Category: Economics

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?



Subscribe now to take a small step toward a much better world: Apple Podcasts | Spotify | YouTube.

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.

A new paper on the economics of AI alignment

A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal can (i) simulate the task in a testing environment and (ii) impose imperfect recall on the AI, obscuring whether the task being performed is real or part of a test. By committing to a testing mechanism, the principal can screen the misaligned AI during testing and discipline its behaviour in deployment. Increasing the number of tests allows the principal to screen or discipline arbitrarily well. The screening effect is preserved even if the principal cannot commit or if the agent observes information partially revealing the nature of the task. Without commitment, imperfect recall is necessary for testing to be helpful.

That is by Eric Olav Chen, Alexis Ghersengorin, and Sami Petersen.  And here is a tweet storm on the paper.  I am very glad to see the idea of an optimal principal-agent contract brought more closely into AI alignment discussions.  As you can see, it tends to make successful alignment more likely.

Health insurance companies are not the main villain

First of all, insurance companies just don’t make that much profit. UnitedHealth Group, the company of which Brian Thompson’s UnitedHealthcare is a subsidiary, is the most valuable private health insurer in the country in terms of market capitalization, and the one with the largest market share. Its net profit margin is just 6.11%…

That’s only about half of the average profit margin of companies in the S&P 500. And other big insurers are even less profitable. Elevance Health, the second-biggest, has a margin of between 2% and 4%. Centene’s margin is usually around 1% to 2%. Cigna Group’s margin is usually around 2% to 3%. And so on. These companies are just making very little profit at all.

And:

In other words, Americans’ much-hated private health insurers are paying a higher percent of the cost of Americans’ health care than the government insurance systems of Sweden and Denmark and the UK are paying. The only reason Americans’ bills are higher is that U.S. health care provision costs so much more in the first place.

And:

In fact, the Kaiser Family Foundation does detailed comparisons between U.S. health care spending and spending in other developed countries. And it has concluded that most of this excess spending comes from providers — from hospitals, pharma companies, doctors, nurses, tech suppliers, and so on…

Recommended, here is the full post.

Tabarrok on Bail

I appeared on the Bail in the Midwest Podcast (Apple) to talk about crime and bail. Here is one bit:

I’ve talked about capturing these people and recapturing them and that of course is what you see on television. That’s the sexy part of it but actually a lot of what is going on, as you well know, is that the bail bondsmen understand the system much better than the the clients do. So what they’re often doing is helping their clients to navigate the system and to remind them that “you have a court date”. They call them up and send them a text, “don’t forget you have to be at court at this time in this place,” you know these these people are not necessarily putting it on their Google Calendar right? So the bail bondsmen they really perform a social service in helping people to navigate the intricacies of the criminal justice system at a time of high stress.

Apple: https://podcasts.apple.com/us/podcast/bail-in-the-midwest-alex-tabarrok-economist-and/id1693408870?i=1000679367738

Spotify: https://open.spotify.com/episode/7dwB1NX43CEqNzBA2crSDp

Podcast Index: https://podcastindex.org/podcast/5314589?episode=30862010733

Podcast Addict: https://podcastaddict.com/episode/https%3A%2F%2Fwww.buzzsprout.com%2F1948722%2Fepisodes%2F16223987-bail-in-the-midwest-alex-tabarrok-economist-and-professor-at-george-mason-university.mp3&podcastId=3902811

Amazon Music: https://music.amazon.com/podcasts/43d45e68-bdaf-41f0-9adc-66aa2f8a0d4b/episodes/dc0940d2-134b-4bd1-88a9-cdf5b7cbfb14/bail-in-the-midwest-bail-in-the-midwest-alex-tabarrok-economist-and-professor-at-george-mason-university

Player FM: https://player.fm/series/bail-in-the-midwest/bail-in-the-midwest-alex-tabarrok-economist-and-professor-at-george-mason-university

Should crypto receive a tax exemption?

Probably not, or so I argue in my latest Bloomberg column.  Excerpt:

The most obvious argument against the proposal is simply that uniform taxation is better than selective tax exemptions. If a lower capital gains tax rate is preferable, then the goal should be to make a smaller cut that applies to all assets. Exempting a single kind of asset is likely to lead to abuses. You might think that boosting crypto is important now, but which sector or asset will be selected next for special treatment? It may be one you don’t think deserves it.

And:

Another problem is that tax exemption is probably not the best route to crypto normalization. What crypto assets and institutions require is predictable treatment, and on that score the nomination of Paul Atkins to lead the SEC is a good sign. Is a capital gains tax rate of zero even sustainable? A future Democratic president could raise the rate back to standard levels, or higher yet. The crypto industry would still be whipsawed by politics.

A tax exemption for crypto also would skew the population of crypto investors, and not necessarily in a beneficial fashion. The US economy offers a variety of options for tax-free savings, ranging from 401(k) plans to IRAs to pension funds. These vehicles make the most sense for investors who are liquid enough to put aside some money and lose immediate access to their funds.

It would be unfortunate if crypto became a preferred tax-free savings vehicle for lower-income groups. Crypto prices may well remain volatile in the future, and crypto investments are still more likely to be associated with scams and questionable business practices. This is obviously true even if you, like me, see plenty of legitimate uses for crypto assets and institutions.

And:

Another issue is one of tax arbitrage. If crypto assets truly are not taxed on their capital gains, many other investment vehicles might, over time, be repackaged in crypto form. Rather than holding some equity in a company, why not hold a crypto token backed by that same company? That is hard to do under today’s laws and regulations, but it may well become easier under a Trump administration, which seems committed to the normalization of crypto. That normalization, however beneficial it may eventually prove, should not be allowed to serve as a way to dodge taxes.

“Be careful what you wish for, you might get it…”

Trump City

Donald Trump wants to create Freedom Cities. It’s a good idea. As I wrote in 2008, the Federal Government owns more than half of Oregon, Utah, Nevada, Idaho and Alaska and it owns nearly half of California, Arizona, New Mexico and Wyoming. See the map (PDF) for more [N.B. the vast majority of this land is NOT parks]. Thus, there is plenty of land to build new cities that could be adopted to new technologies such as driverless cars and drones.

Mark Lutter review the history and motivation and has a good suggestion:

Our favorite possibility is Presidio National Park. Though much smaller than Guantanamo Bay or Lowry Range, its location is ideal. San Francisco is the world’s tech capital, despite its many problems. The federal government can help San Francisco unleash its full potential by developing Presidio. With Paris-level density and six-story apartment buildings, a developed Presidio would add 120,000 residents, increasing San Francisco’s population by 15 percent. Further, given the city’s existing talent density, a Presidio featuring a liberalized biotechnology regime would quickly become a world innovation leader in this sector. America deserves a Bay Area that can compete; turning Presidio into a Freedom City could be an important step in that direction.

I would add only one suggestion let’s call this Trump City.

File:Aerial view - Presidio-whole.jpg - Wikimedia Commons

La ciudad lineal

When does it make sense to organize most of your urban activity on a (more or less) straight line?

If land transport is very costly, as in much earlier times, and a river is available, you might build much of the town right on the river bank.  You can see remnants of this if you travel along the Rhine, though those developments have since expanded in other directions.  Volgograd partially matches this description as well, or so I am told.  But since river transport has declined in importance, such modes of urban organization have fallen out of favor and for obvious reasons.

Might some new technology resurrect the relevance of linear spatial organization?

Perhaps a very rapid airport people mover can make linear organization non-crazy, but I do not see that it would privilege linear organization.  Does not Istanbul airport have a fairly linear structure?  But how scalable is that?

The Saudi plans for Neom attempt to resurrect a very strong and strict linear model, based on a new mode of transport.  From Wikipedia:

The Line is eventually planned to be 170 kilometres (110 miles) long. It could stretch from the Red Sea approximately to the city of Tabuk and could have nine million residents, resulting in an average population density of 260,000 per square kilometre (670,000/sq mi)…Early plans proposed an underground railway with 510-kilometre-per-hour (317 mph) trains that could travel from one end of The Line to the other in 20 minutes.

Supposedly all the shops and sites would be within a five-minute walk of line stops.

Of course this plan may not happen.  But the 317-mph train is essential to the idea.  Just hop on, and travel at super-rapid speeds to where you want to go.  Presumably there are enough tracks with enough stops, like those newish programmable elevators, that you won’t have to accelerate and decelerate too many times.  But, as the number of desirable stops proliferates, that ends up translating into an impractical number of separate individual train tracks.

The core problem seems to be that a linear city requires both super-rapid transport and not too many desirable stops.  It is hard to pull off that combination in the modern world.

Is Conakry the closest the world has to a truly linear city?

Probably that map is a bear sign for the idea.

To read about this topic, you might try:

von Thunen, The Isolated City.

Arturo Soria y Puig, La Ciudad Lineal.

Cerda, The Five Bases of the General Theory of Urbanization, edited by Arturo Soria y Puig.

N.A. Miliutin, Sotsgorod: The Problem of Building Socialist Cities.

And ask your local GPT.

o1 explains why you should not dismiss Fischer Black on money and prices

The prediction of inflation dynamics—how prices change over time—has increasingly confounded modern macroeconomists. Throughout much of the twentieth century, there seemed to be clear relationships linking the money supply, economic slack, and price levels. Monetarism, the school of thought that posits a stable connection between the growth rate of a money aggregate and the subsequent rate of price inflation, emerged from these apparent regularities. However, in the decades since, inflation’s behavior has grown more elusive. At present, even the most sophisticated forecasting models struggle to produce accurate predictions, and this persistent difficulty has led many economists to abandon or at least sideline monetarist frameworks, even as broad conceptual approximations of what drives price-level changes.

Several factors have contributed to the increasing complexity and unpredictability of inflation. First, the financial innovations and regulatory changes of the late twentieth and early twenty-first centuries dramatically altered the relationship between money and economic activity. Monetary aggregates—like M1 or M2—that once served as dependable indicators of policy stance and future inflation now behave erratically due to shifts in the velocity of money, the proliferation of shadow banking, and the globalization of financial flows. Simply put, where money resides and how quickly it moves through the economy has become too fluid and too complex for older monetarist simple rules to capture.

Second, the nature of central banking and fiscal policymaking has changed. Central banks now intervene in a host of unconventional ways, from massive purchases of financial assets to the forward guidance of policy expectations. These tools are not well-explained by the classic monetarist perspective, which centered on controlling a particular measure of the money supply. The recent experience following the Global Financial Crisis vividly illustrates this: The Federal Reserve and other central banks undertook unprecedented quantitative easing programs, dramatically expanding their balance sheets. According to traditional monetarist logic, this rapid increase in the monetary base should have led to substantial inflation. Yet inflation remained persistently below target levels in many advanced economies for years, confounding those who relied on old monetary aggregates as a guide.

Third, the determination of prices today involves a bewildering interplay of global supply chains, technological advances, labor market transformations, and shifts in consumer behavior. Globalization means that prices for goods and services are influenced not just by domestic monetary conditions, but also by distant supply shocks, currency fluctuations, and international competition. Technological change increases productivity and can compress prices in certain sectors, while leaving other parts of the economy less affected. Labor markets have also evolved, with changes in union power, demographic shifts, and altered labor-force participation patterns influencing wage formation and cost pressures. These micro-level frictions and structural changes make the older macro-level equations linking money supply growth to inflation too coarse and imprecise.

Expectations add another layer of complexity to predicting inflation. Modern theories emphasize the importance of how households and firms anticipate future prices. If inflation expectations are well-anchored—due perhaps to the credibility and transparency of central banks—then inflation may remain muted even in the presence of large monetary expansions. This expectations-driven feedback loop can be fragile and influenced by factors that monetarist models never fully accounted for, such as long-standing policy credibility, real-time policy communication, and evolving social norms around price-setting.

The persistent difficulty in accurately forecasting inflation has thus fostered widespread skepticism regarding monetarist frameworks. Economists have increasingly turned to more eclectic, multi-factor models that mix elements of behavioral economics, sectoral and supply-side analyses, and forward-looking expectation frameworks. In these models, money plays at most a peripheral role, subsumed within larger financial conditions indexes or treated as a secondary variable rather than a primary determinant of prices. While many of these frameworks remain works-in-progress, they arguably do a better job reflecting the messy reality of modern economies than the neat but now outmoded equations of monetarism.

Moreover, as central banking has shifted toward inflation targeting and the careful management of expectations, the levers of policy have diverged even further from the simple control of monetary aggregates. Instead, policymakers pay more attention to interest rates, output gaps, and inflation targets. Market participants and researchers look to high-frequency data, surveys of inflation expectations, measures of wage growth, and detailed sectoral price indices to glean insights into future inflation trends.

In sum, today’s difficulty in predicting inflation stems not from a lack of effort or sophistication on the part of economists, but from a world that has grown too complex for the old, more mechanical relationships. As the empirical evidence over recent decades has mounted, it has pushed policymakers and scholars away from monetarism. Central bankers and macroeconomists have concluded that merely tracking money supply is insufficient to explain or predict the course of price levels. They have rejected monetarism not out of ideological bias, but because the data and events of recent history have shown that the old assumptions and simplifications no longer approximate the reality of modern inflation dynamics.

Here is the link, and I will add a few points:

1. o1 is a very good economist.  Try to stump it if you can.

2. I am very familiar with Scott Sumner’s monetary theory arguments about medium of account, cash balances, and the like.  I grew up with those in pretty much the same manner that Scott did.  That said, after decades of watching the data, I have surrendered many of my earlier intuitions.

3. I actually stand to “the quantity theory side” of the current macroeconomic consensus.  That is, I think the quantity theory is sometimes quite relevant, such as right after the pandemic, when the inflation rate rose considerably along with M2 aggregates.  But often quantity theory modes of thought are far less relevant, and we do not have a good theory for distinguishing when.  Note that a lot of the empiricists who work in this area, say for the Fed, do not think money supply magnitudes are very relevant at all.  If anything, I am leaning in Scott’s direction, rather than going out on a limb relative to mainstream doctrine.

4. Basically, the people who dismiss the Fischer Black view would have a tougher time of it if they started with this evidence.

5. In Scott’s comment on his post he starts by citing me and then writes: “[TC] I read Scott as significantly overrating the forecasting power of the nominal in the data. [end TC]”  No, that is misreading me. My post wasn’t considering the forecasting power of nominal data. For instance, I don’t believe that changes in the money supply are a good way of forecasting inflation.  My post was a critique of the view that central banks cannot control inflation, i.e., the view that they do not affect nominal variables. I was not claiming that they have perfect control over inflation.”

A few points: a) I read Scott in general as overemphasizing the nominal, it wasn’t a comment about that post per se.  The data on inflation dynamics show how poorly we understand the nominal.  b) we still need a good way of thinking about inflation, and that re-opens the door to Black-like insights, and c) neither Black nor I claim that central banks cannot affect nominal variables. They do this best when people think they can, or when they are willing to act irresponsibly with the currency or possibly monetary base lever.  But often they are not willing to act irresponsibly, so much of it boils down to expectations.  That is close to Black’s view, though I think he overemphasized expectations as the sole relevant factor.