solar business in Myanmar, and a plea for governments to stop making it so cheap for people to get solar. Next, here's a complaint that government is making it too expensive for people to get solar home systems in the US with a plea for government to start making it cheaper. What brings the world together, apparently, is complaining about government interference in markets. That's something that would be right at home at AEA 2019.

There were a few sessions at AEA that were recorded and "webcast." Here's Alvin Roth's presidential address on  Markets and Marketplaces . Here's David Laibson on  Competition, Equilibrium, Freedom and Paternalism . Here's a session on the  Economics of AI and Robotics . And below there's a panel on Global Inequality and Policy.

There were a few sessions at AEA that were recorded and "webcast." Here's Alvin Roth's presidential address on Markets and Marketplaces. Here's David Laibson on Competition, Equilibrium, Freedom and Paternalism. Here's a session on the Economics of AI and Robotics. And below there's a panel on Global Inequality and Policy.

Week of July 24, 2017

The ranting edition

1. Low Quality Equilibria: There's an important "new" (e.g. it's been circulating in working paper form for a while, but is now published) paper in QJE about why hobby woodworkers waste so much money...just kidding, it's about why people keep buying cheap Chinese knock-off tech products and IKEA furniture...actually it's about the persistent use of predatory financial products and poor financial decision making...OK, it's really about the bind that the evidence-based policy movement finds itself in. Well, truthfully it's actually about agricultural markets in Uganda and why adoption rates of fertilizer and improved seed are low, but not zero. Really, that's what the paper is about.

But it is also about all of those other things. Here's the basic story:
Fertilizer and improved seeds boost agricultural productivity substantially. But it's hard for farmers to tell whether the fertilizer or seeds they are buying are fake. So there are lots of people willing to sell low quality stuff claiming it's high quality--in Uganda, the fertilizer is regularly diluted (30% of nutrients are missing) and the "improved seed" is fake 50% of the time. Classical economics tells us that markets will drive out the low quality products as people learn who is a reliable seller; or that the market will collapse and no one will be willing to buy the fertilizer or seeds at all. But farming, like almost every other human endeavor depends on lots of factors, not just these inputs. And so it's not only hard for farmers to tell whether they were sold a "lemon" even even after using it. Did their crops underperform because the were sold fake inputs or because the weather was bad, or they used it wrong, or their land was too degraded, or there were too many of a certain kind of pest, or because they were sick during the planting season, etc.? After all, some people buying the fertilizer and seeds did get good stuff and have high yields, so it's even harder to tell where the problem lies. So the market doesn't collapse, and low-quality sellers/products don't get driven out of the market but farmers also--for good reason!--don't invest in the inputs as much as would make sense based on the theoretical productivity boost.

Here's where the rant, and the weird introduction to the item, comes in. This situation is incredibly common: in most of life it's hard to tell whether some input--be it technology, or practice, or advice, or an employee--is high quality before you use it, but also after you use it because of the complex nature of most of life. This basic fact seems to be ignored frequently as researchers, policymakers, and advocates try to explain behavior. In almost all our endeavors we are in a Dunning-Krueger low quality equilibrium. We don't know enough to tell high quality from low quality ex ante, or ex post (yes, I'm a Calvinist). Determining causality is hard--even the most highly trained economists and social scientists get it wrong all the time! What hope does the average human have of looking at a complex system and determining which of the hundreds of factors involved was responsible for what portion of the outcomes? Behavioral economics explanations for sub-optimal choices are tempting because they tend to skirt this core issue. True, cognitive biases and limited attention exacerbate these problems and nudges can yield improvement on the margin, but figuring out what matters is hard (an opportunity to link, yet again, to one of my favorite papers, [Not] Learning by Noticing [the wrong things].

This is why Amazon or any crowdsourced product reviews are worthless. And it's why most people, regardless of their financial literacy, can't consistently tell which financial products are good for them and their situation. And it's why evidence-based policy is such a hard sell--when a policy with strong evidence behind it fails to live up to expectations is that because the advice was bad, the implementation was bad or circumstances changed?

Low quality equilibria are everywhere, defeating them is hard, and that's the sobering challenge we face.


2. Digital Finance: Staying in the ranting realm, here's a piece about digital financial services in China that keeps making my eyebrows try to climb into my hairline. The opening point is spot on--digital finance is paying too much attention to Kenya and not enough to other places, particularly China where adoption and use is much, much higher. But the piece has a not veiled at all assumption that digital financial services are an unalloyed good, and an only thinly veiled praise of authoritarian structures.

China doesn't have the same financial exclusion problems that most other countries have (though of course the very poorest are also pretty permanently and even more completely excluded in a digital environment), where private sector providers ignore or actively discourage lower-income customers. But authoritarian structures--whether they are the government, or monopoly private providers like AliPay and WeChat--will exclude people on other criteria. And that will be very bad for those people. I feel like we need a new version of an old saying: the only thing worse than being excluded by capitalists is being excluded by authoritarian monopolies.


3. Our Algorithmic Overlords: Score one for the human beings, sort of?. Betterment, one of the original "algorithmic" financial advisors announced this week that it's adding (even) more human advisors. Apparently people like asking human beings questions, or at least having someone to talk to. That's a trend that Tyler Cowen sees as the actual outcome of increased use of AI and robots: the jobs that humans will do will all be marketing jobs (and honestly, that's what a financial advisor really is, a marketer).

That doesn't bode well for increasing productivity, or wages. Most marketing is a zero-sum game with a few big winners and mostly losers. Here's Neil Irwin on another way of looking at the productivity slump in developed countries and the low-quality jobs equilibrium we seem to be in. Reminds me of Lant's Rant about labor-saving robots (in Uganda!).

Meanwhile, Mark Zuckerberg and Elon Musk are arguing about AI risks and people are choosing sides.

4. Strugglin' in the USA: Prosperity Now, formerly CFED, has a new scorecard on the state of Americans' finances with the takeaway being, "getting by but not getting ahead, citing USFD research on income volatility as one of the key aspects of American financial lives today. One of the more interesting possibilities for helping people deal with volatility and balance short-term and long-term savings needs is now dead: the Trump Treasury is canceling MyRA. I would rant, but really, who has the energy to rant about the Trump administration right now? Note the article title focuses on retirement but the most interesting part of the MyRA was it's potential use as an emergency savings vehicle.

With the death of a savings vehicle, here's some news on a borrowing vehicle: Noah Smith writes on work suggesting people are much better off (consumption rises in all periods) when payday lending is banned. The implication is that very little payday borrowing is funding actual consumption emergencies and being used for reckless spending instead. If payday were banned, perhaps people would turn to Panhandlr (hattip to @matt_levine for the name). I suppose you could file that under digital finance as well, but that would have required putting two rants into one item.


5. Methods: Marc Bellemare, who is also responsible for pointing me to the Uganda paper in Item 1, has a nice post, building on a Twitter thread from Beatrice Cherrier, about the history of Agricultural Economics as a semi-separate discipline and applied economics. It's definitely worth reading all the way through.

And if applied economics wasn't hard enough for you, here's a proposal to make the cut-off for statistical significance p=.005 (10 times harder than the current standard). That sounds less useful to me than doing away with p-values entirely.

From the  DFSLab post described above --obviously not the original source, but I can't figure out where it originally came from. Minor rant: I get very frustrated by category errors in digital finance metrics which exclude card payments from fintech. Cards are fintech! There is nothing special about a phone!

From the DFSLab post described above--obviously not the original source, but I can't figure out where it originally came from. Minor rant: I get very frustrated by category errors in digital finance metrics which exclude card payments from fintech. Cards are fintech! There is nothing special about a phone!

Week of July 17, 2017

Editor's Note: The faiV is brought to you this week by the Aspen Intitute's Financial Security Program EPIC team: Joanna Smith-Ramani, David Mitchell, Katherine McKay, and Katie Bryan. Their views, etc. though YouTube links are probably mine. Check out their work on income volatility and on consumer debt at aspenepic.org. I'll be back next week. 

1. Weaponized Data and American Inequality (Part 3): We learned a lot in reading the faiV’s summary and corresponding links detailing the minimum wage debate consuming economists across the country. While we haven’t reached our own conclusion about whether a $13 minimum wage in Seattle is or isn’t too high, we are following how some state legislatures across the country are actively rolling back minimum wages established by municipal governments. Example? St. Louis was dealt a big blow and the city has received a lot of press this summer.  


(ICYMI the debate, here and here are the two papers that offer opposing outcomes of Seattle’s minimum wage increase. If you don’t have time to read the papers, here’s a fun breakdown from Vice.)

2. Living for the City: CityLab profiled recent research on the intersection of urban development and economic inequality, making us think back to Stevie Wonder’s “Living for the City.” Still relevant. And beautiful. A new study out of the University of Idaho looks at 639 urban counties in the US and the factors that determined when they felt the effects of the 2006-2010 recession. Rarely do we see the Gini coefficient being used in the context of domestic inequality – but we should use this metric more often. Consequently, we were really excited to see this interactive map of the Gini coefficients of counties across the US.

For more on cities, another CityLab piece looks at how housing policies worldwide will only exacerbate urban inequality and housing crises. And this story on how inefficient tax codes, high cost of living, and migration, by both companies and residents, are sending the state of Connecticut spiraling, makes us rethink how we view the fiscal policies of traditionally blue, wealthy states.


3. Income Volatility, Short-Term Savings, Retirement (Oh My): Over the last 18+ months, our team has conducted a deep dive on both the impact income volatility – large fluctuations in week-to-week and month-to-month income – has on US households and potential solutions for mitigating the problem. Our latest briefs look at the role wage insurance could play in helping families cope with job loss or reduced wages and how shortfall savings can serve as a buffer during financial emergencies.

Because we care about both short-term financial stability and long-term security, we also spend our days thinking about comprehensive policy solutions to help expand access to retirement savings opportunities. In our process learning about more about income volatility, we’ve realized it’s particularly hard to save for the long-term when short-term savings are lacking. This new paper looks at the effect income shocks have on retirement savings (the stats aren’t pretty: “96 percent of Americans experience four or more income shocks by the time they reach 70”), and *mark your calendars* later this fall, we’ll be publishing two papers on how volatility affects retirement savings. 

4. China, China, China:
Cash is king. Right? Hard currency has been with us for nearly three thousand years, after all. But maybe not for much longer. As one reporter details, visit urban China and you will likely, “have to deal with being locked out of China’s online payments infrastructure.” Sweden is also rapidly moving to a cashless economy. “Out of Sweden's 1,600 banks, 900 don’t do cash— you can’t deposit it or withdraw it.”

The advantages of going cashless? The claimed benefits tend to be 1) speed - for both consumers and banks, removing cash from transactions is faster 2) curbing illegal activity – Sweden saw a decrease in drug trafficking and illegal employment and 3) financial inclusion – this one needs to be fleshed out more, but we think and are hopeful that going cashless will require more people to open bank accounts, and the benefits of being “banked” are many.  That said, some are concerned that going cashless could undermine other financial inclusion efforts. We may be able to learn from how this plays out in India
, where recent moves toward becoming a cashless economy have disrupted many poor communities. 

5. Consumer Debt: EPIC’s new topic is consumer debt. Debt is back to pre-Recession levels, subprime auto lending is booming, and we have many many questions: how does income volatility impact people’s ability to manage their debt? And, will we pay off our student loans before our children apply to college? Maybe… if you’re one of thousands of distressed borrowers who learned this week that their private student loans may be forgiven. Because the investors who sued them are unable to prove ownership of nearly $5 billion in student loans. It’s like the foreclosure crisis all over again!

U.S. consumers now have a record $12.7 trillion in debt, leaving many wondering whether it’s time for concern. There’s no easy answer. Based on a new paper from UBS, Business Insider reports “The poorest Americans are suddenly worried about repaying their debts.” We don’t know about that “suddenly” part, but you can’t judge a story by its headline, and those making less than $40,000 are increasingly concerned.

Do you know what it means? Source:  Zillow.com  via  The Basis Point  via  Ritholtz.com . Apparently none of them know what it means either. I feel like it must have something to do with the serial linking but that's probably wrong. I'm more confident it might have something to do with the record-low labor force participation rate, not charted here.

Do you know what it means? Source: Zillow.com via The Basis Point via Ritholtz.com. Apparently none of them know what it means either. I feel like it must have something to do with the serial linking but that's probably wrong. I'm more confident it might have something to do with the record-low labor force participation rate, not charted here.

Week of February 13, 2017

1. F*ck Nuance: I know what you're thinking, but that's not what this item is about. It's actually about Kieran Healy's forthcoming paper in Sociological Theory called, well, F*ck Nuance. He argues that the rising demand for "nuance" in sociological theories inhibits clear thinking and useful research. It reminds me of what I've heard a lot of economists say about the demand for complicated formal models in economics papers. It's not what Healy intended, but here's a story about a FinTech start-up ditching FICO scores while offering "the fastest [credit] on the market," which certainly doesn't bother with any nuance like whether the product is good for customers.

2. F*ck Impact: So that's not what Jishnu Das's blog post is actually titled, but it might as well have been. Das (quite ironically, as David McKenzie noted) blogs about how researchers being held accountable for having impact beyond academia, for instance by writing blog posts, is a drag. It's worth reading because there are some valuable nuggets especially about the "poorly specified model" of impact in use and the breakdown of trust between funders and researchers. If you were interested in hearing the thoughts of some development economists who care a lot about having an impact, you could do worse than checking this out. On a different note, the subdued reaction to the post convinces me that the development blogosphere really is dead.   

3. Commitment Savings: In the WSJ, Bernartzi and Beshears argue that evidence from commitment savings evaluations suggest that restrictions around retirement accounts should get even more severe, particularly citing the original Ashraf, Karlan, Yin work in the Philippines. It's true that retirement accounts in the US are very leaky, but the cause isn't just temptation or present bias as Benartzi and Beshears imply. Volatility of incomes and expenses seems to play a large role. Here's a video of Dean Karlan discussing the possibility that less restrictive accounts may work better.

4. Mobility: Kevin Williamson writes in National Review that more should be done to help the poor move to better opportunities. Of course, he's only talking about mobility for the poor within the United States (and he weirdly cites the circa 2000 early evaluations of Moving to Opportunity which were contradicted by later work, but then overturned again by the more recent, more comprehensive work from Chetty et al) and never seems to consider the implications of his argument for trans-national mobility. Here's what I wrote not too long ago about philanthropy stepping in to help the people of Flint, MI move (and here, channeling Hirschman). Speaking of philanthropy, I was disappointed to see that the semifinalists for the MacArthur 100&Change $100 million grants didn't include anyone working on mobility. They're described as "eight bold solutions" but mostly seem to be scaling up ideas with mixed evidence that have been around for a quite a while.


5. Nuance Lives!: At least for Daniel Kahneman, who responds to a blog post analyzing the Replicability Index of the papers on priming cited in Kahneman's Thinking Fast and Slow. Kahneman explains what he missed and how he came to believe too much in the priming results. The nuance comes at the end where Kahneman states that he has not "unbelieved" the individual studies and that he still believes that priming is possible, but has changed his views about the size and robustness of priming effects.

Credit Suisse's 2016 Global Wealth Report provides some perspective on why trans-national mobility is so attractive, and why it's meeting more resistance than in the recent past.  Source :  Credit Suisse Research Institute

Credit Suisse's 2016 Global Wealth Report provides some perspective on why trans-national mobility is so attractive, and why it's meeting more resistance than in the recent past. Source: Credit Suisse Research Institute

Week of January 2, 2017

Pre-AEA/ASSA Edition

1. In Memoriam: The new year began with news of the deaths of two important thinkers on development, economist Tony Atkinson and philosopher Derek Parfit. Here's Tony Atkinson's view of his most important work. Here's a celebratory post from the World Bank's Let's Talk Development blog, here's Beatrice Cherrier's overview of his work as the "founder of modern public economics," and here's a Foreign Affairs piece of Tony's from late 2015, as always focused on inequality and what can practically be done about it. I'll save links for Parfit until next week.

2. Microcredit: I have a new post at Next Billion on what I consider to be one of the most important new research papers on microcredit, an examination of the size and prevalence of subsidy by Cull, Demirguc-Kunt and Morduch. It documents that subsidy is widespread but small--in other words, that delivering pro-poor financial services isn't free, but that it is cheap. Over at CGAP, Greta Bull offers her thoughts on the four drivers of change for financial inclusion in 2017. And here are the most influential posts of 2016 at Next Billion.

3. Cash Aid and Basic IncomeI'm trying not to turn the faiV into a cash and basic income newsletter, but it is a topic that is drawing a lot of attention lately. In the UK, one of the tabloids attacked aid for giving cash to poor people (as opposed to giving cash to rich people?). The Atlantic ran a piece about the history of cash aid in philanthropy and how it is changing current practice. Here's a short history of the idea of basic cash income and here's a round up of both history and current things going on. If you're at #ASSA2017, there's a reception Saturday night to learn more about the Y Combinator basic income experiment in Oakland.  

4. Kahneman and Tversky and Lewis: You've probably seen that Michael Lewis has a new book about Kahneman and Tversky. In case you haven't, here's Sunstein and Thaler's review of the book. Here's a piece by Walter Isaacson about Michael Lewis. And here's a piece from Slate about the irony of Kahneman, our teacher about how easy it is to be wrong, and his faith in results that depended on small samples and have ultimately not held up to replication.


5. Savings: On a more prosaic level, how and why people save remains an important question. Here's Guerin, Kumar and Venkatasubramanian on the use of ceremonial expenditures as a means of informal saving at the IMTFI blog. In related news, Bill Maurer of IMTFI has a book coming out this year on the artifacts of money and transactions (via Diane Coyle's round up of the spring catalogs from econ publishers)

Bonus Ad: Today is the official release date of my book Experimental Conversations: Perspectives on Randomized Trials in Development Economics. Check it out at the MIT Press booth at #ASSA2017 or order one from Amazon (though it now says temporarily out of stock. Is that good news or bad news?)

The  second post in David Roodman's epic review  of the evidence for deworming is now up at GiveWell. The first post looked specifically at some of the worms papers; this post looks at whether results from those papers can be reasonably applied to other contexts. It's a long read but thoroughly worth it. Source:  David Roodman/GiveWell

The second post in David Roodman's epic review of the evidence for deworming is now up at GiveWell. The first post looked specifically at some of the worms papers; this post looks at whether results from those papers can be reasonably applied to other contexts. It's a long read but thoroughly worth it. Source: David Roodman/GiveWell

NEUDC 2016 Special Edition

Editor's Note: The Northeastern Universities Development Consortium (NEUDC) conference was hosted at MIT this weekend. Over two days you get to see an enormous amount of new development research by mostly younger researchers. I held back on faiV this past week, to bring you this special edition--featuring the five papers I found most interesting (of those that are shareable) and since there are far more papers presented than any one person can take in, I recruited Jessica Goldberg, a development economist at Maryland (responsible for interesting papers like this); she in turn recruited Emily Breza (responsible for interesting papers like this) of Columbia GSB and soon of Harvard to contribute; and Lee Crawfurd (also known as Roving Bandit in the glory days of the development blogosphere) of CGD and a PhD candidate at Sussex to weigh in with their own favorites.

Here's my list of the 5 most interesting papers from the weekend:

1. Mentors for Microenterprises in Kenya: Brooks, Donovan and Johnson assign high profit microentrepreneurs to mentor newer entrants. That's a particularly interesting way to potentially change the trajectories of microfirms. The mentored firms see a significant jump in profits driven by learning how to cut costs but don't maintain the gains once mentorship stops.


2. Grants and Plans for Senegalese Farmers: Ambler, de Brauw and Godlonton give $200 grants and develop a farm management plan for smallholders. The grants boost production (by more than $200), but the gains seem to fade out, though higher stock of assets remains. Farm management plans don't have a measurable impact. I find this interesting for many of the same reasons as #1: figuring out how to boost profits of small enterprises is near the top of my list of urgent program/policy questions.    

3. Seasonal Migration in India:  Imbert and Papp use NREGA and choices about short-term migration to better understand why the large gap in earnings between rural and urban migration doesn't lead to more seasonal migration. They estimate that more than half of the income gap is consumed with higher living costs in urban areas, with the rest due to non-economic costs--like being away from home and "hard-living", (e.g. sleeping on the street). There are some interesting policy applications for the design of rural public works/income programs and the development of migration finance and support programs. 

4. Crop insurance contracts in Kenya: There's a general consensus that insurance is one of the most promising margins to help poor households, but we're a long way from figuring out to efficiently and effectively deliver an insurance product that people will take up. Casaburi and Willis study an insurance program in Kenya where farmers can delay the premium payment--noting that premia are usually due at the point where farmers are most liquidity constrained (they can delay payments because the crop is sugarcane farmed under contract so premia can be collected from harvest proceeds). They find a 67 percentage point boost in take-up, with take-up highest among poorest farmers.


5. Saving and Smoothing: One of the ways that financial services should help poor households the most is by boosting their ability to smooth consumption and to absorb shocks. But access alone isn't enough if other constraints prevent households from using the tools like savings and insurance effectively. Aker et al. look at savings nudges to help Senegalese households save and budget. They find that lockboxes and reminders don't influence spending (particularly spending on festivals) but do seem to help households plan ahead and therefore be less susceptible to other shocks. There is a lot of heterogeneity in results though.
 

Jessica Goldberg's, with an assist from Emily Breza, list of 5 most interesting papers:

1. Gambling and Saving in Uganda: Betting on sports events is common among urban Ugandan men and, for those who partake, a substantial expenditure. This paper by Sylvan Herskowitz uses variation in bet outcomes and lab-in-the-field experiments to build a case that betting is a rational strategy for asset management in an environment with low perceived returns to savings.  It’s a novel topic — while we are learning a lot about savings, credit, and even mobile money, I haven’t read anything else about sports betting in developing countries.  But neither the topic nor the approach are trivial, and taking seriously the model that would rationalize the bets is commendable.

2. Workfare and Welfare: This paper from Bhanot, Han, and Jang uses a lab-in-the-field experiment in Kenya to test various attributes of common cash transfer or public works programs, and therefore contributes to the design of such programs. While many evaluations of cash transfer or public works programs focus on outcomes like employment, income, or consumption, this paper also measures subjective wellbeing, which is improved by requiring participants to exert effort in exchange for payment. This adds an additional justification for work requirements rather than cash transfer schemes, which is important since public works can be more expensive to administer and do not always achieve self-targeting.

3. Seasonal Migration in India: [Ed. Note: same paper as above] There’s a lot written about NREGA, but it’s a massive program that not only shares features with workfare programs in many other countries, but also operates at a scale that lets us understand what might happen programs that were rationed were instead made available to more people or for longer durations. Clement and John already have one really important paper about the equilibrium effects of NREGA on private sector wages.  Now, they show that NREGA reduces seasonal migration from rural areas to the cities

4. Crop insurance contracts in Kenya: [Ed Note: same paper as above]: This paper is a nice insight into understanding the demand for insurance, even though the specific pricing structure may be hard to implement outside of a closed marketing chain.  It’s also a contribution to the literature about how the timing of financial access affects outcomes.

5. Economics of Foot Binding: Fan and Wu look at the rise and fall of foot binding in China from an economic lens, particularly noting how the practice interacted with a gender-biased meritocracy and the physical demands of women's labor.



Lee Crawfurd's list of 5 most interesting papers:

1. Football and ethnicity in Africa: When their national football teams win, Chauvin and Durante find, Africans report weaker ethnic identity. [Ed. note: I'm sure Sepp Blatter is emailing this to the Nobel committee as I write]

2. Teaching at the right level in India: Second coolest paper--Muralidharan, Singh, and Ganimian find huge effect sizes from a computer system that gives kids tests, adapts to their level, and gives feedback.

3. Vote-buying in India: Green and Vasudevan are pretty modest about reducing vote-buying by 2 *million* votes with a radio campaign.

4. Aid, hospitals, schools and violence in Afghanistan: Child finds that US health projects reduced conflict, but education projects increased conflict.

5. Trader costs in Nigeria: Startz documents and explains trade costs for market traders in Lagos. We usually focus on how developing countries can export more, but there are also big welfare gains to be had from making importing easier so consumers get cheaper and better goods.

Andreyanov, Davidson and Korovkin find suspicious bidding patterns in Russian sealed-bid electronic procurement auctions, estimating that up to 10% are affected by corruption and up to 30% by collusion among bidders. According to Jessica Goldberg, their presentation has an even more striking chart showing winning bids occurring in the last minute.  Source .

Andreyanov, Davidson and Korovkin find suspicious bidding patterns in Russian sealed-bid electronic procurement auctions, estimating that up to 10% are affected by corruption and up to 30% by collusion among bidders. According to Jessica Goldberg, their presentation has an even more striking chart showing winning bids occurring in the last minute. Source.

Week of October 10, 2016

1. Digital Identity: A few weeks ago we featured a paper on the general equilibrium effects of NREGA in India, which depends on a universal ID system. Next Billion takes a look at India's digital ID system and compares it with Pakistan's program.

2. Insurance (Is Hard All Over): When you read about attempts to launch microinsurance programs for developing countries, it can often seem like insurance markets work very well in developed countries. But insurance is hard no matter where you are, and may be getting harder due to climate risks and our human failings in thinking about large but rare risks. Here's a new brief from the Penn Wharton Public Policy Institute looking at how under-insured many American homeowners are and proposing some steps to get those people to buy insurance

3. Shocks and External ValidityTypically conversations about the external validity of an impact evaluation focus on whether a finding in one place applies to a finding in another place. Here's a new paper by Rosenzweig and Udry looking at external validity issues in the same place but in different times, specifically at how important aggregate shocks can be when impact is likely to vary over time (as with agriculture or schooling). I'm not sure how big a problem not considering time variance is, but it is a good reminder to examine assumptions when applying findings from impact evaluations.

4. Crops, Volatility, Saving and Malnutrition: There's been a lot of progress around the world in reducing childhood malnutrition and stunting, but rates are still shockingly high in India, given the economic development in the last few decades. Here's some new research that establishes that households "save" to deal with volatile prices of pulses by stockpiling wheat (which is less nutritious). In part, saving in wheat is driven by the cost of formal accounts to save in cash.


5. C-C-Ts in the USA: Doesn't quite roll off the tongue like R-O-C-K does it? MDRC, which ran the evaluation of the Family Rewards CCT program in New York, has a new cost-benefit analysis of the program (of note, taking Rozenzweig and Udry seriously, the program was run in 2007, and depending on the exact timing there was an aggregate shock during the program or shortly thereafter). They find that on average it cost $1.07 to deliver $1.00 of value to households, and the program "did not produce positive net present value for taxpayers."

A new way to represent funding needs and overhead costs for non-profits and social enterprises.   Source: Nonprofit Assistance Fund

A new way to represent funding needs and overhead costs for non-profits and social enterprises. Source: Nonprofit Assistance Fund

Week of September 26, 2016

1. Jobs! Jobs! Jobs!: For quite a few years now, my mental model has been that most poor households are "frustrated employees, not frustrated entrepreneurs." In other words, most people aren't held back from their entrepreneurial dreams by lack of access to credit, but they are held back in their dreams of having a job by the lack of jobs. That view is tied heavily to the fact that most microenterprises don't grow at least in part because the owners don't appear to be trying to grow them. This week Chris Blattman and Stefan Dercon released a new working paper about an experiment in Ethiopia where they were able to compare factory jobs to grants for self-employment. They find, among many other details, that those who randomly receive factory employment leave the jobs quickly and those who receive grants for self-employment tended to stay in self-employment and out of the industrial sector. There is a lot going on in this paper so it requires careful reading and some thinking, but it will definitely alter at least my confidence level in my priors.

But the discussion of the new Blattman and Dercon paper revived my memory (hat tips to Rachel Glennerster and Asif Dowla) of this Heath and Mobarak paper on the positive impact of factory work in Bangladesh so there's multiple updating going on for me this week.

I discuss this experiment with Chris Blattman a good bit in my upcoming book--it will be available on January 2nd, 2017. Sign up here to get notified when it's available for order.


2. But Wait, There's More Jobs! Jobs! Jobs!: Karthik Muralidharan and Paul Niehaus have a new paper based off of one of the world's largest RCTs, the roll-out of the new and improved NREGA guaranteed work scheme in India. They find that the program raised incomes of poor households dramatically, but that most of the gains comes from pushing up private sector wage rates, not from income from the program itself. Jonathan Morduch notes that the jump in wages was a factor in the ultra-poor program he studied in Andhra Pradesh not having much impact (many participants left the program to take jobs).

The Muralidharan and Niehaus paper also brings to mind this earlier paper from Breza and Kinnan looking at something similar--how the availability or unavailability of microcredit in India to fund self-employment had generalized effects by altering wage rates. That paper is one of the reasons I believe in the "frustrated employees, not frustrated entrepreneurs" thesis, so now my brain hurts.

3. Even more on Jobs and Wage RatesThe New York Times has a new "Room for Debate" with several perspectives on whether the rising minimum wage in the US is raising incomes and how much of a role minimum wage hikes had in the reduction in poverty reported in the latest census report.

4. FinTech and Intrahousehold Bargaining: Simple, a US FinTech company announced this week a new product that tackles the age-old problem of intrahousehold bargaining head on: a hybrid shared account. In the new Simple account, two people have separate accounts, but each can see the other's activity and they can mutually contribute to and track shared goals (like savings). It's an interesting product for a variety of situations beyond traditional romantic partnerships like parent/child or child/parent in situations of aging parents, or in situations where disability requires something less than complete guardianship. I really hope someone is doing something randomized on this to test effects.
In other US FinTech news, D2D Fund has changed it's name to Commonwealth and EARN has a new version of its Starter Savings Program.


5. And Now For Something Completely Different: Some non-financial but definitely interesting and thought-provoking things from this week: Maria Konnikova has a lengthy article pushing back on the "practice makes perfect" conventional wisdom, and particularly the 10,000 hours hypothesis. Tyler Cowen "doesn't believe in progress, and he wishes you didn't either."  Duncan Green on "Why is it so hard for academics and NGOs to work together?" NYU Law has launched what it says is the first center on law and social entrepreneurship at a law school. Cass Sunstein on "the real reasons so many Americans oppose immigration reform." Having five things in the fifth point of the faiV just seemed right.

Masquerading as a video, here's Paul Niehaus talking about the logistics of GiveDirectly and delivering cash transfers.

Masquerading as a video, here's Paul Niehaus talking about the logistics of GiveDirectly and delivering cash transfers.

Week of September 12, 2016

Editor’s Note: I’ve been 'away' for a while finishing up two books: Experimental Conversations, a collection of interviews about RCTs in development economics and evidence-based policy (pub date January 2017) and The Financial Diaries, based on the US Financial Diaries project (pub date March 2017). I briefly entertained the idea of a “catch-up” faiV, but that might have become the faiVhundred so herewith we’re back to (sort of) five items from (mostly) this week.

1. Income, Poverty and Volatility: The big news of the week in the US was the release of the US Census Bureau’s report on income, showing strong gains across the board (but best for lower income groups) and the largest drop in the poverty rate since 1999. As always, the story is more complicated than the headline statistics. Annual income measures hide year-to-year and month-to-month volatility. And volatility seems to be rising. That means that even though the poverty rate is falling based on annual income, the number of households that spend part of a year in poverty or bounce in and out of poverty from year to year may be increasing.

Aspen EPIC has a wealth of new materials on the topic of volatility including videos, interviews and blog posts.

2. Measurement: Also prominent in US news was the announcement that Wells Fargo, one of the country’s largest banks, had fired 5300 employees and paid a $185 million fine for creating millions of accounts without customer consent (to hit management metrics). Matt Levine has the most useful reporting on the issues and the problem of measurement, calling it an “evil genie...it grants your wishes, but it takes them just a bit too literally." Case in point, Indian banks have apparently been doing essentially the same thing as Wells Fargo, depositing 1 rupee into dormant accounts, so they don't appear dormant. I won’t miss the opportunity to plug Dan Rozas’ work on the large gap between savings accounts and savings account usage in microfinance banks around the world, not just in India.

3. Digital Finance: Visa announced the roll-out of mVisa in Kenya with near-term expansion into Uganda, Tanzania and Rwanda and possibly Nigeria. I must admit I’m a bit confused as mVisa ran a pilot in Rwanda beginning back in 2013. Did that shut down? In any case, mVisa is a significant challenge to m-Pesa, perhaps the first significant challenge, because it works differently—it’s cross-bank and makes customer-to-merchant payment (as opposed to p2p transfers) easier, though it does require smart phones. In other digital finance news, while mVisa is attempting to expand in east Africa, mobile money has now disappeared from South Africa as MTN followed mPesa by shutting down the service in the country because of lack of use. I’ve also seen reports that mobile money use is falling in Nigeria but not sure about how reputable the source is. Anyone know more?   

4. Behavioral Finance (and more): The Urban Institute released a report on a test of a behavioral intervention to help consumers reduce credit card debt. Working with a credit union they tested "rules of thumb" messages to discourage use of credit cards and found the message “Don’t Swipe the Small Stuff”, encouraging people to use cash for small transactions rather than a card, reduced their balances by $104 in six months. To put the result in context, the gains to households (reduced debt/increased savings) were equivalent to 60% of the matched savings incentive in the SaveUSA program, for less than 1% of the cost. On the other hand, the finding that encouraging people to use cash reduces their spending in helpful ways presents something of a problem for boosting the use of mobile money.

In related news, here’s the White House’s Behavioral Sciences Team’s 2016 report.


5. Poverty Measurement: Sort of tying all our topics for the week together, the Grameen Foundation and Innovations for Poverty Action just announced that the Progress Out of Poverty Index will be moving to IPA with funding from several institutions, so that this particular measure of poverty, designed to be operationally useful for MFIs, will continue to be developed and, hopefully, improved.      

Since we're on the topic of poverty measures and volatility and net savings, here's an infographic from the US Financial Diaries, on exactly those issues. (Click on image to see entire infographic on US Financial Diaries website.)

Since we're on the topic of poverty measures and volatility and net savings, here's an infographic from the US Financial Diaries, on exactly those issues. (Click on image to see entire infographic on US Financial Diaries website.)

Week of August 8, 2016

Attack of the Zombies

1. Night of the Living FinLit: I'm increasingly using the persistence of financial literacy programs as a proxy for the "evidence-based" movement. Here's a story about a new $5 million investment in FinLit for low-income youth in Chicago, where apparently half the curricula is devoted to day-trading stocks. Most remarkable is that the story spends its time wringing its hands about the irony of financial services firms funding FinLit, rather than the fact that it doesn't work in any meaningful sense. If the evidence-based movement can't kill FinLit as we know it what hope is there for other policy domains?

2. Priming Zombies:
No the zombies aren't doing the priming, nor are they being primed. Here's a new review of studies of the effect of "eyes" on influencing social behavior--it's one of the "neato" findings in the priming literature that became so popular in the last decade. Like recent replications of other priming interventions, the widely reported effects don't stand up. How long will priming hold on as a zombie idea? 

3. Homelessness Interventions: People tend to have pretty strong priors about what to do about homelessness and panhandlers--it's a policy space that seems like its filled with zombie ideas and interventions. Here's a new study of a natural experiment in providing up to $1500 cash to people at risk of losing their housing in Chicago. It finds that the one-time cash payments significantly reduce homelessness up to 2 years later. Here's a (largely evidence-free) news story about a program in Albuquerque to provide public works jobs and expedited social services access to panhandlers. Here's Matthew Desmond's best-selling recent book, Evicted.   

4. Efficient Markets and Behavioral Finance: No, I'm not calling either a zombie idea. But here's a conversation between Gene Fama and Richard Thaler where they discuss their differences. Here's Justin Fox's book on the history and impact of some of these ideas. Both very good reads.

5. New Paper Round-Up: A number of interesting papers have crossed my desk this week. Here's a strained attempt to continue the theme: Is self-determination a zombie idea? Steven Levitt on making decisions by coin flip. In a way defaults are zombies: Blumentstock et. al. on savings defaults in Afghanistan. Zombie savings accounts: Dupas et. al. on low take-up and use of no-frills savings accounts in Uganda, Malawi and Chile (There's a lot more there, worth looking at, really). See also Rozas. And I've got nothing for this one: Brune and Kerwin on the effect of monthly vs. weekly and Friday vs. Saturday paydays in Malawi.     

Bonus Update: A few weeks ago we featured some musings on client protection in research. Here's a new piece on client protection in digital payments, another important topic that doesn't get much attention. Here's an old piece of mine on the importance of making digital payment systems pro-poor

Week of July 18, 2016

Editor's Note: I barely resisted the temptation to title every item here "Why not What"

1. Why not What: Chris Blattman posts notes from a recent talk he gave at DfID arguing that focusing too much on "what works?" is a mistake. Via Ryan Briggs on Twitter, here's Angus Deaton's 2010 paper making much the same argument.     

2. Why not What, Part II: 
A new paper from Buera, Kaboski and Shin looks at a host of "well-identified evaluations of the impacts of micro-financial interventions" including the microcredit evaluations, the targeting the ultrapoor programs, and cash grants to try to understand why the results are what they are.

3. American Financial Security (or lack thereof): Americans confidence is their ability to afford retirement is creeping up again, but it's not clear why. A new HSBC study finds that 64% of respondents over age 70 are financially supporting others. Andrew Yarrow writes about "the 45%" who are paid less than $15/hour, are "asset poor" and do not have access to employer-sponsored retirement-savings (note that these are not all the same people).

4. Digital Finance "Expansion": Pablo Garcia Arabehety has a perspective on why digital finance a la M-Pesa has not expanded rapidly in Latin America: proximity and simplicity of bill payment and person-to-person transfers (which account for 96% of usage) was already sufficient. Meanwhile, the Kenyan government is proposing to expand its regulation of M-Pesa to enable tax collection.     

5. Measuring Outcomes: Bobbi Gray writes about the balance between "hard" and "soft" outcome measurement, particularly in terms of measuring domestic violence and fear. Those softer measures can play an important role in understanding "why" as well as "what."

Week of April 4, 2016

1. Poorest of the Poor: There's new data from the Bangladesh "graduation model" evaluation that provided livestock and training to very poor women. After three years, results were strikingly positive. Now there's a 7 year follow-up that suggests those gains hold for the long-term and may even continue to increase--importantly with no evidence of negative spillovers and some evidence of positive spillovers to others in the village. Development Impact

2. Debt vs Savings: If you get an influx of cash, should you pay down debt or build up savings? It's a hard question to answer. Allison Schrager argues that paying down debt is conventional wisdom (is it?) but that saving is better than paying down low-interest, long-term debt for millennials. Of course, by rough calculation only 30% of millennials have such debt while the average American household carries $15,000+ of credit card debt. Quartz

3. Efficient Markets: Omar Al-Ubaydli and John List review the findings of field experiments on markets, finding that while there are behavioral quirks that limit market efficiency, many of those quirks disappear when participants have the chance to learn. A useful reminder when thinking about the use of nudges and the application of behavioral economics.
NBER

4. Efficient Markets in Philanthropy: Speaking of efficient markets, I've argued that despite much protestations, charitable giving is an efficient market after all. Here a documentarian discusses the role that story-telling ("propaganda") plays in reinforcing donors' perceptions and expectations, and "legitimi[zing] an entire crooked aid system." Two Dollar Challenge

5. Remittances: Donald Trump revealed his plan for coercing Mexico into paying for a border wall involves threatening remittance flows: a "ludicrous pipedream" that will help money launderers and hurt the poorest. Politico

The rising relative cost of being poor, as seen in housing costs. Source:  Pew

The rising relative cost of being poor, as seen in housing costs. Source: Pew

Week of August 31, 2015

1. Employment and Wages: Despite signs of an improving economy such as lower unemployment rates and increased productivity, take home pay for low-income workers in the U.S. has fallen since 2009. The New York Times

2. Behavioral Economics: Reminders are an oft-cited example of nudges that can improve welfare. Sometimes not following through isn't about forgetting or procrastination, though. An experiment using reminders to pay for child support in Ohio finds negligible effects. MDRC

3. Microfinance: "In the annals of Twitter spats, this is no Nicki Minaj vs. Taylor Swift. But even this muted public shade-throwing is relatively rare among anti-poverty stalwarts of Counts’ and Karlan’s caliber. And since IPA and Grameen Foundation are both NextBillion content partners, I feel the urge to act as referee." (Shockingly, reading some of the comments is worthwhile.) NextBillion

4. Mystery of Microenterprise: Efforts to increase revenues and profits at microenterprises through business training have been largely unsuccessful. But it's not because the business practices being taught don't matter find McKenzie and Woodruff in a new paper. NBER

5. Savings: A new report on digital savings provides an extensive overview of current products from around the world, with a specific focus on how they meet women's saving needs. Women's World Banking