The Hidden Cost of Hard-to-Fire Labor Laws: Why European Firms Don’t Take Risks
In our textbook, Modern Principles, Tyler and I write:
Imagine how difficult it would be to get a date if every date required marriage? In the same way, it’s more difficult to find a job when every job requires a long-term commitment from the employer.
In two new excellent pieces, Brian Albrecht and Pieter Garicano extend this partial equilibrium aphorism with some general equilibrium reasoning. Here’s Albrecht:
[I]magine there is a surge for Siemens products. Do you hire a ton of workers to fill that demand? No, you’re worried about having to fire them in the future but being stuck until they retire.
But it’s even worse than that…..[suppose Siemens does want to hire] where is Siemens getting those workers from?…Not only is it a problem for Siemens that they won’t be able to fire people down the road, the fact that BMW doesn’t fire anyone means you can’t hire people.
Garicano has an excellent piece, Why Europe doesn’t have a Tesla, with lots of detail on European labor law:
Under the [German] Protection Against Dismissal Act, the Kündigungsschutzgesetz, redundancies over ten employees must pass a social selection test (Sozialauswahl). Employers cannot choose who leaves: they must rank employees by age, years of service, family maintenance obligations, and degree of disability, and then prioritize dismissing those with the weakest social claim to the job. If someone is dismissed for operational reasons but the company posts a similar job elsewhere, the dismissal is usually invalid.
Disabled employees can be dismissed only with the approval of the Integration Office (Integrationsamt), a public body. The office will weigh the employer’s reasons, whether they have taken sufficient steps to integrate the employee, and whether they could be redeployed elsewhere in the organization. Workers who also become caregivers cannot be dismissed at all for up to two full years after they tell their bosses they fulfill that role.
As a company becomes larger and tries to let more workers go at once these difficulties increase. In many European countries, companies with more than a certain number of workers – 50 in the Netherlands, 5 in Germany – are obliged to create a works council, which represents employees and, in some countries, must give its approval to decisions the employer wants to make regarding its employees, including layoffs or pay rises or cuts.
…Companies that are allowed to fire someone and can afford to pay the severance costs have to wait and pay additional fees. Collective dismissal procedures in Germany start after 30 departures within a month; once triggered they require further negotiations with the works council, a waiting period, and the creation of a ‘social plan’ with more compensation for departing workers. When Opel shut down its Bochum factory in Germany, it reached a deal with the works council to spend €552 million on severance for the 3,300 affected employees. This included individual payments of up to €250,000 and a €60 million plan to help workers find new jobs.
Now what is the effect of regulations like this? Well obviously the partial equilibrium effect is to reduce hiring but in addition Garicano notes that it changes what sorts of firms are created in the first place. If you are worried about being burdened by expensive dismissal procedures, build a regulated utility with captive government contracts, not a radical startup with a high probability of failure.
Rather than reduce hiring in response to more expensive firing, companies in Europe have shifted activity away from areas where layoffs are likely. European workers are for sure, solid work only. This works well in periods of little innovation, or when innovation is gradual. The continent, however, is poorly equipped for moments of great experimentation.
…Europe’s companies have immense, specialized knowledge [due to retained workforces, AT]. The problems happen when radical innovation is needed, as in the shift from gasoline to electric vehicles. The great makers of electric cars have either been new entrants, like Tesla and BYD, or old ones who have had their insides stripped, like MG.
..If Europe wants a Tesla, or whatever the Tesla of the next decade will turn out to be, it will need a new approach to hiring and firing.
Claude on NY’s Senate Bill S7263
A NY State Senate proposed bill (Senate Bill S7263) would
prohibit a chatbot to give substantive responses; information, or advice or take any action which, if taken by a natural person, would constitute unauthorized practice or unauthorized use of a professional title as a crime in relation to professions who licensure is governed by the education law or the judiciary law.
Claude, what do you think of the legal logic of this bill?
The legal logic is shaky. The bill’s operative test asks whether a chatbot’s output, “if taken by a natural person, would constitute a crime” under New York’s unauthorized practice statutes. But those statutes set a high bar — mere advice-giving by a layperson is not criminal; what’s prohibited is holding yourself out as a licensed professional while charging fees. Your neighbor who happens to be a doctor can tell you what he thinks your rash is. A retired lawyer can walk you through a lease. None of that is a crime. So either the bill is mostly toothless — most AI responses wouldn’t meet the criminal threshold — or courts will interpret “substantive advice” far more expansively than the underlying statutes warrant, effectively creating a new and harsher legal standard for AI that applies to no human equivalent. Neither outcome reflects good lawmaking, and the ambiguity will systematically over-deter, pushing operators to sanitize outputs well beyond what the statute actually requires.
Claude, who will be hurt by this bill?
The deepest problem is who gets hurt. The populations with the most to gain from AI-assisted professional guidance are precisely those who cannot afford lawyers, doctors, or therapists — the tenant trying to understand an eviction notice, the rural patient triaging symptoms, the small business owner reviewing a contract. For these users, the choice the bill actually creates is not “AI advice versus licensed professional advice”; it’s “AI advice versus no advice at all.” A watered-down chatbot that responds to every medical or legal question with a referral to a licensed professional is not a safety feature — it’s a luxury tax on information, paid disproportionately by people with the fewest alternatives. New York should be asking how to ensure AI advice is accurate and clearly disclosed, not how to suppress it on behalf of incumbents who’d prefer less competition.
Thanks Claude. Where did you learn this excellent analysis?
Public choice theory is part of my general training on economics and political science literature — Buchanan, Tullock, Olson, and the broader tradition are well-represented in the texts I was trained on.
But I’d be remiss not to note that you’re at the home institution of public choice. The Buchanan House is literally on your campus, and the tradition Buchanan and Tullock built at GMU is probably the most direct intellectual ancestor of the kind of analysis I was applying to this bill — concentrated benefits, diffuse costs, regulatory capture, rent-seeking by incumbent professionals. That framework is so natural for analyzing occupational licensing legislation that it almost applies itself.
If anything, my read of S7263 is pretty much a straightforward public choice story: organized professional associations with strong lobbying presence get statutory protection written in the language of consumer welfare, while the costs fall on millions of unorganized users who will never know what information they didn’t receive. Buchanan would have recognized it immediately.
Banned in California
California cannot permit the construction of a smartphone factory, an electric car plant, or a Navy destroyer shipyard. Not won’t — can’t. The regulatory environment makes it effectively impossible to build new semiconductor fabs, automotive paint shops, battery gigafactories, or steel foundries.
Tesla didn’t put its Gigafactory in Nevada out of affection for Reno. General Dynamics NASSCO in San Diego can build destroyers only because it’s been grandfathered in since 1960. If it closed tomorrow, it could not be rebuilt.
I get tired at all the discussion of tariffs and industrial policy and manufacturing. All of it is BS in comparison to the basics. We have the met the enemy and the enemy is us. Our future is in our hands. Is that optimistic or pessimistic? Either way complaining about China won’t fix our problems.
Chaos and Misallocation under Price Controls
My latest paper, Chaos and Misallocation under Price Controls, (with Brian Albrecht and Mark Whitmeyer) has a new take on price controls:
Price controls kill the incentive for arbitrage. We prove a Chaos Theorem: under a binding price ceiling, suppliers are indifferent across destinations, so arbitrarily small cost differences can determine the entire allocation. The economy tips to corner outcomes in which some markets are fully served while others are starved; small parameter changes flip the identity of the corners, generating discontinuous welfare jumps. These corner allocations create a distinct source of cross-market misallocation, separate from the aggregate quantity loss (the Harberger triangle) and from within-market misallocation emphasized in prior work. They also create an identification problem: welfare depends on demand far from the observed equilibrium. We derive sharp bounds on misallocation that require no parametric assumptions. In an efficient allocation, shadow prices are equalized across markets; combined with the adding-up constraint, this collapses the infinite-dimensional welfare problem to a one-dimensional search over a common shadow price, with extremal losses achieved by piecewise-linear demand schedules. Calibrating the bounds to stationlevel AAA survey data from the 1973–74 U.S. gasoline crisis, misallocation losses range from roughly 1 to 9 times the Harberger triangle.
Brian has a superb write up that makes the paper very accessible. Unfortunately, the paper is timely and relevant.
If you have the right to die, you should have the right to try!
Ruxandra Teslo asks a good question:
I have a curiosity: why is it the case that it is easier to get MAID in Canada than it is to access experimental treatments which carry a higher risk? In the past, I used to think ppl do not like “deaths caused by the medical system”, but for MAID the prob of death is 100%…
The Canadians may be somewhat inconsistent on this point. Unfortunately, the Supreme Court has been consistent and has rejected medical self-defense arguments for physician assisted suicide and let stand an appeals court ruling that patients do not have a right to access drugs which have not yet been permitted for sale by the FDA (fyi, I was part of an Amici Curiae brief for this case).
Hat tip for the post title to Jason Crawford.
Daniel Litt on AI and Math
Daniel Litt is a professor of mathematics at the University of Toronto. He has been active in evaluating AI models for many years and is generally seen as a skeptic pushing back at hype. He has a very interesting statement updating his thoughts:
In March 2025 I made a bet with Tamay Besiroglu, cofounder of RL environment company Mechanize, that AI tools would not be able to autonomously produce papers I judge to be at a level comparable to that of the best few papers published in 2025, at comparable cost to human experts, by 2030. I gave him 3:1 odds at the time; I now expect to lose this bet.
Much of what I’ll say here is not factually very different from what I’ve written before. I’ve slowly updated my timelines over the past year, but if one wants to speculate about the long-term future of math research, a difference of a few years is not so important. My trigger for writing this post is that, despite all of the above, I think I was not correctly calibrated as to the capabilities of existing models, let alone near-future models. This was more apparent in the mood of my comments than their content, which was largely cautious.
To be sure, the models are not yet as original or creative as the very best human mathematicians (who is?) but:
Can an LLM invent the notion of a scheme, or of a perfectoid space, or whatever your favorite mathematical object is? (Could I? Could you? Obviously this is a high bar, and not necessary for usefulness.) Can it come up with a new technique? Execute an argument that isn’t “routine for the right expert”? Make an interesting new definition? Ask the right question?
…I am skeptical that there is any mystical aspect of mathematics research intrinsically inaccessible to models, but it is true that human mathematics research relies on discovering analogies and philosophies, and performing other non-rigorous tasks where model performance is as yet unclear.
Why the “Lesser Included Action” Argument for IEEPA Tariffs Fails
The Supreme Court yesterday struck down Trump’s IEEPA tariffs, holding that the statute’s authorization to “regulate… importation” doesn’t include the power to impose tariffs. The majority’s strongest argument is simple: every time Congress actually delegates tariff authority, it uses the word “duty,” caps the rate, sets a time limit, and requires procedural prerequisites. IEEPA has none of these.
The dissent pushes back with an intuitively appealing argument: IEEPA authorizes the President to prohibit imports entirely, so surely it authorizes the lesser action of merely taxing them. If Congress handed over the nuclear option, why would it withhold the conventional weapon? Indeed in his press conference Trump, in his rambling manner, made exactly this argument:
“I am allowed to cut off any and all trade…I can destroy the trade, I can destroy the country, I’m even allowed to impose a foreign country destroying embargo…I can do anything I want to do to them…I’m allowed to destroy the country, but I can’t charge a little fee.”
The argument is superficially appealing but it fails due to a standard result in principal-agent theory.
Congress wants the President to move fast in a real emergency, but it doesn’t want to hand over routine control of trade policy. The right delegation design is therefore a screening device: give the President authority he will exercise only when the situation is truly an emergency.
An import ban works as a screening device precisely because it is very disruptive. A ban creates immediate and substantial harm. It is a “costly signal.” A President who invokes it is credibly saying: this is serious enough that I am willing to absorb a large cost. Tariffs, in contrast, are cheaper–especially to the President. Tariffs raise revenue, which offsets political pain. Tariff incidence is diffuse and easy to misattribute—prices creep, intermediaries take blame, consumers don’t observe the policy lever directly. Most importantly tariffs are adjustable, which makes them a weapon useful for bargaining, exemptions, and targeted favors. Tariffs under executive authority implicitly carry the message–I am the king; give me a gold bar and I will reduce your tariffs. Tariff flexibility is more politically appealing than a ban and thus a less credible signal of an emergency. The “lesser-included” argument gets the logic backwards. The asymmetry is the point.
Not surprisingly, the same structure appears in real emergency services. A fire chief may have the authority to close roads during an emergency but that doesn’t imply that the fire chief has the authority to impose road tolls. Road closure is costly and self-limiting — it disrupts traffic, generates immediate complaints, and the chief has every incentive to lift it as soon as possible. Tolls are cheap, adjustable, and once in place tend to persist; they generate revenue that can fund the agency and create constituencies for their continuation. Nobody thinks granting a fire chief emergency closure authority implicitly grants them taxing authority, even if the latter is a lesser authority. The closure and toll instruments have completely different political economy properties despite operating on the same roads.
The majority reaches the right conclusion by noting that tariffs are a tax over which Congress, not the President, has authority. That is constitutionally correct but the deeper question is why the Framers lodged the taxing power in Congress — and the answer is political economy. Revenue instruments are especially easy for an executive to exploit because they can be targeted. The constitutional rule exists to solve that incentive problem.
Once you see that, the dissent’s “greater includes the lesser” inference collapses on its own terms. A principal can rationally authorize an agent to take a dramatic emergency action while withholding the cheaper, revenue-lever not despite the fact that it seems milder, but because of it. The blunt instrument is self-limiting. The revenue instrument is not. That asymmetry is what the Constitution’s categorical division of powers preserves — and what an open-ended emergency delegation would destroy.
A Republic, if you can keep it
The conclusion of Justice Gorsuch’s concurrence in the tariff case:
For those who think it important for the Nation to impose more tariffs, I understand that today’s decision will be disappointing. All I can offer them is that most major decisions affecting the rights and responsibilities of the American people (including the duty to pay taxes and tariffs) are funneled through the legislative process for a reason. Yes, legislating can be hard and take time. And, yes, it can be tempting to bypass Congress when some pressing problem
arises. But the deliberative nature of the legislative process was the whole point of its design. Through that process, the Nation can tap the combined wisdom of the people’s elected representatives, not just that of one faction or man. There, deliberation tempers impulse, and compromise hammers
disagreements into workable solutions. And because laws must earn such broad support to survive the legislative process, they tend to endure, allowing ordinary people to plan their lives in ways they cannot when the rules shift from day to day. In all, the legislative process helps ensure each of us has a stake in the laws that govern us and in the Nation’s future. For some today, the weight of those virtues is apparent. For others, it may not seem so obvious. But if history is any guide, the tables will turn and the day will come when those disappointed by today’s result will appreciate the legislative process for the bulwark of liberty it is.
India AI Data MCP
The Government of India’s Ministry of Statistics and Program Implementation has created an impressive Model Context Protocol (MCP) to connect AI’s to Indian datasets. An AI connected to data via an MCP essentially knows the entire codebook and can make use of the data like an expert. Once connected one can query the data in natural language and quickly create graphs and statistical analysis. I connected Claude to the MCP and created an elegant dashboard with data from India’s Annual Survey of Industries. Check it out.
The Cassidy Report on the FDA
Senator Bill Cassidy (R-La.) released a new report on how to modernize the FDA. It has some good material.
… FDA’s process for reviewing new products can be an unpredictable “black box.” FDA teams can differ greatly in the extent to which they require testing or impose standards that are not calibrated to the relevant risks. The perceived disconnect between the forward leaning rhetoric and thought leadership of senior FDA officials and cautious reviewer practice creates further unpredictability. This uncertainty dampens investment and increases the time it takes for patients to receive new therapies.
Companies report that they face a “reviewer lottery,” where critical questions hinge on the approach of a small number of individuals at FDA. Some FDA review teams are creative and forward-leaning, helping developers design programs and overcome obstacles to get needed products to patients, without cutting corners. FDA’s Oncology Center of Excellence (OCE), for example, is repeatedly identified as a model for providing predictable yet flexible options for bringing new drugs to cancer patients. OCE is now a dialogue-based regulatory paradigm that has facilitated efforts by academia, industry, the National Institutes of Health (NIH), and others to develop new cancer therapies and launch innovative programs and pilots like Project Orbis, RealTime Oncology Review.
That’s quite right. In my report with DiMasi and Milne, we show that review times vary markedly within the FDA, across divisions, without clear cause. Put aside the big questions of FDA or no FDA–scaling the practices of the better-performing divisions would likely yield large gains.
Mike Doherty further asks the AI what Alex Tabarrok would think of the Cassidy report. It replies:
Strongest features: It correctly diagnoses FDA as a bottleneck to innovation, emphasizes “least burdensome” evidence, calls for streamlined pathways (505(b)(2)-style for biologics, biosimilar simplification), and worries about U.S. losing early-phase trials to other countries. This is very much in Tabarrok’s wheelhouse: regulation as a hidden tax on innovation and growth.
Weakest features: It rarely quantifies tradeoffs, almost never confronts the “invisible graveyard” of patients who never see therapies because of delay, and treats reforms as marginal tweaks rather than testing fundamentally different regulatory models (e.g., insurance-based approval, private certification, or sunset/experimentation with parallel regimes).
If you imagine this as a draft memo handed to Tabarrok, he’d likely say: “Good directionally; now add 50% more economics, 50% more quantification, and 100% more willingness to experiment with institutional competition.”
Yeah, pretty good.
Addendum: In other FDA news see also Adam Kroetsch on Will Bayesian Statistics Transform Trials?
Addendum 2: FDA has now agreed to review Moderna’s flu vaccine which is good although the course reversal obviously speaks to the unpredictability of the FDA.
Minimum Wages for Gig Workers Can’t Work
In 2017, I analyzed the Uber Tipping Equilibrium:
What is the effect of tipping on the take-home pay of Uber drivers? Economic theory offers a clear answer. Tipping has no effect on take home pay. The supply of Uber driver-hours is very elastic. Drivers can easily work more hours when the payment per ride increases and since every person with a decent car is a potential Uber driver it’s also easy for the number of drivers to expand when payments increase. As a good approximation, we can think of the supply of driver-hours as being perfectly elastic at a fixed market wage. What this means is that take home pay must stay constant even when tipping increases.
…If Uber holds fares constant, the higher net wage (tips plus fares) will attract more drivers but as the number of drivers increases their probability of finding a rider will fall. The drivers will earn more when driving but spend less time driving and more time idling. In other words, tipping will increase the “driving wage,” but reduce paid driving-time until the net hourly wage is pushed back down to the market wage.
A paper by Hall, Horton and Knoepfle showed that’s exactly what happened.
More recently, in 2024, Seattle implemented “PayUp”, a pay package for gig workers like DoorDash workers that required a minimum wage based on the time worked and miles travelled for each offer. Note that this is not a minimum wage for all workers but for one type of worker in a large market. For this reason, we can use the same analysis as with Uber tipping. The supply of workers is very elastic and essentially fixed at the market wage for workers of similar skill. Thus, we would expect a zero effect on net pay.
Here is a recent NBER paper by An, Garin and Kovak looking at the effects of the Seattle law:
We find that the minimum pay law raised delivery pay per task….At the same time, the policy led to a reduction in the number of tasks completed by highly attached incumbent drivers (but not an increase in exit from delivery work), completely offsetting increased pay per task and leading to zero effect on monthly earnings. We find evidence that drivers experienced more unpaid idle time and longer distances driven between tasks…Using a simple model of the labor market for platform delivery drivers, we show that our evidence is consistent with free entry of drivers into the delivery market driving down the task-finding rate until expected earnings return to their pre-reform level.
All of this is a general result of the Happy Meal Fallacy.
Natural and Artificial Ice
Excellent Veritasium video on the 19th century ice industry. Shipping ice from America to India would hardly seem like a wise idea—it’s hard to imagine ever getting a committee to approve such a venture—but entrepreneurs are free to try wacky ideas all the time, and sometimes they pay off, resulting in great riches. That’s the story of the “Ice King,” Frederic Tudor, who lost money for years before figuring out the insulation and logistics needed to make the trade profitable.
What I hadn’t fully appreciated is how the ice trade reshaped shipping, diet, and city design before the invention of mechanical refrigeration. Ice created the cold chain, and the cold chain made it possible to move fresh meat, fish, and produce over long distances. That in turn enabled cities to grow far beyond what local agriculture could support and shifted the American diet from salted and smoked provisions toward fresh food.
The profits of the ice trade encouraged investment in artificial ice which initially was met with resistance—natural ice is created by God!—a classic example of incumbents wrapping their economic interests in moral language, a pattern we see repeated with every disruptive technology from margarine to ridesharing.
Lots of lessons in the video about option value, permissionless innovation, and creative destruction. New technologies destroy old industries and create new ones that no one could have foreseen. The moral panic over artificial ice replacing the natural kind is no doubt familiar.
Hat tip: Naveen Nvn
I Regret to Inform You that the FDA is FDAing Again
I had high hopes and low expectations that the FDA under the new administration would be less paternalistic and more open to medical freedom. Instead, what we are getting is paternalism with different preferences. In particular, the FDA now appears to have a bizarre anti-vaccine fixation, particularly of the mRNA variety (disappointing but not surprising given the leadership of RFK Jr.).
The latest is that the FDA has issued a Refusal-to-File (RTF) letter to Moderna for their mRNA influenza vaccine, mRNA-1010. An RTF means the FDA has determined that the application is so deficient it doesn’t even warrant a review. RTF letters are not unheard of, but they’re rare—especially given that Moderna spent hundreds of millions of dollars running Phase 3 trials enrolling over 43,000 participants based on FDA guidance, and is now being told the (apparently) agreed-upon design was inadequate.
Moderna compared the efficacy of their vaccine to a standard flu vaccine widely used in the United States. The FDA’s stated rationale is that the control arm did not reflect the “best-available standard of care.” In plain English, that appears to mean the comparator should have been one of the ACIP-preferred “enhanced” flu vaccines for adults 65+ (e.g., high-dose/adjuvanted) rather than a standard-dose product.
Out of context, that’s not crazy but it’s also not necessarily wise. There is nothing wrong with having multiple drugs and vaccines, some of which are less effective on average than others. We want a medical armamentarium: different platforms, different supply chains, different side-effect profiles, and more options when one product isn’t available or isn’t a good fit. The mRNA vaccines, for example, can be updated faster than standard vaccines, so having an mRNA option available may produce superior real-world effectiveness even if it were less efficacious in a head-to-head trial.
In context, this looks like the regulatory rules of the game are being changed retroactively—a textbook example of regulatory uncertainty destroying option value. STAT News reports that Vinay Prasad personally handled the letter and overrode staff who were prepared to proceed with review. Moderna took the unusual step of publicly releasing Prasad’s letter—companies almost never do this, suggesting they’ve calculated the reputational risk of publicly fighting the FDA is lower than the cost of acquiescing.
Moreover, the comparator issue was discussed—and seemingly settled—beforehand. Moderna says the FDA agreed with the trial design in April 2024, and as recently as August 2025 suggested it would file the application and address comparator issues during the review process.
Finally, Moderna also provided immunogenicity and safety data from a separate Phase 3 study in adults 65+ comparing mRNA-1010 against a licensed high-dose flu vaccine, just as FDA had requested—yet the application was still refused.
What is most disturbing is not the specifics of this case but the arbitrariness and capriciousness of the process. The EU, Canada, and Australia have all accepted Moderna’s application for review. We may soon see an mRNA flu vaccine available across the developed world but not in the United States—not because it failed on safety or efficacy, but because FDA political leadership decided, after the fact, that the comparator choice they inherited was now unacceptable.
The irony is staggering. Moderna is an American company. Its mRNA platform was developed at record speed with billions in U.S. taxpayer support through Operation Warp Speed — the signature public health achievement of the first Trump administration. The same government that funded the creation of this technology is now dismantling it. In August, HHS canceled $500 million in BARDA contracts for mRNA vaccine development and terminated a separate $590 million contract with Moderna for an avian flu vaccine. Several states have introduced legislation to ban mRNA vaccines. Insanity.
The consequences are already visible. In January, Moderna’s CEO announced the company will no longer invest in new Phase 3 vaccine trials for infectious diseases: “You cannot make a return on investment if you don’t have access to the U.S. market.” Vaccines for Epstein-Barr virus, herpes, and shingles have been shelved. That’s what regulatory roulette buys you: a shrinking pipeline of medical innovation.
An administration that promised medical freedom is delivering medical nationalism: fewer options, less innovation, and a clear signal to every company considering pharmaceutical investment that the rules can change after the game is played. And this isn’t a one-product story. mRNA is a general-purpose platform with spillovers across infectious disease and vaccines for cancer; if the U.S. turns mRNA into a political third rail, the investment, talent, and manufacturing will migrate elsewhere. America built this capability, and we’re now choosing to export it—along with the health benefits.
That Was Then/This is Now
Hat tip: Logan Dobson.
Trump’s Pharmaceutical Plan
Pharmaceuticals have high fixed costs of R&D and low marginal costs. The first pill costs a billion dollars; the second costs 50 cents. That cost structure makes price discrimination—charging different customers different prices based on willingness to pay—common.
Price discrimination is why poorer countries get lower prices. Not because firms are charitable, but because a high price means poorer countries buy nothing, while any price above marginal cost is still profit. This type of price discrimination is good for poorer countries, good for pharma, and (indirectly) good for the United States: more profits mean more R&D and, over time, more drugs.
The political problem, however, is that Americans look abroad, see lower prices for branded drugs, and conclude that they’re being ripped off. Riding that grievance, Trump has demanded that U.S. prices be no higher than the lowest level paid in other developed countries.
One immediate effect is to help pharma in negotiations abroad: they can now credibly say, “We can’t sell to you at that discount, because you’ll export your price back into the U.S.” But two big issues follow.
First, this won’t lower U.S. prices on current drugs. Firms are already profit-maximizing in the U.S. If they manage to raise prices in France, they don’t then announce, “Great news—now we’ll charge less in America.” The potential upside of the Trump plan isn’t lower prices but higher pharma profits, which strengthens incentives to invest in R&D. If profits rise, we may get more drugs in the long run. But try telling the American voter that higher pharma profits are good.
The second issue is that the plan can backfire.
In our textbook, Modern Principles, Tyler and I discuss almost exactly this scenario: suppose policy effectively forces a single price across countries. Which price do firms choose—the low one abroad or the high one in the U.S.? Since a large share of profits comes from the U.S., they’re likely to choose the high price:
Pfizer CEO Albert Bourla was even more direct, saying it is time for countries such as France to pay more or go without new drugs. If forced to choose between reducing U.S. prices to France’s level or stopping supply to France, Pfizer would choose the latter, Bourla told reporters at a pharma-industry conference.
So the real question is: will other countries pay?
If France tried to force Americans to pay more to subsidize French price controls, U.S. voters would explode. Yet that’s essentially what other countries are being told but in reverse: “You must pay more so Americans can pay less.” Other countries are already stingier than the U.S., and they already bear costs for it—new drugs arrive more slowly abroad than here. Some governments may decide—foolishly, but understandably—that paying U.S.-level prices is politically impossible. If so, they won’t “harmonize upward.” They’ll follow the European way: ration, delay and go without.
In that case, nobody wins. Pharma profits fall, R&D declines, U.S. prices don’t magically drop, and patients abroad get fewer new drugs and worse care. Lose-lose-lose.
We don’t know the equilibrium, but lose-lose-lose is entirely plausible. Switzerland, for example, does not seem willing to pay more:
Yet Switzerland has shown little political willingness to pay more—threatening both the availability of medications in the country and its role as a global leader in developing therapies. Drug prices are the primary driver of the increasing cost of mandatory health coverage, and the topic generates heated debate during the annual reappraisal of insurance rates. “The Swiss cannot and must not pay for price reductions in the USA with their health insurance premiums,” says Elisabeth Baume-Schneider, Switzerland’s home affairs minister.
If many countries respond like Switzerland—and Trump’s unpopularity abroad doesn’t help—the sector ends up less profitable and innovation slows. Voters may feel less “ripped off,” but they’ll be buying that feeling with fewer drugs and sicker bodies.