1. Financial Inclusion: I have no idea what your priors are about financial inclusion, but I think it still matters a lot and you'll be seeing more about that from me in the faiV and elsewhere in coming months. The best way to update your priors on the state of financial inclusion is the Global Findex of course. I've been including things in drips and drabs, but Sonja Kelly and Beth Rhyne of CFI have now published their reasonably comprehensive look at the data, complete with lots of charts, available for everyone (and Sonja definitely deserves a vacation after all her work on this and the Gallup data).
CFI is certainly onboard with the theme of updating priors. The title of the report is "Financial Inclusion Hype vs. Reality" and the Introduction invites you to "Recalibrate." The big message is that despite growth in account ownership, there's no growth in usage and lots of troubling signs, like falling savings rates. You can feel the exasperation in the report, an exasperation that I generally share, given what seems to be a general fatigue around financial inclusion. These data don't in any way support the idea that it's time to move on from financial inclusion. But I'm less concerned than Sonja and Beth about the growing gap between access and usage. Consumer banking does have network effects--value of usage increases rapidly with the number of other users--but those effects take time. The population being served was never likely to be heavy users, which increases the time before network effects surface and become self-reinforcing. So it makes sense to me that as we get better at access, the gap between access and usage should grow for a while.
One place I'm not updating my priors based on this data is showcased in their Figure 6, illustrating that rapid growth in digital payments is not showing up in borrowing or savings. I've always been puzzled by the idea that making it easier for people to spend was going to boost savings.
Given that the empirics in Findex aren't very encouraging on progress in financial inclusion, here's a new paper from Besley, Burchardi and Ghatak laying out the benefits of inclusion. The most interesting thing about it is how well it aligns with what we've been seeing on general equilibrium effects of microcredit--it raises wages for the average worker. That's bad for impact evaluations, but good for more people and a powerful reason to continue investing in inclusion.
2. US Inequality: Speaking of average workers, a big reason for this week's theme is the new BLS numbers on contingent work that set the US Economy commentariat aflame yesterday. The big story is that contingent work--which includes freelancers, gig workers, temps, etc.--has not increased since 2005, the last time it was measured (here's a 2 minute overview). That's pretty remarkable since none of the gig platforms we hear so much about today existed back then. But the numbers are hard to interpret. Ben Casselman has a good overview of the issues here, chief among them being that the BLS asks about "primary" job and counts as non-contingent any regular job regardless of how steady the hours are. So the "no growth" data is consistent with findings from the SHED that 30 percent of Americans now rely on contingent work to make ends meet and from JP Morgan Chase Institute that gig work accounts for about 30% of income for those that do participate.
The bottom line: whatever your priors were, you should probably hold them more weakly than before.
But if you were looking forward to actually updating your priors, here's something I found surprising: income inequality in the US stopped growing some time ago (though the conclusions in that piece beg the question, in the logic sense of that term). And here's a paper from late last year that finds that what can be reasonably thought of as "freelance" professionals--doctors, accountants, lawyers--are responsible for most of the growth in income inequality since 2000.
3. Our Digital Overlords: Another inspiration for this week's theme was this piece by David Leonhardt, reviewing Reinventing Capitalism in the Age of Big Data, a new book that considers the benefits of a data-rich markets for consumers, and the danger that data-rich markets lead to monopolies and less employment. But the thing that most caught my eye, in terms of updating priors, is a casual reference to the story of the Kerala fishermen benefiting from cell phones. That's a story that is very much in doubt, but seemingly few people have updated their priors (see also this). As a side note, if anyone knows of more current research on the story or an effort to sort through the claims (beyond what is in the comments on that piece), please let me know. But searching for that link on the Kerala story, I noticed several other stories on the ICTworks site about surprising failures of digital tools to improve market functioning. My eye was specifically drawn to a story I remember blogging about at least a decade ago: sharing market prices with African farmers via text messaging didn't work out nearly as well as it seemed it would.
My bottom line here is influenced by two studies about police bodycams that were released this week, one in Milwaukee and one in Spokane, which seem to have found opposite effects on a major outcome measure (the number of self-initiated stops police make) without having much other effects. That bottom line is I shouldn't make predictions about how technology will change behavior, or even have strong beliefs after reading a paper about such things.
4. Social Enterprise: If you didn't update your priors about double-bottom-lines based on the recently linked paper from Karlan, Osman and Zinman, here's a new paper from Gine, Mansuri and Shrestha that finds that performance pay in a "mission-oriented nonprofit" has complicated effects that certainly make it hard for managers to use that particular incentive.
This interview from the authors of the new book Unicorns Unite (really that's the title of the book) may change your priors about the value of a book with unicorns in the title, but also about how the world looks from the perspective of a non-profit fundraising or a grant officer evaluating proposals. Even if you don't think that sounds interesting, you should click because it is interesting, especially if you scroll down past the opening questions.
5. Methods, etc.: Updating priors is important, but sometimes they shouldn't be updated because the prior was correct. But those situations are hard to determine because the publication process is biased against confirmations of earlier findings. There's a new journal that aims to change that: The Series of Unsurprising Results in Economics.
For those of you not in the coding side of modern social science research, you may have wondered why everyone was making such a big deal about GitHub's acquisition by Microsoft. Allow me (well Paul Ford actually) to explain.
Moving on to some service journalism here for the economics and econometrics set, here is the first in a series of posts by Sylvain Chabe-Ferrer on hating p-values, and the alternatives. Here is a library of statistical software plug-ins though it doesn't appear to be updated all that often.
Aaron Klein is hoping that people will update their priors about "cashlessness" in the US, by pointing out that volumes of cash are still rising significantly year over year in the US. Read the replies of the Twitter thread, they are useful for figuring out how to update your priors. Source: The Federal Reserve, via Aaron Klein.
