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Week of May 7, 2018

1. Self-Referential Metadata: Last week's faiV included a link to an app to automatically extract data from charts. I joked it would be the most clicked link in the history of the faiV and it certainly was the most clicked link of the week, more than doubling the clicks on any other link. It was also the most clicked of the last few months. Second place was a review of The Financial Diaries, that unfortunately I suspect many people couldn't read more than the first page of (honestly, it's great, but it's not $45 for 24 hours great. And does anyone ever pay that? Why?).
In other faiV news, Gisella Kagy got in touch to let me know the link to her paper about differential profits by gender for Ghanaian tailors was the right one; and I ran into Leora Klapper who let me know that she forwards the faiV to many colleagues each week. And yes, both of those are really just an excuse to say writing the faiV often feels like shouting into the void. So if you do see stuff you like, or just appreciate the faiV generally, please do get in touch every now and then to let me know. And it's also OK to let me know when I'm getting too niche, too snarky, or you have something you think should be featured in the faiV.


2. US Inequality: It was at the Dignity and Debt Network inaugural meeting that I ran into Leora, and a bunch of other researchers working on household finance, debt and related matters. It was a sociology conference so I had to get used to a format that wasn't paper-centric, but, of course, my bias is to noticing papers. A particularly interesting one was by Barbara Kiviat and Rourke O'Brien finding that low credit scores lower the likelihood of a job offer for a female applicant and lowers the offered salary to black applicants. 
One wonders how such biases play out in the gig economy. Here's a piece on the growing use of 1-day gigs by restaurants and retail. It's practices like that which can make a job guarantee emotionally appealing. Here's Annie Lowrey on the growing momentum behind (very very) vague proposals for a jobs guarantee among Democrat candidates.  

3. Rotten Kin: I'm going to use that as a very tenuous jumping off point to rotten kin as a factor that I don't think gets enough attention in the political economy of job guarantees and universal basic income. At least I hear often about discrimination and racism as explanations for why people would oppose such policies (leaving aside disputes about the basic economics). But I think almost everyone has a cousin or uncle or sibling that they think it would be bad for to get a cash stipend or would abuse a job guarantee in some way. I think that plays a big part in people's skepticism, even if they don't voice it publicly because it's not a nice thing to say about your family.
Anyway, here's Munir Squires writing in VoxDev about "kinship taxes" on Kenyan firm growth finding a fifth of women and a third of men would be willing to pay, and pay a lot, to hide income from their networks. But that's just the tip of the iceberg. Think also of the ways that husbands and wives buy certain goods to protect income from each other. And then think about the rotten kin tax that Indian textile firms are paying based on Bloom, Mahajan McKenzie and Roberts' work--obviously that tax is less than the perceived tax paid if you hire non-relations as managers, but still.

4. Our Algorithmic Overlords: Guys, it's time for some philosophy theory. Stephanie Wykstra (who is one of those people who gives me feedback on the faiV) has a perspective on defining fairness and how we should think about whether algorithms being used in criminal justice are fair. This is something I think about a good bit, as witnessed in my review of Automating Inequality: I perceive a lot of folks giving human beings a really odd "benefit of the doubt" as more fair when compared to an algorithm, but simultaneously decrying systematic and institutional racism and misogyny (which exist! and are very bad! and we should do something about them!) that are the result of those same human beings beings who are supposedly more fair than the algorithm being racist and misogynist. For instance, check out the bureaucratic nightmare of fighting deportation.
This seems quite relevant: When Will Workers Follow an Algorithm? That's a newish paper from Kohei Kawaguchi who runs an experiment with vending machine operators and finds that by-and-large they won't obey the algorithm. Now I wish someone would go back to the seaweed farmers. This is the way future computational social science is going to find me by the way--references to seaweed farmers and isomorphic mimicry.

5. Some Other Stuff: It's late in the day. I want to go outside. But I know you've been eager to know which country is roundest. JP Morgan Chase Institute has a look at the financial impact of Hurricanes Harvey and Irma through the lens of the daily transactions of consumers and businesses in the affected areas. One of the ways we know that families around the world cope with disasters is remittances/informal transfers. Which is why we should be worried if global banks are cutting off correspondent bank relationships and therefore raising the costs of remittances.   

 

  From Richard Reeves, Katherine Guyot and Eleanor Krause, here's a look at differing definitions of what "middle class" means in the US (at least according to economists and researchers). Source:  Brookings Institute

From Richard Reeves, Katherine Guyot and Eleanor Krause, here's a look at differing definitions of what "middle class" means in the US (at least according to economists and researchers). Source: Brookings Institute

First Week of May, 2018

For the First Time in Forever

Editor's Note: I apologize if the phrasing on the first item triggers PTSD symptoms in parents of children under 10. In other news, the paywall revolution seems to be gaining steam. I may need to start a Patreon for the faiV to afford subscriptions, but for now I'm just mourning my two favorite columnists, Justin Fox and Matt Levine, disappearing behind Bloomberg's odd paywall. --Tim Ogden

1. Microfinance, Part I (Uses of Credit): For the first time in forever, it seems there's enough new and interesting stuff on microfinance to support not only one, but a couple multiple-link items. Let's start with a useful piece that summarizes findings from several studies that have loomed large in our understanding (or questions about) of how microenterprises use credit, and apparent differences between male-owned and female-owned enterprises. I do find the framing a bit odd, as I don't know anyone who interpreted the results as "women aren't as good at running microenterprises as men" rather than, "women tend to be constrained to operating microenterprises in less profitable industries." When the newer results from Bernhardt, Field, Pande and Rigol emerged, I think the standard take was, "Households optimally allocate credit to their highest-return enterprise." So I think the intriguing thing here is not "women vs men entrepreneurs" but "maybe the industries women are concentrated in aren't less profitable after all." And that makes me think back to a paper from AEA (there's no version online that I can find, but this seems to be a significantly revised version using the same data) finding that female tailors in Ghana earn less than male tailors because they are constrained to making womens' clothes, a sector where there is more competition and lower prices.
Another use of credit for poor households is not to invest in a microenterprise but to smooth consumption when income is seasonal (or volatile for other reasons). Here's a new paper from Fink, Jack, and Masiye examining that dynamic in rural Zambia. Providing credit during the lean season affects the labor market, allowing liquidity-constrained farmers to avoid wage labor for their comparatively less-constrained neighbors, and pushes up wages. The intriguing thing here is another piece of evidence on the general equilibrium effects of microcredit via commodity (in this case, labor) markets.


2. Microfinance, Part II (Everything Else): Well, not everything else, see item 4. Access to credit and other financial services is a tricky thing--and it's not just the financial system that affects it, the justice system, criminal and civil, matters a lot too. Here's a new paper on alternative credit scoring using digital footprints--I haven't read it yet but am generally very skeptical of things like this. Grassroots Capital and CGAP are hosting a webinar on May 15th under the heading "Microfinance: Revolution or Footnote?" based on a conference last year (full disclosure, I was a participant). Of course, now I would want it to be called "Revolution, Footnote, or General Equilibrium Effects Eat Us All in the Long Run?" And applications are open for the 2018 European Microfinance Awards (until May 23) with the theme "Inclusive Finance through Technology." Whoever said the faiV didn't have news you could use? 

3. Methods/Statistics/Etc: Here's even more service journalism: A tool that will convert charts into data points automatically. I actually expect this to be the most clicked link in the history of the faiV. RAs, the robots are coming for your jobs sooner than you think.
Does everyone who cares about statistics read Andrew Gelman's blog regularly? Just in case, there were several posts recently that drew my attention. One is a fairly-standard-but-always-useful post about a specific example of dubious practices, on early childhood education (which morphs into some commentary on how the field of economics deals with these issues with a bonus appearance from Guido Imbens in the comments); another is a pointer to a new paper that tries to avoid some of the more dubious practices on a topic of a lot of interest and a lot of noise--the relationship of macro-growth and child development. But the most interesting is a post about how economists tend to see the world, specifically explaining why apparent bad behavior is good, and apparent good behavior is bad. Behavior in the economics profession is the best segue I can find into this short (audio) interview with Claudia Goldin.
But back to the use and misuse of metrics and statistics. If you don't click on anything else under this item, I do think you should look at these last two links. First, a thread about how most of the world thinks about statistics--as a tool for arriving at the answer you're looking for. And a column from Justin Fox on how pro- and anti-metrics authors end up in basically the same place--measurement is hard, and is only useful if you put the effort into doing it right.

4. Household Finance: Maybe the grab-bag is the right frame for this week's edition of the faiV. I'm including this item just so I could add this link to a look at how terribly non-poor people manage their money. One of the themes I've been increasingly talking about since the US Financial Diaries is how much even small amounts of slack obscure the sub-optimal decisions of the upper 60% of the income distribution. The analogy I make is to lean manufacturing: for the poorest people, we have drained all the slack out of the system so that when any mistake is made the consequences are large and obvious--that's the point of lean! But of course, unlike Toyota which spends massively to train workers on how to deal with mistakes, we give no useful training to these people to cope with their lack of slack, instead just blathering on to them with useless financial literacy training. Meanwhile, those with some slack are the American car companies of the 1970s, oblivious to their poor management of money. This week is when people who filed their US taxes right before the deadline will receive any refunds they were due; my strong prior is that there will be much more money wasted--even as a percentage--in the next 30 days than when the comparatively lower income families received their refunds back in February.
While we're at it, would you consider $200,000 of debt and a payment plan with the IRS for back taxes an example of "bad" financial decisions? What if the person in question was running for governor?

5. Cash Transfers: To round things out, Finland is giving up on it's "not-universal basic income" experiment since voters don't like it and they sort of already have an actual "universal basic welfare" system. There's another "not-universal basic income/cash transfer" experiment starting in the US. And here's Martin Ravallion on the pros and cons of guaranteed employment versus guaranteed income. (Channeling my inner Lant Pritchett: It's about state capacity!).   

  Part of the US inequality story that doesn't get quite as much attention, via the  NY Times Upshot .

Part of the US inequality story that doesn't get quite as much attention, via the NY Times Upshot.

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.

Week of April 16, 2018

Wash, Rinse, Repeat Edition

Editor's Note: Of late, I've been thinking a lot about comments Tyler Cowen made to me in our interview for Experimental Conversations: "..what we're lacking are incentives...to do what I would call synthesis...it's a very intangible skill and it's hard to tell how good someone is at it." There are people doing synthesis (as you'll see in the links), and I like to flatter myself that I'm one of them, but there aren't enough and it is really hard to tell when you're getting it right.--Tim Ogden

1.  Read, Synthesize, Repeat: Two weeks ago I featured a bunch of links about new and new-ish research about cash transfers, including a synthesis by Berk Ozler which particularly draws attention to the growing evidence of negative spillovers from cash transfers. This week Justin Sandefur wrote up his own synthesis, which disagrees with Berk in important ways, and followed up with a Twitter thread summary, which includes the amazing line: "unless cash recipients literally spent the money on gasoline to set fire to their neighbors farms..." Which of course led to a response from Berk and then lots of further replies--much of which center on how to think about the scope of negative spillovers and what to do with data that doesn't seem to be entirely trustworthy. That's the job of synthesis! But there's a long way to go before there's any consensus on the right synthesis.
The site Straight Talk on Evidence has been working on, if not synthesis, at least part of the work of synthesis, sorting through lots of research on US policy interventions and whether it holds up. A few weeks ago they started a series of blog posts on what the path forward should be "when most rigorous program evaluations find disappointing effects." Here's part two with their proposed steps (I try to avoid using the word "solution" even when it's just quoting others). And here's Chris Blattman's Twitter thread response to their proposed steps.
I may have already linked this but in case I didn't, it's relevance to this conversation in particular compels me to include it: The Political Economy of RCTs. Equally I have to include this short article titled "Evidence-Based Claims About Evidence" which challenges the conventional wisdom on how long it takes for evidence to influence physician behavior.
And yes the connection is tenuous, but here's Ideas42 first ever Impact Report on their first 10 years of work. I think there remains a lot of work to be done on synthesizing behavioral science and other approaches and the real world. 


2. Banking: When I first started working with Jonathan at FAI, one of the first things was helping get the book Banking the World out the door--based on work by Jonathan and others estimating that "half the world is unbanked." The World Bank's Findex database has just been updated with 2017 data, with a new report and complete data, and it now seems that the proper statement is "a third of the world is unbanked." Of course, that begs the question of what we mean by unbanked or financial inclusion, and how to think about people who have access to formal accounts but choose not to use them--often because those formal accounts aren't as useful as the alternatives (or in some cases are actively harmful). Obviously, the Findex has a lot to explore and I'm sure I'll be sharing more in the coming weeks as people try to synthesize the findings. 
But coming back to that point about how to think about financial inclusion and exclusion, here's the text of a speech from N.S. Vishwanathan, Deputy Governor of the Reserve Bank of India, about evolving regulation of Indian banks and stressed assets, which closes with an all-too-familiar warning: "There appears to be taking hold a herd movement among bankers to grow retail credit and the personal loan segment. This is not a risk-free segment and banks should not see it as the grand panacea for their problem riddled corporate loan book."
Meanwhile, the US Consumer Financial Protection Bureau under Mick Mulvaney has drastically cut back it's enforcement actions, apparently to zero. The latest is dropping charges and sanctions against an abusive payday lender and scaling back regulations of high-cost consumer lending. Perhaps Mick should place a call to India.

3. Philanthropy: Discussions of philanthropy would be improved if there was more synthesis of public choice economics--too often I see writing about philanthropic actors that seems to start with either an assumption of saintly altruism or evil capitalist intent in disguise. A reasonable example of something better is this new report on "what goes wrong in impact-focused projects" and finds roughly half of the "roadblocks" are funder-created obstacles. 
Another example is an important set of stories about the Silicon Valley Community Foundation, which has become one of the largest foundations in the world, that illustrate that the world of philanthropy is even messier than most human endeavors where altruism, good intentions, power and self-interest collide. Marc Gunther, writing in the Chronicle of Philanthropy, details many accusations of abusive behavior by SVCF's leading fundraiser, who has resigned in the few days since the article was published. There was a lot of work to get the story published, as Marc details here on his own blog, but like so many other "revelations" in this season, the accusations were well-known and apparently ignored by a great many people, including allegedly by the president of SVCF, Emmett Carson. SVCF is no stranger to controversy. Though I've linked these before, as a refresher here's Marc's earlier reporting on SVCFs' role, or lack thereof, in Silicon Valley itself and an excellent piece by Phil Buchanan of CEP on how to think about community foundations' role in the complicated world of philanthropy. And here's Rob Reich (the Stanford political scientist, not the Berkeley Economist) on interrogating the power of large philanthropy.  

4. Our Algorithmic Overlords: I'm not sure if this long essay on what Artificial Intelligence means and doesn't mean and the challenges the use of the term creates qualifies as synthesis, but it is worthwhile reading.
Oh, and Palantir knows a lot more about you than Facebook, in fact, everything about you.
If you're looking for some hope, here's Allison Fine and Beth Kanter on "Leveraging the Power of Bots for Civil Society."

5. Jobs: Leveraging the power of bots, for good or ill is one of the big questions about the future of jobs. The Hechinger Report is running a series on the challenge to education systems of educating students when there is so much uncertainty about what skills those students will need. The Hechinger Report is US-based, but the problem is the same globally. Here's the World Bank on how automation is changing the jobs and development outlook for lower-income countries. I'm linking there because while Arvind Subramanian has a piece in the FT on this very topic today, in my experience very few people (including me) have access to the FT.     
And I've been meaning to link this piece from Tyler Cowen on reining in occupational licensing for a long time and keep forgetting. To fully bring things around full circle, I will say that I don't think Tyler does enough synthesis of the findings that occupational licensing can be good for excluded communities who are denied opportunities in many fields.

Week of April 9, 2018

Editor's Note: I'm very disappointed that no one commented on my clever pun in last week's editor's note. Given the beautiful weather outside, that's my only explanation for my perhaps snarkier-than-recently tone this week. --Tim Ogden

1. Global Development: Hey, does anybody remember the Millennium Villages Project? It seems an age ago in terms of development fads, now that we're all focused on cash grants and graduation programs, and according to some papers would fall into the "long-run" category. Andrew Gelman has a post about a new retrospective evaluation of the program (that he participated in), including a link to an evaluation of the evaluation. The results are surprisingly good, given what I expect most people's priors were at this point. Though I suppose the TUP evaluations should perhaps have shifted those priors in a positive direction. I guess I'm kind of surprised that the results don't seem to have gotten the attention I would have predicted. Of course, I don't think anyone has argued that the MVP should be a model for other programs since Nina Munk's book, so maybe I shouldn't be so surprised.
Lant Pritchett has a list of six other things in development that people aren't paying (enough) attention to, mostly variations on the continuing large gap between even the lower part of the income distribution in rich countries and the upper part of the distribution in poor countries.
Lant's first point is about the huge gains from moving. Here's a piece from a few weeks ago about the lack of geographic mobility, specifically rural to urban migration, in the United States where the overall tone is exasperation at these benighted people who stay in small towns (and ruin things for everyone else; it's an interview with Robert Wuthnow about his new book). It caught my eye because I can't imagine something like this being written about rural people in developing countries (without touching off a lot of blowback). But perhaps we should see more stuff like this about all forms of poor-to-rich geographic mobility. Speaking of those rural people, here's a new paper from Marc Bellemare about one of the dynamics that may be keeping the poorest people in rural areas (at least in Madagascar)--the intensification of income from agriculture.


2. Jobs: Last week I linked to the recent study of scheduling practices at The Gap that found that encouraging managers to set more stable schedules for retail employees led to higher productivity and sales for the firm. The exact mechanism for increased sales isn't completely clear, but it appears that managers shifted hours to more experienced workers, who unsurprisingly were more productive. While the study is encouraging overall--stable schedules are better for (most) workers and for employers--it also has a dark tinge. To see why, consider this Atlantic article about the future of jobs at Walmart (which, to its great credit, was well ahead of The Gap in experimenting with more stable schedules for its hourly workers, and other efforts to stabilize workers income). The macro trend is toward fewer jobs, at least in terms of how we used to define that term, for less-skilled and less-experienced employees, and declining job quality for those people. That's been happening at many companies (think of outsourcing of janitorial, security and similar jobs) for a long time. It seems an awful lot like what I understand has happened in European labor markets which are more regulated--stable jobs are limited, more workers, particularly the young pushed into contingent labor contracts with limited benefits, stability or security. From a distance this is fascinating: similar outcomes from radically different processes. But from a policy perspective it's frightening. In the economic development world, we've been talking for a long time about how to move more people into formal employment, like in developed economies. Meanwhile the developed economies are making great progress moving people into informal employment, like in developing countries. Maybe I should have called this item Global Undevelopment.
And to play to the academic part of my readership for a moment, here's a piece about how every effort to create better incentives in academic jobs makes things worse. I remain baffled at the general assumption in economics that managers know what they are doing, given the management they experience on a daily basis. While I can't vouch for the management abilities at the Open Philanthropy Project, chances are if you're a reader of the faiV you, or someone you know might be interested in these job openings.

3. MicroDigitalFinance: Is a neologism a step too far? Probably. But check out CFI's fellows program research agenda. There's a whole lot of "microdigital" there. Interestingly, to me at least, is that you could copy and paste these questions into a research agenda for the US financial services marketplace and no one would bat an eye, especially the ones about the changing nature of work.
A brief interruption for a public service announcement: If you're going to be in Uganda, for God's sake, DO NOT LOSE YOUR SIM CARD. Matt Levine has a line about fintech re-learning all the lessons of modern finance, painfully and in public. Seems that could apply equally well to a lot of actors in the financial inclusion space, but relearning the lessons of the need for explicitly pro-poor services, institutions and regulations. Take for instance this post from CGAP about pricing transparency for digital services. Who knew that digital finance providers might not be very upfront about their pricing without regulation?
There is still innovation and research happening in "traditional/nondigital" microfinance, thankfully. Here's a new paper from Burke, Bergquist and Miguel on lending to Kenyan farmers to enable them to buy low and sell high, rather than the inverse which is the status quo ex ante. The most interesting part is not that it does help farmers profitability but that they can track general equilibrium effects on prices of both inputs and outputs--and there are effects. It's another piece of evidence that microcredit can have positive general equilibrium effects that are missed in individual-focused impact evaluations (cf. Breza and Kinnan).

4. Our Algorithmic Overlords: With ongoing questions about how automation, AI, tightening labor markets, and shifting skills will affect employment, I suppose we can take some heart in this "against the run of play" piece claiming that progress in AI research has hit a wall. Maybe we have more time for structural adjustment than we thought. Of course, that may give more time for big tech companies to lobby for privacy laws that look tough but actually enable much of their ongoing gathering and use of data outside public view. And here's Lucy Bernholz on the need for civil society organizations to quickly come to terms with "the burden of data." I guess Lucy would be encouraged about CFI's research agenda, above. And I got through that without mentioning the Zuckerberg hearings. Oops.

5. US Poverty and Inequality: You may have already seen that Matthew Desmond and colleagues have "kicked on" from their work on evictions in Milwaukee and built a database of eviction records that covers a good portion of the US. Here's the NYTimes coverage of evictions in Richmond.
Here's a new report on the racial wealth gap and small business, that while useful continues my frustration at focusing on the idea that starting small businesses will directly address the wealth gap. Business ownership only increases wealth if there are buyers of those businesses at some point in the future. Given the pre-existing wealth gap, and the businesses that minorities are able to start, who is going to put a residual value on those businesses high enough to affect wealth? Perhaps we should consider the lessons of the global microfinance movement in building wealth through small business financing?
In case you were wondering, here's a new paper on immigrants and entrepreneurship in the US. First-generation immigrants create about 25% of the new businesses in the US, but this is as high as 40% in some regions. But, of course, those firms create fewer jobs and those jobs aren't as good as jobs in native-owned firms. In other words, they may be very good for boosting incomes (though in general there is no wage premium for entrepreneurs versus their likely earnings from employment) but likely not for building wealth.

  Kieran Healy has a couple of blog posts in recent weeks looking at various ways to represent time series data,  using birth data in the US  and in other countries. In addition to my general interest in data viz, this caught my eye because, well, did you know how much birth rates varied from month-to-month? After contemplating whether there were some basic biologic facts I was unaware of, and soliciting help from a L&D nurse friend, I discovered that birth seasonality is a thing, is consistent across time, culture and geography, and  there is still lots of debate over what factors account for it . And I also discovered that  I have the most common birthday in the US (at least among people born 20 to 40 years after me) . You can see more of  Kieran's visualizations of the baby boom here , and some  cool animated population pyramids (with discussion and code) here .

Kieran Healy has a couple of blog posts in recent weeks looking at various ways to represent time series data, using birth data in the US and in other countries. In addition to my general interest in data viz, this caught my eye because, well, did you know how much birth rates varied from month-to-month? After contemplating whether there were some basic biologic facts I was unaware of, and soliciting help from a L&D nurse friend, I discovered that birth seasonality is a thing, is consistent across time, culture and geography, and there is still lots of debate over what factors account for it. And I also discovered that I have the most common birthday in the US (at least among people born 20 to 40 years after me).
You can see more of Kieran's visualizations of the baby boom here, and some cool animated population pyramids (with discussion and code) here.

Week of April 2, 2018

April Showers on Parade Edition

Editor's Note: Joan Robinson once said, "The purpose of studying economics is not to acquire ready-made answers to economic questions, but to learn how to avoid being deceived by economists." I often feel like the more modern description would be, the purpose of studying economics is not to acquire ready-made answers, but to learn how to rain on as many parades as possible. Or maybe that's just my natural disposition. Anyway, the recurring theme this week is the reining in of optimistic expectations.  --Tim Ogden

1. Global Development: To start us off, how about some rain on the "rising Kenyan middle class" parade? The core point--that gains from rising incomes that don't translate into durable assets can rapidly be erased, a perspective that should sound familiar to anyone with a passing knowledge of anti-poverty policy in the US. 
But the real parade in global development in recent years has been on the value of delivering cash to poor households. This is a train that's been picking up steam for a long while. I would date the current push back to the first studies of Progresa/Opportunidades, the Mexican conditional cash transfer program. Momentum has steadily built around both the positive impact of cash transfers--that recipients don't waste the money, that they use the money productively--and dropping conditions. That momentum was built on many studies, but probably the two most well known in international circles are Blattman, Fiala and Martinez on cash transfers in Uganda, and Haushofer and Shapiro/GiveDirectly in Kenya. Both showed significant gains by recipients of unconditional cash.
Both of those papers were about relatively short-term effects. Both studies included longer-term follow-ups. And you know what's coming: the large positive effects seem to have disappeared in the medium term. Berk Ozler of the World Bank is currently playing the role of Deng (it's the closest I could get geographically) with two lengthy blog posts. The first, keying off comments from Chris Blattman in the recent Conversations with Tyler, but really delving into the recently released update to the Haushofer and Shapiro/GiveDirectly update is the important one for non-specialists. The second is very useful for understanding the specific details of interpretation. The posts also kicked off a number of useful Twitter conversations (here, here, here, here and here, though that's just a sample; just scroll through Chris's and Berk's timelines for more). Berk's first post also takes on the role that academics have played in stoking that momentum and is worth a close read.
I think it's also important to think through what is happening with cash transfers in light of not only other studies of cash (like this one finding positive effects on the personality of Cherokee Native American kids whose families receive cash that was just officially published) but also other interventions. Deworming is one example--one big source of the controversy over the effects of deworming is that there isn't a medium-term biological effect to explain the long-term economic effects. The Moving to Opportunity study is another--no short-term or medium-term gains, only long-term ones. And I have to note that the Native American paper is a frustrating example of Berk's critique of the role academics can play in raising expectations too high--the paper's title and abstract simply reference a large positive effect of cash transfers with no indication of when (now? 10 years ago? 30 years ago?), where or who the participants are, or even the size or mechanism of the transfers.


2. Social Investment and Philanthropy: In one of those Twitter conversations sparked by Berk's posts, Chris gave Berk the endearing nickname "naysaying grumpy pants" (it's a compliment, honest!). This week I had my own "grumpy pants" moment tied to the release of Henry Timms' just published book New Power. Henry is the main force behind Giving Tuesday--and apparently I am the designated Scrooge on that topic, going back to a few posts I wrote for Stanford Social Innovation Review years ago. In the Chronicle of Philanthropy's long profile of Henry and the new book, I get to say things like, "I can't imagine a more useless number than the amount of money given on Giving Tuesday." Without context, that may sound like hard-hearted parade-raining. And I suppose I am parade-raining on the way that Giving Tuesday is mostly being talked about--as a wildly successful movement based on the amount of money given tied to Giving Tuesday campaigns. But what we really should care about is whether Giving Tuesday is leading to people becoming more generous, not whether their donations happen in response to a specific campaign. I'll write some more about Henry's book and New Power in the coming weeks.
In other social investment parade raining, I've been known to get riled about about the social investment rhetoric about "no trade-offs" and "double bottom lines." Here's a new paper from Karlan, Osman and Zinman that explores the trade-offs of a double bottom line in detail. It finds negative consequences for both social and financial performance. Now that's some first-class parade-raining.

3. Methods: I suppose you could call this recent work on whether regression discontinuity designs are reliable--and finds that they are--to be raining on the parades of other methdological approaches. But for good measure, here's Andrew Gelman, well-known parade-raining statistician, with some notably restrained and subtle raining on everyone's parade in response to the RDD paper. My summary: lots of methods are reliable if you do them right, but you're probably not doing them right.
But tying back to the first item and Berk's discussion of the role of academics in miss-setting expectations, here are two useful pieces from outside economics that are worth thinking about if we think of methods as not just the way a study is done or the analysis conducted but the way the results are communicated (and obviously I think that's the right way to think about methods). First, how the continuing enthusiasm for vitamins came to be. Second, Slate Star Codex takes on adult neurogenesis in humans which is particularly fascinating because it's an example of how commonly held beliefs were overturned by new research, and then more new research overturned the new beliefs. Seems particularly relevant to the conversations about cash transfers, no?

4. Microfinance and Digital Finance: Here are two related pieces raining on crypto-parades, which admittedly isn't that hard these days. But neither is about the crazy part of the crypto world. They are raining on some of the fundamental ideas that are used to justify the ultimate value of crytocurrencies. First, here's a story about Ripple and it's struggles with banks who like the idea of a simplified payments infrastructure but don't see any need for a cryptocurrency to be part of that. Second, here's a story about how crypto trades are actually happening--with a trusted intermediary using Skype, because you know having a trusted intermediary is a useful thing in markets.
In other non-parade-raining news, Walmart is getting into the global remittances game, by partnering with MoneyGram(!?!). I suppose that will rain on lots of other global remittance providers parade. And here's a story about why, after all this time, remittances are still so costly and none of the efforts to bring down the cost have worked. Of course, that was before Walmart got involved.
Finally, it's not often I get to feature some US-based microfinance stuff. Here's a new paper from Aspen FIELD on pricing in US microfinance and why it makes sense for lenders to raise interest rates (Note: I played an role advisory role developing the paper). I think a lot of people in international microfinance will sympathize.

5. US Poverty and Inequality: The role of health care costs in driving bankruptcies got a lot of attention a few years ago and was a big part of the push for the ACA. Since the ACA passage though, there hasn't been a meaningful change in bankruptcy rates even though there was a big increase in the number of people insured. Now there's a reassessment of the data on bankruptcy and health care costs that radically revises down the number of bankruptcies that can be attributed to health care costs directly resulting in papers in the New England Journal of Medicine and in AER. Here's a summary of the work, but the very short version is the culprit is loss of income from poor health more than the costs of health care.
And because it's spring temporarily this afternoon, I feel compelled to leave on some good news--or at least my version of good news. The Gap engaged in a rigorous randomized study (!) to determine if their scheduling practices--which as in most US retail leads to erratic and volatile schedules for retail workers--were helpful to the bottom line. The answer is no. Volatile schedules are bad for workers and bad for business (summary; full report). Hey, did I just suggest there was no trade-off to treating workers better?

Week of March 19, 2018

The Wheel of Morality Edition

Editor's Note: The reference this week is to the classic bit on the cartoon Animaniacs. The connection is in the first item.--Tim Ogden

1. Household Finance, Debt Specifically: This week I had the chance to talk about the moral dimensions of debt with Fred Wherry, as part of Aspen EPIC's focus on consumer debt in the US (and there are more conversations about debt before and after in that video). One of the things that doesn't get mentioned in the video is that the ancestor of mine who was rescued from debtor's prison later became the official Collector for Jersey City. It's a topic that fascinates me because attitudes toward debt vary so widely across time, culture, context and individual. It often seems like perspectives on debt are pulled from the Wheel of Morality. Just the selective use of the words "credit" and "debt" could be fodder for 100,000 words or more, much less the tension between the lack of access to credit coinciding with troubling debt burdens in many contexts.
To get up to speed on the current situation with consumer debt in the United States, you couldn't ask for a better overview than Aspen EPIC's just published primer. Well, you could ask for one, but given the gaps in the underlying data, you wouldn't get it. And to push some more moral buttons, here's a profile of one of the most influential figures in consumer debt today: Dave Ramsey. If you don't know who that is, you really do need to read the profile.


2. Microfinance and Digital Finance: I suppose I'm sending a message by increasingly conflating these two categories. This piece from NextBillion on the need for Indian MFIs to digitize at least gives me an excuse this week. But while I figure out what message I'm sending (or at least intending to send), here are a couple of recent pieces about digital accounts helping people save more. First, a paper from the job market that I missed about M-Pesa boosting savings among those whose alternatives were most costly. And a new paper about an experiment with female entrepreneurs in Tanzania finding digital savings accounts boosted savings rates. My priors aren't shifted much by these, but they are shifted some.  
To maintain some strategic ambiguity, here's a new paper that fights the digital invasion--there's nothing less digital than grain storage. Providing farmers with a way to communally store grain at harvest has high take-up and as a result were able to sell grain later at a higher price. An intervention to allow individual cash savings for inputs was less successful, though possibly because there wasn't much margin to improve on.

3. Methods and Economics: It took a lot of willpower (though apparently not ego-depleting) not to put this item first, but I worry that my excitement over things like this is not normative for the faiV readership. But for those of you in this niche, here's a new comment from Guido Imbens on the Cartwright and Deaton critique of RCTs (and if you prefer a simpler version, here's my interview of Deaton for Experimental Conversations which gives an overview of most of the issues). To give you a flavor of Imbens perspective: "Nothwithstanding the limitations of experimentation in answering some questions, and the difficulties in implementation, these developments have greatly improved the credibility of empirical work in economics compared to the standards prior to the mid-eighties, and I view this as a major achievement by these researchers."
Imbens places RCTs within "the credibility revolution" in empirical economics (which of course is the crux of the debate--how much do RCTs improve credibility?). The credibility revolution, in turn, has played a big role in the growth of empirical economics compared to theory and econometrics. Here's Sylvain Chabe-Ferret with an overview of "the empirical revolution in Economics", some thoughts on the path forward and a treasure trove of links. I have to note here, for those not so enmeshed in the details, that while Deaton is a critic of RCTs, he is a part of the credibility/empirical revolutions through his careful and detailed work with surveys.
Finally, here's something form the Royal Economic Society with the headline "Tweeting Economists Are Less Effective Communicators Than Scientists". I haven't read it yet but how could I not link it when it has such an exquisite combination of direct and implied slights on economists?

4. US Inequality, Immobility and Instability: I'm assuming that any of you with an interest have already seen the new results on mobility and the central problem of immobility for African-American men from Chetty, et. al. so well illustrated by the NYT's piece. Hidden in Chetty's shadow are a couple of other pieces on this topic that deserve attention. Inspired by Chetty et al's earlier work on variation in mobility geographically, here's Davis and Mazumder on racial differences within geographies, finding that low mobility in the Southeast is driven by whites; African-Americans in the Southeast have higher mobility than those in the Northeast and Midwest. And here's Guyot, Reeves and Winship with a different approach to the question of African-American male immobility and marriage rates, which confirms the latest Chetty et. al. results.
Our work in the US Financial Diaries ties helps shine a light on short-term instability as a factor in immobility. There are a couple new pieces in that domain. Alieza Durana looks at instability in the suburbs and how it contributes to general feelings of insecurity. And Molly Kinder and Kristin Sharp look at the prospects for improving stability by changing the workforce (or at least how and what people are trained to do.)
Finally, the St. Louis Fed Center for Household Financial Stability (tm) has an upcoming symposium on whether college is still worth it, given the disparate returns to education. My synthesis of some of the recent work: college is most expensive for people with the lowest rates of return to enrollment. That'll have an impact on mobility, for sure.

5. Our Algorithmic Overlords: Last week I talked about how AI seems to be just as interested in gaming manager's incentive schemes as humans. Here's a piece about computers liking spurious correlations just as much as human story-telling brains, it's just that they are much faster at finding the spurious correlations.
I could hardly avoid a mention of the current kerfuffle over the Facebook/Cambridge Analytica revelations. Asif Audowla sent me this link which helps tell the story if you've been buried under a rock. I use the word kerfuffle purposely: I'm still really unsure what to think about all of this, with the pieces I see about fake news proliferating without the need for psychographic targeting, about how hard it is to influence people, and about partisan bias in the reaction to the story. So, I leave this one to you dear readers to tell me what to think. To help you along in that process, here's a piece from New Inquiry that's quite on topic: Privacy for Whom? 

  Following on those studies of US mobility, this chart depicts the mobility, or lack thereof, of the white and African-American men and women. It's worth thinking hard about the similarities and differences here. To help you do that,  check out this thread from Arindrajit Dube  which puts the chart below in context. 

Following on those studies of US mobility, this chart depicts the mobility, or lack thereof, of the white and African-American men and women. It's worth thinking hard about the similarities and differences here. To help you do that, check out this thread from Arindrajit Dube which puts the chart below in context. 

Week of March 12, 2018

Editor's Note: I keep telling myself that I'm going to start fighting back against the tyranny of the new, but it never seems to happen. But this week I'm taking a small step by pulling stuff I've been accumulating for the last month that hasn't made it into the faiV. Plus some new stuff of course. Get ready for a link heavy faiV. And in case any of you are wondering what I look like, I'll be interviewing Fred Wherry about the sociology of debt in the United States on Tuesday, the 20th. Register to watch the live stream here.--Tim Ogden

1. Microfinance and Digital Finance: Apparently the "farmer suicide over indebtedness" hype train is kicking up again in India. That's not to imply that farmer suicides are not a serious issue. But Shamika Ravi delves into the data and points out that indebtedness doesn't seem to be the driver of suicides and so attacking lenders or forgiving debts isn't going to fix the problem. Certainly poverty and indebtedness add huge cognitive burdens to people that affect their perceptions and decisions in negative ways, including despair. Here's a new video about poverty's mental tax--there's nothing new here, but a useful and simple explanation of the concepts.
Last year (or the year before) I noted Google's decision to play a role in safeguarding people in desperate straits from negative financial decisions: the company banned ads from online payday lenders, in effect becoming a de facto financial regulator. This week, Google announced another regulatory action. Beginning in June it will ban ads for initial coin offerings (if you don't know what those are, congratulate yourself). While I'm all for the decision, it's strange for Google to conclude that these ads are so dangerous to the public that they should be banned, but not for three more months. Cryptocurrency fraudsters, get a move on! Meanwhile, the need for Google and Apple (and presumably Facebook, Amazon, Alibaba and every other tech platform) to step up their financial regulation game is becoming clearer. In an obviously self-promotional, but still concerning survey web security firm Avast found that 58% of users thought a real banking app was fraudulent, while 36% thought a fraudulent app was real. I don't really buy the numbers, but my takeaway is: people have no idea how to identify digital financial fraud. I wish that seemed more concerning to people in the digital finance world.


2. Our Algorithmic Overlords: I've had a couple of conversations with folks after my review of Automating Inequality, and had the chance to chat quickly with Virginia Eubanks after seeing her speak at the Aspen Summit on Inequality and Opportunity. My views have shifted a bit: in her talk Eubanks emphasized the importance of keeping the focus on who is making decisions, and that the danger that automation can make it much harder to see who (as opposed to how) has discretion and authority. A big part of my concern about the book was that it put too much emphasis on the technology and not the people behind it. Perhaps I was reading my own concerns into the text. I also had a Twitter chat with Lucy Bernholz who should be on your list of people to follow about it. She made a point that has stuck with me: automation, at least as it's being implemented, prioritizes efficiency over rights and care, and that's particularly wrong when it comes to public services.
I closed the review by saying that "the problem is the people"; elsewhere I've joked that "AI is people!" Well at least I thought I was joking. But then I saw this new paper about computational evolution--an application of AI that seeks to have the machine experiment with different solutions to a problem and evolve. And it turns out that while AI may not be people, it behaves just like people do. The paper is full of anecdotes of machines learning to win by gaming the system (and being lazy): for instance, by overloading opponents' memory and making them crash, or deleting the answer key to a test in order to get a perfect score. I think the latter was the plot of 17 teen movie comedies in the '80s. Reading the paper is rewarding but if you just want some anecdotes to impress your friends at the bar tonight, here's a twitter thread summary. It's funny, but honestly I found it far scarier than that video of the robot opening a door from last month. Apparently our hope against the robots is not the rules that we can write, because they will be really good at gaming them, but that the machines are just as lazy as we are.
To round out today's scare links, here's a news item about a cyberattack against a chemical plant apparently attempting to cause an explosion; and here's a useful essay on our privacy dystopia.

3. US Poverty and Inequality: Definitely just trying to catch up here on things that have been building up. Here's a new paper on studying income volatility using PSID data, with a review of prior work and finding that male earnings volatility is up sharply since the Great Recession. There's been a bunch of worthwhile things on US labor force participation in the last few weeks. First here's Abraham and Kearney with "a review of the evidence" on declining participation. Here's a comparison of the UK and US considering why US has fallen behind in participation from Tedeschi. And here's a story from this week about how falling unemployment is affecting hiring and participation.
Returning to the theme of volatility, here's a short video from Mathematica Policy Research on how income volatility affects low-income families. Jonathan is following up on the US Financial Diaries research into income volatility and looking at how it disproportionately affects African-American households, and interacts with the racial wealth gap. But it turns out that even though African-American households are disproportionately income, asset and stability poor, they are even more disproportionately depicted as poor in media

4. Social Investment and Philanthropy: I mentioned above that you should be following Lucy Bernholz. Via Lucy, here's a report on the massive challenge of digital security for civil society organizations. I'll take a moment to editorialize--funders are way way behind in recognizing how big a change digitization is when it comes to their own and nonprofits operations. It's not just security, though that's likely the first place that a crisis will strike. But beyond that, it's crazy that major foundations do not have CIOs on their boards of directors, and that grant applications don't include a technology infrastructure review. The ability to use technology is already a major factor in nonprofits ability to have an impact (either directly by how they deliver services or indirectly in how they can track their activities and improve), while most funders are still viewing IT as an overhead cost to be minimized. That has to change. 
In other worrying trends in philanthropy that aren't getting enough attention--the explosive growth of Donor Advised Funds continues. Recently information about Goldman Sachs' DAF leaked--which is significant because part of the reason DAFs are popular is because they shield information about who donors are. Which makes it particularly interesting that Steve Ballmer and Laurene Powell Jobs, and others among the list of wealthiest people in the world are using Goldman's DAF, because the justification for DAFs is allowing those not wealthy enough to fund their own foundations to gain some of the benefits. Sounds like a gaming of the rules that an AI would be proud of.

5. Methods and Statistics: I feel like I couldn't show my face around here anymore if I didn't link to the world's largest field (literally) experiment. It was in China of course. I feel like this instance satisfies all of the objections raised by Deaton or Pritchett or Rozenzweig, but I'm sure I've missed something. By the way, anybody else have a feeling that relatively soon people are going to be questioning the importance of any study that wasn't done in China or India? 
So you better jump on the chance to read about how to measure time series share of GDP in the United States (and how hard it is to say anything about manufacturing's changing role in the economy). After all it only affects about 350 million people, not enough to really care about. 
Meanwhile, Andrew Gelman of all people makes the case for optimism about statistical inference and replication. I'm not sure of whether to interpret the kerfuffle over Doleac and Mukherjee's paper on moral hazard and naloxone access as bolstering or undermining Gelman's point. I'm going to choose to be optimistic for now though, against my nature.
And finally, here's a visual, interactive "textbook" on probability that has some really cool stuff. But I don't think what it's doing is going to help the problem of people not understanding causal inference.

  Figuring out how to do the right thing is hard. This table is from  a Danish government study  of climate change impact of various methods of carrying stuff. Apparently if you properly use, re-use and dispose of a standard plastic bag, it has much less climate impact than reusable cotton bags. If I'm interpreting it correctly, it means that you'd have to use an organic cotton bag something like 20,000 times before net climate impact was the same as the plastic bag's. Of course, that all depends on whether the plastic bag is properly used and disposed of. I bet neither estimate incorporates virtue compensation. 

Figuring out how to do the right thing is hard. This table is from a Danish government study of climate change impact of various methods of carrying stuff. Apparently if you properly use, re-use and dispose of a standard plastic bag, it has much less climate impact than reusable cotton bags. If I'm interpreting it correctly, it means that you'd have to use an organic cotton bag something like 20,000 times before net climate impact was the same as the plastic bag's. Of course, that all depends on whether the plastic bag is properly used and disposed of. I bet neither estimate incorporates virtue compensation. 

Week of March 4, 2018

Editor's Note: I again triumphantly wrestled the faiV from Tim Ogden’s clutches this week. Well, actually, he asked me to take over while he’s in transit today. Inspired by this week's amazing Pooh noir Twitter thread, I decided to dedicate this faiV to some powerful investigations (of the journalistic, not private eye, not private eye type). --Jonathan Morduch

1. Crappy Financial Products: The results are no surprise, but it remains troubling to see the numbers. “Color and Credit” is a 2018 revision of a 2017 paper by Taylor Begley and Amitatosh Purnanandam. The subtitle is “Race, Regulation, and the Quality of Financial Services.” Most studies of consumer financial problems look at quantity: the lack of access to financial products. But here the focus is on quality: You can get products, but they’re lousy. Too often, they’re mis-sold, fraudulent, and accompanied by bad customer service. These problems had been hard to see, but they’ve been uncovered via the Consumer Financial Protection Bureau Complaints database, a terrifically valuable, publicly accessible—and freely downloadable—database. (Side note: this makes me very nervous about the CFPB’s current commitment to maintaining the data.)

Thousands of complaints are received each week, and the authors look at 170,000 complaints from 2012-16, restricted to mortgage problems. The complaints come from 16,309 unique zipcodes – and the question is: which zipcodes have the most complaints and why? The first result is that low income and low educational attainment in a zipcode are strongly associated with low quality products. Okay, you already predicted that. On top of those effects, the share of the local population identified as being part of a minority group also predicts low quality. No surprise again, but you might not have predicted the magnitude: The minority-share impact is 2-3 times stronger then the income or education impact (even when controlling for income and education). The authors suspect that active discrimination is at work, citing court cases and mystery shopper exercises which show that black and Hispanic borrowers are pushed toward riskier loans despite having credit scores that should merit better options. So, why? Part of the problem could be that efforts to help the most disadvantaged areas are backfiring. Begley and Purnanandam give evidence that regulation to help disadvantaged communities actually reduces the quality of financial products. The culprit is the Community Reinvestment Act, and the authors argue that by focusing the regs on increasing the quantity of services delivered in certain zipcodes, the quality of those services has been compromised – and much more so in heavily-minority areas. Unintended consequences that ought to be taken seriously.

2. TrumpTown: Another great database. ProPublica is a national resource – a nonprofit newsroom. They’ve been doing a lot of data gathering and number-crunching lately. Four items today are from ProPublica. The first is the geekiest: a just-released, searchable database of 2,475 Trump administration appointees. The team spent a year making requests under the Freedom of Information Act, allowing you to now spend the afternoon getting to know the mid-tier officials who are busily deregulating the US economy. The biggest headline is that, of the 2,475 appointees, 187 had been lobbyists, 125 had worked at (conservative) think tanks, and 254 came out of the Trump campaign. Okay, that’s not too juicy. Still, the database is a resource that could have surprising value, even if it’s not yet clear how. Grad students: have a go at it. (Oh, and I’d like to think that ProPublica would have done something similar if Hilary Clinton was president.)

3. Household Finance (and Inequality): This ProPublica story is much more juicy, and much more troubling. Writing in the Washington Post, ProPublica’s Paul Kiel starts: “A ritual of spring in America is about to begin. Tens of thousands of people will soon get their tax refunds, and when they do, they will finally be able to afford the thing they’ve thought about for months, if not years: bankruptcy.” Kiel continues, “It happens every tax season. With many more people suddenly able to pay a lawyer, the number of bankruptcy filings jumps way up in March, stays high in April, then declines.” Bankruptcy is a last resort, but for many people it’s the only way to get on a better path. Even when straddled with untenable debt, it turns out to be costly to get a fresh start.

The problem will be familiar to anyone who has read financial diaries: the need for big, lumpy outlays can be a huge barrier to necessary action. Bankruptcy lawyers usually insist on being paid upfront (especially for so-called “chapter 7” bankruptcies). The problem is that if the lawyers agreed to be paid later, they fear that their fees would also be wiped away by the bankruptcy decision. So, the lawyers put themselves first. The trouble is that the money involved is sizeable: The lawyers’ costs plus court fees get close to $1500. The irony abounds. Many people tell Kiel that if they could easily come up with that kind of money, then they probably wouldn’t be in the position to go bankrupt. Bankruptcy judges see the problem and are trying to jerry-rig solutions, but nonprofits haven’t yet made this a priority. So, for over-indebted households, waiting to receive tax refunds turns out to be a key strategy.

4. Municipal Finance and Household Finance (and Inequality): In a related vein, check out this Mother Jones/ProPublica investigation of bankruptcy in Chicago. The title says it all: “How Chicago Ticket Debt Sends Black Motorists Into Bankruptcy. A cash-strapped city employs punitive measures to collect from cash-strapped residents — and lawyers benefit.” The focus is on the city’s reliance on fees from parking tickets to help balance the books – which can add up for residents and lead to bankruptcy. Even a single unpaid parking ticket can create havoc for poorer households. The situation is hard not to connect to Ferguson, Missouri, the scene of the riots after the shooting of Michael Brown, where, among other abuses of the citizenry, the city used the courts and police as revenue-generating mechanisms.)

Ticket debt in Chicago is concentrated in areas that are predominantly poor and black, because there isn’t slack to pay the initial tickets, making it more likely that debt results. A fairer system would impose fines on a scale connected to individuals’ income and ability-to-pay. But, for now, we have a decidedly regressive system in which the least-able-to-pay face disproportionately large penalties.

5. Social Investment: The final ProPublica story is a collaboration with the New York Times. Many have reported on the rising cost of drugs, but we don’t often see deep reporting on those who pay the price. The personal stories are both familiar and shocking. Two common threads: many people are too poor to easily pay the drug prices but not so poor that they have access to generous public benefits. They’re caught in between. The result is that individuals end up juggling which medicines to take in the same way that cash-strapped families juggle which bills to pay each month – only with much higher stakes.
 
A second theme is (again) problems posed by large, lumpy, upfront costs. For example: “…Novo Nordisk, the company that sells her fast-acting insulin, Novolog, and her diabetes medication, Victoza, requires low-income Medicare beneficiaries to first spend $1,000 on drugs in each calendar year before they can qualify for free drugs through its program. In a cruel twist, Ms. Johnson doesn’t have that $1,000 to spend, so she resorts to not taking some drugs for months until she reaches the company’s threshold.” The stories highlight ways in which health problems are often financial problems.
 
In a related way, JPMorgan Chase Institute analysis shows that many people defer health spending until they get tax refunds. (Out-of-pocket health spending increased by 60% in the week after getting a tax refund.) Tax refund season is one of the few moments when families have big, lumpy sums to spend on doctors (if they don’t spend them all on filing for bankruptcy).

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.

Book Review Special Edition: Automating Inequality

1. Algorithmic Overlords (+ Banking + Digital Finance + Global Development) book review: I'd like to call myself prescient for bringing Amar Bhide into last week's faiV headlined by questions about the value of banks. Little did I know that he would have a piece in National Affairs on the value of banks, Why We Need Traditional Banking. The reason to read the (long) piece is his perspective on the important role that efforts to reduce discrimination through standardization and anonymity played in the move to securitization. Bhide names securitization as the culprit for a number of deleterious effects on the banking system and economy overall (with specific negative consequences for small business lending). 
The other reason to read the piece is it is a surprisingly great complement to reading Automating Inequality, the new book from Virginia Eubanks. To cut to the chase, it's an important book that you should read if you care at all about the delivery of social services, domestically or internationally. But I think the book plays up the technology angle well beyond it's relevance, to the detriment of very important points.
The subtitle of the book is "how high-tech tools profile, police and punish the poor" but the root of almost all of the examples Eubanks gives are a) simply a continuation of policies in place for the delivery of social services dating back to, well, the advent of civilization(?), and b) driven by the behaviors of the humans in the systems, not the machines. In a chapter about Indiana's attempt to automate much of its human services system, there is a particularly striking moment where a woman who has been denied services because of a technical problems with an automated document system receives a phone call from a staffer who tries very hard to convince her to drop her appeal. She doesn't, and wins her appeal in part because technology allowed her to have irrefutable proof that she had provided the documents she needed to. It's apparent throughout the story that the real problem isn't the (broken) automation, but the attitudes and political goals of human beings.
The reason why I know point a) above, though, is Eubanks does such an excellent job of placing the current state in historical context. The crucial issue is how our service delivery systems "profile, police and punish" the poor. It's not clear at all how much the "high tech tools" are really making things worse. This is where Bhide's discussion is useful: a major driver toward such "automated" behaviors as using credit scores in lending was to do an end-run around the discrimination that was rampant among loan officers (and continues to this day, and not just in the US). While Eubanks does raise the question of the source of discrimination, in a chapter about Allegheny County, PA, she doesn't make a compelling case that algorithms will be worse than humans. In the discussion on this point she even subtly undermines her argument by judging the algorithm by extrapolating false report rates from a study conducted in Toronto. This is the beauty and disaster of human brains: we extrapolate all the time, and are by nature very poor judges of whether those extrapolations are valid. In Allegheny County, according to Eubanks telling, concern that case workers were biased in the removal of African-American kids from their homes was part of the motivation for adopting automation. They are not, it turns out. But there is discrimination. The source is again human beings, in this case the ones reporting incidents to social services. The high-tech is again largely irrelevant.
I am particularly sensitive to these issues because I wrote a book in part about the Toyota "sudden acceleration" scare a few years ago. The basics are that the events described by people who claim "sudden acceleration" are mechanically impossible. But because there was a computer chip involved, many many people were simply unwilling to consider that the problem was the human being, not the computer. There's more than a whiff of this unjustified preference for human decision-making over computers in both Bhide's piece and Eubanks book. For instance, one of the reasons Eubanks gives for concern about automation algorithms is that they are "hard to understand." But algorithms are nothing new in the delivery of social services. Eubanks uses a paper-based algorithm in Allegheny County to try to judge risk herself--it's a very complicated and imprecise algorithm that relies on a completely unknowable human process, that necessarily varies between caseworkers and even day-to-day or hour-to-hour, to weight various factors. Every year I have to deal with social services agencies in Pennsylvania to qualify for benefits for my visually impaired son. I suspect that everyone who has done so here or any where else will attest to the fact that there clearly is some arcane process happening in the background. When that process is not documented, for instance in software code, it will necessarily be harder to understand.
To draw in other examples from recent faiV coverage, consider two papers I've linked about microfinance loan officer behavior. Here, Marup Hossain finds loan officers incorporating information into their lending decisions that they are not supposed to. Here, Roy Mersland and colleagues find loan officers adjusting their internal algorithm over time. In both cases, the loan officers are, according to some criteria, making better decisions. But they are also excluding the poorest, even profiling, policing and punishing them, in ways that are very difficult to see. While I have expressed concern recently about LenddoEFL's "automated" approach to determining creditworthiness, at least if you crack open their data and code you can see how they are making decisions.
None of which is to say that I don't have deep concerns about automation and our algorithmic overlords. And those concerns are in many ways reinforced and amplified by Eubanks book. While she is focused on the potential costs to the poor of automation, I see two areas that are not getting enough scrutiny.
First, last week I had the chance to see one of Lant Pritchett's famous rants about the RCT movement. During the talk he characterized RCTs as "weapons against the weak." The weak aren't the ultimate recipients of services but the service delivery agencies who are not politically powerful enough to avoid scrutiny of an impact evaluation. There's a lot I don't agree with Lant on, but one area where I do heartily agree is his emphasis on building the capability of service delivery. The use of algorithms, whether paper-based or automated, can also be weapons against the weak. Here, I look to a book by Barry Schwarz, a psychologist at Swarthmore perhaps most well-known for The Paradox of Choice. But he has another excellent book, Practical Wisdom, about the erosion of opportunities for human beings to exercise judgment and develop wisdom. His book makes it clear that it is not only the poor who are increasingly policed and punished. Mandatory sentencing guidelines and mandated reporter statutes are efforts to police and punish judges and social service personnel. The big question we have to keep in view is whether automation is making outcomes better or worse. The reasoning behind much of the removal of judgment that Schwartz notes is benign: people make bad judgments; people wrongfully discriminate. When that happens there is real harm and it is not obviously bad to try to put systems in place to reduce unwitting errors and active malice. It is possible to use automation to build capability (see the history of civilization), but it is far from automatic. As I read through Eubanks book, it was clear that the automated systems were being deployed in ways that seemed likely to diminish, not build, the capability of social service agencies. Rather than pushing back against automation, the focus has to stay on how to use automation to improve outcomes and building capability.
Second, Eubanks makes the excellent point that while poor families and wealthier families often need to access similar services, say addiction treatment, the poor access them through public systems that gather and increasingly use data about them in myriad ways. One's addiction treatment records can become part of criminal justice, social service eligibility, and child custody proceedings. Middle class families who access services through private providers don't have to hand over their data to the government. This is all true. But it neglects that people of all income levels are handing over huge amounts of data to private providers who increasingly stitch all of that data together with far less scrutiny than public agencies are potentially subject to. Is that really better? Would the poor be better off if their data was in the hands of private companies? It's an open question whether the average poor person or the average wealthy person in America has surrendered more personal data--I lean toward the latter simply because the wealthier you are the more likely you are to be using digital tools and services that gather (and aggregate and sell) a data trail. The key determinant of what happens next isn't, in my mind, whether the data is held by government or a private company, but who has the power to fight nefarious uses of that data. Yes, the poor are often going to have worse outcomes in these situations but it's not because of the digital poorhouse, it's because of the lack of power to fight back. But they are not powerless--Eubanks stories tend to have examples of political power reigning in the systems. As private digital surveillance expands though, the percentage of the population who can't fight back is going to grow.
So back to the bottom line. You should read Automating Inequality. You will almost certainly learn a lot about the history of poverty policy in the US and what is currently happening in service delivery in the US. You will also see lots to be concerned about in the integration of technology and social services. But hopefully you'll also see that the problem is the people.

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.

Week of February 5, 2018

Editor's Note: I'm back. --Tim Ogden

1. Digital Finance: When I name an item "digital finance" you know I'm going to be talking about mobile money and fintech--but should you? Is there something that's particularly more digital about mobile money than about payment cards or plain-old ATMs (both of which are, of course, fintech). Arguably paying a vendor with a credit card requires fewer real world actions than using mobile money--there are certainly fewer keys to be pressed. That's the overriding thought I had when looking at this new research from CGAP and FSD Kenya on digital credit in Tanzania: digital credit looks like credit cards. It's being used to fill gaps in spending, not for investment; is mostly being used by people with other alternatives; it's mostly expanding the use of credit (on the intensive margin); and it's really unclear whether it's helping or hurting.
Perhaps the most striking thing is that digital credit is not being used for "emergencies." Part of the interest, I think, in mobile money and digital credit was that it might enable users to better bridge short-term liquidity gaps given the well-documented volatility of earnings. But that's not what seems to be happening. Again it seems to be mirroring other forms of digital finance that we don't really call "digital finance", namely payday loans (which after all typically involve an automated digital transfer out of the borrowers checking account). Borrowers are very likely to miss payments (1/2 of borrowers) or default (1/3 of borrowers, based on self-reports, not administrative data). Given that, these papers (one, two, three, four) on whether access to payday loans helps or hurts seem like they should be required reading for digital credit observers (and don't forget the links from Sean Higgins a few weeks ago). The gist--they do help when there really are emergencies like natural disasters, but hurt a lot when there aren't.

This week in the US is providing an unusual window into emergencies and digital finance. The sharp declines in the US stock market caused a lot of folks to go look at their portfolios, which brought down a new generation of digital finance websites like Wealthfront and Betterment. Even Fidelity and Vanguard had problems. There's an element there of concern about mobile money systems in developing countries: we really don't know what a "run" on a mobile money platform would look like and how systems and people would be able to handle outages whatever their cause. But the more important story is that the problems encountered were probably pretty good for consumers. Preventing people from accessing their accounts in the perceived emergency of stock prices dropping kept them from panic selling, which is a thing humans do a lot. In fact, for those customers that could log in, they found lots of artificial barriers to taking action. Digital finance's key contribution in this case wasn't expanding access, it was limiting it.


2. Household Finance: Which brings us back to the ever recurring theme of household finance: it's complicated and we really don't understand it very well. What we do understand is that it's very hard for people to make sound decisions (causal inference is hard!) when it comes to money. Here, at long last, is the write-up of work by Karlan, Mullainathan and Roth on debt traps for fruit vendors. You may remember this being referenced in the book Scarcity--but if not, the basics are that people in chronic debt who have their loans paid off fall quickly back into chronic debt. That also seems like something digital credit observers should be thinking about.

Here's another understudied puzzle: consumers do seem to react to stock market gyrations even though only a small portion of Americans have meaningful investments in stocks. Really, the figure is a lot lower than you likely think. But if it's not sold out yet, you can start investing in stocks at a big discount today--not because of the decline of the stock markets, but this curious offer to buy a "gift card" for $20 worth of stock in major companies for $10. I stared at this for a long time wondering, "Should I use this as a teaching tool for my kids? And if so, should the lesson be arbitrage or why not to invest in individual stocks?"
   
3. Our Algorithmic Overlords: I promised a review of Virginia Eubanks new book Automating Inequality this week, but I'm not ready yet. In the meantime, I'll point you to Matt Levine's discussion of how little of what we do matters and how big data is starting to illustrate that. It's a riff that starts from a new paper showing that what banks do doesn't seem to matter much, which I suppose is a big support to the point above about how hard household finance is--even highly paid professionals can't seem to do anything that makes a difference.

And the founder of the Electronic Frontier Foundation died this week. I found this reflection thought-provoking in a number of directions: "I knew it’s also true that a good way to invent the future is to predict it. So I predicted Utopia, hoping to give Liberty a running start before the laws of Moore and Metcalfe delivered up what Ed Snowden now correctly calls 'turn-key totalitarianism.'”

4. Aspirations, and Risk: I've been linking fairly frequently lately (e.g. this overview from David Evans or Campos et al in Togo) to work that might fall into a broad category of "boosting aspirations,” though even whether that moniker is accurate is still unclear. But there are a number of papers finding that if you help people believe that what they do matters and they can improve their lives (regardless of what the data from banks tell us), that can have a big positive effect on their behavior and outcomes. Here's a post on promising early results of another of these studies, with Jamaican entrepreneurs.

Of course, with our good economist hats on we should wonder about persistence of aspiration-raising, and general equilibrium effects. Here Galiani, Gertler and Undurraga find that boosting aspirations through the visible gains of neighbors wears off pretty quickly.

But I've been thinking about this more and more through the lens of risk, particularly on the back of Jonathan's write-up of the new Townsend results on risk-adjusted returns for poor farmers last week. If you haven't read that yet, you definitely should. Perhaps one of the reasons that aspiration-raising is working is that it is boosting people's willingness to take on risk. I'll be writing a lot more about this in next week's faiV.

5. Surprise:
I'm easing back into the faiV, and it's late in the day. So I'm going to surprise all of you and just stop there for now. But I can't not have a link, so go play this game about the "retail apocalypse" in the US that Bloomberg put together. And for the American GenXers out there, prepare for flashbacks to Kings Quest.

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 December 4, 2017

In terms of this week's through-line, I figured I might as well get in on the Star Wars jokes that are going to plague us all, apparently, for the rest of time--Tim Ogden

1. Social Investment: Last week I was at European Microfinance Week. Video of the closing plenary I participated in is here. My contribution was mainly to repeat what seems to me a fairly obvious point but which apparently keeps slipping from view: there are always trade-offs and if social investors don't subsidize quality financial services for poor households, there will be very few quality financial services for poor households.
Paul DiLeo of Grassroots Capital (who moderated the session at eMFP) pointed me to this egregious example of the ongoing attempt to fight basic logic and mathematics from the "no trade-offs" crowd. This sort of thing is particularly baffling to me because of the close connection that impact investing has to investing--a world where everything is about trade-offs: risk vs. return; sector vs. sector; company vs. company; hedge fund manager vs. hedge fund manager. The logic in this particular case, no pun intended, is that a fund to invest in tech start-ups in the US Midwest is an impact investment, even though the founder explicitly says it isn't, because it is "seeking potential return in parts of the economy neglected by biases of mainstream investors." If that's your definition of impact investing you're going to have a tough time keeping the Koch Brothers, Sam Walton and Ray Dalio out of your impact investment Hall of Fame. Sure, part of the argument is that these are investments that could create jobs in areas that haven't had a lot of quality job growth. But by that logic, mining BitCoin is a tremendous impact investment. You see, mining BitCoin and processing transactions is enormously energy intensive. And someone's got to produce that energy, and keep the grid running. Those electrical grid jobs are one of the few high paying, secure mid-skill jobs. Never mind that BitCoin mining is currently increasing its energy use every day by 450 gigawatt-hours, or Haiti's annual electricity consumption. And, y'know, reversing the trend toward more clean energy. Hey anyone remember the good old days of "BitCoin for Africa"?


2. Philanthropy: There are plenty of trade-offs and questions about impact in philanthropy, not just in impact investing, and not just in programs. Here's a piece I wrote with Laura Starita about making the trade-offs of foundations investing in weapons, tobacco and the like more transparent.
I could have put David Roodman's new reassessment of the impact of de(hook)worming in the American South in early 20th century under a lot of headings (for instance, Roodman once again raises the bar on research clarity, transparency and data visualizations; Worm Wars is back!; etc.). The tack I'm going to take, in keeping with the prior item, is the impact of philanthropy. The deworming program was driven by the Rockefeller Sanitary Commission and is frequently cited, not only as evidence for current deworming efforts, but as evidence for the value and impact of large scale philanthropy. Roodman, using much more data than was available when Hoyt Bleakley wrote a paper about it more than 10 years ago, finds that there isn't compelling evidence that the Rockefeller program got the impact it was looking for. Existing (and continuing) trends in schooling and earnings appear unaltered. 
Ben Soskis has a good overview of the seminal role hookworm eradication had in the creation of American institutional philanthropy. His post was spurred by an article I linked back in the fall about the return of hookworm in many of the places it was (supposedly?) eradicated from by Rockefeller's philanthropy. We may need to rewrite a lot of philanthropic history to reflect that the widely cited case study in philanthropic impact didn't eradicate hookworm and may not have had much effect. And while we're in the revision process, it may be useful to reassess views on the impact of the Ford Foundation-sponsored Green Revolution: a new paper that argues that there was no measurable impact on national income and the primary effect was keeping people in rural farming communities (as opposed to migrating to urban areas). Given what we now generally know about the value to rural-to-urban migration, that means likely significant negative long-term effects.
If you care about high quality thinking about philanthropy, democracy and charitable giving in general, which I of course think you should, you should also be paying attention to some of Ben Soskis' other current writing. Here he is moderating a written discussion of Americans' giving capacity. And here's a piece about how the Soros conspiracy theories are damaging real debate about the role of large scale philanthropy in democratic societies.
In the spirit of the holidays, I feel like I should wrap up an item on philanthropy with some good news. In the last full edition of the faiV I mentioned the MacArthur Foundation's 100&Change initiative, which is picking one idea to get $100 million to "solve" a problem. For all the problems I have with that, the program is doing something really interesting, thanks to Brad Smith and the Foundation Center. All of the proposals, not just the finalists, are now publicly available for other foundations to review.

3. Frustrated Employees: One of the core conceits of the microfinance movement is the idea that many (most?) poor people are frustrated entrepreneurs, with lots of ideas and opportunities available if only they had access to credit. It's one of the reasons that we didn't get the impact we were looking for from massive expansion of microcredit.
The idea of frustrated entrepreneurs still lives on for a lot of the general public, but I think (hope?) it's been largely abandoned within the core of the industry. But just in case, I thought I would pass along some more evidence that the poor are frustrated employees, not frustrated entrepreneurs. Here's a paper looking at small enterprise owners in Mexico, who shrink their businesses when jobs come to town, in anticipation presumably of giving up the grind of entrepreneurship for the dream of a paycheck. And here's a look at Thai entrepreneurs operating multiple micro-enterprises that concludes that it's not lack of credit that's holding back their businesses, but their own lack of skills.
One of the paradoxes of the microfinance movement was that co-existing with the idea that the poor were frustrated entrepreneurs just waiting to be unleashed was the emphasis on providing a loan with conditions that made entrepreneurial risk-taking difficult if not impossible. Field and Pande showed quite a while ago that if you relaxed the constraints on loan payment, some borrowers would make riskier investments and gain from it. Here's a recent follow-up to that work which adds further evidence--again finding that borrowers with a more flexible contract end up with higher business sales, but also that the contract does a good job of inducing self-selection of borrowers who do have more of the necessary characteristics for entrepreneurial success.
It's not just people in lower income countries that are frustrated employees. Many employees are frustrated employees--frustrated that the jobs they have are terrible. Here's Zeynep Ton on the case for relieving that frustration and creating better jobs.

4. Our Algorithmic Overlords: A couple of quick hits here. First, the Illinois Department of Children and Family Services tried to use big data and algorithms to predict which children were at most risk. They're scrapping the program "because it didn't seem to be predicting much."
And here's Zeynep Tufecki on the dystopia we're building "just to make people click on ads." Definitely not the impact we were looking for.

5. Household Finance: If there's any impact the microfinance movement was not looking for, it was to replicate the troubling situation with debt that we see in many lower income American (and European, though to a lesser extent) households. It's one of the reasons the industry was so fixated on emphasizing that they were making entrepreneurial loans not consumption loans. The Urban Institute has a new interactive map on debt in America, with data down to the county level. There's a lot to explore there--CityLab has a nice summary overview if you just want some takeaways. The Mimosa Index is doing something conceptually similar for microfinance, albeit at a much grosser level due to data constraints. Hey, MicroSave what about doing something like this for digital credit in Kenya?
And to tie everything together, from trade-offs to impact, here's some new work from Emily Gallagher and Jorge Sabat (via Ray Boshara's blog post) on the trade-offs households have to make between savings and debt--finding (in the US) that the short-term sub-optimal choice of saving at low interest rates while carrying high-interest debt pays off in the medium-term. The mechanism is having some liquidity to meet shocks without running up more debt. I have some ideas (and some organizations willing to try them) about how to maintain liquidity while reducing debt, so if you'd be interested in funding a pilot, just let me know. 
Ray's post is motivated by thanking his dad for giving him advice as a teenager to always have some savings on hand, even if it meant ultimately paying more in interest on loans, advice that now has an empirical basis. I can't let that opportunity for one of my standard harangues pass by: the state of personal finance advice is horrific. Here's a piece from the NY Times this week which under the heading of getting "better at money in 2018" advises readers that cutting out small indulgences can add up and that they should spend more on take-out to be happy. Gosh I wonder which of those pieces of advice is more likely to be taken?  

Via Barbara Magnoni of EA Consultants, a little video about international remittances to hopefully brighten your weekend. It's certainly better than a Star Wars joke.

Week of November 27, 2017

Editor's Note: Two weeks ago, I told you that the faiV would be off for two weeks, and that's technically still true, because this isn't the faiV.--Tim Ogden

1-4. An Experimental Podcast: Every month or so someone asks me if I've considered doing the faiV as a podcast. The answer is not really, because the faiV doesn't lend itself to audio at least when I'm not ranting. Also because I rarely listen to podcasts because I don't commute and realistically I'm never going to sit at my desk and listen to audio for 30 minutes or more.

But because of the Thanksgiving holiday and travel this week to European Microfinance Week I wasn't able to the faiV. So I thought it was a good time to experiment with an addendum to the faiV in podcast form. Thankfully Graham Wright of Microsave agreed to experiment with me. So we recorded a conversation about digital finance, its potential and its pitfalls, inspired by Graham's post, "
Can Fintech Really Deliver On Its Promise For Financial Inclusion?"

We discuss whether mission matters, barriers to adoption, the tensions in building agent networks and why everyone who says "X is not a silver bullet" is lying. All in just over 30 minutes. Give it a listen and let me know if you'd like to hear more conversations like it.

 

Table of Contents:
1:45 - Can Digital Finance be Transformational for the Rural Poor?

3:51 - Does it matter that most DFS providers have never had a "pro-poor" mission?

7:54 - Does the US and microfinance experience foretell the future of digital finance?

13:42 - Biggest challenge for DFS: Lack of Education, Lack of Infrastructure or Lack of Consumer Protections?

21:50 - The Tensions of Agent Networks

27:00 - Financial Inclusion and Silver Bullets

31:13 - The Consequences of Removing Frictions

And because I can't stop myself, here are links to some of the things we talk about:

Graham's original post that inspired the conversation
Cathy O'Neil's book Weapons of Math Destruction
Cull, Demiguc_Kunt and Morduch: Microfinance Meets the Market and The Microfinance Business Model
[Note: Jonathan and I had a long email discussion today about whether my description of for-profits serving more poor customers overall, while non-profits are more likely to serve poorer customers and women is true given how the microfinance industry has rapidly evolved and the limitations to data. We didn't resolve the question.]
Mersland et. al. on loan officer "mission drift"
Don't Swipe the Small Stuff
MicroSave work on agents: Solving Agents' Liquidity Problems; Improving Agent Network Performance; Enhancing Agent Networks


5. the faiV Live: And if you really miss the faiV, the closest you'll get this week is the livestream of the closing session from European Microfinance Week where I'll be discussing the future of microfinance with Paul DiLeo, Renee Chao-Beroff and John Alex at 09:30 EST/15:30 CET.

Week of November 13, 2017

The Trolling Edition

Editor's Note: In this week's edition I'm using the world "trolling" broadly, and less negatively than it is often used. I'm using it to describe pieces that raise the ire or the fears of readers, not to suggest that the ideas are purposefully wrong or misleading. 
Thankfully (pun intended) I have some time to come down from the ire that writing this edition produced in me. There won't be a faiV the next two weeks because of vacation and travel, though I may produce a special edition coming out of European Microfinance Week which I'll be attending. If you're there, feel free to troll me--Tim Ogden


1. Our Algorithmic Overlords: I saw someone joke on Twitter recently that the best way to do a literature review was to complain on Twitter that "no one is studying..." and just use the incensed replies that come pouring in. It's an interesting form of trolling. This week Cathy O'Neil, author of Weapons of Math Destruction and perhaps better known as mathbabe.org, had an Op-Ed in the New York Times saying, "Academics aren't paying attention to our algorithmic overlords." Of course, I agree with the need to pay attention--hence this regularly featured topic--but it's a curious framing that academics aren't paying attention. In fact, all of the examples she gives of areas where academics need to be paying attention to algorithms and their effects are areas of intense academic work. Say the use of sentencing algorithms. Or teacher assessments. Or dynamic scheduling.  
And it's not just the specific instances. There's also work on the big picture of the use of algorithms and big data in policy making. Or simply understanding how companies will approach gathering and using data and algorithms (How could I not link to a paper so excellently titled as "Seeing Like a Market"?). Or how about a whole academic center "examining the social implications of artificial intelligence"? The conspiracy theorist in me couldn't help noting that the center, at NYU, was officially announced the day after O'Neil's op-ed which proposes an academic center, though they have a 2nd annual report on the use of AI and 10 recommendations to guide research and accountability.  
I can hardly be opposed to academic research centers, but it seems to me that what's missing is not academics paying attention or research centers devoted to the topic, but a Consumer Algorithm Protection Board. Yes, this is a pipe dream given the dire outlook for the Consumer Financial Protection Board, but it is a pipe dream I'm particularly fond of. Anyone want to help me make the case for it?

2. Household Finance: Before the algorithmic overlords item gets ridiculously long, let's move on to something that could fit either under algorithms, protection boards, or household finance. Entrepreneurial Finance Lab, which uses psychometrics to assess creditworthiness, has a piece on the FICO blog about how their testing for personality traits like impulsiveness and delayed gratification predicts default rates. It's such a good example of why I've been a fan of EFL while being queasy at the same time, it almost felt like I was being trolled. On the positive side it's an operationally relevant way of assessing borrowers who otherwise would be shut out of access to credit. On the queasy side, there's apparently huge variation in different cultures (while the metric remains predictive), and real questions about the immutability of the features they are testing--which cuts both ways. If they're mutable there's a question about what we are measuring; if they're immutable, what do we do about people who lost the "present bias" lottery? It's a good thing to protect people from themselves by not offering them credit they are likely to default on, but it still leaves me queasy nonetheless.
In terms of others being trolled, here's a piece about Refinery29's ongoing series where women share a week-long financial diary, and then readers rip apart their life choices. I'm not entirely sure whether it's the ones sharing or the ones critiquing that are the trolls, perhaps both.
And since we're on the topic of diaries and I've already gone fishing for help on one research interest of mine, here's another: I read this week that more than 100,000 puertoriquenos have migrated to Central Florida since this fall's hurricanes. Wouldn't it be great to do financial diaries of those households? It's a really unique opportunity, wouldn't be very expensive to do, and it breaks my heart to see it go to waste. If you think so too, call me.

3. US Inequality: The big news this week in the US is the Republican tax plans. Here's Saez and Zucman's take. And here's Tyler Cowen arguing that argument that corporate tax cuts will lead to more investment is empirically sound (which some will undoubtedly believe is trolling on Cowen's part).
Beyond the current tax issues, here's a new paper that attributes growth in income inequality to relatively small-scale business owners (as opposed to corporate executive pay or passive investment income). And here's a thought-provoking post about a different impediment to fighting extreme inequality: the very high cost of investing in low-income neighborhoods because of land-use restrictions. And on that theme, this piece from Felix Salmon on who gets hired to lead organizations is also an important part of the story on inequality and mobility. 

4. Evidence-Based Policy and Methods: One could easily argue that this new paper from Alwyn Young is trolling the entire community of economists who "grew up" in the age of instrumental variables. It certainly has generated a lot of concerned responses about the need to reassess a lot of work relying on IV. Nancy Cartwright, meanwhile, has been similarly trying to punch holes in people's faith in the use of RCTs for guiding policy (and I'm sure some in the movement would think of her in trolling terms). Here's a new paper (with co-authors) on the challenge of moving "evidence-based policy" from ideas to local implementation
I know a lot of MFI executives who have felt trolled by the research community over the years. But for anyone who is ready for more on the question of who does microcredit help and who doesn't it help, here's a podcast with Alice Evans and Rachael Meager discussing Meager's paper (covered way back in January) on how to better understand the results of the microcredit impact evaluations.

5. Philanthropy and Social Investment: Finally, this week there were several pieces on philanthropic practice that felt like they were directly trolling me. First, Gabe Kleinman wonders "Why aren't foundation's actually helping their grantees like VCs?" Kleinman is apparently unaware this is an idea that is more than 20 years old. By the time I came into the space a little over 10 years ago, one of the first pieces I tried to commission was tentatively titled, "picking over the corpse of venture philanthropy" because it was already "old news" by then. And like Cathy O'Neil's piece, Kleinman gives lots of examples of things foundations "should be doing" where foundations are actually doing those things, he is simply unaware of them. Overall, it's a fine example of the annoyingly common, but intellectually bankrupt "non-profits should act more like businesses" idea that fails in two ways: it holds up how businesses operate in theory rather than reality; and shows a profound ignorance of the challenges of social investing. 
Speaking of the challenges of social investing, there is a new philanthropic effort (with big time funding including Gates) targeted at "systemic change," lamenting that it is hard to for funders to collaborate and there are few "big ideas" or non-profits able to effect systemic change. Again, grrrrrr. One of the reasons for the challenges noted is the "venture philanthropy" mindset which if taken at face value discourages collaboration and emphasizes short-term metrics. But it's also true that there have been (and continue to be) lots of collaborative efforts--these ideas are not new--and they often struggle because it's virtually impossible to arrive at agreement on how systems should change, who gets a seat at the table and what priorities should be. Co-Impact will make grants of up to $50 million for up to 4 years, which is nice, but hardly seems like the scale necessary for systemic change if those words mean what I think they mean. For comparison, the grants are at most half of 100&change, which has narrowed down to surprisingly prosaic ideas that I don't think anyone would describe as systemic.
Finally, to end on a positive note, here's a piece about how the Hewlett Foundation has retooled it's grant reporting process so that's its more useful for everyone. The trolling element? I'm not a Hewlett grantee.

  Duck of Minerva  also known as Steve Saideman writes about the peer review process and who is doing the work in various social sciences. It's a whole new form of inequality!

Duck of Minerva also known as Steve Saideman writes about the peer review process and who is doing the work in various social sciences. It's a whole new form of inequality!

Week of November 6, 2017

The Conundrum Synthesis Edition

Editor's Note: This week I attended a 2-day AspenEPIC meeting on consumer debt (in the US) and then a day with the Filene Institute on the "Mind-Money Connection." This week's title is inspired by some of Ray Boshara's comments at EPIC about conundrums in understanding consumer debt. But both events once again illustrated the desperate need for more synthesis of ideas and experience between the developing world and the developed world on financial inclusion. Ray also pointed out to me that while I introduced myself when I took over writing the faiV nearly 2 years ago, it's not apparent on a regular basis who the "I" is. So from now on, I'm going to sign these notes each week--Tim Ogden

1. Appropriate Frictions and End-User Behavior: A key theme of the EPIC conversations on debt from my perspective was the importance of differential frictions in access to various kinds of debt. One example: it's much more time consuming to open a home equity line of credit than a credit card account. There are reasons for that of course: we want people to be careful about borrowing against their home, because we fear the consequences for people if they default. But the cost of unsecured credit is so much higher, and various forms of debt are so interlinked, that households can end up in worse straits precisely because we tried to protect them. The true conundrum of appropriate frictions is that the process of determining the best form of credit for a household is in itself a friction that drives consumers toward those willing to provide credit without a care for its impact on the household--a somewhat obtuse but accurate way of describing predatory lenders.
This is one of the lessons from microcredit. Demand for microcredit in most contexts is actually quite low, and rarely did microcredit have much of an impact on local moneylenders. The reason of course being that taking a microloan usually involves a lot of friction, while borrowing from a moneylender is low friction. Those operating in the US will immediately see the exact overlap with payday/auto-title lending vs. working with a community development credit union.
But it's not just a question of the behavior of consumers. Front-line staff also play a role; they are an under-recognized form of end-user that has to be taken into account. Here's some new work by Beisland, D'Espallier and Mersland on "personal mission drift" among credit officers of Ecuadorian MFIs. Now don't look away because this is about microcredit or Ecuador--it's directly applicable to any kind of financial service offered to any kind of customer anywhere. Beisland et al. find that as credit officers gain experience they tend to serve fewer "vulnerable" clients (e.g. smaller loans, young borrowers, disabled borrowers). Why? Because it takes too much time--there are those frictions again. Figuring out how to offer quality products, especially credit, with appropriate frictions for both the borrowers and the credit officer, is a conundrum everywhere.
For further evidence of this, check out the similarities between this piece from Bindu Ananth about conversations with newly banked customers in Indian cities, and this report on "Generational Money Chatter" in the US from Hope Schau and Ignacio Luri (especially from GenXers and Millennials). The common theme I perceive: lots of questions and uncertainties about products and providers, little faith in the "systems," and confusion about where to turn for trustworthy advice.    


2. Frictions, Temptation and Digital Finance: Those of you working in the digital finance world may already be thinking about how digital tools can lower frictions--after all, not only can FinTech tools more quickly and easily gather data from consumers, but they often cut the front-line staff right out of the equation! Take that, friction!
Oh but friction can be useful. This is one of those areas where I'm constantly baffled at the disconnect between the developed and developing worlds. In the developed world, it's generally understood that the goal of payment and digital finance innovation is usually to remove friction specifically for the purpose of getting people to spend more money, more often. Amazon didn't develop and patent one-click ordering out of concern for saving people time (Interesting side note, Amazon's patent on one-click expired last month--exogenous variation klaxon!). The sales pitch that credit card issuers make to merchants has always been that credit cards induce people to spend more.
Here's one of my favorite new pieces of research in a long time: a study of how people in debt management plans handled spending temptation (if that description is too dry to get you to click, try this one: "Target is the Devil!"). The sub-text, and sometimes text, is how hard retailers and some credit providers work to break down the frictions that prevent people from spending.
What's the connection to digital finance, particularly in developing countries. I'll enter there through this piece from Graham Wright based on a debate at the recent MasterCard Foundation Symposium on Financial Inclusion. Graham was asked to make the argument against the hope for digital finance serving poor customers. His list of five reasons why digital finance is "largely irrelevant" in the typical rural village is worth reading at face value. But it's also worth thinking about in terms of how much of digital finance is aimed at removing frictions, how it's failed to remove some of those frictions for poorer customers and what can (or will) happen to poor households when appropriate frictions are removed.

3. Quality Jobs: Another conundrum that deserves more global synthesis is the struggle to create quality jobs for low-income households. Certainly one factor of quality jobs is how much they pay. While there's little doubt that productivity has a big role to play in wages, it's not always clear, particularly since 1973 (the year I was born, coincidence?) how close that link is. Stansbury and Summers have a draft of a paper arguing that the link is still pretty strong. Josh Bivens and Larry Mishel push back, arguing that policies that undermined workers' power led to a divergence of wage growth and productivity growth, and a continuing decline in jobs that pay well enough to be quality jobs.
The stagnant wages for many workers since the 1970s is one of the reasons it's clear to me that it is no longer sufficient to look at having a job as binary. Here's a new review on jobs and recidivism that finds evidence that the quality of job is what matters in helping the formerly incarcerated stay out of prison. Here's a paper from Haltiwanger, Hyatt and McEntarfer on another aspect of job quality--a chance to move up the "job ladder"--and who is getting the opportunity to move up. The surprising news: less-educated workers are more likely to move from a low-productivity firm to a high-productivity one (which should lead to higher wages, but per Mishel et al above, perhaps not).
There's more than one way to take on raising the quality of jobs. Here's work from Akram, Chowdhury and Mobarak on the effect of people moving out of poor areas for better jobs. In short, they are studying a program that subsidizes rural Bangladeshi villagers migrating to cities during the low agricultural season. We already know that raises the wages of the migrants, but it also helps those who don't migrate by tightening the labor market in the villages. Here's where I have to mention that geographic mobility in the US is declining. Meanwhile, take the example of Chicago where segregation continues to shut people out of access to quality jobs, and more. Time for more programs to help Chicagoans migrate, I think, perhaps by reducing some of the frictions.

4. Evidence-Based Policy: Rachel Glennerster examines several cases where evidence led to scaling up programs, asking "When do innovation and evidence change lives?" She doesn't mention the scale-up of the seasonal migration program in Bangladesh mentioned above, but highlights several different models of research and scaling. For those more technically minded, Eva Vivalt has a new version of her paper and an accompanying blog post on research generalizability--how much we can expect a research finding to hold when it is tried elsewhere (or just scaled up). But if you're just looking for examples of research findings that did or didn't hold in differing contexts, take a look at this thread responding to Jess Hoel's appeal for examples to use in her teaching. 
Of course one factor in how generalizable research findings are is the contexts the research is conducted in. David Evans mapped the papers presented at the recent NEUDC conference in three ways (see the comments for the third one). Do you see too much concentration?

5. Neoliberalism: Finally, here's Dani Rodrik on the state of economics and the use of the term neoliberalism. I'm not going to pretend that I can do the piece justice in summary form, so I'll just provide the link and tell you to click on it. Here's the backstory of how the piece ended up in Boston Review.

  In case you were too lazy to click on the link to  David Evans' mapping  of 2017 NEUDC papers, here's the first chart. To get the other two, you're going to have to click. And scroll. Via  Development Impact .

In case you were too lazy to click on the link to David Evans' mapping of 2017 NEUDC papers, here's the first chart. To get the other two, you're going to have to click. And scroll. Via Development Impact.