1. The Search for Truth: The New York Times Magazine has a long piece about Amy Cuddy, the social psychologist of "power posing" fame, and the messy process by which her research has been popularized and then discredited. The piece suggests that Cuddy (though it by no means holds her out as blameless) has been uniquely and personally targeted as the face of unreplicable and bad social science in an era of changing research practices and expectations, perhaps because she is a woman. More broadly it ponders whether the process and social conventions of communication around challenging social science research may do more harm than good. It points specifically to Uri Simonsohn, Joseph Simmons and Andrew Gelman and their roles in both calling out bad social science and in specifically highlighting Cuddy's power posing paper as an example.
It's well worth the long read, careful consideration but also some critical evaluation. The piece comes at a very interesting time, with the Weinstein saga, #MeToo, and more specifically the push back about Econ Job Market Rumors and bad behavior in economics. It's important to read the piece in the context of such things as EJMR and this anecdote from Rohini Pande (in an interview with David McKenzie this week) relating how a "senior male World Bank economist wrote to our senior male colleagues at MIT and Yale asking that they review our work and correct our mistakes" in one of her early papers (with Esther Duflo; see question 4 in the link, but read the whole thing, it's very good on a lot of topics).
But on reflection, I don't think the idea that Cuddy was uniquely targeted or treated more harshly than others holds water. It only appears so to a New York Times reporter because Cuddy's works is the kind that gets broad attention. Remember when Ben Goldacre kicked off "Worm Wars" with an amazingly condescending piece asking people not to point and laugh at Miguel and Kremer for the supposed "errors" in their Worms paper because they shared their data? Or the language and dudgeon around Reinhart and Rogoff's Excel error? Or the intemperate words flowing around the failure to replicate John Bargh's priming work? From another field, here's some pointed language challenging a recent result on gene editing alleging some pretty basic errors.
Of course, the commonality of bad behavior in academic circles doesn't excuse it. But that cuts both ways. Cuddy has also been using this faulty logic in her own defense. As far as I can tell, her main defense has always been "everyone was engaging in bad research practices, so it's not my fault", and that's definitely the implication that the NYT article gives. I don't see much distance between that and people excusing sexual harassment because they were "raised in the '60s and '70s."
Could the practice of social science be better? There's no question, but it's also not clear exactly how, other than the obvious avoidance of misogyny, ad hominem and personal attacks. But that line is difficult to see sometimes because the nature of social science research requires a great deal of personal investment. It's hard not to feel attacked when one's research, quite literally one's life's work, is criticized.
To me, the most thought-provoking part of the NYT piece is when Simmons, reviewing an email he sent to Cuddy about follow-up work on whether the power posing research was reliable, says "that email was too polite" given how serious he thought the problems were. And there is a lot of bad science that needs to be called out. This week, there's yet another update to the Brian Wansink saga--several papers flat out misrepresent who the study participants were (e.g. a paper claiming participants were 8-11 when they were 4-5). Not calling bad science out, I think, is a real contributor to real world problems, like Chief Justice John Roberts being able to call good political science research "sociological gobbledygook."
Here's a Chris Blattman thread on his reactions. Here's Andrew Gelman's response to the NYT piece and for the sake of this topic it is one of the few posts anywhere on the internet where you should read the comments. Someone in one of the Twitter threads wondered about the responsibility of Gelman and other bloggers like Tyler Cowen to police their comments. I'm sympathetic to this idea, but I'm old enough to remember policing comments on my own blog. It's an incredibly time-consuming and soul sucking affair with lots of trade-offs. The "business model" of blogging just doesn't allow it. In fact, in some ways it was the business model required to police commentary, also known as paid journalism, that led to blogging: the gatekeepers of commentary shut out too many voices who should be heard. Science, and the pursuit of truth, is hard.
Week of October 9, 2017
1. Evidence-Based Policy: Yesterday I was at a workshop hosted at Yale SOM and funded by the Hewlett Foundation on how to better connect evidence to policy. The workshop was part of a bigger project and a series of reports are coming that I will share when they are available. There was a lot of good discussion, but I thought I would share two thoughts that I find to be missing appropriate weight in evidence-based policy discussions. First, there is often discussion of a mismatch in the time horizons of researchers, implementers and policy makers. While this is no doubt true, the mismatch between those groups is trivial in comparison to the mismatch all those groups have with the amount of time it takes for change that people can feel to occur. Deworming's important effects--on earnings, not school attendance--are only felt decades after treatment. Moving to Opportunity similarly has a decade-scale effect. Few if any of the researchers, implementers or policymakers are still going to be around when the world really is undeniably different because of them.
Which brings me to the second point. The enterprise of evidence-based policy is grounded in marginal improvements across large groups of people--and that's a good thing! I'm a big believer in the value of marginal improvements (QED). But people have a really, really hard time noticing or caring about marginal improvements. Human beings prefer stories about big changes for a few people with unclear causality a lot more than they do about marginal gains with sound causal inference. I'm more and more convinced (because of evidence!) that hope is a key ingredient for even marginal impact, but hope comes from Queen of Katwe, not from 1/10 a standard deviation improvement in average test scores. So the unanswered question for me in this conversation is, "How do we manage the tension between the policies that are good for people and the policies that people want?"
In other evidence-based policy news, here's a rumination on the difficulty of applying research to practice in democratization (specifically Myanmar). And here's Andrew Gelman on not waiting for peer review, particularly in Economics, to start putting evidence into practice.
2. Evidence-Based Operations: OK, so there's one more thought: the gap between policy and research, and operations. But rather than a long discussion on that topic, here's a very good new piece on the operational choices of front-line social workers and the gap between policy (whether evidence-based or not) and practice. The challenge in the spotlight is not the Marxist-style view of workers dissociated from their work by rules but workers dissociated because of having too many morally-fraught choices. More light-heartedly, here's a piece that illustrates how hard it is to go from evidence to operational choices, as reflected through the failure of the US men's soccer team (I told you it would return). There is growing attention to front-line staff and the "product" as actually experienced by the beneficiary in impact evaluations, but much more is needed as far as I'm concerned.
3. Our Algorithmic Overlords: Speaking of operations, one of the areas where more attention is needed is the way that operations are being instantiated into algorithms that are opaque or entirely invisible. Ruben Mancha and Haslina Ali argue that that the unexamined algorithm is not worth using. Of course, they are arguing from ethics, not from business profits, where it's abundantly clear that unexamined algorithms are worth using.
Here's a piece about technology-related predictions from Gartner, a tech industry research and advisory company. Skip the first three to see some striking predictions about AI-generated false information, such as that people in "mature economies will consume more false information than true information." There's a threat to advancing evidence-based policy that definitely wasn't on the agenda yesterday. I started my career at Gartner way back in 1995 and I remember one of the first things we were given to read was an an article in Scientific American about the coming age of fake photography and video. Apparently that future has finally arrived.
Week of October 2, 2017
1. Abusive Practices: This is the part of the faiV that is different. But, perhaps contrary to the evidence, I have to hang onto the belief that making abusive practices in many domains more visible will in fact play a role in changing those practices. So first up is a piece about abuse of the elderly in Nevada where for years shady operators, aided and abetted by courts, legislators, medical professionals and other nominally civil servants have cooperated to revoke the rights and steal the assets of vulnerable people. That may seem an abstruse topic, but I think it has lots of parallels in many domains. Often, abuse of the vulnerable is tied to weak institutions or institutions that have no duty to those abused. Here we have strong institutions in many cases explicitly designed and supposedly devoted to protecting the vulnerable, which were turned against the people they were supposed to protect and which made challenging what was going on virtually impossible. As an aside, I have to commend Beth Rhyne of CFI who began talking years ago about the challenges that an aging global population would bring to financial inclusion and protection efforts.
At the other end of the age spectrum, here's a piece about the "1% winners/99% losers" labor market of young football/soccer players in England. It's a form of vocational school that consistently lies to 10 year-olds and their families and then dumps the vast majority of them at age 16.
Stretching even further afield, I'm hoping that many folks will find the time to read, or at least scan, the NY Times article on Harvey Weinstein, the movie mogul, and his decades of sexual harrassment and abuse and cover-ups. I'm particularly struck, if not surprised, because Weinstein moved in supposedly progressive circles. His behavior was apparently an open secret but did not dissuade many from working with him and for him and apparently participating in the glossing over of the abusive practices that let him continue. This piece about the lack of criticism coming from Hollywood is particularly pointed.
And now to connect this back to something more faiV-like: I hope the Weinstein saga provides further momentum behind efforts to reform practices and behavior in the social sciences, particularly when it comes to the academic job market. There is a rapidly growing effort particularly in Economics (with offshoots as far as I can tell in Political Science and Sociology) to make job market information more transparent, but more importantly move it away from sites like EconJobRumors which facilitate abusive behavior. Check out the hashtag #EJMinfo for more. This is a rare obvious opportunity to choose between the type of behavior that enabled Weinstein, and the type of behavior that will make such abusive practices and behavior impossible.
2. Economic History, History of Economics, and Evidence: Pseuderasmus, the pseudonym for an economic historian whose real name I don't know, has a long (long, long) post about the productivity gap that opened between India and Japan in the first 30 years of the 1900s. It's filled with fascinating historical details, so even a skim of it will be rewarding. The short version is that the power of unions in Japan was restrained by demographics, culture and the government which allowed manufacturers there to innovate far more quickly and increase productivity. This in turn left Japanese workers eventually far better off than Indian workers where labor unions exerted more power.
Beatrice Cherrier and Andrej Svorencik have a new paper examining the history and evolution of the Clark Medal and it's winners. Again there are plenty of interesting details to reward even a skim. I took particular note of the concentration of winners--eight universities account for all winners in terms of where their degree was earned, and 10 for all winners in terms of employment when they won. So economists are apparently uniquely good at identifying talent early, right? Right?
Finally, this week I stumbled on a newish site, Straight Talk on Evidence, that reviews not the evidence for various programs and policies (for instance as the Cochrane Collaboration, AidGrade or 3ie does), but the claims made by studies that are part of the evidence base. It's a project of the Laura and John Arnold Foundation. Here is their review of an evaluation of CCTs in the United States and of a Heckman paper on the long-run health impact of early childhood education.
Week of September 25, 2017
1. Basic Income: I haven't touched on basic income in what seems like months, but that's because there was little to report. This week Planet Money has an episode (adapted from 99% Invisible) on the details of what basic income is and how it might be delivered. And apparently last week, Y Combinator announced some more details of their US Basic Income study. If details matter to you, you'll be pleased to know that the work in Oakland that received a lot of attention last year was a feasibility study and now they are planning an RCT with 3000 individuals in two different states.
2. Methods and More: My next book of interviews is about big data and machine learning (If you have a better name than "Dated Conversations," let me know). Susan Athey is the first person I interviewed for the new book this past spring (I hope to have some excerpts of that interview available soon) in part because of some things Athey had written on how machine learning will change the field of economics. There's a new version of a (preliminary) paper on the topic. It has details.
More specifically on details and methods, here's a new paper on the use of randomization to study network effects, a quite tricky prospect. But when it comes to methods and details mattering, two items this week really hit the nail on the head. First, Buzzfeed of all places has a lengthy piece examining the myriad problems that have emerged as people examine the details of studies published by Brian Wansink's Food and Brand Lab at Cornell. Missing data, mis-described studies, statistical errors, it's stunning. This week also saw publication of what is many ways the exact opposite of what appears to be have happened at the Food and Brand Lab: David Roodman's incredibly detailed review and replication of the research on the relationship between incarceration (or decarceration) and crime rates for the Open Philanthropy Project. The starkest contrast for me isn't actually the attention to detail but the philosophy. The Wansink saga began with a blog post that indicated that the Lab was torturing data until it said what they wanted; the Roodman review and replication was done because they were concerned that their beliefs were wrong.
3. Microfinance, US and Global: My expertise and knowledge is definitely concentrated in global microfinance rather than microfinance in the US, but because of the work on the US Financial Diaries I'm learning a lot more about the US. This week for instance I got to hang around the outskirts of the Opportunity Finance Network meeting. There are no links here but a couple of things have really struck me and so I wanted to note them, and invite you to tell me what you think/have seen, etc.
First, I was really surprised about how open the US microfinance community is about the presence of and need for subsidy. Globally I see an almost totemic adherence to the idea of self-sustainability, even in the presence of compelling evidence of the prevalence of subsidy. I'm sure that's a consequence of how those industries have evolved but I'm curious about any ideas about the details of the US microfinance history that led to this.
Second, two parallel conversations really struck me. One was about "community investment" in order to create "quality jobs." The second was about how to use technology to cut down costs of making loans, costs that are mostly about staffing--or in other words, how to expand microfinance by lowering the need for quality employees in the lenders. I bring this up not to point fingers about hypocrisy, but to raise the inevitable trade-offs for MFIs everywhere about reach and cost. The tension doesn't seem to exactly be on the surface in the US but it is more apparent than in global conversations, where the value of the jobs created by the global microfinance movement seem to be ignored, especially in the rush to digital finance services.
Week of September 18, 2017
1. Microenterprise and Household Finance: I assume that most of you are familiar with David McKenzie's business plan competition in Nigeria (there's even a Planet Money episode about it!) and his cash drop work (I have to use this self-serving link of course). David and co-authors have a new paper in Science (summary/blog version here) testing the effectiveness of business training for microenterprises in Togo and find that a standard business curricula did not do much (in line with lots of other business training studies, though most are plagued by too little power) but a curriculum based on boosting personal initiative did have large effects.
I see this as lining up with a stream of research finding that boosting aspirations or "hope" can have meaningful impact in many different contexts (see for instance, this recent work on effects of watching Queen of Katwe) and through a variety of interventions (any one know of an overview of recent work in this vein?). It also helps explain why there seem to be only small effects of business training on businesses that objectively should have lots of gains from marginal improvements in operations--if you don't believe that running your microenterprise better will matter...
In other microenterprise/microcredit news, I learned this week about a study (new draft coming soon apparently) that tests allocating microcredit based on peer views of microenterprise owner business skills. Those ranked highly do in fact see large returns to a $100 cash drop (8.8 to 13% monthly returns). I heard about the study from this excellent thread from Dina Pomeranz on a talk by Abhijit Banerjee and Esther Duflo on what new they've learned since that "old" book Poor Economics came out.
Finally, here's a new piece from Bindu Ananth that should go on your "must read" list. I couldn't agree with this statement more: "[T]he field of household finance has failed to examine the financial lives of low-income families in sufficient detail." She examines specifically issues with how to think about insurance vs. savings, high frequency saving and borrowing, and financial complexity. I will continue to beat the drum on two points: 1) low-income households are having to make financial decisions that would challenge a finance MBA, with large consequences for sub-optimal choices, and 2) almost all the advice we have on making wise financial choices is built on an assumption that the life-cycle model holds true, and may not in fact be good advice if the life-cycle model doesn't hold.
2. Premium Mediocre and American Inequality: I'll lead this off with a concept that I'm not quite sure what to make of, but does have me thinking: Premium Mediocre. The post goes on way way too long, but it's worth reading at least through the first couple of scrolls for some new ways to think about the old problems of inequality and mobility, or lack thereof, and what it does to household decision making.
This summer I mentioned but failed to link to a study on how delivering food stamps more frequently lowered the rate of shoplifting in grocery stores in Chicago. Here's a new paper that shows a much larger and long-term effect of food stamp receipt. Children whose families received food stamps for more years (due to staggered roll out of the program in the 60s and 70s) were less likely to be convicted of any crime as an adult, with larger effects on violent crime.
The importance of such safety net programs in the United States is growing as we learn more about how household finances are changing. Not only is year-to-year volatility seemingly increasing, and month-to-month volatility seemingly spreading, but lifetime earnings aren't just stagnant--they're falling. Some new work indicates that since the late 1960's American men's expected lifetime earnings began falling each year (into the present). That can make premium mediocre a stretch for each new cohort. It also perhaps helps explain this new and fairly shocking chart, based on Case and Deaton's work discussed extensively in the faiV this spring, that has been circulating on Twitter this week.
Week of September 11, 2017
1. Digital Finance: There's a regular theme I hit when it comes to digital finance--digital gives much more power to providers, government or private sector, than physical cash does. And that is something we should worry about. So my confirmation bias when into overdrive when this crossed my feed this week: China is detaining ethnic and religious minorities in Xinjiang Province and one of the criteria for detention is people who "did not use their mobile phone after registering it." Brett Scott objects to cashlessness for both its inherent nature as a tool of surveillance and for more pecuniary reasons: unlike cash, every digital transaction generates fees. Which in turn gives power to the organizations that have a seemingly insatiable appetite for categorizing and controlling people. Hey, ever wonder why Facebook is pushing hard into payments, even into fundraising for non-profits?
Scott uses Sweden's progress toward cashlessness as a foil. Want to guess which other country beyond China and Sweden has made the most progress toward digital-only payments? Somaliland. Huh. Elsewhere, the progress of digital finance seems to have slowed to a crawl: 76% of mobile money accounts are dormant, and the average active user only conducts 2.9 transactions a month. Perhaps that's because of a huge gap in usability that will require a similarly large push in education (according to Sanjay Sinha).
Given the near unrelenting negativity above, I feel like I have to say for the record: I don't oppose digitisation. I oppose not recognizing and planning for the negative consequences of digitisation.
2. Global Finance: Digital finance and mobile money is generally about very local transactions. But another important use is long-distance transactions, particularly remittances. But international transfers of funds require banks to have relationships that cross borders. The technical term is "correspondent banks." What correspondent banks do is vastly simplify and accelerate the flow of funds across borders. So it's a problem that correspondent banking relationships are shutting down as a result of "de-risking," which is banking jargon for "avoiding anything that may draw the attention of regulators who have the somewhat arbitrary ability to impose massive fines." The IFC reports that more than a quarter of banks responding to their survey reported losing correspondent bank relationships with compliance costs the most common reason; and 78% expected compliance costs to increase substantially for 2017.
And now for a bit of levity, if you can call it that. Matt Levine has the incredible story of how the Batista brothers, owners of a large Brazilian meat-packing company, made money shorting the Brazilian Real--they knew recordings of their conversations with President Michel Temer about bribes were going to be released. Is that insider trading?
3. US Poverty and Inequality: This week the US Census Bureau released its report on income and poverty in the United States in 2016. The new was good, at least on a relative basis: incomes are growing across the board and poverty is down. But...the majority of gains are still going to upper income groups, and inequality continues to rise as a result. The bottom half of the distribution is only now getting back to where it was in 1999 or earlier. Here's Sheldon Danziger's take on the data and the policy implications. The Economic Progress Institute has a good overview (with good charts) of the poverty data specifically, which focuses on how safety net programs reduce the number of people below poverty by "tens of millions."
The 8+ million who are above the Supplmental Poverty Measure threshold because of refundable tax credits (e.g. the EITC and the Child Tax Credit) particularly caught my eye because of this profile of a US Financial Diaries household that I just finished. Amy Cox, for the year we followed her, is one of those people. For the year, she is above the SPM because of tax credits. But she receives all of that in one lump sum in February. So for 11 months of the year, she's poor. In 9 months of the year, she's around 75% of the SPM threshold. But officially, she's not poor. Makes me think it's time for a Supplemental Supplemental Poverty Measure that takes into account how many weeks a year someone is below the line.
In other US Financial Diaries news, here's Jonathan Morduch speaking about Steady Jobs without Steady Pay at TEDxWilmington this week (skip ahead to 1:30:00).
Week of September 4, 2017
1. Evidence-Based Policy and Methods: One of the reasons I took a few weeks off was in late August I was part of a panel at Stockholm International Water Week sponsored by Water.org on the "evidence base for WASH microfinance." If you've been following the evaluations of microfinance or of WASH you know that evidence base is thin (in more ways than one). Preparing for the panel got me thinking about the strange state of evidence-based interventions. [Warning: I'm going to oversimplify for the next few paragraphs; if you want not oversimplified I recommend the detailed write-ups GiveWell has on both deworming and WASH] Arguably deworming is the sine qua non of evidence-based interventions right now, but the arguably mostly comes not from whether there is some other intervention with a better claim, but that there are large swathes of people who don't believe the evidence for deworming: epidemiologists. Why? Because there isn't a plausible biological mechanism to explain where the gains from deworming come from. There is no consistent detectable effect of deworming on weight or anemia for instance.
In the meantime, there's no question that if you remove bacteria and viruses from water, people won't get sick and will have all sorts of positive short-term health gains. But the most rigorous evaluations of WASH interventions don't find detectable effects on incidence of diarrhea or other health or economic indicators. The most-likely story is that there are so many vectors for infection that people end up consuming contaminated water despite the WASH interventions (and given that doctors in US hospitals still won't wash their hands regularly, that's very plausible). In that way, WASH has a lot in common with microfinance--single point interventions in complex and broken systems are unlikely to produce large long-term effects.
So the state of play is that the intervention with a clear biological mechanism has no effect and the one with no clear biological mechanism has large effects. I hope I'm not the only one who finds that a bit discomfiting.
So what to make of all of this? The point I made at the conference is that building an evidence base isn't just about methodology but about what is being measured. In the WASH + microfinance space, I think the right metrics are about whether well-functioning markets are being created (see my rant about low-quality equilibria, or my "vaccine or antibiotic" theory of change for microfinance piece) where poor households have more actual ability to choose, including the option to not have to think about whether their water is clean.
A second important point is that there is a long way to go figuring out how to measure things we care about. To that point specifically, Rachel Glennerster and Claire Walsh have a post about the difficulty of measuring women's empowerment via surveys and the limitations of how empowerment is currently being measured. They have some useful specific suggestions for improving the current methods. Perhaps there will be some real traction here, as Glennerster was named the new Chief Economist of DfID this week.
Bonus Overflow Links: David McKenzie has a post about re-interviewing participants in unrelated evaluations. Kieran Healy is writing a book about Data Visualization for Social Science and posting most of the content as far as I can tell.
Week of August 7, 2017
This week's faiV is a fun change of pace of just visualizations & graphics - click through to see.
1. The Global Middle Class: By now, Branko Milanovic's elephant chart should be quite familiar. Nancy Birdsall of CGD has a new post about the state of the global middle class that delves into the elephant chart and other data looking at the state of the middle class globally.
2. Global Inequality: Another chart that may be somewhat familiar but certainly should be top of mind these days. Our World in Data looks at inequality, from a lot of perspectives, here before and after taxes and benefits in developed countries.
3. US Inequality (and Debt): Speaking of inequality before and after redistribution, Catherine Rampell at the Washington Post has a couple of interesting recent posts on policy to help (or not) lower-income workers. The first chart here made lots of waves this week in a post by David Leonhardt, and provides the visceral oomph behind the need to reassess policy in the US. Although this data and similar charts have been circulating for quite awhile, it still thankfully grabs attention.
Whether or not the top chart is related to the bottom chart is one of the questions that Aspen's EPIC is taking on this year. Regardless of the direct connection between income inequality and rising debt, the fact that we are back to record levels of credit card debt seems concerning since it's likely not the .001 percent taking on this debt. That being said, rising debt could also be a sign that finally consumer confidence is returning and people feel that their incomes may start rising again.
4. Statistics GIFS: You can't say I don't know my audience--you guys go crazy for things like this, at least that's what the click data says. The two images at the top are from Rafael Irizarry at Simply Stats, in a post about teaching statistics and how to think about data. Helpfully, the post includes the code to recreate each of the images (and he's got a lot more where these came from).
This week there was also a revival of the Autodesk post about how visualizations can mislead that I featured a while back. It's here again because Jeff Mosenskis of IPA made an underappreciated awesome joke about also being wary of violin plots.
5. Low Quality Equilibria: I couldn't pass this one up when I saw it this week, given my recent rants. Who knew that removing frictions from sharing market information would make it impossible to ever tell if any product was good or not?
Week of August 1, 2017
1. More Ranting (Low-Quality Equilibria and Digital Currency): Following up on my rant last week about the prevalence of low-quality or sub-optimal equilibria because people have such a hard time figuring out what matters, here's another paper that caught my attention because it so thoroughly confirms my priors. The basics: a field experiment provided repair technicians with varying amounts and frequency of feedback. Performance suffered when feedback was weekly versus monthly because the technicians overreacted to each report. In other words, they had a hard time figuring out which details mattered to their own performance. The study could inspire another about "isomorphic mimicry" and the technology of management but I'll save that for another time.
Instead, I'll move on to a different rant about digital finance. In my world, there's only a tenuous connection between the digital finance groups and the cryptocurrency (e.g. BitCoin) groups, but the former certainly should be paying attention to the latter. As Matt Levine put it this week (again, he says this a lot): "The job of the cryptocurrency revolutionaries is to re-learn all of the old lessons of modern finance, one at a time, in public, in embarrassing ways." Right now those old lessons being re-learned seem particularly focused on how hard it is to manage and secure a money supply. I really hope that the digital finance advocates are paying attention to how often various "unhackable" and "secure" cryptocurrencies are being hacked. The spirit of Willie Sutton lives on, and as more "money" is stored in digital form, there will inevitably be more theft. And there's very little reason to believe that average users will employ security practices better than the supposed sophisticated users currently adopting cryptocurrencies. I fear though that the fate of much of digital finance is to "re-learn all of the old lessons of financial services, one at a time, in public, in especially embarrassing ways because they ignored the cryptocurrency movement's repeated mistakes."
2. Global Development (rants): On to more traditional faiV-ing. Kevin Starr has a new rant on the many outside groups making hay over government-funded private schools in Liberia (We need a hashtag to go along with #lantrant, I'm proposing #starrant). Someone once told me there were a lot less education experiments in the US than in other countries because more people were paying close attention and fighting any policy experiments where the outcomes were not already known. That may have been true, but it's certainly not true anymore in Liberia at least. Kevin's plea is to let the Education Minister do his job.
And here's a rant (with a link to another) against the "getting better" narrative that points out how much the world has improved, to the point where it is certainly the best time in history to be alive. I find the argument here pretty annoying, but not annoying enough to rant about myself. Pointing out that fewer children are dying of malnutrition and more people can read (for instance) in no way implies "this is fine."
In fact it's far more common for the "getting better" crowd to argue for more and for taking risks to make more progress, rather than settling for the status quo as Kottke says they are. In that vein, philosopher Peter Singer is probably the best known advocate for doing more, particularly associated with the "drowning child" thought experiment. Except it's not always an experiment. Last week, French philosopher Anne Dufourmantelle died while trying to rescue some actual drowning children. She was particularly known for her work on taking risks.
Week of July 24, 2017
1. Low Quality Equilibria: There's an important "new" (e.g. it's been circulating in working paper form for a while, but is now published) paper in QJE about why hobby woodworkers waste so much money...just kidding, it's about why people keep buying cheap Chinese knock-off tech products and IKEA furniture...actually it's about the persistent use of predatory financial products and poor financial decision making...OK, it's really about the bind that the evidence-based policy movement finds itself in. Well, truthfully it's actually about agricultural markets in Uganda and why adoption rates of fertilizer and improved seed are low, but not zero. Really, that's what the paper is about.
But it is also about all of those other things. Here's the basic story:
Fertilizer and improved seeds boost agricultural productivity substantially. But it's hard for farmers to tell whether the fertilizer or seeds they are buying are fake. So there are lots of people willing to sell low quality stuff claiming it's high quality--in Uganda, the fertilizer is regularly diluted (30% of nutrients are missing) and the "improved seed" is fake 50% of the time. Classical economics tells us that markets will drive out the low quality products as people learn who is a reliable seller; or that the market will collapse and no one will be willing to buy the fertilizer or seeds at all. But farming, like almost every other human endeavor depends on lots of factors, not just these inputs. And so it's not only hard for farmers to tell whether they were sold a "lemon" even even after using it. Did their crops underperform because the were sold fake inputs or because the weather was bad, or they used it wrong, or their land was too degraded, or their were too many of a certain kind of pest, or because they were sick during the planting season, etc.? After all some people buying the fertilizer and seeds did get good stuff and have high yields, so it's even harder to tell where the problem lies. So the market doesn't collapse, and low-quality sellers/products don't get driven out of the market but farmers also--for good reason!--don't invest in the inputs as much as would make sense based on the theoretical productivity boost.
Here's where the rant, and the weird introduction to the item, comes in. This situation is incredibly common: in most of life it's hard to tell whether some input--be it technology, or practice, or advice, or an employee--is high quality before you use it, but also after you use it because of the complex nature of most of life. This basic fact seems to be ignored frequently as researchers, policymakers, and advocates try to explain behavior. In almost all our endeavors we are in a Dunning-Krueger low quality equilibrium. We don't know enough to tell high quality from low quality ex ante, or ex post (yes, I'm a Calvinist). Determining causality is hard--even the most highly trained economists and social scientists get it wrong all the time! What hope does the average human have of looking at a complex system and determining which of the hundreds of factors involved was responsible for what portion of the outcomes? Behavioral economics explanations for sub-optimal choices are tempting because they tend to skirt this core issue. True, cognitive biases and limited attention exacerbate these problems and nudges can yield improvement on the margin, but figuring out what matters is hard (an opportunity to link, yet again, to one of my favorite papers, [Not] Learning by Noticing [the wrong things].
This is why Amazon or any crowdsourced product reviews are worthless. And it's why most people, regardless of their financial literacy, can't consistently tell which financial products are good for them and their situation. And it's why evidence-based policy is such a hard sell--when a policy with strong evidence behind it fails to live up to expectations is that because the advice was bad, the implementation was bad or circumstances changed?
Low quality equilibria are everywhere, defeating them is hard, and that's the sobering challenge we face.
