In Hume’s spirit, I will attempt to serve as an ambassador from my world of economics, and help in “finding topics of conversation fit for the entertainment of rational creatures.”
The US Democrats and Republicans, together with other political activity around the world, probably takes up too much space in my head. In 1945, C.S. Lewis gave a talk on “Membership,” later published in his collection, The Weight of Glory and Other Addresses. Lewis is writing one of his Christian apologetics in this essay. However, when he writes in the second sentence that he is “thinking only of natural values,” that is his way of setting aside his primary topic of Christian faith and discussing secular society for a few lines. Here’s Lewis:
To be happy at home, said Johnson, is the end of all human endeavour. As long as we are thinking only of natural values we must say that the sun looks down on nothing half so good as a household laughing together over a meal, or two friends talking over a pint of beer, or a man alone reading a book that interests him; and that all economies, politics, laws, armies, and institutions, save insofar as they prolong and multiply such scenes, are a mere ploughing the sand and sowing the ocean, a meaningless vanity and vexation of spirit. Collective activities are, of course, necessary, but this is the end to which they are necessary. …
A sick society must think much about politics, as a sick man must think much about his digestion; to ignore the subject may be fatal cowardice for the one as for the other. But if either comes to regard it as the natural food of the mind–if either forgets that we think of such things only in order to be able to think of something else–then what was undertaken for the sake of health has become itself a new and deadly disease. There is, in fact, a fatal tendency in all human activities for the means to encroach upon the very ends which they were intended to serve. Thus money comes to hinder the exchange of commodities, and rules of art to hamper genius, and examinations to prevent young men from becoming learned. It does not, unfortunately, always follow that the encroaching means can be dispensed with.
Here’s my earlier meditation on the Samuel Johnson quotation, “To Be Happy at Home is the Ultimate Result of All Ambition” (December 26, 2018), with relation to an earlier similar comment from Blaise Pascal. As I wrote there: “I aspire to remember and to live out the value of happiness at home. But I recognize in myself the contradiction of aiming at rest through agitation. I know that my opinion of myself, along with the opinions of those who have known me longer and more intimately, should matter most. But I recognize in myself a desire to receive attention and plaudits from those who barely know me at all.”
Alexis de Tocqueville came from France and traveled across the United States in 1831, and several years later published his reflections about Americans and America in the classic Democracy in America. In volume 2, published in 1840, he titled Chapter 13, “Why the Americans Appear So Restless Amid Their Well-Being.” In the chapter, he meditates on why the Americans, many of whom seem so very well-off by the French standards of the time, nonetheless often seem so restless and melancholy. He points to a combination of materialism, the opportunities for economic and mobility that lead to fear of missing out, and the way in which a desire for equality can sharpen itself and strengthen these other factors.
As the US approaches Election Day tomorrow, Tocqueville offers food for reflection. In particular, I’ve long been intrigued by his comment: “When inequality is the common law of a society, the greatest inequalities do not strike the eye. When all is nearly level, the least inequalities offend it. This is why the desire for equality always becomes more insatiable as equality is greater.” Here’s a longer passage:
It is a strange thing to see with what kind of feverish ardor the Americans pursue well-being, and how they appear tormented constantly by a vague fear of not having chosen the shortest road that can lead to it. The inhabitant of the United States is attached to the goods of this world, as if he was assured of not dying, and he hastens so much to seize those goods that pass within his reach, that you would say that at every instant he is afraid of ceasing to live before enjoying them. He seizes all of them, but without gripping them, and he soon lets them escape from his hands in order to run after new enjoyments.
A man, in the United States, carefully builds a house in which to spend his old age, and he sells it while the ridgepole is being set; he plants a garden and he rents it as he is about to taste its fruits; he clears a field, and he leaves to others the trouble of gathering the harvest. He embraces a profession, and he leaves it. He settles in a place that he soon leaves in order to carry his changing desires elsewhere. If his private affairs give him some respite, he immediately plunges into the whirl of politics. And when, near the end of a year filled with work, he still has a little leisure, he takes his restless curiosity here and there across the vast limits of the United States. He will do as much as five hundred leagues in a few days in order to distract himself better from his happiness. …
Equality leads by a still more direct road toward several of the effects that I have just described. When all the prerogatives of birth and fortune are destroyed, when all the professions are open to everyone, and when you can reach the summit of each one of them on your own, an immense and easy career seems to open before the ambition of men, and they readily imagine that they are called to great destinies. But that is an erroneous view that experience corrects every day.
The same equality that allows each citizen to conceive vast hopes makes all citizens individually weak. It limits their strengths on all sides, at the same time that it allows their desires to expand. Not only are they powerless by themselves, but also they find at each step immense obstacles that they had not at first noticed. They destroyed the annoying privileges of a few of their fellows; they encounter the competition of all. The boundary marker has changed form rather than place. When men are more or less similar and follow the same road, it is very difficult for any one of them to march quickly and cut through the uniform crowd that surrounds and crushes him. This constant opposition that reigns between the instincts given birth by equality and the means that equality provides to satisfy them torments and fatigues souls.
You can imagine men having arrived at a certain degree of liberty that satisfies them entirely. They then enjoy their independence without restlessness and without fervor. But men will never establish an equality that is enough for them. Whatever efforts a people may make, it will not succeed in making conditions perfectly equal within it; and if it had the misfortune to arrive at this absolute and complete leveling, there would still be inequality of intelligence that, coming directly from God, will always escape the laws. No matter how democratic the social state and political constitution of a people, you can therefore count on each of its citizens always seeing near himself several points that are above him, and you can predict that he will obstinately turn his attention solely in their direction. When inequality is the common law of a society, the greatest inequalities do not strike the eye. When all is nearly level, the least inequalities offend it. This is why the desire for equality always becomes more insatiable as equality is greater.
Among democratic peoples, men easily gain a certain equality; they cannot attain the equality they desire. The latter retreats from them every day, but without ever hiding from their view, and by withdrawing, it draws them in pursuit. They constantly believe that they are about to grasp it, and it constantly escapes their grip. They see it close enough to know its charms, they do not come close enough to enjoy it, and they die before having fully savored its sweet pleasures.
It is to these causes that you must attribute the singular melancholy that the inhabitants of democratic countries often reveal amid their abundance, and this disgust for life that sometimes comes to seize them in the middle of a comfortable and tranquil existence.
A number of Tocqueville’s themes about American restlessness continue to ring true to me: a drive for higher consumption, “a vague fear of not having chosen the shortest road that can lead to it,” and how people are “always seeing near himself several points that are above him.” The drive for “equality” sometimes seems to me to have stronger element of pulling down those with higher incomes and wealth (which I favor in mild doses) rather than of helping those with the lowest income and opportunities (which I would favor in large doses). In certain settings, even a factual statement that American have a high average standard of living by world standards can be met with virulent and even profane disagreement. The fluidity, ambition, and plenty that characterize the United States are also part of what makes Americans susceptible to the overpromising and bombast of politicians.
Forbes magazine has just published its annual list of the 400 wealthiest Americans, who this year hold a total of $8 trillion in wealth. It’s a gobsmacking amount of money, but we also live in a world where trillions are not unheard of. Here are a few thoughts and perspectives.
The promised Social Security benefits under current law exceed the projected inflows of revenue by about $29 trillion over the next 75 years, according to the actuaries. The promised Medicare benefits under current law exceed the projected inflows of revenue by about $60 trillion over the next 75 years. So if the US government somehow had an extra $8 trillion to play with, it could address either about one-quarter of the Social Security underfunding or about one-eighth of Medicare underfunding–but not both. My first point here is just that while US wealth held by the wealthiest is enormous, it is not an unlimited amount; indeed, the existing promises already made by just these two programs are much larger.
However, there’s no question that US wealth has been growing fast than the economy as a whole. This figure shows the ratio of wealth-to-GDP in the US since about 1960.
From the 1960s up through the 1980s, the ratio of total US wealth to the GDP was roughly 4–that is, with some fluctuations, total assets rose in proportion with the size of the economy. But in the the 1990s, this changed. There was a burst of stock market wealth in the 1990s and a burst of real estate wealth in the early 2000s, and in 2007 on the eve of the Great Recession, wealth was 4.9 times the size of GDP. After the Great Recession, the wealth-to-GDP ratio fell back to the historical level around 4. But a few years later, driven particularly by rising stock prices (which have risen almost six-fold since 2010), wealth-to-GDP took off again, topping out at a multiple of 5.5 in late 2021 and 2022, then sinking a bit, and now apparently pushing to a new high.
This pattern affects how one thinks about the rising inequality of wealth. If the wealth-to-GDP ratio remained the same over time, but the top 1% or 0.1% had a larger share, then the wealth gains at the top would come at the expense of wealth at the middle and the bottom. But with a rising wealth-to-GDP ratio, it’s possible for absolute quantity of wealth at the middle and the bottom to remain much the same, even as the quantity of wealth rises at the top. One might object that both scenarios are unpleasant, and I wouldn’t argue the point too vehemently, except to say that the two scenarios are unpleasant in different ways and with different implications.
The Federal Reserve now runs a website with detailed breakdowns of wealth data, updated quarterly. This figure shows the share of wealth held by different groups. this is household data, so with 134 million or so households in the US (and an average of 2.5 people per household), the top 1 percent consists of 1.34 million households. That top 1% held 8.6% of total wealth in 1989, and how holds about 15% of total wealth. Meanwhile, the bottom 90% of the wealth distribution held 77.2% of total wealth in 1989, but now holds 68.3% of total wealth.
This figure shows the types of assets held by different groups: again, remember that the number of households represented by the first bars, the top 0.1%, is only one-ninth as large as the second bar, and both are much smaller than the bars that follow.
The next figure shows the same data, but instead of presenting it in dollars, it shows the share of assets held by each group. What’s interesting here, I think, is that those at the top of the wealth distributino are more likely to hold assets in the form of stocks and “unincorporated businesses.” hare of assets held by each group. Those further down the distibution hold a greater share of wealth in real estate.
There are a number of proposals out there for wealth taxes, but in my own mind, it seems significant that a number of European countries that tried wealth taxes then repealed them. One common problem is that exemptions and exceptions start getting built into the law: for wealth held by the family farm, for wealth in other family businesses, for historical properties, for family heirlooms, for works of art, and so on and so on. Another problem is how to value wealth that isn’t being bought and sold in the market, and yet another problem is what happens when wealth is held in other countries. I’ve discussed here some more practical alternatives to a wealth tax, like focusing on the rule that allows the value of assets to be “stepped up” at death, so that heirs do not pay tax on earlier capital gains (see here and here). Indeed, just rolling back the US estate tax rules to 2004–which was hardly a time of confiscatory taxation–could raise about $100 billion per year in revenue.
Discussions with the US about the American health care system often counterpose the well-known issues of the US health care system (high costs, lack of health insurance, unequal access to care, lower health outcomes than many other high-income countries) with a nebulous alternative often called “national health insurance, like all the other countries in the world” or sometimes “Medicare for all.” I refer to the alternatives as “nebulous” because the suggestion seems to be that these alternative plans offer all the health care demanded, with all or the vast majority of costs covered by someone else.
When it comes to broad statements about national health insurance, it’s also important to specify what national models you have in mind–because national health insurance systems vary substantially across high=income countries. The Commonwealth Fund has recently published a webpage offering “International Health Care System Profiles” for 31 countries. Many of the countries are high-income: the US, Canada, ten countries in Europe, Japan, Australia, Taiwan, Israel. But there also a selection of other large economies around the world: China, India, Brazil, Nigeria, Ethiopia, Indonesia, Phillippines, and others. Each country health care profile runs about 20 pages: that, is the Commonwealth Fund is trying to ride the thin line between a reasonably in-depth overview and information overload.
When comparing the health care systems of other countries to the US health care system, the most common comparisons I hear are other English-speaking countries, and in particular Canada and England. Both countries have 100% population coverage for national health insurance, and both spend about 11% of GDP on health care, as opposed to 18% of GDP going to health care spending in the US. On one hand, the lower health care spending in those countries seems attractive, allowing for additional consumption of other goods and services; on the other hand, I suspect that concrete and specific American proposal to cut total health care spending by one-third–to the UK and Canada level–would go down in flaming defeat.
Moreover, the Canadian and English systems are quite different from one another. In Canada, 69% of people have private health insurance to complement the public program; in the UK, only about 12% have private health insurance. In Canada, the national health care system is organized on the provincial level–rather like giving all 50 US states the lead authority for organizing health insurance–while the British system is nationally organized. As a result, determination of wages for health care providers looks different: most British physicians are on salary, with most specialists paid directly by the National Health Service, while a number of Canadian physicians still work on a fee-for-service basis.
In short, it’s not enough just to bewail the US health care and health insurance system. Other national models differ substantially among themselves. Indeed, Germany, Netherlands, and Switzerland have organized their national health insurance systems around individual-level health insurance, combined with regulated competition among insurers. A serious discuss of US health care reform has a number of lessons to learn from other countries, but the healtgh care systems of other countries differ substantially, and a serious discussion needs to dig into the details. The national-level profiles from the Commonwealth Fund are a useful starting point on the journey to literacy in the choices of health care policy.
I have made no secret of my deep skepticism about President Trump’s tariff policies since he announced his “Liberation Day” tariffs in April 2025. My first-blink “Thoughts on the Trump Tariffs” from a few days after the announcement has held held up reasonably well, and I have posted follow-ups on the subject a number of times since. For an overview of economic thinking on the subject, I recommend the six-paper symposium on tariffs in the Summer 2026 issue of the Journal of Economic Perspectives (where I work as Managing Editor).
Of course, I’m sure that all readers of this blog have already scrutinized these papers at great depth. But on the off chance you were pursuing other plans when the issue was published in August, it seemed worth mentioning here. I will not try here to summarize the papers in depth, but instead just to tell you something interesting about each one.
In “US Tariff Policy since 1789,” Miguel Acosta, Lydia Cox, Andrew Greenland, John Lopresti, Christopher M. Meissner, Martin Rotemberg, and Sharon Traiberman describe their efforts to construct a detailed database of tariffs back through 1789–a monumental task which involves classifying products in a consistent way over long periods of time and then tracking down tariff rates as they were published in 19th century Congressional documents. They emphasize the three R’s of historical tariff policy: “the use of tariffs as a key revenue stream prior to the Civil War; the restrictive tariffs of the newly emergent industrial economy after the Civil War; and the period of “reciprocity” that emerged beginning in the 1930s.” I was intrigued by how tariff policy has over time come to focus on very specific goods (say, types of cheese) as a way of focusing tariffs on some countries rather than others. Here’s a graph showing the number of products with tariffs on them over time–a number that keeps rising as the tariffs become more detailed.
In “Labor Market Responses to Tariffs: Frictions, Dynamics, and Policy Responses,” Rafael Dix-Carneiro and Brian K. Kovak present evidence on patterns of jobs lost to trade over time. They argue: “A central finding is that trade liberalization and import competition can generate sizable and highly localized labor market disruptions. Specifically, employment and earnings losses tend to be concentrated in particular regions, sectors, and occupations, and adjustment is often slow, with effects extending beyond directly affected workers to entire local communities.” In analyzing patterns of adjustment, they show that the costs fall especially heavily on older workers with less flexibility to shift their lives. They also find that when industries are protected from import competition by tariffs, they often react by investing more in capital equipment and by earning higher profits, rather than by keeping employment high. They make a case for “smoothing policies,” to cushion the costs of trade shocks for those bearing the highest costs, with the goal of helping to facilitate the longer-run benefits of trade for the economy as a whole.
In “Should We Tax Trade? A Pigouvian Perspective,” by Arnaud Costinot and Iván Werning point out that it is straightforward to draw up a model showing that that those who create the disruptions of trade should also pay for the social costs–but that real-world trade policy is also not so simple. They suggest the “Targeting Principle”: “The economy may be distorted and government intervention may be warranted. Yet one cannot conclude that a tariff is optimal without making it compete with other available instruments. The Targeting Principle suggests that trade policy is acupuncture with a fork and calls for using needles instead. … Let us return once more to the case where domestic redistribution is the only motive for trade policy intervention. On the one hand, it is unrealistic to assume that no other policy instruments are available to achieve this goal. As Rodrik (1995) puts it, “Saying that trade policy exists because it serves to transfer income to favored groups is a bit like saying Sir Edmund Hillary climbed Mt. Everest because he wanted to get some mountain air. There was surely an easier way of accomplishing that objective.” The takeaway is that arguments for specific tariff policy focused on narrow geopolitical or economic goals are likely to be more persuasive than sweeping and general pro-tariff arguments.
In The Incidence of Tariffs: Rates and Reality,” Gita Gopinath and Brent Neiman dig into the question of whether tariffs are paid by foreign producers–as President Trump promised in April 2025–or whether they raise prices for US consumers. They point out that through the end of 2025, the actual tariff rates paid were only about half of the announced statutory rates, because “[s]hipment lags, product and company-specific exemptions, utilization of the US-Mexico-Canada Agreement (USMCA), and evasion and heterogeneous enforcement all contribute to the large gap between statutory and actual rates.” With these kinds of factors taken into account, their estimates are that more than 90% of the tariffs were passed though to US buyers–a finding that they point out is consistent with a number of other studies.
In “Global Imbalances, Tariffs, and Industrial Policy, Pierre-Olivier Gourinchas, Gene Kindberg-Hanlon, Manasa Patnam, Lorenzo Rotunno, and Michele Ruta work through the question of tariffs or industrial policy in general can reduce trade deficits. They re-affirm the conventional (among economists) argument that tariffs alone are unlikely to have much affect on trade deficits, because trade deficits are a macroeconomic outcome driven by domestic savings and invesment levels. Similar logic applies to targetted industrial policy. However, what they call “macroeconomic industrial policies” involving financial repression and forced savings raise different issues. They write:
The term “financial repression” refers to a group of policies. It may involve limiting the interest rates available on deposits in the domestic banking sector or limiting the availability of other financial assets, in order to reduce funding costs, while simultaneously limiting lending rates on loans to businesses in targeted sectors. These policies are often combined with forced saving policies that can include prohibitions on dividend payments by corporations (to encourage higher retained earnings), reserve requirements on export earnings, mandatory saving requirements in pensions or similar products, or even weak social safety net provision that requires high private saving for insurance purposes.
The goal of rules and incentives that drive up saving and limit investment options for households is to make it cheaper and easier for domestic firms to raise investment capital. China is of course a major example of such policies. By driving up domestic savings and investment, these policies can lead to trade surpluses–but a policy of lower consumption and limited financial investment opportunities is unlikely to be a political winner for any US politician.
In Evaluating the Fiscal and Distributional Implications of Tariffs,” Kyle Pomerleau and Erica York look at how prominent organizations like the Congressional Budget Office, the Tax Policy Center run by the Brookings Institution and the Urban Institute, the Yale Budget Lab, the Penn/Wharton Budget Model, and the Tax Foundation formulate their stimates for total revenue to be raised by the tariffs (at least as they existed in 2025), and also how some of these organzations formulate estimates of who pays for tariffs across the income distribution. On the first question, tariffs at more-or-less the 2025 levels would raise about $2.5 trillion in revenue over the next 10 years–that is, an average of $250 billion per year–or someone less if the model takes into account how tariffs will slow the economy. In distributional terms, the tariffs tend to weigh more heavily on middle-income and low-income households, and less on those near the top of the income distribution.
As I wrote back in April 2025, President Trump owns the tariffs. He imposed them without Congress passing any new laws, and when the courts have told him that he did not have the legal power to do so, he has then offered one different legal rationale after another. He made extravagant promises about how the tariffs: for example, when President Trump was talking about the tariffs to come, he said: “All I know is this: We’re going to take in hundreds of millions of dollars in tariffs, and we’re going to become so rich, you’re not going to know where to spend all that money! I’m telling you – you just watch. We’re going to have jobs, we’re going to have open factories, it’s going to be great.” As I wrote in April 2025: “President Trump’s claims about the benefits of tariffs seem based on demonstrably false beliefs. … I confess to a darker thought. Part of me hopes that Trump will keep his tariffs in place until the costs are broadly apparent to all, so that a modern consciousness of why this approach doesn’t work can take effect for the next few decades.”
For many low-income countries, perhaps the greatest deficit they face is a lack of the human skills that build economic growth. The new artificial intelligence tools improve access to a wide range skills. Thus, the World Bank devoted its flagship World Development Report 2026 to “The Promise of Artificial Intelligence.”
For a vivid example, consider agricultural extension agents, who are goverment-funded to travel across rural areas providing insight into how output might be improved. The WDR writes:
The planning guidelines of the Food and Agriculture Organization of the United Nations (FAO) for agricultural extension services specify one agent for every 500–2,000 rural inhabitants, depending on a country’s production systems and the density of its population. But the reality on the ground falls short. Recent estimates indicate that in Nigeria, for example, a single public extension agent may serve anywhere from 5,000 to 10,000 farmers. In India, which has one of the largest public extension systems in the world, with about 120,000 extension professionals—the ratio of extension workers to farmers is about 1 to 5,000 … A gap in service delivery is evident not only in the number of extension agents available to farmers, but also in the quality and responsiveness of the advice they provide. Public extension advice tends to be structurally generic (designed for an average farmer in an average season) …
If local farmers have some access to a smartphone in the nearest village, and can query an AI tool about local conditions, crops, and what’s working for others, including the ability to send along pictures of the landscape and how the crops are faring, it can make make the difference between extreme poverty and malnutrition in a given year–or not. One experiment with AI advisors in Ethiopia providing locally customized advice increased wheat yields 38%.
As the report points out, low-income countries are unlikely to be significant players in the near term in developing frontier cutting-edge AI models, or in producing the most sophisticated semiconductor chips. But in a number of contexts, the use of AI often benefits those starting with less experience or skill, because those workers, firms, and government have the most room for gains from greater access to knowledge and skill. A number of companies and governments in lower-income countries are already using these tools, including use of chatbots for questions and feedback on public services and from the customers of firms. Small AIs can be “built for one narrow task, such as identifying a crop disease or screening a medical image.” The report notes:
Many developing countries face shortages of highly skilled workers. AI can help by enabling less experienced workers to perform more advanced cognitive tasks, allowing some work to be shifted away from scarce specialists and making existing workers more productive. First, if AI automates more expert tasks within an occupation, it lowers the entry requirements for people to carry out the work in that occupation.There is evidence of such leveling up across cognitive occupations, including customer support,professional writing, and software development. Second, AI can shift a given cognitive task to adjacent occupations that employ people with less expertise, such as shifting the task of medical-image screening from scarce medical specialists to lower-level health care providers. Third, AI makes people more productive at what they currently do. For example, generative AI tools improve the quality of instruction in schools by supporting teachers with lesson planning, generating learning materials matched to students’ skill levels, and providing quicker feedback on student work.
The WDR is open about acknowleding a range of practical issues. AI will also disrupt some industries in lower-income countries: for example, AI agents seem likely to displace a number of workers at call centers. Benefits from AI require complementary investments in physical and human infrastructure. Low-income countries may wish to have a process for adaping existing open-source AI tools for local use and/or foor designating certain AI tools as trustworthy. The use of AI in schools can be a decidedly mixed blessing, but the possibilities for customized tutoring when teachers are scarce seem substantial.
Living in the environment of US higher education, as I do, one hears a lot of concern about the use of AI in writing research papers, or in writing novels. A chief concern is that the use of AI involves a loss of something precious and ineffably human. Those issues matter. But the WDR reminds us that the potential gains and tradeoffs may look quite different in low-income developing economies.
The amounts of money being spent on the hardware and buildings behind the new AI boom may turn out to be enormously large by historical standards. How is it being financed?
Stijn Van Nieuwerburgh tells the story in “Financing the AI Buildout” (Brookings Papers on Economic Activity, Fall 2026, conference draft version). As he points out, the new AI technologies are often discussed as a new form of software, and how the capabilities of that software are developing. The software perspective is true, but partial. The new AI technologies are also a physical capital boom. Indeed, our public discourse on AI seems to have entered a period where one set of concerns is that Ai software will be so cheap and available that it will lead to mass unemployment, while another set of concerns is that building the physical capital behind the AI boom–including data centers, semiconductor plants, additional energy production, and more–will be extraordinarily expensive. I’m alwas loathe to make predictions, but I feel confident in saying that the new AI technologies will not be both cheap and expensive at the same time.
Van Nieuwenbergh walks through a set of calculations to forecast the size physical capital AI investment in the next few years, based on current plans and the recognition that not all the current plan will actually happen. He produces this historical comparison, which needs to be taken with a few grains of salt. The AI buildout is a prediction, while the others actually happened. Also, the time periods vary: the railroad investment, the second-highest number on the right-hand column, lasted much longer than these predictions for the AI buildout. Still, the estimates for the cost of the AI buildout are striking.
Where are firms getting the funding for this buildout? Remember, stock market wealth is not an immediate source of funding–unless you sell the stock to someone else. One of the economic puzzles of the last decade or so is that big US tech companies were holding huge amounts of cash, more than $1 trillion (for example, I wrote about this back in 2013, here and here). A common question has been: What investment opportunity were they waiting for? The answer appears to be the AI buildout. Van Nieuwenbergh writes:
Aggregate capital expenditures by Oracle, Microsoft, Amazon, Meta, and Alphabet rose from roughly $97 billion in 2020 to more than $400 billion in 2025 and are projected to exceed $800 billion in 2026. On current estimates, capex will surpass the five firms’ combined operating cash flow for the first time in 2026. The figure therefore marks an important transition: internal cash generation remains substantial, but it is no longer sufficient to finance the projected pace of investment without greater reliance on external capital or financing structures that shift assets and obligations away from the operating companies’ balance sheets.
The new outside financing is a combination of equity and debt finance. The equity finance is arriving in the form of “[s]pecialized data center developers, REITs [real estate investment trusts], infrastructure funds, and private equity investors.” The debt finance includes bank loans and bonds, but private credit funds provide a growing share.
For those with an interest in private credit in particular, Puriya Abbassi, Iñaki Aldasoro, and Sebastian Doerr provide an overview of “Financing the digital economy: the role of private credit “ (BIS Quarterly Review, September 2026, pp. 17-30). In contrast to bank loans, which often require that a borrower have physical collateral to back up the loan, private credit funds make loans based on expected cash flows and intangible assets. As banks have become more tightly regulated, private credit funds have expanded, and as of 2025 had loan amounts outstanding of $2.5 trillion. As the authors note: “Aggregate [private credit] borrowing by tech firms rose from around $22 billion (22% of total private credit) in 2010 to over $1 trillion (44%) by 2025.” These private credit funds typically operate by getting money from investors that is usually committed for the middle-term of five to eight years, and cannot be withdrawn. If a bank has many loans that go sour, the bank has been lending out money of depositors, which can cause a problem; if a private credit fund loan portfolio goes sour, the investor in that fund would suffer losses, but there is much less reason to think that those losses would propogate into banking or the rest of the financial system.
One of the strengths of a market economy is that some companies can succeed, while others fail, without endangering the health of the economy as a whole. But when the scale of the investment gets this big, and the risks are distributed across a web of interlocking companies, it’s natural to wonder about which investors will bear the losses if the AI boom doesn’t generate revenue as fast as expected–and whether losses from those investors might be substantial enough to affect the broader economy. Some readers will remember the dot-com boom-and-bust when the overall stock market fell by about 50% from March 2000 to October 2002, and many internet companies fell by even more. There was a recession for eight months in 2001. But although the economy took a hit and a number of companies vanished outright, the technology of the internet didn’t go away, and the physical capital boom behind the internet was put to productive use.
In some ways, the physical capital boom surrounding AI puts me in mind of a rhetorical question I remember hearing about the California gold rush in the mid-1800s: During the California gold rush, which group got richer: the gold miners, or the people who sold picks and shovels to the gold miners? Many of the gold miners were unsuccessful, so the average gain for a gold miner wasn’t all that high. But every gold miner, successful or not, needed to buy the tools. Right now, the stock market prices of AI software companies are sky-high. But some of those companies are likely to become unsuccessful goldminers–who nonetheless had to pay the costs for the physical investment in the new technologies.
Economists and policy-makers know, in a broad sense, how to respond to a negative shock to aggregate demand in an economy, like the financial meltdown leading to the Great Recession of 2007-09. The financial crisis shrinks demand in the economy, recession hits, and unemployment rises. The government can play a role in softening and shortening the recession through expansionary fiscal policy (spending increases and tax cuts) or monetary policy (lower interest rates). To be clear, this policy recipe is not about building robust long-term economic health, which would require thinking about education and job training, incentives for capital investment, research and development of new technology, and balancing the benefits and costs of regulation. But softening and shortening the immediate blow of recessions is a worthwhile objective.
But when the shocks that hit the economy are about about aggregate supply, like the pandemic recession, the policy prescriptions based on responding to demand shocks don’t apply as well. The key difference is that with a negative shock to aggregate demand, inflation is naturally tamped down, so when the government acts to stimulate the economy, there is little risk of inflation taking off. But in a negative shock to aggregate supply, unemployment rises and prices also start rising. Thus, if the government stimulates the economy, it can reduce immediate hardship, but at risk of driving inflation higher. Thus, there’s no inflationary pressure after the Great Recession, but there certainly was after the pandemic recession.
In addition, they add a complicating factor, what Michael Kremer (Nobel ’19) called the O-ring theory of development. After the space shuttle Challenger broke apart after liftoff in 1986, the study of what caused the crash focused on the O-rings, a rubber gasket used to seal a connection between two pipes. Apparently the rubber gasket became brittle when unusually cold, but this feature was not well-known at the time. The key insight of the O-ring theory of development is that the performance of a complex piece of machinery can be limited by the weakest component–even when everything else is going just fine. The pandemic revealed various O-rings in the US economy, like the cargo ships sitting offshore and waiting to offload. The authors write:
One weak link can reduce or destroy the value of everything else. That multiplicative structure is what makes today’s economy so exposed to supply shocks: as products became more complex, a generation of globalization built long supply chains, and a problematic input at one stage—a chip, a mineral, a precursor chemical—can shut down production far beyond it. These supply shocks behave quite differently from the textbook demand cycle. Their effects develop slowly, propagate through supply chains in waves—delivery delays, then input shortages, then margin compression, then price pass-through—and unwind with long and uneven lags. … What distinguishes the new era is thus not necessarily the blast radius of any single shock, but instead their frequency and overlap. Disruptions (especially in energy) may tend to have smaller effects than those of their historical counterparts, but they arrive more often and, increasingly, on top of one another.
To put it another way, the prevailing gestalt a few decades back was that truly important supply shocks were relatively rare. The modern a parade of supply shocks coming thick and fast in a more interconnected global economy–where some of the interconnections impose O-ring constraints and costs.
Orszag, Nostrand, Barbieri, and McDermott also emphasize that many of these O-ring constraints are physical or geographic: shortages of key components, the capacity of ports, an underwater seabed cable severed, a chokepoint for the passage of shipping, a country with most of the world’s capacity to refine rare earth materials (China) or producing the highest-end computer chips (Taiwan), or even tanks and planes crossing a border. A string of six major supply-side disruptions in six years, at times interrelated and reinforcing each other, starts to look less like “bad luck” and more like “the way things are going to be.” The authors argue that economists and economics are being pushed into a world where we need to think as “geopolitical supply-siders,” attuned to the prevalence of supply-side shocks and how they propagate through an economy.
The Medicaid program spends close to $1 trillion annually, with about 65% of that coming fom the federal government and the rest from state governnments. This is almost, but not quite, one-in-five dollars of total US health care spending. Medicaid is not quite as big as Medicare, which is about $1.2 trillion per year, but Medicaid alone is almost one-in-five dollars of total US health care spending. James Hamlette and Karen Kopecky offer a check check-in on the Medicaid program in “Who’s Driving Medicaid’s Enrollment Growth?” (Economic Commentary: Federal Reserve Bank of Cleveland, October 13, 2026). As they write about Medicaid:
[I]t finances primary and acute medical care and long-term care for eligible low-income individuals. The criteria for eligibility have changed over time, and today, eligible populations span a wide range, including children, pregnant women, low-income elderly and disabled individuals, and working adults in low-wage jobs. The program is jointly administered and funded at federal and state levels. It requires states to provide specific benefits—including inpatient and outpatient hospital services, physician services, nursing home services, mental health services, and preventative care for children—with the option to cover additional services such as prescription drugs, home- and community-based services, and dental care. Healthcare services have grown over time as a proportion of US consumption spending and gross domestic product, and Medicaid outlays per capita have reflected this trend (Congressional Research Service, 2026), increasing steadily in recent decades and reaching four times their 1990 level in 2024.
As the authors emphasize, the main driver behind Medicaid spending growth is that many more people are enrolled in the program. In 1990, about 10% of all Americans were in Medicaid: now, it’s approaching 30%. Indeed, average spending per person in Medicaid–adjusted for the overall rate of inflation–has barely budged since 1990.
Hamlette and Kopecky dig into the Medicaid enrollment details and show: “The main drivers of this coverage expansion have changed over time. Prior to 2000, enrollment growth was driven by an increase in coverage of children and their families. From 2000 to 2013, enrollment growth was driven by an increase in coverage of childless nondisabled and disabled adults,2 with similar increases in the number of working and nonworking adults on Medicaid. Since 2014, the Affordable Care Act (ACA) Medicaid expansion has driven growth, with expansion states extending coverage to adults earning up to 138 percent of the federal poverty level, and enrollment growth during this period has been driven primarily by working adults.”
But in thinking about Medicaid, it’s important to remember that different groups can have very different health care expenses. For example, the disabled and the elderly together are 17.3% of the Medicaid population. but just over half of all Medicaid spending.
The main current proposals for holding down Medicaid costs seem to involve requiring that Medicaid recipients work. But given that Medicaid spending on non-disabled, non-elderly adults is only about 15.8% of the total–and many of them are already working–the cost savings from this approach are likely to be limited. A more productive approach might be to dig into how different states have designed their Medicaid program. Mark Shepard and Jacob Wallace dig into these issues in “Understanding Medicaid Managed Care: The Procured Competition Model” in the Spring 2026 issue of the Journal of Economic Perspectives(where I work as Managing Editor). As they note in their abstract, they “discuss the key policy levers across procurement, competition, and consumer choice in this model. Throughout, we highlight open research questions, arguing that the enormous variation in how states design these programs—combined with limited evidence on what works—represents a promising area for high-impact scholarship.”
Global population is expected to keep rising for the next 50-60 years, because it will take awhile for the demographic force of declining birthrates to overcome the life expectancies. In addition, the world still has lots of very poor people: for example, about 800 million people around the world live below the World Bank extreme poverty line of $3/day, and of course hundreds of millions more are not far above that line. With a rising world population, and one where we hope the standard of living for the poorest will be rising, more food production will be needed. So how is the world doing in this area?
Growth in total agricultural output can come from several sources: more land, more irrigation, more intensive use of inputs (labor, materials, and capital), and increased productivity given the same amounts of land, irrigation, and inputs (say, from improved farming practices, better weather information, improved seeds, and so on). To do these calculations, gains in agricultural output that cannot be attributed to measurable factors like land, irrigation, and inputs are then ascribed to productivity gains.
In the 1960s, most growth of agriculture came from more intensive use of inputs. By the 1990s and early 2000s, most of the growth of agricultural output was coming from producitvity gains, with very little coming from land expansion or additional inputs. But since about 2011, growth of agricultural output has slumped. Productivity gains are way down, although expansion of land and inputs have made up some of the difference. In a nutshell, this is global challenge of finding ecologically-sound ways of increasing agricultural output.
Of course, these factors vary by region. But even in the areas with relatively rapid growth in agricultural output, that growth is being driven by additional inputs (like South Asia) or by additional land (sub-Saharan Africa).
The particular focus of this year’s GAP report is on “regenerative agriculture,” defined as “a set of contextually appropriate farming and management practices and tools oriented toward improving soil and ecosystem health as a primary goal, with enhanced biodiversity, watershed function, and resilience as downstream benefits. Which practices qualify depends on local soil, climate, and production system conditions. This definition aligns practices, principles, and outcomes, centering ecosystem health as the mechanism through which broader gains are achieved.” In my own mind, this focus starts from the hard fact that additional inputs and land are driving growth of total agricultural output, recognizes that expanding agriculture to marginal and heavily fertilized land will have environmental tradeoffs, and then uses this lens to think about productivity gains that could minimize these environmental consequences. The possibilities in this area seem real, but the report is forthright in noting:
Regenerative agriculture (RA) has drawn growing attention, in part because its practices target the input use and natural capital depletion that the current output growth model largely depends on. Yet the potential contribution of RA practices to TFP [total factor productivity] growth has, thus far, only been a conceptual claim rather than an empirical finding. No study in the current literature directly measures changes in TFP growth attributable to RA.
