When I was growing up, the only white-collar worker on either my father’s or mother’s side of our family was my Uncle Malcolm, husband of my mom’s older sister. He worked in the New Orleans office of the Maryland Casualty Company. I never quite knew just what Uncle Malcolm did, but because each day he wore to work a coat and tie, I was aware that his job differed greatly from those held by all the other men in my family, including my pipefitter father.

Sometime in the early 1970s, when I was 12 or 13 years old, amazing news swept through my family: Uncle Malcolm was going to fly to a business meeting in Baltimore. I’d never known anyone who flew commercially, so this development struck me as stupendous. And stupendous it was.

To see Uncle Malcolm off from the airport on his exotic journey were my parents, my three siblings and me, my maternal grandparents, and my Uncle Eddie with his wife and two daughters. An entire clan gathered at the airport just to watch Uncle Malcolm board the plane. (This was long before non-passengers were prohibited from going through security.)

I remember it well. It was a nighttime flight. I stood at the airport-terminal window looking out at the nose of the big jetliner that Uncle Malcolm had just boarded, envying him for doing something that I’d never done and had no reason to think that I would ever do. Standing next to me, gazing at the plane, was my Uncle Eddie. 

“I hope,” I told him without much real hope, “that one day I’ll get to fly in an airplane.”

“I bet you will one day,” Uncle Eddie replied kindly, although with how much sincerity I cannot say.

My First Flight

My dream came true early one morning in July of 1977 when two friends and I flew — each for the first time in our lives — from New Orleans to Washington, DC. We saved furiously for this vacation. I still remember that I was more excited about the prospect of actually flying in an airplane than about the time that my buddies and I were to spend in DC and, later in the trip, New York City. (Fun fact: We were in Manhattan for the 1977 blackout – a story for another day.)

Of course, we could afford only coach-class seats on our Delta Airlines 727 jet. But these seats were quite nice, and not only because we got to check our luggage for free. As soon as the plane reached cruising altitude, one of the stewardesses (as they were then called) came through with full meals for us. She draped a pristine and pressed white cloth across each of our tray tables before setting before each of us a large, delicious, three-course hot breakfast. She then offered us, without charge, mimosas. I’m still proud of — and not a little surprised by — the 19-year-old me for refraining from imbibing so early in the morning.

Even coach-class commercial aviation back then was pricey, but it was also — by today’s standards — luxurious. That luxury, alas, was testimony to the failure of government regulation of commercial aviation.

Regulating, then Deregulating, Commercial Aviation

Prior to deregulation that began in the late 1970s, interstate commercial air travel was governed by the 1938 Civil Aeronautics Act. With that legislation, the federal government restricted entry into the industry. It also established and assigned interstate routes, and regulated the fares that airlines charged passengers for seats on planes that flew those routes. This regulation was meant to ensure airline profitability and, thus, aimed to restrict competition among the airlines. On interstate routes, airlines could not compete for customers by lowering prices, which were set by the Civil Aeronautics Authority, later to become the Civil Aeronautics Board (CAB).

The airlines in the mid-20th century did indeed profit from the government’s regulatory efforts on their behalf. Nevertheless, even the government cannot prevent competition; its interventions can only divert competition into other channels that are less beneficial for consumers.

Unable to compete by lowering fares, airlines competed on the customer-service front. Compared to today, the standard coach seat during the era of regulation had more legroom. Full meals were common. As opposed to today’s use of the hub-and-spoke system, direct flights were the norm. (Although this costly feature was required by the regulators, it likely would have been commonplace even without being mandated.) And flight attendants were overwhelmingly young and attractive single women. Forced to pay high prices to fly, at least customers got something in return for the additional dollars the regulators obliged them to fork over for the privilege of flying.

Deregulation of fares allowed market experimentation to discover how better to serve airline passengers. Airfares fell dramatically, which seems necessarily to be an obvious benefit for consumers. But we know this fall in airfares to be a benefit to consumers only because it happened in a more-competitive market. Obviously, consumers would love to pay the lower fares while still having more legroom, more direct flights, and full meals with free booze in coach class served by attractive and charming flight attendants.

Competition Takes Place on Many Different Margins

These nice amenities aren’t free, however. They must be paid for. If the flying public had valued those regulation-era amenities enough to continue paying regulation-era airfares, airlines would have been happy to continue to supply those amenities at those high fares. But the public spoke with its purse: competition revealed that most air passengers prefer to pay lower prices, even if doing so means fewer amenities, than to pay higher prices in exchange for the many amenities. (The relatively few customers with different preferences choose to upgrade to seats in ‘economy plus’ or in first class.)

Flying today is much less costly, in real terms, than it was before airlines were deregulated. (And, by the way, deregulation did nothing to slow the improvement in airline safety.) As such, the commercial-aviation experience today — unlike when I was a boy and young man — is commonplace and hardly luxurious (adjusting for the reality that, nevertheless, when in an airplane you are flying through the air while seated in a chair, an experience that everyone before the twentieth century would have regarded as miraculous). Even for a working-class American family today, going to the airport simply to behold a relative boarding an airplane is as unimaginable as going to a local bus stop simply to behold that same relative boarding a bus.

Too Few Consumers Felt the Discount Spirit

It’s worth noting that competition also reveals the limits to consumers’ tolerance for sacrificing amenities for lower fares. Spirit Airlines’ business model was to eliminate as many as possible ‘free’ amenities, stripping the base ticket price down and charging separately for virtually everything else, including carry-on bags, seat selection, snacks, even water. Spirit also offered infamously little legroom.

Because ‘optimal’ market outcomes cannot be divined in the abstract — because these outcomes can only be discovered through competitive market processes in which entrepreneurs are free to experiment — it was a good idea to run this experiment. As it happens, though, too few consumers were willing to pay even low fares for that level of minimal amenities. Spirit was on the verge of bankruptcy well before the price of aviation fuel was sent soaring by the war in Iran, which is why JetBlue in 2022 offered to merge with Spirit – a move that would have enabled JetBlue to obtain Spirit’s equipment and landing slots.

In a monumental feat of economic ignorance, the Biden administration sued to block the merger on the grounds that it would reduce competition and raise fares. Spirit has now gone forever to the economic spirit world.

Bird’s Eye View

Here’s the view from 30,000 feet. When producers are allowed to compete on all margins, including price, they discover the optimal mix of prices and amenities that best satisfy their customers. When governments obstruct that competition, it gets redirected into changing the quality of goods and services such that the resulting price-quality mixes are less desirable than would be the mixes that emerge without government intervention.

After airlines were deregulated almost 50 years ago, consumers revealed that they wanted lower prices with less quality. And by more recently rejecting the bare service offered by Spirit Airlines, consumers revealed that quality can be so low that even very low prices are insufficient compensation to put up with such low quality. These results emerged from competitive market processes and deserve respect. But alas, just as airline regulation forced American air passengers to buy what they would have preferred not to buy, the government’s continuing itch to override market processes will oblige consumers in the future — whenever such interventions occur — to suffer worse economic outcomes.

Even great economists can make poor or incomplete arguments. George Stigler, a titan of the Chicago school alongside luminaries like Milton Friedman, Gary Becker, and half a dozen other Nobel Laureates, wrote an essay about what he saw as a surprising inconsistency in Adam Smith’s Wealth of Nations.

His article, “Smith’s Travels on the Ship of State,” makes the case that “The Wealth of Nations is a stupendous palace erected upon the granite of self-interest.” This seems uncontroversial, given Smith’s famous description of how the market harnesses self-interest to benefit society. People are “led by an invisible hand” to benefit their fellow man, even without plannning to. 

Indeed, markets create order through the signals and incentives created by prices, profit, and loss. Stigler praises Smith for his clear-eyed analysis of self-interested behavior in the market. Smith undeniably cast politicians, rulers, and the ‘man of system’ as self-interested actors.

Besides the profit-seeking of the butcher, the brewer, and the baker through voluntary exchange, Smith also recognized that business could (and would) seek profit through government protection, government subsidies, and government regulations. Smith famously said: “People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the publick, or in some contrivance to raise prices.”

Smith warned that governments tend to play a hand in this political profit-seeking – sometimes unintentionally. For example: 

A regulation which obliges all those of the same trade in a particular town to enter their names and places of abode in a publick register, facilitates such assemblies. It connects individuals who might never otherwise be known to one another, and gives every man of the trade a direction where to find every other man of it.

But, Professor Stigler argues, Smith did not apply the assumption of self-interested behavior consistently: “Smith gave a larger role to emotion, prejudice, and ignorance in political life than he ever allowed in ordinary economic affairs.” Smith’s vision becomes clouded when he analyzes political actors and behaviors. And that’s a symptom of a deeper malady in Smith – his failure to rigorously and consistently apply self-interest in all human behavior:

“It is in the political arena that Smith implicitly locates the most numerous and consistent failures of self-interest in guiding people’s behavior, but this is not the only place where self-interest fails….Every failure of a person to make decisions which serve his self-interest may be interpreted as an error in logic: means have been chosen which are inappropriate to the person’s ends.”

Stigler argued there was no meaningful distinction between market behavior and political behavior: “no clear distinction can be drawn between commercial and political undertakings: the procuring of favorable legislation is a commercial undertaking.” This sounds similar to “Politics Without Romance,” in which James Buchanan argues for “symmetric” assumptions about people in politics and people in markets. We should not assume that people become more altruistic or less self-interested when they engage in political activity. But Buchanan makes this point:

“The public choice theorist should, of course, acknowledge that the strength and predictive power of the strict economic model of behaviour is somewhat mitigated as the shift is made from private market to collective choice. Persons in political roles may, indeed, act to a degree in terms of what they consider to be the general interest. Such acknowledgment does not, however, in any way imply that the basic explanatory model loses all of its predictive potential, or that ordinary incentives no longer matter.”

Such a point seems straightforward and modest, yet Stigler sees the world differently. Stigler contends that because political actors thrive on self-interest, exhorting them to altruism is a futile exercise. After all, one could not really lower the price of eggs by encouraging egg producers to lower their prices. Why bother asking politicians to ignore their constituents, snub their friends, or abandon the pet projects that secure their power?

“Why tell the sovereign that free trade is desirable, if one has no method of disarming the merchants and manufacturers who have obtained the protectionist measures….Why believe that better turnpikes await only the appointments of a better class of commissioners?”

And Stigler has a point. The experience of politics is not pretty. Public Choice economics elaborates the theory of special interests and collective action, and documents why political activity is best explained by self-interested behavior. When Smith encourages the sovereign to act in principled, rather than self-aggrandizing, ways, Stigler understandably asks, “how now Professor Smith?”

Smith was optimistic about the force of self-interested behavior leading to social benefit, and also correcting miscalculations and errors, because of competition given the incentives of profit and loss and the signals transmitted by prices. There’s a whole literature about the efficiency and inefficiency of political markets. Bryan Caplan’s Myth of the Rational Voter and Donald Wittman’s The Myth of Democratic Failure are two prime examples along with the public choice literature.

Hayek, however, claims that “the facts of the social sciences are what people think and feel.” So, is it possible to change what people find to be in their self-interest? I’m not referring to changing the material payoffs or benefits they receive, say through greater monetary or physical penalties, but to their valuing states of the world differently. In a famous article written with another Nobel Laureate (Gary Becker), Stigler rules such a question out of bounds for economists. After all, with tastes there is no arguing.

But there is an obvious distinction between politics and commercial arenas: prices! For our purposes, we don’t need to determine how efficient or inefficient political signals and competition are to recognize it does not have a market price system. Therefore, we should be more cautious about assuming that self-interested behavior will operate as efficiently and effectively as it does in private markets.

Stigler and Becker flatten the landscape of human motivation, treating our inner drives as static one-dimensional data points. While analytically clean, this approach eviscerates the complexity of human beings. This is not what Smith would (or did) do.

As a moral philosopher, Smith believed that people (whether in markets or in government) can and should be reasoned with. Our morals form through social interaction, and those morals then shape our behavior. Smith famously criticized Mandeville’s assertion that all human action is, by definition, self-interested and therefore inherently self-oriented and vice-ridden.

Smith correctly points out that the moral weight of our decisions does not rest on the existence of the self, but on what the self takes an interest in. And presumably human beings can choose their interests. Smith reasons accordingly, even if it seems like he fails to apply a narrow self-interest lens at times. But let me tell you from personal experience, not all commissioners are made equal. Smith would encourage us to exhort public officials to do well and hold their feet to the fire when necessary.

The legal foundation for taxing every import into the US has now rested, at various points in the past year, on a 1977 emergency powers law, a 1974 statute designed for a monetary system that no longer exists, and — if the administration’s next move is what trade lawyers expect — a Depression-era provision that has never once been used to impose actual tariffs in almost a century. At some point, running out of legal justifications is a signal worth heeding.

In February, the Supreme Court ruled that President Trump’s sweeping IEEPA tariffs were unlawful. The Court’s rebuke was clear: Congress had not clearly delegated that kind of sweeping tariff power to the executive branch, and the President “enjoys no inherent authority to impose tariffs during peacetime.”

Before the ink was even dry on that opinion, the White House signed Proclamation No. 11012 and imposed a new 10-percent tariff on basically every imported good. This time, the administration cited Section 122 of the Trade Act of 1974 and the so-called “balance-of-payments authority.”

In a 2–1 decision, the Court of International Trade struck that one down, too.

Section 122 and the Next Legal Fight

Section 122 of the Trade Act of 1974 was written for a monetary world that no longer exists. Prior to this statute, several foreign currencies were pegged to the dollar, and the dollar was, in turn, pegged to gold at $35 per ounce. This changed in 1971 when President Nixon severed the dollar’s link to gold and, in turn, hit the world with a 10 percent surcharge on imports. Congress, watching all of this happen in real time, wanted to give the president a narrow, carefully-defined emergency power to impose temporary tariffs when the US faced specific, identifiable, and measurable monetary crises.

The statute authorizes the President to act to deal with “larger and serious United States balance-of-payments deficits.” This phrase had a precise, technical meaning. Economists measured the balance of payments using three specific metrics: the liquidity balance, the official settlements balance, and the basic balance. Without going into too much detail, these tools were designed to track whether the US had enough gold and reserves given the dollar’s fixed exchange rate.

With a floating exchange rate system and fiat money, however, these measures are all but obsolete. The Bureau of Economic Analysis stopped reporting them in 1976, just two years after the Trade Act of 1974 (and with it, Section 122) was enacted.

Gleaning from the court’s ruling, the Trump administration argued that the “balance-of-payments deficit” is a living concept that should be updated for modern conditions. Today, they said, the correct measure is the current account deficit.

Courts Question the President’s Premise

The Court of International Trade was not convinced by this argument. The court reasoned that Congress used specific words that had specific meaning in 1974, and that their job is to interpret what those words meant when they were written, not to update their meaning in light of the world today. As the court put it, “the ‘balance of payments’ as an accounting principle always nets to zero. 

To the extent that is the case, if the President has the ability to select among the sub-accounts to identify a balance-of-payments deficit, unless every sub-account is balanced, the President would always be able to identify a balance-of-payments deficit.” In footnote 33, they go further, saying, “Defendants argue that ‘the balance-of-payments current account [is] the only reasonable measure of a balance-of-payment deficit.’ This argument lacks support in either the statute’s text or legislative history. Defendants’ position is the President has discretion to identify any actionable deficit for purposes of Section 122(a)(1). But Section 122 would lack an intelligible principle if the President could simply identify any deficit account, or if the phrase ‘balance-of-payments deficits’ could change with context.”

In other words, the court pointed out that if it accepted the government’s premise, any President could always point to a “deficit” somewhere and, on that basis, justify tariffs. In a system with an unconstrained imagination, that is no real limit on presidential power. As we have seen in recent years, courts have been increasingly reluctant to accept broad, open-ended delegations of Article II authority to the executive.

Why Most Plaintiffs Lost

The court’s ruling issued a permanent injunction — essentially an order to “stop it” — but it applies only to the actual importers who brought suit, not to every plaintiff in the case. Specifically, the injunction covers the State of Washington, which imported goods through the University of Washington, a small New York spice company called Burlap and Barrel, and a Florida toy company called Basic Fun.

The other plaintiffs were dismissed for lack of standing because they could not show they directly paid the tariffs, only that they might face higher costs as downstream purchasers. The court found that too speculative. Those claims were dismissed without prejudice, however, meaning the plaintiffs are free to refile if they can later establish proper standing.

The Latest Legal Theory: Section 338

The game of whack-a-mole that we have seen vis-à-vis tariff policy is certainly not going to stop. The Section 232 tariffs on products such as steel and aluminum remain in place and could still be expanded or modified, and the administration has already begun the process of implementing Section 301 tariffs. But there is another tariff authority that could be used as well: Section 338 of the Tariff Act of 1930.

This section gives the President the authority to impose tariffs of up to 50 percent on imports from any country that “discriminates” against US commerce. Unlike IEEPA and Section 122, this is an unambiguous statute that allows the president to do so. The very first line of the section reads, “the President when he finds that the public interest will be served shall by proclamation specify and declare new or additional duties as hereinafter provided.”

This as-yet-unused authority has three features that make it the likely next step in the tariff saga. First, it allows for tariff rates up to 50 percent. This is already higher than most of the IEEPA tariff rates that were imposed before they were struck down. Second, it only requires that the President “finds as a fact” that a foreign country is discriminating against US commerce, with no mandatory investigation, no notice-and-comment period, and no notification to Congress required. Third, it allows the President to issue a total ban on imported goods from a country that does not relent in response.

Given all of this, the obvious question is “why didn’t the President use this authority to begin with?” There are a few potential reasons. First, any tariff rates announced are not allowed to be implemented for a period of at least thirty days after the proclamation is issued. While the president famously issued extensions, pauses, and delays in rolling out several of the tariffs he announced throughout 2025, this thirty-day period does mean that the authority granted here is not as immediate as the President may have liked.

Second, the statute assigns the US International Trade Commission with the duty to “ascertain and at all times to be informed whether any of the discriminations against the commerce of the United States…are practiced by any country; and… to bring the matter to the attention of the President, together with recommendations.” Because of this, it’s not clear that the President can act unilaterally and at his discretion or if he needs some pro forma report from e.g. the US Trade Commission before he can act. Could he, for example, raise tariffs on Switzerland because he didn’t like the way their former president talked to him without US Trade Representative Jamieson Greer recommending that he do so? It’s unclear.

Finally, sweeping tariffs of the sort that the administration seems to prefer are legally difficult under Section 338. The statute requires that the tariffs be country-specific and must be designed to “offset” any damages done. This makes it harder to implement broad, sweeping tariffs, though, as we saw last summer, the White House is perfectly able to use mail-merge to send letters to numerous countries announcing new tariff rates, perhaps obviating this concern.

Which Will Run Out First — Courts’ Patience, or the President’s Claims to Authority?

The problem the President is going to run into is that he has now tried and failed to claim open-ended tariff authority twice. It is clear that courts are reading congressional delegations very carefully and very narrowly. If the President tries to use a Depression-era statute designed to address discrimination to reconstruct the IEEPA tariffs, he will almost certainly face a very skeptical bench. If it looks like IEEPA, walks like IEEPA, and sounds like IEEPA, we shouldn’t be surprised if the court treats it like IEEPA.

A recent Wall Street Journal report on a workplace trend called “tokenmaxxing” offers a revealing glimpse into some of the confusion attending America’s AI boom.

Some companies, the Journal reports, are experimenting with measuring an employee’s engagement with AI by tracking “tokens”—the units into which the system converts text typed into prompts. Now, in some workplaces, it seems token consumption has become a badge of an AI user’s engagement, experimentation, or productivity.

This is a striking moment. During what often feels like a national celebration—or national heart attack—over the transformative productive potential of artificial intelligence, we are publicly debating if an employee’s value might be measured by the volume of text sent to and from a chatbot.

The controversy deserves more attention than its odd jargon suggests. It exposes a central uncertainty in the AI revolution: what, exactly, does productive use of AI mean?

Reporting in Built-In, Ellen Glover reports that tokenmaxxing “is taking much of the tech industry by storm… individuals are ranked on leaderboards based on how much they use AI, with generous perks and incentives encouraging them to push these tools to their limits… The assumption is that the more you use AI, the more productive you must be. Those who lean in the hardest will come out on top.”

She adds that some employees take advantage of the fact that now “systems use AI agents to work autonomously for hours on end, reviewing and editing large codebases and writing entire programs while their human users are out living their lives.”

Tokens are real enough. Large language models do not “read” language as humans do. They convert words, punctuation, fragments of words, and other text elements into tokens—standardized units processed mathematically. The more tokens used, generally, the more computing resources consumed. AI providers often charge by token volume. Tokens therefore matter to engineers, accountants, and software managers.

When tokens migrate from a technical unit used in billing into a measure of employee performance, however, we risk confusing the cost of computation with the creation of value.

Admittedly, that equation would not be new. Management history is full of attempts to measure what is easy to measure rather than what is important. There are blunt historic examples: the British government in Delhi put a bounty on dead cobras, enterprising Indians bred cobras to kill for the bounty. During the Vietnam War, strategy said the goal is “winning the hearts and minds of villagers,” but the “body count” became the actual metric. Closer to the topic at hand, IBM in the 1980s began to measure productivity by lines-of-code-written (“source lines of code” or SLOC). The example has become a classic in the field: the incentives favored programmers who wrote long, inefficient code to meet their quotas. A programmer who could nail a complex problem with five elegant lines of code was measured “unproductive.”

Now we seem to be testing the equation: prompts sent = value created.

The temptation is understandable. Measuring real productivity in knowledge work has always been difficult. If a machinist produces 50 precision parts in a shift and another produces 20, comparison is at least possible. But how does one compare two analysts, marketers, editors, researchers, lawyers, or managers?

One employee may produce fewer memos but better decisions. Another may write more pages but create confusion. One may solve a crisis with a ten-minute insight. Another may consume three days generating activity. In modern office work, the most valuable contributions are often invisible until later.

Artificial intelligence does not eliminate this problem and may indeed intensify it.

Suppose one employee uses AI constantly—drafting emails, summarizing calls, rewriting notes, brainstorming slogans, asking endless follow-up questions, generating presentation decks, and polishing language. Another uses AI sparingly but strategically—clarifying a difficult concept, checking a spreadsheet formula, testing objections to a proposal, accelerating a first draft, then applying judgment and revision. Tokenmaxxing makes the question sound rhetorical: Which employee is more productive? But the answer is not obvious.

Heavy AI usage can reflect creativity and initiative. It can also reflect confusion, dependency, indecision, poor training, performative busyness, or simple fascination with a new tool. Light AI usage can reflect resistance and stagnation. It can also reflect mastery, efficiency, and independent competence.

A few independent researchers, including the code-analysis site Jellyfish, have rushed to study the efficacy of tokenmaxxing. Their initial conclusions are limited but telling. In an April 15, 2026, article, Nicholas Arcoland, Ph.D., reported that “We analyzed 12,000 developers across 200 companies in Q1 of this year. What we found is that while more tokens do correlate with more output, they come at a dramatically higher price point per unit…

“At a high level, token usage varies wildly across developers.

“The typical user (50th percentile) consumes about 51 million tokens per month on AI coding. Meanwhile, the 90th percentile user consumes more than seven times that amount, at roughly 380 million tokens per month. A relatively small group of power users is driving a disproportionate share of total token consumption….

“What do you get for all those tokens?

“…higher token usage does lead to more output, but not proportionally. The cost per merged PR increases from just $0.28 in the lowest usage tier to $89.32 in the highest.

“More tokens means more output, but at a much higher price per unit.”

Metrics tend to have appeal because they relieve managers of judgment. A leaderboard of token usage appears objective; numbers can be ranked. Executives can announce measurable progress in AI adoption. Thus, the issue is made objective but apparent objectivity is not actual understanding.

Deep gains in productivity often are achieved not by doing more tasks faster, but doing the right tasks, avoiding the wrong tasks, framing problems correctly, and making better decisions. An AI system may generate five possible marketing campaigns in seconds. It still takes judgment to decide if any fit the brand, the market, the budget, or the moment. AI can summarize 10 reports. It still takes conceptual clarity to know what matters in them. AI can produce a polished memo. It still takes responsibility to decide whether or not the memo should be sent.

A 2025 McKinsey & Company report, “What Is Productivity,” pointed out that an astonishingly small group of firms contribute to the lion’s share of productivity growth (fewer than 100 out of 8,300 in three countries accounted for two-thirds during the period studied). They all made one or more of five strategic moves: 1. Scaling more productive business models or technologies. 2. Shifting regional and product portfolios toward the most productive businesses. 3. Reshaping customer value propositions to increase revenue and value added. 4. Building scale and network effects. 5. Transforming operations to raise labor efficiency and reduce external cost at scale.

Yes, broadly stated those achievements point to decisions at the executive level. At the same time, however, the rarity of success suggests a top-down emphasis by those executives on human agency: the capacity to choose goals, prioritize means, recognize context, exercise responsibility, and direct tools toward purposeful ends. They make the difference between activity and achievement. AI can assist agency, serve as its tool; but at least for now cannot replace the need for it.

And the consequences go well beyond the issue of tokenmaxxing. Much of the public rhetoric around AI assumes that productivity rises automatically as machine usage rises. Add more AI, and output climbs. Replace more workers, and efficiency follows.

History offers reasons for caution.

When spreadsheets became common, the best executives were not those who opened the most spreadsheets. When search engines arrived, the best researchers were not those who ran the most searches. When calculators spread, the best mathematicians were not those who pressed the most buttons. Because our tools amplify our ability when guided by ability.

So with AI. The worker who asks sharper questions, spots errors quickly, knows when to distrust outputs, understands the customer, grasps the larger objective, and accepts responsibility for results may create more value with modest AI use than another worker who generates oceans of machine text.

Thus companies adopting the token-use metric may be measuring the wrong thing in their very first phase of adopting AI. Better might be to ask harder questions: did project cycle times improve? Customer satisfaction rise? Revenue per employee increase?

Innovations such as tokenmaxxing to measure programmer productivity are the lifeblood of firms in a free economy, of course. This example deserves special scrutiny only as an indicator of strategies under consideration by the explosively growing, fiercely competitive, and internationally important AI sector.

Such innovations in a vibrant American market economy are tested by the standard of profitability, so tokenmaxxing ultimately will be measured by its competitive advantage in advancing the overall productivity of the U.S. economy. Here is the decisive advantage of the United States in the much-touted AI competition. In a recent article in The Daily Economy, I looked at the People’s Republic of China’s bid for international hegemony, including in AI. 

In the end, decisions about advancing AI are political in China. It is a warning to the United States to reckon the costs of yielding development of AI to regulations and dictates. The recent confrontation between Anthropic and the Pentagon over Anthropic’s “guardrails” for the use of AI goes to the heart of the issue.

It is the free-market economy that has delivered the incomparable progress of artificial intelligence, with all its protean potential. It is an advantage America cannot afford to squander. 

Socialists often criticize US trade restrictions on Cuba. A recent example is the flotilla organized by activists attempting to deliver aid to the island that aimed to draw attention to the embargo. Participants and commentators often frame Cuba’s poverty as a direct result of US policy: lift the embargo, the argument goes, and Cuba will prosper.

What should we make of this argument? For one, the primary driver of Cuba’s persistent poverty is the Cuban government’s own economic policies, including state control, chronic misallocation, and long-standing restrictions on private enterprise. These institutional mistakes would keep Cuba poor even without the embargo.

That said, there’s little doubt that trade barriers cause economic harm, and socialists are right to recognize this. But here one might wonder: can socialists coherently object to trade restrictions while also opposing free market capitalism more broadly?

Many think the answer is yes. The socialist target isn’t free exchange as such, but private ownership of productive property. Socialists object to an economy where capitalists own the means of production and workers sell their labor for wages or a salary. Socialism, by contrast, would create a kind of “workplace democracy,” where firms are owned and operated by workers themselves. They’d collectively make decisions about production, investment, and distribution rather than take orders from a single boss. This could mean workers directly voting on major business decisions or periodically electing managers to act on their behalf. Suppose, for example, that a worker-owned pizzeria is deciding whether to shift from traditional pizza to a more upscale artisanal menu. In a traditional capitalist firm, the owner would have the final say. In workplace democracy, the cooks, servers, and other employees would collectively decide how to proceed. While there might be some conflicts between growth and equality, writes Mike Beggs at Jacobin, such a model would aim to “harmonize firm-level democracy with macroeconomic expansion and a solidaristic wage.”

Under this style of socialism, markets would still play an important role. Central planners wouldn’t decide how to allocate resources to the pizzeria or determine how many pizzas it has to bake. Instead, the pizzeria would compete with rival restaurants for customers just as it would under capitalism. The goal is to retain the information markets provide in the form of prices, profits, and losses while “socializing” ownership of firms.

At first glance, it seems as though this version of socialism is perfectly compatible with free trade. You could have an economy in which firms are democratically owned and still allow free trade both within and across borders.

That’s fine as far as it goes. But there’s a tension lurking in the background. Consider that a central justification for free trade is that it enables all parties to voluntarily enter into an economic agreement in the expectation of mutual benefit. As Adam Smith puts the point:

Whoever offers to another a bargain of any kind, proposes to do this. Give me that which I want, and you shall have this which you want, is the meaning of every such offer; and it is in this manner that we obtain from one another the far greater part of those good offices which we stand in need of.

If I want the apples you have, and you want the oranges I have, we’re both better off as a result of a trade. Trade barriers — tariffs, quotas, embargoes, and the like — block these sorts of exchanges. That’s why critics of the Cuba embargo argue that it makes people worse off: it prevents them from engaging in mutually beneficial exchange, which an abundance of research shows is a source of human prosperity.

Once you see trade in this light, it becomes harder to draw a bright line between the kinds of exchanges socialists want to allow and the kinds they want to prohibit. As I mentioned earlier, to qualify as socialist, an economy must not permit capitalists to own the means of production and hire wage laborers. This means that a socialist economy must prohibit freely agreed-upon, mutually beneficial capitalist labor agreements. For instance, suppose Barry doesn’t want to take on the risks and responsibilities that come with being a co-owner of a coffee shop; he’d rather work for a steady wage as a barista for a corporate giant. Nevertheless, a socialist economy wouldn’t allow him to do so. (Otherwise, it would start drifting toward capitalism.)

It’s not clear why trading barista labor for money is all that different from trading apples for oranges. In both cases, people are making voluntary agreements in the expectation that they’ll be better off as a result. Here, then, is the tension. On the one hand, socialists criticize trade restrictions on the grounds that they block mutually beneficial exchange and thereby make people worse off. On the other hand, they want to restrict or eliminate capitalist employment of wage laborers — even when workers voluntarily choose those arrangements.

So something has to give. You can’t easily say, “Let people trade as they see fit because they expect it to benefit them,” while also saying, “But don’t let them sell their labor as they see fit, even when they expect it to benefit them.” 

If mutual benefit justifies freely trading apples for oranges, it’s hard to see why it doesn’t also justify freely trading labor for wages. And if workers may trade their labor freely, they may trade it to capitalists — a conclusion that socialist defenders of free trade are sure to find unwelcome.

Headline inflation cooled in April, but not enough to give the Federal Reserve much comfort. The Consumer Price Index rose 0.6 percent last month, down from March’s 0.9 percent increase. Yet the year-over-year rate moved in the wrong direction, rising to 3.8 percent from 3.3 percent and extending the reversal of the disinflationary trend that had prevailed earlier this year.

Core inflation told a less encouraging story. Excluding volatile food and energy prices, CPI rose 0.4 percent in April, double the 0.2 percent pace recorded in each of the prior two months. The year-over-year core rate also ticked up, rising to 2.8 percent from 2.6 percent.

The moderation in headline CPI mainly reflected slower energy price growth. Energy prices rose 3.8 percent in April, well below March’s 10.9 percent surge, while gasoline prices climbed 5.4 percent after jumping 21.2 percent in March. Even so, gasoline prices are up 28.4 percent over the past year, reflecting the cumulative effect of the oil shock tied to the conflict involving Iran and disruptions to shipping through the Strait of Hormuz.

But the April report was not simply an energy story. Shelter, which accounts for about one-third of the CPI, rose 0.6 percent after increasing 0.3 percent in March, although the increase is likely due to mismeasurement stemming from last fall’s government shutdown. Food prices rose 0.5 percent, with grocery prices up 0.7 percent. Several core categories also posted sizable increases: household furnishings and operations rose 0.7 percent, airline fares jumped 2.8 percent, personal care rose 0.7 percent, and apparel increased 0.6 percent. New vehicle prices, communication prices, and medical care moved lower, but not by enough to offset the broader firming elsewhere.

The three-month trend is the clearest sign that price pressures have strengthened. From February through April, headline CPI averaged 0.6 percent per month, equivalent to roughly a 7.4 percent annual rate. That figure is distorted by March’s energy spike, but core inflation points in the same direction without the energy noise. Core prices averaged roughly 0.27 percent per month over the same period, or about 3.2 percent annualized, above the 2.8 percent year-over-year core rate.

The Federal Reserve officially targets the personal consumption expenditures price index, not CPI. But the April CPI report still gives policymakers little reason to consider easing. Inflation remains above target, core inflation has picked up, and the recent monthly data look worse than the year-over-year figures suggest. Markets agree: the CME Group’s FedWatch tool shows futures pricing in an almost certain hold at the Fed’s June meeting and little expectation of a rate cut this year.

The labor market does not provide much of an offsetting argument. April payrolls rose 115,000, and the unemployment rate held steady at 4.3 percent. Average hourly earnings rose 0.2 percent in April and 3.6 percent over the past year. That is not an overheated labor market, but neither is it one showing enough weakness to justify rate cuts in the face of firmer inflation.

Following the April FOMC meeting, Chair Powell described an economy “expanding at a solid pace,” with a labor market that had changed little and inflation that remained elevated. The latest data support that characterization. Powell also pointed to tariffs and oil-driven energy costs as important sources of above-target inflation. The April CPI report complicates that diagnosis. Energy clearly mattered for headline inflation, but the acceleration in core prices, the pickup in shelter, and the breadth of monthly gains suggest price pressures are not confined to oil or tariffs. Additionally, the latest Producer Price Index out today, a leading indicator for future consumer price rises, points to hotter inflationary pressures on the horizon.

That matters for policy. If inflation were only the result of a temporary energy shock, the Fed could look through some of the increase. But when core inflation accelerates and shelter costs pick back up, easing becomes much harder to justify. Rate cuts would do little to produce more oil or clear shipping lanes, but they could add demand to an economy where inflation is already running too hot. 

The Fed should not overreact to one CPI report. But it should not ignore the signal either. Headline inflation remains elevated, core momentum has firmed, and the labor market is not weak enough to call for easier policy. The case for cutting rates is extremely weak. The Fed should hold.

Immigration to the United States is a complex and thorny topic. Setting aside the impact of immigration on American culture and politics, as well as the balance of taxes and spending, this AIER explainer looks at the economics of immigration, both legal and illegal.

To understand the economic effects of immigration, we need to understand the motivations for immigrants to come to the US, particularly the economic incentives. Various economic models can be used to analyze which types of immigrants countries like the US tend to attract and what impacts they have. While no single model provides a complete picture, together they offer a more comprehensive understanding of the economic effects of immigration.

Labor as a Factor of Production

Factor Complementarity

The simplest way to think about immigration is as an increase in the labor supply. Labor is a factor of production, that is, a general type of input into the production process. Other factors of production may include land, capital, natural resources, and entrepreneurship. Technology is usually not considered a factor of production. Instead, technology is thought of as those ideas, processes, and techniques that make all factors of production more productive.

Entrepreneurs hire labor to make and do things. Without labor, entrepreneurship, capital, land, and the like are not productive. By the same token, without capital, land, and labor are not productive. This feature of factors of production is called factor complementarity: the more other factors a given factor can interact with and supplement, the more productive it is. Each hour of labor is more productive when it can use more capital (machines, entrepreneurship).

What entrepreneurs pay owners of labor (workers) in exchange for their services is called a wage. Wages are the price of labor (and human capital). The price of capital is usually called the interest rate, the price of entrepreneurship is economic profit, and the price of land is land rent.

Workers want to go where the wage is highest. If they can make more money in another industry or another location, they have a clear incentive to switch industries or locations. By balancing labor supply and demand, this constant switching in the economy drives long-run wage differences between industries and locations toward zero.

Thinking of immigrants and other workers as mere quantities of labor risks oversimplification, however. Like other workers, immigrants bring their distinct talents and interests into the labor market, learn on the job, and create new ways of doing things. Even unskilled workers have different levels and types of specialized knowledge that keep them from being perfectly interchangeable. Workers can also be capitalists: investors or entrepreneurs. By one estimate, immigrants in the US start businesses at 1.8 times the rate of natives. Illegal and legal immigrants have different outside options and therefore different levels of bargaining power with their employers.

In all these ways immigrants and workers are much more complex than mere quantities of labor, but to understand an economic phenomenon, we often have to start with a simple model before adding complexities.

Mobility and Specific Factors

Labor is mobile across industries and, if regulations allow it, across locations in the long run.

But how long is the long run? If we exclude human capital from the definition of “labor” and consider “labor” to refer only to raw, manual labor power, then labor moves quickly and readily across industries and, if allowed, locations. The skills required for picking crops, cleaning rooms, preparing fast food, mowing lawns, and such can be easily learned, and so workers can move easily among these jobs. We shouldn’t expect wages for these jobs to be very different. If demand for cleaning rooms rises, causing cleaners’ wages to rise, workers should move from fast food into cleaning, causing wages to fall back for cleaners and rise for fast food workers, until they are roughly equal and there is no longer any incentive to switch jobs.

But human capital is much more occupation- and industry-specific. It is difficult to apply the skills of a physician to the job of computer programming. The wage return to human capital should equilibrate only slowly across industries. Nevertheless, the same processes still do work, even if over a generation or two. If the demand for computer programming falls because of AI, for example, we should expect programmers’ wages to fall, while everyone else benefits from cheaper, better software. Programmers themselves will look for work in careers where the skills they’ve developed will be of some use, but the effect is even stronger on the upcoming generation. Fewer students will strive to learn programming skills; instead, more are likely to apply themselves to medicine, law, or finance, assuming wages in those fields remain high. As more new workers flood these fields instead of programming, the wages for computer programmers will gradually recover to attract the people needed to perform tasks that cannot be automated, while the wages for physicians, attorneys, and finance workers will fall, until the wages across these higher-skilled industries are roughly equal and there is little financial incentive for students to develop one set of skills rather than another.

In a dynamic economy, equilibrium is never actually reached. But the theoretical equilibrium does work like a kind of gravitational force, drawing workers away from where they are least needed and toward where they are most needed.

Labor mobility across locations is very observable where it’s allowed. In the United States there are ordinarily no restrictions on moving from place to place. As a result, we should expect wages for the same skill level in different places to be roughly equal unless some places are nicer than others to live in, that is, have different amenities.

US evidence suggests that total real compensation (price-adjusted wages plus amenities) does tend to equalize across locations, for a given skill level, when fully open immigration is allowed.^[1] In 2000, the places with the lowest real wages in the US were places like Santa Cruz, Honolulu, San Francisco, Santa Barbara, San Jose, rural Hawaii, and Jacksonville, North Carolina (Chen and Rosenthal, 2008). San Diego, Cape Cod, rural Montana, and rural Vermont were also near the bottom. Presumably, these are the nicest places in the country to live in: workers were willing to accept lower wages to be there. Among the highest-earning geographies were Kokomo, Indiana; Wilmington, Delaware; Flint, Michigan; Waterbury, Connecticut; Detroit; Trenton; Philadelphia; and Hartford, Connecticut. Houston, Newark, and Baltimore were also high on this list. These are, apparently, the least nice places in the country to live in: workers had to have high wages (relative to rents) to live there.^[2]

Still, we must remember that wages, like other prices, coordinate countless bits of information in the heads of employers and workers, relating to tastes, opportunities, and other circumstances. These circumstances and consumer tastes are constantly in flux, and therefore wages never reach a static equilibrium.

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The Heckscher-Ohlin and Stolper-Samuelson Theorems

The Heckscher-Ohlin and Stolper-Samuelson Theorems help explain how immigration affects the United States economy, which is an advanced country rich in physical and human capital. These theorems are usually used to explain the effects of foreign trade, but their logic applies equally well to immigration.

The Heckscher-Ohlin Theorem (1933) posits that different places start out with different factor endowments and then infers that places will specialize in producing the goods that intensively require their relatively abundant factors and import goods that intensively require their relatively scarce factors.

For example, the United States is capital- and land-abundant, but labor-scarce by contrast. This might also be phrased as the US having a high ratio of skilled labor to unskilled labor, and a low ratio of labor to land, compared to most other countries.

The Heckscher-Ohlin Theorem then predicts that the US will be a low-cost producer of goods that use a lot of capital, skilled labor, and land relative to unskilled labor, because those inputs are relatively cheap, and a high-cost producer of goods that use a lot of unskilled labor relative to capital, skilled labor, and land, because that input is relatively expensive. So the US will be able to sell capital- and land-intensive goods abroad while importing labor-intensive goods.^[3]

The Stolper-Samuelson Theorem says that a change in the relative prices of goods more than proportionally changes the prices of the factors used intensively in their production (Samuelson, 1948). For example, let’s say the US starts out with no trade with the rest of the world. Capital-intensive and land-intensive goods are cheap, and labor-intensive goods are expensive because of the US factor endowments. Once the US opens to trade, capital-intensive and land-intensive goods rise in relative price domestically, and labor-intensive goods fall in relative price. The overall effect is to increase US productivity, as David Ricardo discovered, and as Ludwig von Mises and Donald Boudreaux have elaborated. But holders of capital and land benefit from trade, while holders of labor lose from trade, even taking into account lower prices on imported and import-competing goods.

Note that by “holders of capital” we include skilled workers, who hold a lot of human capital. “Holders of labor” are unskilled workers, who have only their raw manual power to offer. They are relatively scarce in the US, so with international trade, companies will try to economize on their use, and consumers will buy goods made with a lot of unskilled labor from abroad, where these goods can be made more cheaply.

The phenomenon of factor price equalization(FPE), predicted by these two theorems, has been much debated in economics. Everyone agrees that FPE happens to some extent, but the question is how much of the growing inequality between the wages of skilled and unskilled workers in the US and other advanced industrialized economies is the result of globalization (trade, capital mobility, and immigration) versus technology.

The counterintuitive truth to keep in mind is that the United States’ aggregate economic gains from globalization are larger the more that globalization changes factor prices—that is, suppresses the wages of the unskilled and boosts the wages of the skilled. The reason for this lies in the theory of comparative advantage, cited above. Economies benefit from trade the more their domestic prices without trade diverge from world prices. That’s the primary reason small countries benefit more from trade than large countries (Alesina, Spolaore, and Wacziarg, 2000). If trade really lets Americans economize on unskilled labor that is relatively expensive to us, that’s a huge benefit to the US economy, but it also drives up inequality. By contrast, in poor countries trade reduces inequality because skilled labor is scarce and unskilled labor is abundant. As a result, trade, capital mobility, and immigration should reduce absolute poverty, since unskilled workers in poor countries are the poorest people on earth.

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Comparing Trade and Immigration

In the real world, opening trade has not led to anything near complete factor price equalization worldwide. (Remember that we do observe substantial FPE across locations in the US, however!) Even unskilled workers in the US make a much higher wage than unskilled workers in, say, Bangladesh or Bolivia. The reason for this is that total factor productivity (TFP) is higher in the US because our level of technology is higher, our laws and political system are more stable, and the government interferes less with the free-market system. As a result, an American unskilled worker is far more productive than a Bangladeshi unskilled worker. An American skilled worker is far more productive than a Bangladeshi skilled worker. Capital and land are more productive here, too.

Herein lies the economic difference between trade and factor mobility. When capital and labor can move across borders, they can access the TFP of the most productive economies. It’s clear that unskilled workers have an incentive to move from unskilled-labor-abundant economies, where wages are low, to unskilled-labor-scarce economies like the US, where wages are high. That follows just from factor endowments. But there’s even a case for skilled workers to move from developing countries to the US because TFP is higher here, allowing them to earn higher wages even though they are leaving a place where their assets are relatively scarce for one where their assets are relatively abundant.

For this reason, the economic gains from immigration are potentially much higher than those for trade. At the current margin, just about every worker in a low-TFP economy could become more productive by moving to a high-TFP economy (Clemens, 2011). The world as a whole could be much more productive and richer if workers could seek the highest wage their labor commands.

Now, there are two important things to note about this prediction. The first is that this conclusion follows only if mass immigration doesn’t have massive negative effects on TFP. Some critics of immigration have posited that this is precisely what will happen because of immigrants’ use of the welfare state, voting patterns, or cultural values and intelligence (Jones, 2022). Any full assessment of immigration policy must assess these claims and take those with strong evidence into account.

Second, as with trade, the economic gains from immigration are larger the greater the pre-immigration wage differences between economies. If healthy, English-speaking Bangladeshi unskilled workers moved to the US en masse, they’d be expected to drive down the wages of native unskilled workers, and this process is part of what generates the economic gains from Bangladeshi immigration.

Some pro-immigration commentators deny this effect. They say that immigration not only increases the supply of labor, it also increases the demand for goods and services, which in turn offsets the wage effect of immigration.

This claim is incorrect. First of all, the mechanism by which they claim immigration raises wages here implies that it increases prices. That’s the whole reason producers would bid up labor to produce more goods. But if immigration drives up prices, then it still drives down real, inflation-adjusted wages. Second, immigration can’t affect aggregate demand much in the long run. Aggregate demand affects choices most in the short run, until expectations change and prices adjust. Furthermore, the Federal Reserve should be expected to offset the alleged demand effects of immigration with tighter monetary policy, in order to reach its inflation target.

As supply and demand would predict, an exogenous increase in the supply of a factor of production will reduce its price. Immigrants will bid down the wages of native workers with precisely the same skill sets and industrial and occupational concentrations. But does this theoretical result happen in practice?

The Evidence on Immigration’s Distributional Effects

Does unskilled immigration reduce the wages of unskilled workers already here? Economists haven’t come to a consensus on this point. A key point of dispute concerns whether most unskilled immigrants to the US constitute a substitute for unskilled native labor, or not. Most unskilled immigrants to the US do not natively speak English. As a result, they may be less productive than native unskilled workers in service industries.

An influential early review of the literature suggested that the wage effects of immigration are much stronger than those of trade (Borjas, Freeman and Katz, 1997). Since then, economists have tried to identify “natural experiments” that let them draw causal conclusions more confidently.

One such natural experiment may be the Mariel Boatlift of 1980, which brought to South Florida an estimated 125,000 Cuban refugees, most of whom hadn’t finished high school and did not speak English. The original Boatlift study showed no wage effects (Card, 1990). An influential reassessment then showed a negative effect on the wages of high school dropouts (Borjas, 2017). However, a subsequent critique showed that the data Borjas used are unreliable because the sample sizes are too small to infer wages for the broader populations under investigation (Clemens and Hunt, 2019).

If immigrants are more complementary to native workers than substitutes for them, then they don’t compete much with native workers. Effectively, they offer different factors of production. That’s just what a study of “occupational task-intensity” data finds (Peri and Sparber, 2009). Along the same lines, Ottaviano and Peri (2012) find that in the long run, immigrants increase the wages of natives at all skill levels.

A more recent, high-quality study finds that Mexican immigrants impelled to the US by the peso crisis reduced native low-skilled wages and raised rents in the short run, but in the long run only reduced the wages of those low-skilled natives who entered the labor market in high-immigration years and reduced rents in locations where immigrants disproportionately entered the construction sector (Monras, 2020). Further work taking immigrants’ location decisions into account finds that immigrants concentrate in high-productivity cities so that they can earn money to send home. As a result, they improve the productivity and wages of natives more than they would otherwise (Albert and Monras, 2022).

The bulk of the evidence is therefore consistent with economic theory. Immigrants reduce the wages of natives with whom they directly compete, but they raise the wages of most native workers in the long run. Skilled immigration to the US is widely regarded as having positive effects on most workers, with the possible exception, in the short run, of native workers in identical occupations and industries.

What Economics Can Teach Us About Immigration

Economic theory tells us that immigration directly benefits economies for the same reason and in the same manner that trade does: it allows labor to work where it is most productive, making all other factors of production more productive. The government is no better at centrally planning labor markets than it is other markets: by incorporating dispersed, tacit knowledge, wages coordinate the choices of immigrants and their employers in myriad ways that no one could foresee. Moreover, immigration has a big positive effect on productivity that trade does not have: it gives workers everywhere access to the most advanced technology.

Popular discourse on immigration does not track the insights of economics. Immigration should have the biggest benefits for America as a whole precisely when it drives down the wages of our scarcest factor of production, unskilled labor. The same is true of trade. For these reasons, economists have often proposed policies to “compensate” low-skilled natives for the fact that their wages under globalization will be lower than under autarky.

Our biggest mistake, however, might be to think of people as if they were factors of production, rather than to understand that factors of production are things that people own. All of us at one time had only unskilled labor to offer the labor market. Many immigrants end up starting businesses and becoming owners of capital, raising the productivity of native Americans. Moreover, if American policies better supported skill development and productive work, fewer workers would have only unskilled labor to offer the market.

As Adam Smith discovered, economic progress depends on deepening the division of labor, which in turn is made possible by ever-larger networks of exchange. As a form of voluntary exchange for mutual benefit, immigration deepens labor markets and facilitates a more finely-grained division of labor.

This explainer does not address the indirect effects of immigration on the economy, which may work through culture, politics, or the welfare state. Those indirect effects are the ones most difficult to measure, and controversy about them is likely to continue. But before we can have a sensible conversation about immigration policy, we need to understand the economic basics.

References

Albert, C. and Monras, J. (2022) “Immigration and Spatial Equilibrium: The Role of Expenditures in the Country of Origin,” American Economic Review, 112(11), pp. 3763–3802. Available at: https://doi.org/10.1257/aer.20211241. 

Albouy, D. (2016) “What Are Cities Worth? Land Rents, Local Productivity, and the Total Value of Amenities,” The Review of Economics and Statistics, 98(3), pp. 477–487. 

Alesina, A., Spolaore, E. and Wacziarg, R. (2000) “Economic integration and political disintegration,” American Economic Review, 90(5), pp. 1276–1296. 

Bernard, A.B., Redding, S.J. and Schott, P.K. (2013) “Testing for Factor Price Equality with Unobserved Differences in Factor Quality or Productivity,” American Economic Journal: Microeconomics, 5(2), pp. 135–63. Available at: https:// doi.org/10.1257/mic.5.2.135. 

Borjas, G.J. (2017) “The Wage Impact of the Marielitos: A Reappraisal,” ILR Review, 70(5), pp. 1077–1110. Available at: https://doi.org/10.1177/0019793917692945. 

Borjas, G.J., Freeman, R.B. and Katz, L.F. (1997) “How much do immigration and trade affect labor market outcomes?,” Brookings Papers on Economic Activity, 1997(1), pp. 1–90. 

Card, D. (1990) “The Impact of the Mariel Boatlift on the Miami Labor Market,” ILR Review, 43(2), pp. 245–257. 

Chen, Y. and Rosenthal, S.S. (2008) “Local Amenities and Life-Cycle Migration: Do People Move for Jobs or Fun?,” Journal of Urban Economics, 64, pp. 519–537. 

Clemens, M.A. (2011) “Economics and emigration: Trillion-dollar bills on the sidewalk?,” Journal of Economic Perspectives, 25(3), pp. 83–106. 

Clemens, M.A. and Hunt, J. (2019) “The labor market effects of refugee waves: reconciling conflicting results,” ILR Review, 72(4), pp. 818–857. 

Jones, G. (2022) The Culture Transplant: How Migrants Make the Economies They Move to a Lot like the Ones They Left. Redwood City, Calif.: Stanford University Press. 13 

Leontief, W. (1953) “Domestic Production and Foreign Trade; The American Capital Position Re-Examined,” Proceedings of the American Philosophical Society, 97(4), pp. 332–349. 

Monras, J. (2020) “Immigration and Wage Dynamics: Evidence from the Mexican Peso Crisis,” Journal of Political Economy, 128(8), pp. 3017–3089. Available at: https://doi. org/10.1086/707764. 

Ottaviano, G.I.P. and Peri, G. (2012) “Rethinking the effect of immigration on wages,” Journal of the European Economic Association, 10(1), pp. 152–197. 

Peri, G. and Sparber, C. (2009) “Task Specialization, Immigration, and Wages,” American Economic Journal: Applied Economics, 1(3), pp. 135–69. Available at: https://doi. org/10.1257/app.1.3.135. 

Samuelson, P.A. (1948) “International Trade and the Equalisation of Factor Prices,” The Economic Journal, 58(230), pp. 163–184. Available at: https://doi.org/10.2307/2225933. 

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Endnotes

^[1] One paper that purports to find otherwise – Bernard et al. (2013) – does not attempt to adjust wages for local prices or amenities, substantially vitiating its results.

^[2] See also Albouy (2016).

^[3] Leontief (1953) found that US exports were more labor-intensive and less capital-intensive than its imports, but the well-known “Leontief Paradox” is explicable in that the US appears to have had a durable comparative advantage in skilled labor-intensive production.