Let me turn over the microphone to David Neumark and Peter Shirley:
The disagreement among studies of the employment effects of minimum wages in the United States is well known. What is less well known, and more puzzling, is the absence of agreement on what the research literature says – that is, how economists even summarize the body of evidence on the employment effects of minimum wages. Summaries range from “it is now well-established that higher minimum wages do not reduce employment,” to “the evidence is very mixed with effects centered on zero so there is no basis for a strong conclusion one way or the other,” to “most evidence points to adverse employment effects.” We explore the question of what conclusions can be drawn from the literature, focusing on the evidence using subnational minimum wage variation within the United States that has dominated the research landscape since the early 1990s. To accomplish this, we assembled the entire set of published studies in this literature and identified the core estimates that support the conclusions from each study, in most cases relying on responses from the researchers who wrote these papers.
Our key conclusions are: (i) there is a clear preponderance of negative estimates in the literature; (ii) this evidence is stronger for teens and young adults as well as the less-educated; (iii) the evidence from studies of directly-affected workers points even more strongly to negative employment effects; and (iv) the evidence from studies of low-wage industries is less one-sided.
Here is the full NBER paper.
Not too much, as I argue in my latest Bloomberg column. Here is one excerpt:
In September 2020, Kraken, one of the leading crypto exchanges, obtained a banking license from the state of Wyoming, thereby giving it access to the federal payments infrastructure. Part of the deal is that Kraken has to hold 100% reserves for its crypto assets, in essence treating them as a parking garage is supposed to manage cars. It is easy to imagine federal regulators forcing crypto exchanges into the banking system on a larger scale, and perhaps banks buying up or merging with crypto houses, again with stringent reserve requirements.
It is unclear what such regulation would accomplish. Crypto exchanges would become more bureaucratic and less innovative, as they would have a greater stake in the financial status quo. Non-U.S.-based crypto exchanges, and anonymized systems, could still be used to transfer funds secretly or illegally. Still, banks are something the federal government has a lot of experience regulating, and U.S. regulators would achieve a certain illusion of control.
A more general principle is that the platforms easiest to regulate also tend to be the most legitimate and the least likely to engage in or encourage wrongdoing. Again, the net effect will be to make crypto, at the global level, harder to monitor and control.
The better strategy would be to encourage the ascendancy of American-based crypto firms, and slowly allow them to evolve into a more traditional part of financial markets.
There is a plausible argument that, eventually, crypto exchanges should be regulated as financial clearinghouses. But the crypto platforms are currently small and are not sources of systemic macroeconomic risk. It remains to be seen how they ought to evolve or which functions they ought to serve, or indeed if they will succeed at all.
Recommended, I cite Hayek at the very end.
Jeff Kaufman has some good parenting tips:
A few weeks ago Anna (4y) wanted to play with some packing material. It looked very messy to me, I didn’t expect she would clean it up, and I didn’t want to fight with her about cleaning it up. I considered saying no, but after thinking about how things like this are handled in the real world I had an idea. If you want to do a hazardous activity, and we think you might go bankrupt and not clean up, we make you post a bond. This money is held in escrow to fund the cleanup if you disappear. I explained how this worked, and she went and got a dollar:
When she was done playing, she cleaned it up without complaint and got her dollar back. If she hadn’t cleaned it up, I would have, and kept the dollar.
Some situations are more complicated, and call for bets. I wanted to go to a park, but Lily (6y) didn’t want to go to that park because the last time we had been there there’d been lots of bees. I remembered that had been a summer with unusually many bees, and it no longer being that summer or, in fact, summer at all, I was not worried. Since I was so confident, I offered my $1 to her $0.10 that we would not run into bees at the park. This seemed fair to her, and when there were no bees she was happy to pay up.
Over time, they’ve learned that my being willing to bet, especially at large odds, is pretty informative, and often all I need to do is offer. Lily was having a rough morning, crying by herself about a project not working out. I suggested some things that might be fun to do together, and she rejected them angrily. I told her that often when people are feeling that way, going outside can help a lot, and when she didn’t seem to believe me I offered to bet. Once she heard the 10:1 odds I was offering her I think she just started expecting that I was right, and she decided we should go ride bikes. (She didn’t actually cheer up when we got outside: she cheered up as soon as she made this decision.)
I do think there is some risk with this approach that the child will have a bad time just to get the money, or say they are having a bad time and they are actually not, but this isn’t something we’ve run into. Another risk, if we were to wager large amounts, would be that the child would end up less happy than if I hadn’t interacted with them at all. I handle this by making sure not to offer a bet I think they would regret losing, and while this is not a courtesy I expect people to make later in life, I think it’s appropriate at their ages.
I also recommend the board game Wits and Wagers. In the game you make bets based on questions like “In what year was the computer game Pong released? or “How many ridges are on the outside of a dime.” It’s a clever and fun game because it teaches you not only to estimate and bet accordingly but also to adjust your bets based on seeing how other people bet. Thus, it often happens that a player will less background knowledge can win, precisely because they are less confident and so pay more attention to the information available in other people’s bets. Aumann would approve.
Hat tip: Julia Galef.
Yesterday I pointed out How Rapidly ‘First Doses First’ Came to Britain. The United States is also moving in that direction but more slowly. First we ended holding second doses in reserves. Now the CDC has new policies:
CNBC: The Centers for Disease Control and Prevention quietly changed its guidance on Covid-19 vaccine shots, saying it’s now OK to mix Pfizer’s and Moderna’s shots in “exceptional situations” and that it’s also fine to wait up to six weeks to get the second shot of either company’s two-dose immunization.
We will see what happens if new variants start to takeoff in the US, as seems likely, and as the number of people immunized starts to slow as we move from first does to having to vaccinate people for the second dose. More second doses means fewer resources for first timers. Biden’s 100 million in 100 days, for example, was already under-ambitious but it’s not even 100 million people it’s 100 million doses or only about 67 million people given that some will be in line twice.
The paper I want to highlight in this post is “Price Floors and Employer Preferences” by John Horton. In this piece he conducts a randomized control trial on an online labor market, randomly assigning 4 different minimum wage levels ($0, $2, $3, and $4) to 160,000 job postings. This experimental design conveys several advantages over conventional empirical work. First, selection effects and biases based on the economic performance of the firms and the states/countries they are in are automatically controlled for by random assignment. Second, the online platform collects detailed measures on the pre-experiment attributes of all workers, the productivity of workers on the job, and the number of hours worked overall. These data are extremely important to analyzing the effects of the minimum wage but are not measured in the most popular empirical works on the topic. Finally, the computerized nature of the data leaves almost no room for measurement error.
…There are four main results: “(1) the wages of hired workers increases, (2) at a sufficiently high minimum wage, the probability of hiring goes down, (3) hours-worked decreases at much lower levels of the minimum wage, and (4) the size of the reductions in hours-worked can be parsimoniously explained in part by the substantial substitution of higher productivity workers for lower productivity workers.”
The significant reductions in hours worked come from two sources according to Horton’s analysis. First, firms are economizing on now more expensive labor; the labor demand curve slopes downward. Second, the substitution of higher productivity workers meant that jobs were completed faster, so the total hours worked went down. Both of these responses to the minimum wage hurt low productivity workers…
Interestingly, these results are consistent with finding little to no dis-employment effect in an observational study that only measures wages and headcounts (which is what the vast majority of the most popular studies do). This is because almost all of the effects of the minimum wage came from substitution of higher productivity for lower productivity ones, which wouldn’t show up in headcounts, and reduction in hours worked, which is not measured in most conventional data sets.
Here is the full short piece by Maxwell Tabarrok. File under “RCT gold standard for me but not for thee!”
Tim Harford writes about the whiplash he experienced from the debate over delaying second doses in Britain.
What a difference a couple of weeks makes. In mid-December, I asked a collection of wise guests on my BBC radio programme How to Vaccinate the World about the importance of second doses. At that stage, Scott Gottlieb, former head of the US Food and Drug Administration, had warned against stockpiling doses just to be sure that second doses were certain to be available, Economists such as Alex Tabarrok of George Mason University had gone further: what if we gave people single doses of a vaccine instead of the recommended pair of doses, and thus reached twice as many people in the short term? This radical concept was roundly rejected by my panel
…. “This is an easy one, Tim, because we’ve got to go with the scientific evidence,” said Nick Jackson of the Coalition for Epidemic Preparedness Innovations. “And the scientific evidence is that two doses is going to provide the best protection.”
My other guests agreed, and no wonder: Jackson’s view was firmly in the scientific mainstream three weeks ago. But in the face of a shortage of doses and a rapidly spreading strain of “Super-Covid”, the scientific mainstream appears to have drifted. The UK’s new policy is to prioritise the first dose and to deliver the second one within three months rather than three weeks…..the recommendation comes not from ministers but from the Joint Committee on Vaccination and Immunisation (JCVI).
Strikingly, many scientists have given the move their approval.
See also Tyler’s previous post on this theme.
By the way, if the J&J single-dose vaccine comes in at say 80% effective it is going to be interesting to see how people go from ‘a single-dose at 80% effective is too dangerous to allow for 8-12 weeks’ to ‘isn’t it great we have a single-dose 80% effective vaccine!’.
Anti-money laundering laws are hugely expensive and largely ineffective at their stated purpose.
Necessarily applying a broad brush, the current anti-money laundering policy prescription helps authorities intercept about $3 billion of an estimated $3 trillion in criminal funds generated annually (0.1 percent success rate), and costs banks and other businesses more than $300 billion in compliance costs, more than a hundred times the amounts recovered from criminals.
… If authorities recover around $3 billion per annum from criminals, whilst imposing compliance costs of $300 billion and penalizing businesses another $8 billion a year, it is reasonable to ask if the real target of anti-money laundering laws is legitimate enterprises rather than criminal enterprises.
That’s Ronald Pol from a new paper, Anti-money laundering: The world’s least effective policy experiment? Together, we can fix it.
I would add two elements. The anti-money laundering laws are also injurious to innovation in areas like cryptocurrency where privacy is a goal and there is no bank to fine or from which to demand paperwork. These laws are also a injurious to liberty as they essentially require banks to spy on their customers and report to the government and they are inconsistent with constitutional principles. The key AML laws really only date from the 1990s and should be scrapped rather than “fixed “(which I think is Pol being sly as he never suggests any real solutions.)
A controversial study on the effect of a radical rise in the legal minimum wage level came out Tuesday, pitting employers against employees in the midst of negotiations for the next year’s wage standard.
Researchers at the Korea Economic Research Institute analyzed in the study the impact of the 16.4 percent increase in the 2018 wage level on low-income workers to find that many low-paying jobs were erased, while those who were employed enjoyed higher pay. The institute is affiliated with the country’s top business lobby, the Federation of Korean Industries.
The minimum wage is updated on an annual basis, and the rate currently stands at 8,590 won ($7.10) per hour. In 2018, the rate rose 16.4 percent from 6,470 won a year earlier to 7,530 won, the steepest increase in 17 years.
The KERI report said the employment rate in 2018 for workers directed affected by the hike — those who were getting paid less than the 2018 legal wage in 2017 — was as much as 4.6 percentage points lower than other income groups.
Some 15.1 percent of this group were jobless in 2018.
The study calculated that between 27.4 percent and 30.5 percent of the unemployment cases were due to the higher wage level, which prompted employers to cut jobs.
Here is the article. I cannot find this study, it may well only be in Korean (addendum: here is the link in Korean), and I note it is connected to a business lobby. Still, I will take this opportunity to ask: what else do we know about the recent and radical South Korean wage hike?
Here are some general remarks at Wikipedia. And here is a relevant paper about minimum wage hikes in Hungary: small disemployment effects after four years, and most of the burden carried by consumers, which implies the monopsony model does not apply — in that model prices should fall!
And do read Brian Albrecht on the minimum wage.
It’s a slam-dunk case that doubling the federal minimum wage — it’s been $7.25 since 2009 — would lead to significant declines in employment opportunities for workers with few skills or little experience. According to data from the Bureau of Labor Statistics for 2019 (before the pandemic), in 47 states, at least one-quarter of all workers earn less than $15 per hour. In 20 states, half of all workers earn less than $18 per hour, and in 30 states, the median hourly wage is less than $19.
These statistics show that $15 is a very high wage floor. For employers to keep all their workers would require raising the wages of a huge share of the national workforce. But the number of workers affected would be so large that this wouldn’t happen. Instead, the number of jobs in the low-wage workforce would shrink.
The nonpartisan Congressional Budget Office confirms this basic intuition, estimating that joblessness would increase by 1.3 million if the national hourly wage floor were hiked to $15 [TC: and that is pre-pandemic]. The CBO also concluded that this policy would reduce business income, raise consumer prices and reduce gross domestic product.
That is from Michael Strain at Bloomberg. I would add this. No matter what you think about the recent literature on the minimum wage, all economic theories imply that minimum wages should be decided at the state and local level, given the economic heterogeneity of the United States. That is the message that you as an economist should be carrying forward.
Do you think Puerto Rico should be a state? Should they have a $15 minimum wage too? Come on. Yes, it is easy enough to make an exception for them, and by the way the median manufacturing wage in Mississippi is below $15 as well. Rinse and repeat.
I am sorry to speak in such terms, but the reality is that an allied cabal of activists and left-wing economists have combined on social media to insist on a particular approach to minimum wage economics and to bully those who disagree.
Ask yourself a simple question: were any of them calling for a temporary two-year cut in the minimum wage for restaurants and small businesses during a devastating pandemic? If not, are they really carrying forward the banner of science?
That has been one common response to my recent post asking people to be consistent across assumptions about elasticities. And that is true, those differing elasticities are not all exactly the same. Yet a few points remain relevant:
1. If you see the world as dynamic, full of entrepreneurship, and solving problems fairly rapidly and effectively, you should tend to think that a wide variety of elasticities will be high. Conversely, if you think we are all sluggish, overregulated, creatures of routine boobs, you will tend to see a wide variety of elasticities as being pretty low.
That doesn’t have to follow, but if you instead have your own Rube Goldberg approach, well let’s please hear about it in more detail.
2. The elasticities that “most people on Twitter want” are “long run labor demand inelastic” (minimum wage hike good!) and “short run industry supply curve elastic” (stimulus is good!). In other words, they want the short-run elasticity to be higher than the long-run elasticity. By insisting that not all elasticities are the same, they actually have made the problem more difficult for themselves.
3. Individual firm and aggregate supply curves of course can differ. To get the aggregate curve to be more dynamic and responsive than individual curves, typically you would invoke some notion of increasing returns. But a pandemic is exactly when increasing returns are least likely.
Plausibly there are increasing returns to greater vaccine use. But nominal stimulus? Nope. We are not living in a world of “my pet shop is doing so well I am going to spend money on your movie theater.” Apart from the high multiplier associated with public health improvements, we right now live in a world of bottlenecks and sectorally specific problems. Trying to get increasing returns on your side isn’t going to help, in fact it will work against you.
In sum, I am not saying there is no way you can get all of your elasticities to fit together in the preferred manner. After all, if nanotechnology works, alchemy may work too. I am just asking you to…show your work. And in the meantime be less moralizing and dogmatic. Perhaps you cannot in fact, right now, have all of the things you want.
By July it will all be over. The only question is how many people have to die between now and then?
Youyang Gu, whose projections have been among the most accurate, projects that the United States will have reached herd immunity by July, with about half of the immunity coming from vaccinations and half from infections. Long before we reach herd immunity, however, the infection and death rates will fall. Gu is projecting that by March infections will be half what they are now and by May about one-tenth the current rate. The drop will catch people by surprise just like the increase. We are not good at exponentials. The economy will boom in Q2 as infections decline.
If that sounds good bear in mind that 400,000 people are dead already and the CDC expects another 100,000 dead by February. We have a very limited window in the United States to make a big push on vaccines and we are failing. We are failing phenomenally badly.
To understand how bad we are failing compare with flu vaccinations. Every year the US gives out about 150 million flu vaccinations within the space of about 3 months or 1.6 million shots a day. Thus, we vaccinate for flu at more than twice the speed we are vaccinating for COVID! Yes, COVID vaccination has its own difficulties but this is an emergency with tens of thousands of lives at stake.
I would love it if we mobilized serious resources and vaccinated at Israel’s rate–30% of the population in a month. But if we simply vaccinated for COVID at the same rate as we do for flu we would save thousands of lives and hundreds of billions of dollars in GDP. The comparison with flu vaccinations also reminds us that we don’t necessarily need the National Guard or mass clinics in stadiums. Use the HMOs and the pharmacies!
And let’s make it easier for the pharmacies. It’s beyond ridiculous that we are allowing counties to set their own guidelines for who should be vaccinated first. We need one, or at most 50, set of guidelines and lets not worry so much at people jumping the queue. (The ones jumping the queue are probably the ones who want to get back to the bars and social life the most so vaccinating them first has some side benefits.)
Of course, the faster we vaccinate the more vaccine quantities will become the binding constraint which is why we also need to approve more vaccines, move to First Doses First (delay second doses like the British), and use Moderna half-doses. Fire on all cylinders!
Time is of the essence.
Hat tip: Kevin Bryan and Witold Wiecek.
If you think “stimulus” is effective right now, presumably you think supply curves are pretty elastic and thus fairly horizontal. That is, some increase in price/offer will induce a lot more output.
If you think we should hike the minimum wage right now, presumably you think supply curves are pretty inelastic and thus fairly vertical. That is, some increase in price for the inputs will lead not to much of a drop in output and employment, maybe none at all. The supply curve is fairly vertical.
You might somehow think that supply is elastic with respect to output price, but inelastic with respect to input price. Is there a model that can generate that conclusion? It is the net profit on the marginal output units that should matter for decisions. And did you start with that model, or develop it afterwards to justify your dual intuitions?
Do you right now favor both a lot of stimulus and a big minimum wage hike? What are your assumptions about elasticities? Show your work!
Do you favor a minimum wage hike, but also think a lot of immigrants to this country won’t lower real wages by very much if at all? The latter view would seem to imply a fairly elastic demand for less skilled labor. (The new labor can be absorbed into the market with only a small price change.) Are your assumptions about elasticities consistent there as well?
Are your assumptions about elasticity with respect to stimulus and elasticity with respect to tax cuts consistent?
If you favor a minimum wage hike, do you criticize wage subsidies because inelastic demand for labor means most of the value of the wage subsidy will be captured by the employer? Or do you somehow want both policies at the same time, because they both involve “government helping people”?
If you favor a minimum wage hike because you think the demand for labor is inelastic, does that mean you don’t see “downward sticky wages” as a big problem? After all, the demand for labor is inelastic, right?
What are your assumptions about elasticities? And are those even the assumptions that actually matter to you?
How many economists do you know who start with beliefs about elasticities and then apply them consistently, before considering the politics of the conclusions?
How many of you actually think you are consistent across all of these views about elasticities? How many of you think you actually have a jerry-rigged model (“increasing returns for me but not for thee?”) that holds it all together?
Inspired by these tweets from Garett Jones.
I’m an advisor to a number of firms, including several in the crypto space such as Elrond (eGLD coin). When I signed on as an advisor more than two years ago, Elrond was almost completely unknown, which wasn’t surprising as they were based in Romania. I thought the Romanian base was a positive, however, because it meant that Elrond could hire extremely well-educated computer scientists, mathematicians and software engineers at below Silicon Valley prices. Moreover, the blockchain world, true to its foundations, is decentralized. Like a modern day Erdos, Vitalik Buterin operates out of his suitcase. The Silicon Valley of the blockchain is the internet. Why the blockchain world has evolved differently than Silicon Valley is an interesting question (with implications for whether SV could loses its centrality) but because it is decentralized I thought location was less important than the quality of the team. And the team, led by hard-charging founder Beniamin Mincu, is excellent. In the last two years the Elrond team has built a completely modern blockchain from the ground up using secure proof of stake and sharding to achieve a potential throughput of upwards of 16 thousand transactions per second with 6s latency and $.001 transaction cost and a toolkit for developers. I was also impressed by the commitment Elrond had to security, including formal verification methods, and especially to making Elrond accessible to the masses. Today Elrond/eGLD is on a tear and by market cap it is one of the top 50 projects in the space with a strong upward trend.
Will Elrond take over the world? I hope so! But, of course, it is unclear. Aside from ranking Elrond versus other projects the space itself still doesn’t have a killer app for the masses. In 2017 near the peak of the market at that time, Vitalik Buterin tweeted:
So total cryptocoin market cap just hit $0.5T today. But have we *earned* it?
How many unbanked people have we banked?
How much censorship-resistant commerce for the common people have we enabled?
How much value is stored in smart contracts that actually do anything interesting?…
The total market cap is now close to a trillion, about twice the level when Vitalik tweeted, and these are still good questions. Bitcoin has established itself as a new asset class that is rapidly supplanting gold as a store of value (gold is lame) but not as a payments platform. Ethereum, Elrond and competitors like Algorand were built for smart contracts, including things like stable coins which will be used for payments, but smart contracts are capable of doing much more. In theory, smart contracts let people cooperate in new ways, potentially unlocking trillions in value. But we aren’t there yet.
Decentralized finance or DeFi is one suggestive hint of where things are going. Already many billions of dollars are “lent” and “saved” using DeFi. The lending and saving, however, is almost entirely done in one cryptocurrency for another. In essence, the DeFi system is leveraging off of crypto speculation and trading.
Nevertheless, something interesting is happening in DeFi. The DeX’s or decentralized exchanges have shown that automated market makers can perform the services of market order books used by the traditional exchanges like the NYSE at lower cost while being easily accessible from anywhere in the world and operating 24/7/365. Thus, every exchange in the world is vulnerable to a DeX.
Also, although DeFi is a place where you can easily lose all your money to mistakes, scams, and bugs (not to mention changes in asset values), DeFi is rapidly developing state-of-the-art security. Only the paranoid survive on the blockchain which means that the systems that do survive are robust. Balaji Srinivasan recently tweeted that Bitcoin is the most powerful algorithm in the world and few algorithms have been as battle-tested as Bitcoin. In a similar way, DeFi will be secure or die and security in a blockchain world will be more secure than anywhere else.
Combining security with accessibility is what’s hard. It’s telling that Coinbase is one of the most successful firms in the crypto space despite performing services which are in some tension with the philosophical foundations of crypto. Satoshi Nakamoto would probably be a little disappointed to learn that people were depositing their Bitcoins in a bank! I can understand the impulse, however. It’s almost magical how you can move money on a blockchain without input or permission from any authority. But when you click the button and your money disappears it’s terrifying as you pray for the invisible hand of the miners to restore your money in another account. Elrond’s soon to be released Maiar app, a wallet that interacts with the Elrond blockchain using only a phone number, will be an interesting test of whether a blockchain platform can duplicate the ease of use of something like PayPal or Zelle.
The other interesting development in the space are zero knowledge proofs. Zero knowledge proofs let someone prove that they know a piece of information or the results of a computation without revealing the information. ZK proofs started in the academic literature but research in their uses and applications has exploded as computer scientists like Silvio Micali start blockchains and blockchains like ZCash hire computer scientists who advance the scientific literature (to give just one example). Truly anonymous digital cash is one application but more generally zero knowledge proofs let people buy and sell information in a way which has always been difficult and seemed impossible (how can you sell a piece of information without showing it to someone first but then having seen the information why would they buy it?).
Bottom line is that crypto is still waiting for the killer app which will make it 21st century infrastructure but there has been tremendous scientific progress in blockchains since the ur-date, 1/3/2009. Modern platforms like Elrond are faster, more robust, and more powerful than past platforms and the potential is there for transformative growth.
That is the new book by Tim Harford, due out February 2.
From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics.
Here is an excellent Reason segment on vaccine policy and First Doses First including extensive interview with me.