Month: February 2026

The import of cross-task productivity

by  Tyler Cowen in

Given that LLMs seem to be able to automate so many small tasks, why don’t we see large productivity effects?

I drafted a short paper recently exploring the possibility that it’s for the same reason (or at least one of the reasons) that labor is typically bundled into multi-task jobs, instead of transacted by the task, in the first place: because performing a task increases one’s productivity not only at the task itself but at related tasks.

For example, say you used to spend half your time coding and half your time debugging, and the LLM can automate the coding but you still have to do the debugging. If you’re more productive at debugging code you write yourself, this (1) explains why “coder” and “debugger” aren’t separate jobs, and (2) predicts that the LLM won’t save half your time. If you’re half as productive at debugging code you didn’t write, or less, the LLM saves you no time at all.

So I was excited to see @judyhshen  and @alextamkin’s paper from a week or two ago finding basically just that!

At least the way I’m thinking about it, “cross-task learning” should make the productivity impacts of automating tasks more convex: – Automating the second half of a job should be expected to have much more of an impact than automating the first half; and – If the machines can learn from their and each others’ experience, as a worker learns by doing from her own experience, then automating two jobs will have more than twice the impact of automating one.

That is from Philip Trammell.  Here is his short piece.  Here is the Shen and Tamkin paper.  This is all very important work for why the AI growth take-off will be much slower than the power of the models themselves might otherwise indicate.  The phrase “…and then all at once” nonetheless applies.  But when?

These short pieces and observations are likely among the most important outputs economists will produce this year.  But are they being suitably rewarded?

Oliver Kim reviews *How Africa Works*

by  Tyler Cowen in

That is the new book by Joe Studwell, my podcast with him should be coming out pretty soon.  Here is Oliver’s new review.  Excerpt:

Botswana is Studwell’s poster child for a successful democratic developmental coalition. (For this reason, it featured heavily in Acemoglu and Robinson’s Why Nations Fail as an example of “inclusive institutions”.)

Under the sound leadership of Seretse Khama, local chiefs were carefully co-opted at independence and the Botswana Democratic Party built up into a genuine national force. Khama also created a capable civil service, initially staffed by remaining Europeans, but gradually Africanized with sterling Batswana talent. This meant that when diamonds were discovered just around independence, the windfall was carefully managed, avoiding the worst effects of Dutch Disease. These mining revenues helped raise Botswana to upper middle-income status, making it the fourth-richest country in continental Africa.

Botswana’s chief failing, in Studwell’s view, was adhering too much to responsible policy orthodoxy—i.e., not enough industrial policy. There was no vision for large-scale industrialization, no coherent plan to create large numbers of factory jobs. Moreover, the political dominance of large cattle owners (Botswana was a society of pastoralists rather than farmers) meant that redistribution was never in the cards. The result is a relatively rich society, but one that is highly unequal.

You will be hearing my views on these issues soon enough.  Oliver, of course, writes one of the very best Substacks in all of economics.

Optimal timing for superintelligence

by  Tyler Cowen in

There is a new paper by Nick Bostrom with that title:

Developing superintelligence is not like playing Russian roulette; it is more like undergoing risky surgery for a condition that will otherwise prove fatal. We examine optimal timing from a person-affecting stance (and set aside simulation hypotheses and other arcane considerations). Models incorporating safety progress, temporal discounting, quality-of-life differentials, and concave QALY utilities suggest that even high catastrophe probabilities are often worth accepting. Prioritarian weighting further shortens timelines. For many parameter settings, the optimal strategy would involve moving quickly to AGI capability, then pausing briefly before full deployment: swift to harbor, slow to berth. But poorly implemented pauses could do more harm than good.

Via Nabeel.

Thursday assorted links

by  Tyler Cowen

1. Using Claude Code for academic work.

2. Younger Firms and CEOs Allow More Work from Home.

3. Extractive taxes were indeed a major force behind the French Revolution.

4. How much will “the human touch” persist?

5. “It was one attempt to do so, by Charles Jones of Stanford University, that entertained the negative top rate of -26%. If high earners produce a lot of ideas that help society, then “subsidising the discovery of new ideas through low tax rates may be as effective as redistribution in raising worker welfare”, he writes.” (The Economist)

6. Moral intuitions about love, romance, and reproduction are not Coasean.

7. Do not exercise options unless you have to!

8. I know Paul, he has very high standards.

9. Claims about Mexico’s security posture.

I Regret to Inform You that the FDA is FDAing Again

by  Alex Tabarrok in

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.

The economics of mass deportation

by  Tyler Cowen

Following the removal of 50% of unauthorized immigrants, in the short run average native real wages rise 0.15% nationally, driven by an increase in the capital-labor ratio. In the long run, however, native real wages fall in every state, and by 0.33% nationally, as capital gets decumulated in response to a lower population. Consumer prices in the sectors intensive in unauthorized workers – such as Farming – rise by about 1% relative to the price of the average consumption basket, while most other sectors experience negligible relative price changes.

That research result is from Javier Cravino, Andrei A. Levchenko, Francesc Ortega & Nitya Pandalai-Nayar.

Past Automation and Future A.I.: How Weak Links Tame the Growth Explosion

by  Tyler Cowen in

From Charles I. Jones and Christopher Tonetti:

How muchof past economic growth is due to automation, and what does this imply about the effects of A.I. and automation in the coming decades? We perform growth accounting using a task-based model for key sectors in the U.S. economy. Historically, TFP growth is largely due to improvements in capital productivity. The annual growth rate of capital productivity is at least 5pp larger than the sum of labor and factor-neutral productivity growth. The main benefit of automation is that we use rapidly-improving machines instead of slowly-improving humans on anincreasing set of tasks. Looking to the future, we develop an endogenous growth model in which the production of both goods and ideas is endogenously automated. We calibrate this model based on our historical evidence. Two key findings emerge. First, automation leads economic growth to accelerate over the next 75 years. Second, the acceleration is remarkably slow. By 2040, output is only 4% higher than it would have been without the growth acceleration, and by 2060 the gain is still only 19%. A key reason for the slow acceleration is the prominence of “weak links” (an elasticity of substitution among tasks less than one). Even when most tasks are automated by rapidly improving capital, output is constrained by the tasks performed by slowly-improving labor.

And an important sentence from the paper itself:

…, the key gain from automation is that it allows production of a task to shift away from slowly-improving human labor to rapidly-improving machines.

The authors stress that those are preliminary results, and the numbers are likely to change.  For the pointer I thank the excellent Kurtis Hingl, who is also my research assistant.

My New Jersey history podcast with “Exit Interviews”

by  Tyler Cowen in

Exit Interviews is a new podcast run by David Piegaro.  I am honored to be one of the first few guests, along with Chris Christie.  Think of this session as “Tyler Cowen as regional thinker.”  Almost 100% fresh material, not to mention some trolling directed at Central and South Jersey, Philly too.  Here is my episode.

Definitely recommended, and let us hope that David Remnick gets on soon to defend the honor of River Vale vs. Hillsdale in Bergen County…

Immigration and health for elderly Americans

by  Tyler Cowen in

We measure the impact of increased immigration on mortality among elderly Americans, who rely on the immigrant-intensive health and long-term care sectors. Using a shift-share approach we find a strong impact of immigration on the size of the immigrant care workforce: admitting 1,000 new immigrants would lead to 142 new foreign healthcare workers, without evidence of crowd out of native health care workers. We also find striking effects on mortality: a 25% increase in the steady state flow of immigrants to the US would result in 5,000 fewer deaths nationwide. We identify reduced use of nursing homes as a key mechanism driving this result.

That is from a new NBER working paper by David C. Grabowski, Jonathan Gruber & Brian E. McGarry.