Week of July 24, 2017

The ranting edition

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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