Category: Economics
Is there an intermediate position on immigration?
It is a common view, especially on the political right, that we should be quite open to highly skilled immigrants, and much less open to less skilled immigrants. Increasingly I am wondering whether this is a stable ideological equilibrium.
To an economist, it is easy to see the difference between skilled and less skilled migrants. Their wages are different, resulting tax revenues are different, and social outcomes are different, among other factors. Economists can take this position and hold it in their minds consistently and rather easily (to be clear, I have greater sympathies for letting in more less skilled immigrants than this argument might suggest, but for the time being that is not the point).
The fact that economists’ intuitions can sustain that distinction does not mean that public discourse can sustain that distinction. For instance, perhaps “how much sympathy do you have for foreigners?” is the main carrier of the immigration sympathies of the public. If they have more sympathies for foreigners, they will be relatively pro-immigrant for both the skilled and unskilled groups. If they have fewer sympathies for foreigners, they will be less sympathetic to immigration of all kinds. Do not forget the logic of negative contagion.
You also can run a version of this argument with “legal vs. illegal immigration” being the distinction at hand.
Increasingly, I have the fear that “general sympathies toward foreigners” is doing much of the load of the work here. This is one reason, but not the only one, why I am uncomfortable with a lot of the rhetoric against less skilled immigrants. It may also be the path toward a tougher immigration policy more generally.
I hope I am wrong about this. Right now the stakes are very high.
In the meantime, speak and write about other people nicely! Even if you think they are damaging your country in some significant respects. You want your principles here to remain quite circumscribed, and not to turn into anti-foreigner sentiment more generally.
Steve Davis, Elon Musk’s Go-To Cost-Cutter Is Working for DOGE
A Bloomberg profile of the excellent Steve Davis:
Elon Musk’s deputy Steve Davis has spent more than 20 years helping the billionaire cut costs at businesses like SpaceX, the Boring Company and Twitter ….[now] Davis is helping recruit staff at DOGE, Musk’s effort to reduce government waste, in addition to his day job as president of Musk’s tunneling startup, the Boring Company.
At Boring, Davis has a reputation for frugality, signing off on costs as low as a few hundred dollars, according to people familiar with the conversations — unusual for a company that has raised about $800 million in capital. He also drives hard bargains with suppliers of products like raw steel, sensors, or even items as small as hose fittings, said the people, who asked not to be identified discussing private information.
His favorite directive for staff doing the negotiations: “Go back and ask again.”
…Davis started working for Musk in 2003, when he joined SpaceX, at the time a new company. He had just earned a master’s degree in aerospace engineering from Stanford University, and distinguished himself at the startup by solving hard engineering problems. At one point, Musk tasked the engineer with finding a cheaper alternative to a part that cost $120,000. Davis spent weeks on the challenge and figured out how to do it for $3,900, according to a biography of Musk. (Musk emailed back one word: “Thanks.”)
…Multitasking has proved a Davis signature, dating back to his student days. While he was working on his doctorate in economics at George Mason University in Fairfax, Virginia, Davis was working full time at SpaceX and owned a frozen-yogurt shop called Mr. Yogato in Washington’s Dupont Circle. Alex Tabarrok, one of Davis’ professors, remembers him juggling the multiple roles.
“I told him, ‘Look, you’re getting a Ph.D., you can’t be having a job and running a business at the same time,” Tabarrok recalls. “Focus on getting your Ph.D.”
But Davis declined to give up any of his pursuits, at one time incorporating business trends at Mr. Yogato into an academic paper and bringing some yogurt into class for sampling. Tabarrok can’t recall Davis’ grades, but says he stood out anyway. He “had so much energy, and was so entrepreneurial,” Tabarrok says. “It’s been kind of exciting to see him become one of Elon’s most trusted right-hand men.”
Davis’s GMU training in political economy will serve him very well in Washington.
See also my previous post, an MR classic, Why We Can’t Have Nice Things–Elon Musk and the Subways.
Addendum: 2013 profile of Steve and another of his businesses, Thomas Foolery a bar in DC where you paid for drinks according to plinko. Hat tip: Kevin Lewis.
Merry Christmas!
Wishing all our readers a wonderful day and New Year!
Dean Ball speaks
o1 and o1-pro are a cut above other models at economic history writing. they can combine knowledge of historical facts with economic analysis in a *much* more creative and cogent way than earlier models. it’s not just math and code, folks.
Here is the link.
The importance of transportation for productivity
We quantify the aggregate, regional and sectoral impacts of transportation productivity growth on the US economy over the period 1947-2017. Using a multi-region, multi-sector model that explicitly captures produced transportation services as a key input to interregional trade, we find that the calibrated change in transportation productivity had a sizable impact on aggregate welfare, magnified by a factor of 2.3 compared to its sectoral share in GDP. The amplification mechanism results from the complementarity between transport services and tradable goods, interacting with sectoral and spatial linkages. The geographical implications are highly uneven, with the West and Southwest benefiting the most from market access improvements while the Northeast experiences a decline. Sectoral impacts are largest in transportation-intensive activities like agriculture, mining and heavy manufacturing. Our results demonstrate the outsized and heterogeneous impact of the transportation sector in shaping US economic activity through specialization and spatial transformation.
That is from a recent NBER working paper by
Stephen Miran nominated to head the CEA
Here is Stephen on Twitter, Harvard PhD, mostly he has been in the private sector. The NYT has further information.
Via Jon Hartley.
Artificial Intelligence in the Knowledge Economy
The rise of Artificial Intelligence (AI) has the potential to fundamentally reshape the knowledge economy by solving problems at scale. This paper introduces a framework to study this transformation, incorporating AI into an economy where humans form hierarchical firms: Less knowledgeable individuals become “workers” solving routine problems, while more knowledgeable individuals become “solvers,” assisting workers with exceptional problems. We model AI as a technology that transforms computing power into “AI agents,” which can either operate autonomously (as co-workers or solvers/co-pilots) or non-autonomously (only as co-pilots). We show that basic autonomous AI displaces humans towards specialized problem solving, leading to smaller, less productive, and less decentralized firms. In contrast, advanced autonomous AI reallocates humans to routine work, resulting in larger, more productive, and more decentralized firms. While autonomous AI primarily benefits the most knowledgeable individuals, non-autonomous AI disproportionately benefits the least knowledgeable. However, autonomous AI achieves higher overall output. These findings reconcile seemingly contradictory empirical evidence and reveal key tradeoffs involved in regulating AI autonomy.
Important results, and largely in accord with my own intuitions. That is from a new paper by Enrique Ide and Eduard Talamas.
AI is Not Slowing Down, Except for Stop Lights
After 25.3 million fully autonomous miles a new study from Waymo and Swiss Re concludes:
[T]he Waymo ADS significantly outperformed both the overall driving population (88% reduction in property damage claims, 92% in bodily injury claims), and outperformed the more stringent latest-generation HDV benchmark (86% reduction in property damage claims and 90% in bodily injury claims). This substantial safety improvement over our previous 3.8-million-mile study not only validates ADS safety at scale but also provides a new approach for ongoing ADS evaluation.
As you may also have heard, o3 is solving 25% of Frontier Math challenges–these are not in the training set and are challenging for Fields medal winners. Here are some examples of the types of questions:
Thus, we are rapidly approaching super human driving and super human mathematics.
Stop looking to the sky for aliens, they are already here.
Unconventional Indicators of National Aspiration
What are your top indicators of national aspiration? Percentage of GDP devoted to R&D would be a good conventional indicator. What about some unconventional indicators? My top five:
1) Top marginal tax rate
2) Space Program
3) Distance to travel to mother’s home
4) Tallest statue
5) Cultural exports
On these, the US and India perform well. India leads on tallest statue and its space program is impressive for a developing country. Cultural exports are currently low but historically high–I would not be surprised at a rebound. A lot of eastern European countries such as Hungary and Romania have flat taxes with top rates of 10-15%. Israel has a space program.
I am always surprised by how little people tend to move from the family home. In the US:
…80% of young adults migrate less than 100 miles from where they grew up. 90% migrate less than 500 miles. Migration distances are shorter for Black and Hispanic individuals and for those from low-income families
If anything this seems to be down in the US despite the much greater ease of moving today than in the past.
Your unconventional indicator?
Hat tip: Connor.
Why are Top Scientists Leaving Harvard?
Harvard magazine has an excellent interview with three scientists, Michael Mina, Douglas Melton and Stuart Schreiber, all highly regarded in their fields of life sciences, who have recently left Harvard for the private sector.
Why did they leave? Mina tells an incredible story of what happened during the pandemic. At the time Mina was a faculty member at the Chan School of Public Health, he is extremely active in advising governments on the pandemic, and he brings Harvard millions of dollars a year in funding. But when he tries to hire someone at his lab, the university refuses because there is hiring freeze! Sorry, no hiring for pandemic research during a pandemic. In my talk on US Pandemic Policy I discuss the similar failure of the Yale School of Public Health and how miraculously and absurdly Tyler stepped in to save the day. The rot is deep.
Melton also notes the difference in speed of response between the public and private/commercial sector:
Polls have shown that principal investigator biologists now spend up to 40 percent of their time—it’s a shocking number, 40 percent of their time—writing grants.
In industry, the funding allows for very rapid change. There’s no writing a grant and waiting six months to see if it could get funded, and then waiting another six months for the university to make arrangements to receive the funds. The speed with which you can move into a new area is not comparable.
Years ago, the pharmaceutical industry rarely did discovery research. But now, pharmaceutical companies do basic science. That’s been a good shift, in my opinion, but it’s been a shift.
“The computational resources, the sequencing, the chemical screening— it’s not comparable to what we can do in any university.”
Everything gets done much quicker. For example, when you want to file for a patent at a company, the next morning there are two patent attorneys in your office ready to write that patent. The computational resources, the sequencing, the chemical screening— it’s not comparable to what we can do in any university. It’s a whole order of magnitude different.
Our last hire at GMU took well over a year to complete. It’s outrageous. There are no functional reasons why universities should be so slow. Don’t forget, Harvard has an endowment of $50 billion!
Melton also asks whether a new private-public partnership model is possible:
Why can’t we find a way—since many of our undergraduates and graduates will end up working in industry—why can’t we find a way for them to do their studies and their Ph.D. and their postdoctoral work in conjunction with Harvard, with MIT, and with Vertex? There are reasons for that, but we haven’t been imaginative enough to think about a compromise.
Hat tip: R.P.
Is Indian food the world’s best?
From my latest Bloomberg column:
Why is the food so good? I have several overlapping hypotheses, most of them coming from my background as an economist. Interestingly, India’s culinary advantages can be traced to some good and some not-so-good aspects of Indian society.
First, food supply chains here are typically very short. Trucking, refrigeration and other aspects of modernity are widespread, but a lot of supply chains are left over from a time when those were luxuries. So if you are eating a vegetable, there is a good chance it came from nearby. That usually means it is more fresh and tastes better.
The sad truth is that India still has very high rates of food spoilage, especially when food is transported longer distances. The country is making significant progress building out its transportation networks, but in the meantime the American culinary tourist enjoys the best of all worlds: Our purchasing power is high, and we can spend our money eating super-local.
And:
India also has high income inequality. That means there is plenty of cheap labor competing to cook for diners with higher incomes. The “thickness” of the competition leads to innovation and experimentation — there are a lot of restaurants, food stalls, truck stops and the like. It is a buyer’s market. Furthermore, some of India’s best dishes, such as Bengali sweets, are very labor-intensive. Indian desserts that are mediocre in US restaurants receive the proper care and attention in Kolkata.
And:
Then there is the cultural side. India is a “food nation.” When I ask locals which are the best places to eat, which I regularly do, I am repeatedly struck by how many have strong opinions. When everyone is a food critic, standards rise accordingly. It also makes it easy for the visitor to get quality recommendations.
There are further good arguments at the link. In Bangalore I had a superb meal, Kayasth food, by Manu Chandra in Lupa, this was a special menu:
The Marginal Revolution Podcast–Options!
Today on the MR Podcast Tyler and I talk about The Quest to Price Options. First, we run through the amazing history of option pricing theory from Bachelier to Black, Scholes and Merton with stops in between for Einstein, Samuelson, Thorpe and Kassouf.
We then look at how understanding options changes how one sees the world. Here’s one bit:
TABARROK: In the Hayekian-Mises business cycle theory, the interest rate is really the key thing. Everyone’s just following the interest rate. Interest rate falls because of government increases supply of money or something like that and everyone just goes into investment.
COWEN: Yes. It was Black himself who said, “No, it’s changes in the risk premium that are doing the work.” That was what he was working on before he died. The papers of mine he wanted to see, were actually on the same idea. The changes in the risk premium might be driving investment. How do we think about those in a business cycle context?
TABARROK: Yes. Those seem to be much more important than the pure interest rate itself. There’s a lot of investment decisions that you can think about like an option. Suppose you have a 10-year mineral lease, which gives you the right to drill an oil well anytime in the next 10 years. Well, when should you drill? It seems obvious that the higher the price of oil, the greater should be your incentive to drill. The price of oil goes up and down. You don’t want to drill the well and then find out that oil prices have dropped below the cost of extraction.
Once the well has been drilled, the costs are sunk, literally in this case. You can think about the decision to drill the oil well as exercising the option to drill. You want to use some model to figure out when, given the volatility of oil prices, is the optimal time to drill the well.
COWEN: It’s related to seeing all these underdeveloped or undeveloped storefronts in American cities. Oh, there’s something that used to be a store. Now, it’s all boarded up. Why don’t they put something in there? Why doesn’t the price adjust? Sometimes it’s regulation, legal issues, but sometimes it’s option value.
You’re not sure what you’re going to put in. You don’t want to have to remodel the thing again. Maybe it should be a restaurant, but your town is not yet ready for a Brazilian churrascaria and, in the meantime, everyone’s waiting.
….It’s a major problem in economicdevelopment. The Danish government is relatively credible. Many, but not all, parts of the US government are. That enables investment and growth. There’s plenty of countries, if you just look at the books, a lot of their laws don’t sound that much worse, say, than US laws. They might even sound better but no one knows what the law will be two, three, 10 years from now. It’s just harder for them to mobilize the proper incentives.
This is our last podcast of the year. What topics should we take on next year?
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Technological Disruption in the US Labor Market
Deming, Ong and Summers have a good overview of long-run and very recent changes in the US labor market. Using a measure of occupational titles the authors find:
The years spanning 1990-2017 were the most stable period in the history of the US labor market, going back nearly 150 years.
It’s a bit too early to distinguish an AI revolution from a COVID shock but the last four years look to be more disruptive than any since the 1970s and over a slightly longer period there are trends including a decline in retail, as consumers shift to online shopping and delivery, and a decline in office work, the latter especially suggesting an AI effect:
There were 850,000 fewer retail sales workers in the US in 2023 compared to 2013 even though the US economy added more than 19 million jobs over this period.
There are nearly five hundred thousand fewer secretaries and administrative assistants in the US labor force now than there were a decade ago. At the same time, management and business occupations have grown very rapidly. There were four million more managers and 3.5 million more business and financial operations jobs in the US in 2023 than there were in 2013.
Keep in mind that these changes are occurring as employment and wages overall are rising.
o1 is still doing well on monetary economics
This is one of these “don’t bother reading through everything unless you already know what I am talking about” posts.
Scott Sumner has a long rebuttal to o1 on monetary theory, offering many criticisms. He does not like the quality of the answer given by the AI. But I view the AI more positively here, at least relative to the current state of the research literature, which admittedly is not so satisfying. I think Scott, a’la Kasparov, is being spooked by “the machine,” and his usual clarity of thought is not always present in this exchange. Here are a few points in response to Scott:
1. Nominal relationships seemed much clearer in the age of Milton Friedman and now they are extremely murky (and yes economists may have been wrong in Friedman’s time about this, but that is not the point). Scott seems to deny this, and I am not sure why. The Monetary History persuaded a significant batch of highly intelligent economists that there was a pretty stable relationship between the monetary aggregates and nominal income. Hardly anyone holds this view today. o1’s portrait of this change seems to me more accurate than Scott’s insistence that inflation has become easier to predict over time.
2. Scott in his criticisms is focused mainly on whether inflation prediction has become harder over time, but mainly o1 is answering why it is so hard today to explain inflation dynamics. (Revisit the question: “Please write an essay on how current macroeconomists find inflation dynamics so very difficult to predict, and why that has made them reject various forms of monetarism, even as approximations of what is going on behind price level behavior.”) So he is grading it on the wrong issues.
3. Scott writes “It [o1] mentions a bunch of irrelevant stuff like QE, and misses the key point that the payment of interest on reserves and the zero lower bound problem have made the money multiplier far more unstable.” Inflation forecasting has been a problem before and after the ZLB. And the payment of interest on reserves was a huge one-time problem for forecasting, but the literature rightly ignores or downplays this as a general issue over time, because it isn’t. So here o1 is closer to the research consensus than Scott is.
4. Most of all, Scott goes out of his way to avoid presenting or even citing a better approach to inflation dynamics. You might look at this 2011 post from Scott on inflation dynamics. It endorses the quantity theory, which I think is true sometimes, but doesn’t go into why the evidence has gone so badly in the other direction.
4b. More seriously, Scott seems to dismiss the price level concept altogether. For instance he once wrote: “In the past, I’ve frequently argued that inflation is an almost meaningless and useless concept. I’m not even aware of any coherent definitions of the concept.” I don’t think this is a defensible point of view, and you have to compare Scott’s criticisms of the o1 model to his own approach, which is fairly nihilistic. And I think wrong. If inflation were higher and someone offered Scott an inflation-indexed contract to sign, would he be unable to evaluate such a transaction? Obviously not.
5. As a side note, I think o1 also did better than the varied observations by Krugman on inflation dynamics over the years. Most recently I recall Krugman arguing that we didn’t have a recession the year before because the initial inflation was almost entirely about supply side shocks. That view has been refuted by a number of recent research papers, some of those cited on MR, showing it was both a supply side and demand side phenomenon.
More generally, here is one recent model of price level dynamics, you can read through the model and results. Real wages matter in many of these investigations, which Scott dismisses and o1 endorses. Here is an attempt to forecast price inflation for 2024, again you can look at the model, which is not so simple and I would also say not super-impressive (I intend no criticism of the authors here, the questions are hard). It is still a puzzle why inflation rates were not even lower during the 2008-2010 period. In other words, interest on reserves may have mattered less than models would suggest.
I understand full well that “kitchen sink” approaches are unsatisfying to many economists. Yet when there is in fact a clear theoretical answer to an economics problem, usually o1 gives it to you.
If you ask o1 Scott’s oil and price theory question, it gets the right answer. The second sentence is: “Whether that quantity is higher or lower than before depends on why the price rose.” In other words, it does not reason from a price change.
So I think Scott is seriously underrating o1 as a reflection of what the profession believes on inflation dynamics. Scott has a right to disagree with that consensus, but I don’t see he has put up the evidence to establish a better view. In any case, on these issues o1 beats both Sumner and Krugman, noting that each is putting forward a fairly extreme point of view. Notably, o1 pro, a yet more advanced model, comes up with a better answer yet. Or you can ask it to spend at least 5000 logic tokens answering the question. Yes people it is worth $2500 a year.
Arnold Kling comments. And Kasparov did eventually come around.
Tax arbitrage through your business
That is the topic of my latest Bloomberg column, here is one bit:
This phenomenon is one reason that many office jobs in Nordic countries seem so pleasant. The workers have nice lunches and the use of comfortable and stylish furniture, which they are not taxed on, though of course their take-home pay may be less.
If you think that such workplace comforts make people happier than cash, then you may approve of such arrangements. And it is one vision for how to make society marginally less competitive.
An alternative model is that, with a proliferation of workplace perks and a diminution of earning power, workers become somewhat less ambitious on the earnings front. Peer norms may change, and the dynamism and innovation of the economy can decline accordingly. There are, in fact, signs of these problems in current-day Europe.
And this:
A recent study looked at some comparable effects in Portugal where the in-kind benefits accrue to a firm’s owners rather than its workers. When people own enough of a firm to control its behavior, they charge some of their personal consumption to the firm. Or, to put it another way: They draw more in-kind income from the firm, and take less cash. That lowers their total tax burden.
For the top quintile of the Portuguese income distribution, once those people are able to control a business, about 20% to 30% of their consumption expenditures are switched to benefits reaped within the firm. For the top 1% of earners, attaining a position of business manager is associated with an almost 18% drop in monthly expenditures. And lest there be any doubt about what’s happening here, the paper notes that “business expenditures on hotels and restaurants significantly increase by 9.8% in the birthday month of the owner-manager and by 6.1% in the birthday month of the owner-manager’s spouse.”
Worth a ponder.