A new NBER paper by Allcott, Kim, Taubinsky and Zinman takes a close look at the behavioral economics of payday loans and finds that most common regulations make borrowers worse off.
Critics argue that payday loans are predatory, trapping consumers in cycles of repeated high interest borrowing. A typical payday loan incurs $15 interest per $100 borrowed over two weeks, implying an annual percentage rate (APR) of 391 percent, and more than 80 percent of payday loans nationwide in 2011-2012 were reborrowed within 30 days (CFPB 2016). As a result of these concerns, 18 states now effectively ban payday lending (CFA 2019), and in 2017, the Consumer Financial Protection Bureau (CFPB) finalized a set of nationwide regulations. The CFPB’s then director argued that \the CFPB’s new rule puts a stop to the payday debt traps that have plagued communities across the country. Too often, borrowers who need quick cash end up trapped in loans they can’t afford” (CFPB 2017).
Proponents argue that payday loans serve a critical need: people are willing to pay high interest rates because they very much need credit. For example, Knight (2017) wrote that the CFPB regulation \will significantly reduce consumers’ access to credit at the exact moments they need it most.” Under new leadership, the CFPB rescinded part of its 2017 regulation on the grounds that it would reduce credit access.
At the core of this debate is the question of whether borrowers act in their own best interest. If borrowers successfully maximize their utility, then restricting choice reduces welfare. However, if borrowers have self-control problems (“present focus,” in the language of Ericson and Laibson 2019), then they may borrow more to finance present consumption than they would like to in the long run. Furthermore, if borrowers are “naive” about their present focus, overoptimistic about their future financial situation, or for some other reason do not anticipate their high likelihood of repeat borrowing, they could underestimate the costs of repaying a loan. In this case, restricting credit access might make borrowers better off.
First, the authors find that borrowers clearly understand their own behavior. When asked, borrowers predict that they have a 70% probability of borrowing again in the next eight weeks which is almost exactly (74%) the actual borrowing probability. Experienced borrowers are better at predicting their own probabilities of borrowing again so learning also takes place.
Just because they can predict their own behavior doesn’t meant that borrowers like their own behavior (a drunk might predict they will get drunk again without “desiring” to get drunk again) and indeed the authors show with a clever experiment that many borrowers are willing to pay to modestly constrain their own choices. Overall, however, borrowers gain from payday lending so when the authors model payday loan regulations with borrower preferences (their “best”, long-run preferences) regulation reduces welfare:
Payday loan bans and tighter loan size caps both reduce welfare in our model. By contrast, 18 states have banned payday lending, and some states have particularly stringent loan size caps, such as the $300 limit in California.
The best regulation in the model is a rollover restriction which prevents borrowers from borrowing again and again and again. Rather than a blanket regulation, however, I’d prefer a self-exclusion option which would allow people to ban themselves from borrowing in much the same way that people with gambling problems can ban themselves from gambling establishments.
The bottom line is that payday lenders are serving a need and benefiting their customers. Preventing people from accessing payday lenders typically makes them worse off but that doesn’t mean that the customers are entirely sensible or without problems both internal and external. The most revealing statistic in the paper is one the authors mention only in passing:
although our participants are liquidity constrained and we sent two reminder emails, our gift card vendor reports that only 44 percent of the $100 gift cards were claimed
It’s no surprise that people who leave free money on the table have planning problems and need to borrow, it’s just that preventing them from borrowing doesn’t make them better off.
We model a simple market setting in which fragmentation of trade of the same asset across multiple exchanges improves allocative efficiency. Fragmentation reduces the inhibiting effect of price-impact avoidance on order submission. Although fragmentation reduces market depth on each exchange, it also isolates cross-exchange price impacts, leading to more aggressive overall order submission and better rebalancing of unwanted positions across traders. Fragmentation also has implications for the extent to which prices reveal traders’ private information. While a given exchange price is less informative in more fragmented markets, all exchange prices taken together are more informative.
That is a new American Economic Review piece by Daniel Chen and Darrell Duffie. My slight rewording of their argument is this: with market fragmentation, you can split up your order across exchanges and thus submit more total orders, with less fear of the prices moving against you. Fair enough, but what does this mean for the supposed greater efficiency of a single medium of exchange? Might there be reasons why a multitude of exchange/payment media, including foreign currencies and crypto, could give you further liquidity?
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And a very good book at that:
My main argument is that Jacob’s approach to urbanism and economics was developed parallel to, and perhaps benefited from, a much broader field of knowledge than is generally understood. Therefore, the chapter considers a wide context, including the revolutionary critique of planning espoused by Alison and Peter Smithson throughout the 1950s, on the one hand, and the Austrian-school theory of spontaneous order, on the others. Decades before Jacobs’s remarkably hypotheses, liberal theorists had advanced a demoralizing critique of central design as a challenge to the legacy of collectivist planning while advocating market-based solutions and demonstrating the crucial role that informal commerce played in spontaneous order.
That is from the new and noteworthy Anthony Fontenot, Non-Design: Architecture, Liberalism & the Market.
Ann Bernstein: From your knowledge of India and Indonesia, what are the core causes of their lack of educational
progress? These are places with highly qualified civil servants and, at least in India’s case, a democratic
government. How do you see this problem? How do we get out of this trap?
Lant Pritchett: I’m head of this very large research project called RISE and we’re spending millions of dollars to
find out the answer to that question. One of the countries where education improvements have been dramatic
is Vietnam. At a tiny fraction of the spending in most countries – including South Africa – Vietnam is achieving
OECD levels of learning. When we asked our Vietnam team why the country has produced this amazing success,
they told us: ‘because they wanted it’.
On one level, that seems silly; on another level, it is the key. Unless, as a society, you agree on a set of achievable
objectives and actually act in a way that reveals that you really want those objectives, you cannot achieve
From Noahpinion’s interview with Marc Andreessen:
[C]rypto represents an architectural shift in how technology works and therefore how the world works.
That architectural shift is called distributed consensus — the ability for many untrusted participants in a network to establish consistency and trust. This is something the Internet has never had, but now it does, and I think it will take 30 years to work through all of the things we can do as a result. Money is the easiest application of this idea, but think more broadly — we can now, in theory, build Internet native contracts, loans, insurance, title to real world assets, unique digital goods (known as non-fungible tokens or NFTs), online corporate structures (such as digital autonomous organizations or DAOs), and on and on.
Consider also what this means for incentives. Up until now, collaborative human effort online either took the form of a literal adoption of real-world corporate norms — a company with a web site — or an open source project like Linux that had no money directly attached. With crypto, you can now create thousands of new kinds of incentive systems for collaborative work online, since participants in a crypto project can get paid directly without a real-world company even needing to exist. As great as open source software development has been, far more people are willing to do far more things for money than for free, and all of a sudden all those things become possible and even easy to do. Again, it will take 30 years to work through the consequences of this, but I don’t think it’s crazy that this could be a civilizational shift in how people work and get paid.
Finally, Peter Thiel has made the characteristically sweeping observation that AI is in some sense a left wing idea — centralized machines making top-down decisions — but crypto is a right wing idea — many distributed agents, humans and bots, making bottom-up decisions. I think there’s something to that. Historically the tech industry has been dominated by left wing politics, just like any creative field, which is why you see today’s big tech companies so intertwined with the Democratic Party. Crypto potentially represents the creation of a whole new category of technology, quite literally right wing tech that is far more aggressively decentralized and far more comfortable with entrepreneurialism and free voluntary exchange. If you believe, as I do, that the world needs far more technology, this is a very powerful idea, a step function increase in what the technology world can do.
I agree. See also my earlier post Blockchains and the Opportunity of the Commons:
Today smart contracts on blockchains like Ethereum (and Elrond, AT!) have the potential to create a sophisticated set of global common resources that will form the foundation for much of the economic and social structure of this century–this is the opportunity of the blockchain commons.
Imagine if we accepted, for the foreseeable future, that we can only write on a given blockchain ten times per second, but instead of writing ten single transactions, made ten additions to the blockchain, each attesting to thousands of transactions. Despite the scale-up, there would be no significant rise in the number of kilobytes being added to the chain.
In short, I’m talking about a fix that would mean the same blockchains that I brazenly called puny would suddenly become mighty.
This fix is the adoption of cryptographic proofs — a concept that captured my imagination when I was a PhD student under Professor Avi Wigderson, one of the pioneers of this area of mathematics, and when I was a postdoc under Professor Madhu Sudan, another of the founding fathers of this field. After 20 years in academia, today I am president of StarkWare (@StarkWareLtd on Twitter), a company I co-founded to move this fix from the realm of theory to reality – a reality that will scale-up blockchain to an unprecedented degree.
Currently, Bitcoin establishes integrity the way you do it with your waiter or waitress. As you sit at your table, the waiting staff present a bill with the food you ordered, taking up the role of the “prover.” You check the calculation — making you the “verifier.”
With Bitcoin, the miner of a new block is the “prover.” Every block acts as proof that the payments contained in it are valid. And the nodes, meaning the many computers which host and synchronize a copy of the entire Bitcoin blockchain, naively replay each transaction in the block to verify that it is correct.
With cryptographic proofs, instead of recording this data-heavy information to the blockchain, we write on the chain in a kind of shorthand — proofs which verify that transactions have been conducted with integrity. All the heavy computational lift, meaning the work done to obtain the proof, happens in the cloud, not the blockchain.
It is logic we’re all familiar with in other areas of life. A large company may have its flagship office in central Manhattan, but wouldn’t dream of using such prime real estate for its huge factory, where the heavy lifting takes place.
That is the new NYT David Brooks column, here is one excerpt:
Not all the time, but often, the attractive get the first-class treatment. Research suggests they are more likely to be offered job interviews, more likely to be hired when interviewed and more likely to be promoted than less attractive individuals. They are more likely to receive loans and more likely to receive lower interest rates on those loans.
The discriminatory effects of lookism are pervasive. Attractive economists are more likely to study at high-ranked graduate programs and their papers are cited more often than papers from their less attractive peers. One study found that when unattractive criminals committed a moderate misdemeanor, their fines were about four times as large as those of attractive criminals.
Daniel Hamermesh, a leading scholar in this field, observed that an American worker who is among the bottom one-seventh in looks earns about 10 to 15 percent less a year than one in the top third. An unattractive person misses out on nearly a quarter-million dollars in earnings over a lifetime.
The overall effect of these biases is vast. One 2004 study found that more people report being discriminated against because of their looks than because of their ethnicity.
In a study published in the current issue of the American Journal of Sociology, Ellis P. Monk Jr., Michael H. Esposito and Hedwig Lee report that the earnings gap between people perceived as attractive and unattractive rivals or exceeds the earnings gap between white and Black adults. They find the attractiveness curve is especially punishing for Black women. Those who meet the socially dominant criteria for beauty see an earnings boost; those who don’t earn on average just 63 cents to the dollar of those who do.
The idea has not held up. As I write the rate on 6-month T-Bills is 0.06%. That is pretty close to zero, right?
And yet everyone is debating what will happen with the rate of price inflation. No one is claiming it is indeterminate, as the simplest liquidity trap models suggest. Nor, with rising rates of price inflation, can it be argued that inflation inertia is dominant. Instead, it is obvious that the Fed has let the current inflation happen. It is true that the inflationary pressures stem from (roughly) coordinated acts of monetary and fiscal policy, rather than monetary policy alone. But no one is doubting that the Fed is in charge of forthcoming rates of inflation.
(And if the T-Bill rate is ever so slightly above zero, rather than at or below zero, that too seems to stem from higher expected rates of price inflation in the first place.)
I agree with those individuals who suggest that the currently higher rates of price inflation will not be with us 4-5 years from now, and that is because the Fed does not want that to happen.
Paul Krugman recently wrote (NYT):
Seriously, both recent data and recent statements from the Federal Reserve have, well, deflated the case for a sustained outbreak of inflation. For that case has always depended on asserting that the Fed is either intellectually or morally deficient (or both). That is, to panic over inflation, you had to believe either that the Fed’s model of how inflation works is all wrong or that the Fed would lack the political courage to cool off the economy if it were to become dangerously overheated.
In other words, the Fed to a considerable degree can indeed control the rate of price inflation, and with nominal T-Bill rates very close to zero. Open market operations on T-Bills alone won’t do it, but of course the Fed can use the expectations channel, and can deal in other assets as well — just as they do when they wish to be more expansive. Or maybe you think it is the promised currency path (not my view), but that too would be effective in either direction, if desired. Thus the liquidity trap doctrine is dead, discarded once it no longer provides an argument for an ever-more expansive fiscal policy.
NYTimes: New York City built only 163,000 units of housing in the 2010s, fewer than the 205,000 created in the 1930s, during and after the Great Depression, according to a city report. From 2009 to 2018, the New York metro region added 0.5 units of housing for every new job, down from 2.2 units per job in the previous decade.
The article continues:
In December, a New York Supreme Court judge annulled the city’s rezoning plan for Inwood…The Inwood plan would have increased the allowable height and density in parts of the neighborhood, which could have brought 3,900 new units to the area, including 1,600 below-market apartments, according to the Department of City Planning. The city is appealing the decision.
The judge agreed that the city’s environmental review process, which aims to measure the impact of development, did not adequately study a number of concerns, including the risk of racial displacement and the effect of speculative development on local businesses, many of which can be more valuable to landlords as land sales.
This is another illustration of how collective decision making impedes innovation. Neither judges nor regulators should be making these “balancing” decisions which politicizes and creates veto players who can dam innovation at low-cost to themselves. Decisions about when and where to build should by left to the spontaneous order operating under the principles of private property and the rule of law.
Look at this nonsense and imagine if every decision had to be so studied for every group and interest that one could possibly imagine:
“They don’t have to study the racial impact? That’s ridiculous,” said Michael Sussman, the petitioners’ attorney, who argued that speculation would have an outsize impact on minority residents in the area, many of whom live in rent-regulated apartments.
In the early 1940s, Friedman’s own analysis of monetary policy adhered closely to the dismissive tone prevalent in much other Keynesian literature of that vintage. His solo-authored contribution to 1943’s Taxing to Prevent Inflation, written while he was at the Treasury, plotted growth rates of the nominal money stock and nominal income for the United States for the period 1899-1929. To the modern reader, the scatter plot in Friedman’s paper indicates that the monetary growth/income relationship is clearly positive, and reasonably tight by the standards of rate-of-change data. That was not, however, the judgment Friedman reached in his 1943 paper, in which he concluded instead that the relationship was “extremely unstable.”
That is from p.95 of the recent Edward Nelson two-volume set on Milton Friedman — one of the best books written on any economist!
That is the topic of my latest Bloomberg column, here is one excerpt:
If anything, crypto is more likely to hurt the currencies of countries that are doing very poorly, such as Venezuela. Fiat currency won’t just go away, so over the long run crypto could actually boost the value of the dollar by stifling the rise of potential competitors.
A second point, oft neglected in the crypto community, is that crypto prices won’t continue to go up forever at high rates. It doesn’t matter whether money supply deflation is built into a crypto system, or that new and valuable uses will be discovered each year. At some point the market will figure out the value of crypto and incorporate that information into a high level of price for those assets. From then on, expected rates of return will be — dare I say — normal.
Compare the crypto market to the art market, which for a long time didn’t grasp the potential value of an Andy Warhol painting. For years, prices went up a lot. At this point, however, a liquid market remains, and the expected value of an investment in Warhol is not necessarily better or worse than the value of an investment in other well-known works of art.
It is an entirely defensible (albeit contested) view that the market still hasn’t appreciated the full value of crypto. This state of affairs may yet endure for some while, but it will not last for decades.
The irony is that so many of the arguments made by crypto types imply especially low pecuniary rates of return on crypto. To the extent crypto is useful as collateral or for liquidity purposes, people will be more willing to hold crypto at lower pecuniary rates of return, just as they are willing to hold cash, or just as the collateral uses for U.S. Treasury bonds raise their price and lower their expected rates of return.
If we eventually arrive at a world in which equities are expected to rise by say 5% to 7% a year, and Bitcoin by say 1%, then that will be a sign crypto has made it. The more general point is that while crypto has been a highly unusual asset class for its entire history, it won’t act like an unusual asset class forever.
Satoshi and Vitalik Buterin are not only significant innovators, but also the two most important monetary economists of our time.
Some quick comments in response to questions and discussion about my paper Could Vaccine Dose Stretching Reduce COVID-19 Deaths? (written with the all-star cast of Witold Więcek, Amrita Ahuja, Michael Kremer, Alexandre Simoes Gomes, Christopher M. Snyder and Brandon Joel Tan.
1) Any method of increasing vaccine supply will require other changes in the supply chain such as more needles. We think alternative dosing can increase supply quickly with the fewest supply chain disruptions.
2) If we had started Moderna with 50 ug dosing no one would be advocating for 100 ug dosing, thereby halving supply. Rather than “full” or “half-doses,” which bias thinking, we should talk about alternative dosing and ug.
3) Judging by neutralizing antibodies, a 50 ug dose of, for example, Moderna looks to be more effective than standard dosing of many other vaccines including AZ and J&J and much better than others such as Sinovac. Thus alternative dosing is a way to *increase* the quality of vaccine for many people.
4) A 50 ug dose vaccine available today is much higher quality than a 100 ug dose vaccine available one year from now.
5) There are substantial risks from following the current approach, as India and now parts of Africa illustrate. Alternative dosing has a very large upside but small downside since we could switch back to standard doses. For example, Great Britain and Canada delayed the second dose to 12 and 16 weeks respectively but have since reduced the dosing interval as more supplies have become available.
6) The greatest risk to immune escape comes from the unvaccinated. Alternative dosing protects not only those who are dosed but by reducing transmission also reduces risks to the unvaccinated.
7) The key question we face now is not whether there are objections and complications to alternative dosing (there are) the key question is what additional information, available quickly could resolve the most uncertainty? In other words, what can we learn soon that would most aid decision makers?
See the paper for details and also my previous post, A Half Dose of Moderna is More Effective Than a Full Dose of AstraZeneca.
Addendum: It should be clear that this isn’t about the United States, it is about getting high-quality vaccine to places that have little to none.
…the magnitude of the earnings disparities along the perceived attractiveness continuum, net of controls, rivals and/or exceeds in magnitude the black-white race gap and, among African-Americans, the black-white race gap and the gender gap in earnings.
1. It is often the educated (and often left-wing) coastal elite that commits the most lookism and also enforces it through internal norms of dress, thinness, etc.. Yet they are so desperate to believe they are better people than competing white interest groups (amazing how unself-aware they are about how obvious this is) that they just don’t want to bring looksism to your attention. Upon presentation, this will receive the “yes, that’s bad too” treatment, and then it won’t be talked about any more. Looksism will continue unabated, and indeed it may intensify as some other isms decline.
2. It is worth keeping this information in mind when trying to hire people or find untapped sources of talent.
Here is a long post, full of insight and citations, basically arguing that sticky wage models are better for macro than sticky price models. Sticky wage models had been deemphasized because real wages seemed to be acyclical, but sticky prices can’t quite do the work either. The post is hard to summarize, but my reading of it is a little different than what the author intends. My takeaway is “Sticky wages for new hires are the key, and we didn’t have real evidence/modeling for that until 2020, so isn’t this all still up in the air?” I am a big fan of the Hazell and Taska piece, which I consider to be one of the best economics contributions of the last decade, but still…I don’t exactly view it as confirmed and all nailed down. I do believe in nominal stickiness of (many not all) wages, but I still don’t think we have a coherent model matching up the theory and the empirics for how nominal stickiness drives business cycles. I thus despair when I see so many dogmatic pronouncements about labor markets.
For the pointer I thank João Eira.