Broadsheet

Stripe Press was kind enough to send me several books it had published, and one of these was J. Storrs Hall’s Where Is My Flying Car?. I had been meaning to read this book for a while, especially after Tyler Cowen recommended it and Jason Crawford gave it a glowing review, so I was glad Stripe gave me a copy. I promptly stuck it on my shelf, paid for the audiobook, and listened to it while walking around San Francisco. That’s called ordinary abundance, folks!

In 2011, Peter Thiel famously said: “We wanted flying cars, instead we got 140 characters.” When I first saw that quote, I chuckled, because for my entire life, we’ve had flying buses. And again and again, as I sit on a flying bus and marvel at the thrill of takeoff, and reflect on how amazing it is that man has conquered the air, I look around and see my fellow passengers with their window shades drawn, their noses buried in a book or staring at a phone.

If we had flying cars, we’d enjoy the thrill for a few weeks, and then we’d be back to tweeting on our phones and wondering when the trip would be over.

I’ve noticed a loose collection of beliefs and attitudes that I’ve decided to call “engineerism”, because I see it most often among engineers. I coined the term when I was in college, when I noticed that the engineering majors in my physics classes tended to think differently about the world than the physics majors like myself did. Later, I recognized “engineerism” in various sci-fi novels — Lucifer’s Hammer and Footfall by Larry Niven and Jerry Pournelle, The Peace War by Vernor Vinge, and so on.1

When I say “engineerism”, I am not talking about Friedrich Hayek’s “engineering mentality” — the belief that society can be designed and optimized like a machine.2 Nor am I referring to Evgeny Morozov’s “technological solutionism”, which is the idea that social problems can be fixed with technology. If I had to define what I call “engineerism” in succinct, simple terms, it would be something like: “The idea that if a technology can be built, we ought to build it.” Simply put, engineers like to engineer things, and they become disgruntled when society does not give them the resources to do this.

Of course, engineerism is not quite so simple in the real world. It involves a lot of thinking habits that come in handy in engineering — linear approximation, back-of-the-envelope calculations, and so on. And in America, it also involves a set of beliefs that have sort of accreted over the years — for example, a belief in the importance of nuclear power.

I’ve had the concept of engineerism kicking around in my mind for many years, but in Where Is My Flying Car? I have found its perfect encapsulation — you might even say its Bible. Nowhere are both the value and the limitations of engineerism more perfectly on display than in this book.

Where Is My Flying Car? occupies an interesting middle space between genres. Futurism is about predicting the future. Science fiction is about (among other things) speculating on possible futures. And history of technology explains the past. Where Is My Flying Car? has bits of all three of these, but fundamentally it’s a book of retrofuturism — it’s about the technologies we thought we would get but didn’t, and why we didn’t, and how we could get them now.

The main technology Hall talks about is, unsurprisingly, flying cars. The other three are cold fusion, nanotechnology (Hall’s own area of research), and nuclear (fission) power. Hall argues that a combination of overregulation, scientific groupthink, bad funding mechanisms, and cultural aversion prevented us from achieving all four of these.

The Galileo Fallacy

Wait…cold fusion? Is that even real?? Well, not as far as we know, no. In 1989, two top chemists reported that they had managed to get much more heat out of a nuclear experiment than chemistry would be able to produce. The chemists thought that they had discovered a way to produce nuclear fusion without injecting huge amounts of energy — smashing ions together at insanely high speed, blasting them with a laser, etc. If it worked, cold fusion would be an incredible energy source.

So naturally, a lot of people tried to follow up on cold fusion. A wave of initial replication efforts mostly failed (though some people claimed to find the effect). But there have been plenty more efforts, including:

A Japanese government project in the 1990s, with funding of around $20 million
A project by Toyota in the 1990s, with around $18 million in funding
A project by the Electric Power Research Institute in the 2000s, with around $10 million in funding
A project by Google in the 2010s, with $10 million of funding

None of these efforts have reliably reproduced the effect that the two chemists claimed in 1989. A few of the researchers found some strange anomalies and possible new physical effects, but nothing even remotely similar to the kind of energy source that cold fusion would represent — and no consistent evidence that fusion is causing the occasional anomalies.3 Some other scientists have found ways to enhance fusion using chemical techniques vaguely reminiscent of the methods in the 1989 experiments, but nothing remotely close to the scale of what “cold fusion” would require. There’s interesting nuclear physics going on in solid-state chemistry, but the original burst of excitement around the 1989 experiment looks like it was misplaced.

That’s not the way Hall tells it, though. He claims that cold fusion is a promising area of research, and that what he terms the “Machiavelli Effect” — basically, vested interests trying to shut down research that would supersede their own research programs — strangled the promising field of cold fusion in its cradle by stigmatizing it and depriving it of funding.

That story just doesn’t pass the smell test. Multiple optimistic, good-faith research efforts, from various countries, from both the public and private sectors, have each thrown tens of millions of dollars at the idea, despite repeated lack of success. That is just not what a marginalized area of science looks like. Yes, lots of people regarded (and regard) the idea of cold fusion as kooky, but plenty of others didn’t and don’t — including the people who headed the many multimillion-dollar research efforts.

Hall knew about all of those efforts, and their outcomes, when he published the 2021 version of his book. But although he mentions some of them, he continues to insist that cold fusion research was mainly stifled by malign social influences. And in his projections of the possibilities of the future, cold fusion figures prominently.

This suggests one weakness of engineerism — the stubborn, contrarian belief that if someone tells you something is impossible, it must be possible. Yes, people sneered unfairly at cold fusion back in the 90s, but that doesn’t mean it must actually work. Not everyone who gets persecuted by the Church is Galileo.

Hall’s stubborn love for the idea of cold fusion also has the unfortunate effect of reducing the credibility of other parts of his book. I am no expert in nanotech, and Hall is an expert. But when he relies on the magical effects of atom-sized nanotech to support key parts of his future visions, I’m skeptical of how much of that is based on careful homework and how much is based on pure optimism. When Hall tells us that nanotech should eventually be able to rebuild the U.S.’ entire existing infrastructure in a few hours, I naturally wonder if the back-of-the-envelope calculations that support that conclusion were the only ones he needed to do.4 If Hall hadn’t gone all-in on cold fusion, I would have probably been less instinctively skeptical of the nanotech sections.

To the stars! (But why?)

One of Hall’s main points in Where Is My Flying Car? — and the book’s best point, in my opinion — is that physical technology began to stagnate when energy use began to stagnate. In fact, I wrote a post about this a decade ago, before the first edition of Hall’s book even came out! Here’s what I wrote:

Why did mid-20th-century sci fi whiff so badly? Why didn't we get the Star Trek future, or the Jetsons future, or the Asimov future?…[W]e ran out of energy…In the industrial age, we got better at carrying energy around with us. And then, at the dawn of the nuclear age, it looked like we were about to get MUCH better at carrying energy around with us. One kilogram of uranium has almost two million times as much energy in it as a kilogram of gasoline.

I didn’t know it at the time, but I was talking about the Henry Adams Curve. This is a curve of energy use per capita in the U.S., which was rising smoothly but suddenly leveled off in the 1970s:

Source: J. Storrs Hall via Benjamin Reinhardt

In fact, the curve is too simplistic, but the basic point is solid. We failed to transition to energy sources better than fossil fuels.

It’s a simple truth that if you want your economy to escape poverty, you need lots of energy consumption:

Source: Energy For Growth Hub via Alec Stapp

But that doesn’t mean wealth is always inherently tied to energy. U.S. primary energy use per person stagnated after 1970 and has been falling since the turn of the century:

And yet since the turn of the century, even as energy use has fallen, U.S. per capita GDP has grown by 40%!

This is the magic of dematerialization, and it’s the reason economic growth doesn’t inevitably exhaust the planet’s resources. Not only have humans in rich countries figured out how to produce the same physical stuff with far less energy use, but we’ve found lots of other stuff we like that isn’t physical. Around 1970, Americans started spending more on services than on goods, and the gap has only grown wider since then:

Interestingly, something similar is even happening in China — the country that fetishizes manufacturing the most, and whose autocratic state has moved heaven and earth to provide cheap energy, steamroll the environmental movement, and maintain manufacturing primacy:

It’s possible that this is just a fundamental feature of human nature. Perhaps eventually, once we all have plenty of food, big houses filled with gadgets and nice furniture, and cheap enough transportation to go out to eat twice a week, our desires just naturally turn toward things like health care, entertainment, and spa visits for our dogs.

Nor is it clear that there’s any limit to dematerialization. It might be possible to immerse humans in totally realistic virtual reality environments — allowing us to live in any sort of world we wanted — for only a modest amount of energy. We could conceivably explore virtual galaxies, create virtual ecosystems, live as dinosaurs or sentient spaceships, experience hundreds of lives, all for the low price of an AI to run the whole simulation.

Hall doesn’t really talk about alternative future visions like this. His triumphant futures always revolve around the conquest of the physical — real spaceships, real weather control, real flying cars. And yet he never really explains why we should expend such massive amounts of energy and resources conquering the physical world — it’s simply presented as a triumphant, “Wouldn’t this be awesome?” kind of vision.

But it’s very rare for humans to undertake grandiose endeavors if similar or greater enjoyment can be had closer to home. We’re not going to conquer the stars just because engineers think it’s cool. This is a second limitation of engineerism — the conviction that difficult feats of engineering are desirable in and of themselves.

Of course, there are a few individuals who do think that conquering the physical universe is just really damn awesome, and occasionally they command enough resources to make it happen. But even then, it’s questionable whether they truly derive more value from the physical world or the virtual. Elon Musk has done far more to conquer space than any other human in the last half century, but he personally has never even been to orbit. He has spent a lot of time tweeting, though.

Maybe in the end, 140 characters is just what humanity wants the most?

The wrong energy revolution

Of course, I do think the United States needs more abundant energy. We excel in the production of services, but J. Storrs Hall is exactly right when he says that our failure to harness cheaper sources of energy has limited our ability to produce physical goods — and to undertake the kind of engineering feats that we might want to undertake if we had enough energy.

Hall blames America’s energy stagnation on culture — on “ergophobia” (fear of energy), and on an environmental movement that has become more of a religion than a scientifically guided enterprise. I think Hall is generally on the right track here, but I think he gets the specifics a bit wrong. Americans aren’t afraid of energy, they’re afraid of land use; the 70s saw the anti-growth movement impose restrictions not just on power plants, but on housing, factories, infrastructure, and every other kind of physical development.

And it was this more parochial environmentalism — the desire to preserve “open space” near people’s suburban houses — that paralyzed America’s physical economy far more than the climate movement. Endangered species law was often abused to block development, but the underlying motivation was almost always NIMBYism rather than green religion.

Where I think Hall goes even more wrong, though, is in his predictions about what kind of energy technology can break our long stagnation. Hall puts his faith in nuclear fission power, first and foremost. Only the coming of a “second atomic age”, he predicts, will make energy too cheap to meter. And like many, he blames misguided safety regulations for robbing us of this nuclear future.

On one hand, I think Hall is pretty much right about the past. Nuclear power has its risks, of course, but I agree that we significantly overstated the risks and overregulated nuclear power as a result. We obviously could have chosen a different path, because France actually did choose a different path. Most of France’s electricity comes from nuclear power, and has since the 1980s. That could have been us, too, if we hadn’t been so spooked by Three Mile Island.

But the idea that embracing nuclear would have led to cheap, plentiful energy is…well, pretty suspect. France has plenty of nuclear power, but its electricity costs 28 cents per kWh, compared to 18 cents in America. France’s electricity is much cleaner — nuclear power has allowed it to reduce its carbon emissions enormously. But nuclear has not made energy abundant in France.

Perhaps this is also because of regulation? Maybe France allows nuclear, but simply makes it too expensive. Other countries that encourage nuclear construction can bend the cost curve down, and harness scaling effects to make nuclear cheaper and cheaper…right?

Well…maybe. China has probably done the best job of bending the nuclear cost curve downward, and even there, reactor costs aren’t lower than they were in 2010:

But at the same time, there has been another energy revolution that has nothing to do with nuclear. Solar power has become cheaper at absolutely stupendous rates:

You’d think Hall would love the solar revolution, but he doesn’t even recognize that it exists. As far as I can tell, he only mentions solar once, and it’s to dismiss the whole thing with an airy hand-wave:

The currently fashionable “renewables,” such as wind and solar power, have largely escaped the attacks. Battery-powered electric cars are the darlings of the Greens. But this is because they are simply not capable of providing anywhere near the energy or range that civilization depends on at a price it can afford.

This belief — that nuclear power is for real and solar, wind, and electric cars are B.S. — seems to be part of American engineerism. I don’t see why it should be. Getting electricity from sunlight and trapping it in batteries is an inherently very cool engineering task. And yet if you talk to American engineers about energy, nine times out of ten it’s just nuclear, nuclear, nuclear.

Chinese engineers, on the other hand, are embracing the electric revolution with gusto. They’ve created electric cars so cheap and high-quality that they’re conquering the global auto market. And despite the fact that China has kept nuclear costs down, and is perfectly willing to build nuclear, it’s building a lot more solar:

J. Storrs Hall barely even mentions China in his book, and this is one of its biggest failings. We don’t have to think very hard about the hypothetical technological details of nuclear vs. solar; we can just watch what China does. China is ruthlessly focused on growing its economy, its manufacturing industries, and its geopolitical power; it is not swayed by hippie environmentalists. When coal was the cheapest power source, China burned as much as it could.

And yet now, China is building solar far faster than it’s building nuclear. Why? Because solar has, broadly speaking, won the technological race. Intermittency was the last big problem, and batteries have gotten good and cheap enough to make solar reliable. If this were not the case, China would not be transitioning its economy to solar power as rapidly as possible.

Why does American engineerism long for nuclear even after it’s clear it’s been surpassed (for most applications) by something even cheaper and better? My best guess is that this is a historical grudge. In the 70s and 80s, environmentalists told engineers they weren’t allowed to build nuclear power. A lot of engineers still chafe at being told what not to build, and some probably resent solar and batteries for being the things environmentalists told them to go build instead.

But this has resulted in a bunch of American engineers becoming trapped in a retrofuturistic daydream, unable to take advantage of the very real revolution in electric technology.

Why don’t we have flying cars?

Which brings me, at last, to flying cars. Hall spends a lot of the book explaining why flying cars are technologically feasible, going through details like the difficulty of flying a plane, prospects for a future air traffic control system to control high volumes of flying cars, and so on.

My guess is that human-piloted flying cars were always going to be a bridge too far, for safety reasons alone — teenagers probably can’t be trusted to fly aircraft over populated areas, to say nothing of potential terrorists. But in the age of AI, we probably don’t need human pilots; we can just automate everything. Here’s a video of EHang’s pilotless VTOL craft giving someone a ride:

The EHang vehicle can’t move along roads, so it isn’t a true, classic flying car. But…close enough, right?

EHang may take off, but for right now it’s a niche type of transportation, authorized at only a few select locations. China has built the world’s most extensive network of high-speed trains, but seems in no hurry to roll out flying cars to the masses. Why?

The obvious answer is that demand for flying cars is limited. Where are you going to go in a flying car? For short distances you already have ground cars, which go slower but are probably a lot cheaper to drive and easier to park. For long distances — international travel, business travel to other cities, etc. — you have airplanes, which are really just flying buses.

There’s an intermediate distance — maybe about 150 to 500 miles — where flying cars might be able to beat both airplanes and ground cars. I had GPT calculate travel times for ground cars, flying cars of the type described in J. Storrs Hall’s book, and airplanes:

Flying cars do OK over short distances, but over intermediate distances they’re the clear winner. (Incidentally, this is also the distance range over which high-speed rail is usually thought to compete effectively with cars and airplanes.)

The real question is what there is within 150 to 500 miles that you’d A) want to visit often enough to justify owning a flying car, and B) be willing to travel 1-3 hours to get to. You certainly don’t need to go that far to shop for groceries or go to the gym. You’re probably not going to go to that many restaurants that require you to travel 1-3 hours each way.

That basically leaves commuting and vacations.

A 1-hour commute is fairly punishing; a 2-hour commute is absolutely brutal; a 3-hour commute is impossible. For shorter commutes, cars (or trains, if they exist near you) work just fine. Even with flying cars, most people aren’t going to want to live 200 miles from their place of work.

As for vacations, these are rare. When people do take trips, they tend to take luggage (which is a lot more expensive to move through the air than along the ground). Planes work perfectly well for most trips, which leaves flying cars to handle short-range vacations. If you’re in San Francisco, that could mean a weekend in Tahoe or Yosemite, or a beach trip to Santa Barbara. Those trips are nice, I’m sure, but probably don’t come close to justifying the expense of flying cars.

In his book, J. Storrs Hall addresses this issue by arguing that if lots of people had flying cars, new destinations would spring up at the requisite distances. First of all, this completely ignores the cold start problem. Without enough flying cars, the new destinations can’t spring up; without enough destinations, owning a flying car is an unattractive proposition.

But even if tourist resorts and awesome restaurants and cool stores sprang up to blanket the American countryside in order to take advantage of swarms of flying cars, their business would have to be diverted from existing destinations closer to where people live. America is a very built-up country with lots of shops, restaurants, and entertainment spots. If you flew your flying car to go eat at a restaurant 100 miles away, you’d be spending almost an hour in transit each way, instead of driving 15 minutes to a restaurant nearby. Sure, you’ll go to the more distant restaurant sometimes, because it’s probably a lot more famous and high-quality than whatever happens to be in your local neighborhood. But will you go often enough to justify owning a flying car?

We should also consider changes in communication technology, which can substitute for some percentage of physical travel; we can now text or video chat with friends, colleagues, or even potential lovers some of the time instead of always driving to see them. Or we can simply amuse ourselves watching TikTok or reading Substacks instead of motoring around the countryside like in 1925 or cruising the strip like in 1960.

In Where Is My Flying Car?, Hall acknowledges this substitutability, but waves it away, saying it would be a shame if communication technology outpaced transportation technology. And yet that may be exactly what’s happening. Young Americans traveled fewer than half as many miles per day in 2022 as they did two decades earlier:

This is just another example of dematerialization of economic output. The internet is substituting for cars. And if the internet is substituting for regular cars, why are people going to rush out and buy flying cars?

In other words, the answer to the question in the title of this post is that you won’t get a flying car — at least, not anytime soon — because you don’t really want one.

This leads me, at last, to the biggest pitfall of engineerism: It focuses too much on supply and not enough on demand. To many engineers, the most important question is “Can we build this?”, not “Why would anyone want this?”. This is a common pitfall for startups, but it applies equally well to futurists (and retrofuturists).

Engineers can grouse all they want, but the blunt fact is that in the long run, technology gets built because human consumers want it. Sometimes, those consumers are governments, who want weapons for war and monuments to prove their greatness. That can sometimes look like building things just for the coolness factor, but in the end, monument-builders tire of making pyramids. And in capitalist, individualist, democratic societies — the kind Americans (roughly speaking) still live in today — the consumers are regular people who mostly just want to get to work on time, watch some funny stuff online, sleep in a comfy bed, and enjoy a nice night out or a vacation once in a while.

Engineers often fail to understand this. Building things is their passion; they want to build, build, build, because it’s awesome. But society will only give them the resources to build the truly big stuff — space elevators and Mars colonies and fleets of flying cars — if they can justify it with a broad-based value proposition. “Hey, let’s embrace our destiny and conquer the stars” makes for a fun rallying cry, but the actual future of technology will be driven by parents shopping for diapers.

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Heinlein’s “The Man who Sold the Moon” probably deserves to be on this list, but I actually haven’t read it.

This is also the mindset that Dan Wang ascribes to China’s leaders in his excellent book Breakneck.

In fact, the U.S. government is now trying again, with another $10 million effort.

In fact, just for fun, I spent a couple hours talking to AI about those calculations, and they are not, in fact, the only ones you need to do.

Session 18: Psychology and Economics
Thu, Sep 3 2026, 8:00am - Fri, Sep 4 2026, 7:00pm PDT

Thursday, September 3, 2026

Sep 3

8:00 am - 9:00 am PDT

Check-in and Breakfast

Sep 3

9:00 am - 9:40 am PDT

What do we really know about risk preferences for binary lotteries?

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Presented by: Charles D. Sprenger (California Institute of Technology)

Camila Farres (California Institute of Technology), Ted O’Donoghue (Cornell University)

We conduct a comprehensive experiment on decision-making for binary lotteries—specifically, lotteries that yield a positive amount or zero. Such lotteries form the basis of many empirical results revealing violations of expected utility (EU) and motivating behavioral alternatives. However, the space of binary lotteries has not been comprehensively explored, and thus the predictions of various behavioral alternatives to EU have not been fully assessed even within this limited domain. We provide this exploration, and discover empirical patterns that stand in stark contrast to the predictions of existing behavioral models. In particular, the data indicate that risk attitudes are driven largely by relative probability comparisons between two options, with absolute magnitudes of probabilities playing a minor role. We show that the data is largely consistent with the model of “upside potential” proposed by McGranaghan et al. (2025).

Sep 3

9:40 am - 10:20 am PDT

The Misallocation of High-Value Work

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Presented by: Jason Somerville (University of California, Santa Barbara)

Carl Meyer (Stanford University), Germán Reyes (Middlebury College)

Aggregate productivity depends on whether productive inputs are allocated to their highest-value uses. We document a novel form of misallocation within a single individual performing a cognitive task. In an online experiment, participants complete a 30-question mathematics exam with random question order and randomly timed enhanced incentives (“bonus boosts”). Performance falls by 9.5 percentage points from the first to the last question, and 82 percent of participants exhibit a decline. Yet 58.0 percent of participants report no preference over when to receive bonus boosts, and willingness to pay for these boosts is constant across timing options. This indifference is costly: assigning boosts early rather than late raises expected bonus earnings by 9 percent. The misallocation aligns with miscalibrated beliefs about productivity: pre-exam forecasts imply constant performance, and post-exam hindcasts capture only 55 percent of the actual decline. These findings identify miscalibrated beliefs about within-worker productivity trajectories as an under-recognized source of misallocation.

Sep 3

10:20 am - 11:00 am PDT

Break

Sep 3

11:00 am - 11:40 am PDT

Model-Directed Attention and the Persistence of Wrong Mental Models: Evidence from Firm Pricing

Presented by: David Huffman (Cornell University)

Yi Han (Renmin University of China), Yiming Liu (Humboldt University of Berlin)

We show a way that wrong mental models can persist even in data-rich environments, and potentially even resist encounters with peers who have the correct model: by remaining silent about data features they cannot explain, simple wrong models direct attention away from disconfirming patterns and explanations. Field evidence comes from 13,000 gas station managers, 20 percent of whom have a simple model, discounts raise sales, that is silent about intertemporal substitution (IS), evident in the data as sales dips before and after a pre-announced discount. Managers who neglect IS show measurable inattention to these dips, believe fuel demand is more elastic, set lower prices, earn lower profits, andtheir neglect persists with experience. Online experiments on Prolific provide tighter identification and causal evidence: exposure to the simple peer model reduces attention to IS patterns, while a targeted attention intervention raises recognition of those patterns and induces switching to the correct model. Encountering the correct model at a later stage helps correct beliefs, but does not fully undo the impact of having the wrong model first.

Sep 3

11:40 am - 12:20 pm PDT

Beliefs Over Contracts

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Presented by: Francis Annan (University of California, Berkeley)

Collin B. Raymond (Cornell University)

We study how firms choose among incentive contracts and how accurately managers predict their e!ects. Using a survey of managerial beliefs and a large-scale field experiment, we randomly assign agents at the market level to several widely used, expenditure-equivalent incentive schemes. In the field, the best-performing contract increases agent output and firm revenue by over 20% relative to the status quo, despite being ranked lower by managers, whereas the worst-performing contract performs as predicted. Managers correctly identify underperforming contracts but systematically underestimate top- performing ones. We document the sources of performance differences—labor supply responses rather than selection or pricing and the determinants of managerial predictability: contract complexity and managerial hierarchy. Our results highlight the importance of contract design for firm performance and reveal systematic limits to managerial cognition in shaping incentives.

Sep 3

12:20 pm - 2:00 pm PDT

Lunch

Sep 3

2:00 pm - 2:20 pm PDT

Do Firms Know What Workers Want?

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Presented by: Simon Cordes (University of Bonn)

Max Müller (University of Bonn)

Labor supply depends on wages and amenities, and standard models implicitly assume that firms hold accurate beliefs about workers’ amenity valuations. In a survey with firms and workers in Germany, we measure workers’ valuations of amenities and firms’ beliefs about workers’ valuations. We find that firms systematically underestimate workers’ valuations of all amenities. These misperceptions are driven by interpersonal projection: managers project their own preferences—they value amenities less—onto workers. Through the lens of a simple model of imperfect competition, we show that firm misperceptions result in (i) labor shortages and (ii) excess labor costs for biased firms, and increase the market power of unbiased firms. Empirical tests confirm these predictions: a simple calibration suggests that non-providing firms could reduce their labor costs by 5% by providing amenities.

Sep 3

2:20 pm - 2:40 pm PDT

Insuring Wisdom: Intermediaries in the Market for Medicare Advice

Presented by: Elaine Shen (University of California, Berkeley)

Margaret Kallus (University of California, Berkeley)

Sep 3

2:40 pm - 3:00 pm PDT

Knowledge Transfer and Strategic Similarity

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Presented by: Joseph Feffer (Stanford University)

Filip Tokarski (Stanford University)

This paper studies when strategic understanding acquired in one mechanism can be transferred to another. We introduce a framework in which agents’ knowledge is represented as a set of payoff comparisons they can make, and use it to formalize what it means to understand that a strategy profile is an equilibrium. We first apply this framework to mechanisms that are strategically equivalent—that is, share the same game form up to relabeling of actions—and show that agents’ understanding of equilibrium transfers across such mechanisms once the relevant action correspondences are explained to them. We then define strategic analogy, a weaker notion that allows not only actions but also types to be remapped, and show that understanding of equilibrium transfers across strategically analogous mechanisms once agents recognize how actions and types correspond. Applications include single item auctions, scoring auctions, and nonlinear pricing with capacity constraints.

Sep 3

3:00 pm - 3:20 pm PDT

Geographic Price Extrapolation, Learning, and Housing Search: Evidence from Danish Movers

Presented by: Matteo Saccarola (University of Chicago)

Using population-wide Danish administrative registers on housing transactions, I document an asymmetric, hockey-stick relationship between origin market prices and overpay- ment for comparable homes. Quantitatively, the elasticity of overpayment with respect to the origin-destination price difference is 3.9 percent (p < 0.01) when movers relocate from more expensive to cheaper housing markets. In contrast, buyers moving to more expensive locations exhibit little systematic overpayment, and their purchase prices are unrelated to prices at origin. I interpret these patterns through a housing search model in which buyers enter with price beliefs anchored in their origin market and update those beliefs gradually during search. Despite homogeneous learning, endogenous stopping generates the observed asymmetry at purchase: buyers predisposed to overpay transact quickly before fully learning the local price level, while those predisposed to underpay search longer and converge toward local prices. The model yields additional predictions that I test using administrative and survey data. The evidence supports origin-based price extrapolation with subsequent learning rather than preference-based explanations such as reference dependence.

Sep 3

3:20 pm - 4:00 pm PDT

Break

Sep 3

4:00 pm - 4:40 pm PDT

Strategically Controlling Worldviews

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Presented by: Danil Dmitriev (University of Georgia)

Cuimin Ba (University of Pittsburgh), Ziqi Hang (Texas Tech University), Freddie Papazyan (Texas Tech University)

This paper studies persuasive behavior when the sender can control both the information the receiver observes and the model through which it is interpreted (the narrative). Even when the receiver begins with a correctly specified model and understands the sender’s strategic incentives, the sender can manipulate him and often secure her preferred action with probability one. The key mechanism highlights a strong complementarity between strategic communication of information and narratives, allowing the sender to strictly outperform a Bayesian persuader with commitment power. We fully characterize the sender-optimal equilibrium for a broad class of information technologies. Softer information lowers the bar for full manipulation, while harder information expands the set of environments where any manipulation is possible. The results provide a formal foundation for understanding the widespread success of disinformation.

Sep 3

4:40 pm - 5:20 pm PDT

Deception Aversion

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Presented by: Evan Friedman (Paris School of Economics)

Béla Elmshauser (Paris School of Economics), Yoon Joo Jo (Texas A&M University)

In communicating private information, opportunities to lie by misreporting the truth also present opportunities to deceive by inducing inaccurate beliefs. While many studies document truth-telling despite material costs—commonly attributed to lying aversion—such behavior may also reflect aversion to deceiving others. Disentangling the two preferences is challenging because deception depends on the sender’s unobserved second-order beliefs. In a novel game, we show theoretically how to identify deception aversion from choice data alone, under minimal assumptions on beliefs. In a laboratory experiment, we find strong evidence of deception aversion: many subjects lie to avoid deception; structural estimates imply that 30% are deception-averse.

Sep 3

5:20 pm - 7:00 pm PDT

Dinner

Friday, September 4, 2026

Sep 4

8:00 am - 9:00 am PDT

Check-in and Breakfast

Sep 4

9:00 am - 9:40 am PDT

Limited Propagation and Contingent Thinking

View Paper

Presented by: Ran Spiegler (Tel Aviv University & University College London)

Andrew Ellis (London School of Economics)

Abstract. We model an agent who updates her beliefs over a set of variables after observing some of them without fully propagating their implications. We provide a representation of updated beliefs that exhibit limited propagation along a directed acyclic graph, and show that it is implemented by a variant on a standard propagation algorithm. Failures of contingent thinking occur when the agent’s inferences travel through fewer graph paths from hypothetical variables relative to given ones. We characterize the model’s relationship to Bayesian updating and familiar non-Bayesian benchmarks. Contingent thinking is necessary for Bayesian updating, and failures cause correlation neglect and violations of iterated expectations. Our frame- work offers a new perspective into experimental evidence on contingent thinking, reinterpreting effects such as the winner’s curse or the Monty Hall fallacy. We illustrate the framework with applications, ranging from public good contribution games to the recreational puzzle Kakuro.

Sep 4

9:40 am - 10:20 am PDT

Intergenerational Race-Based Trauma and Financial Market Participation

Presented by: Vicki Bogan (Duke University)

Lisa A. Kramer (University of Toronto), Chi Liao (University of Manitoba), Alexandra Niessen-Ruenzi (University of Mannheim)

This paper examines whether historical race-based financial trauma shapes current household financial market participation. Our analysis exploits geographic exposure to the Freedman’s Savings Bank (FSB), established in 1865 to encourage Black Americans to save. The bank collapsed in 1874 due to fraud and mismanagement. Using restricted-use Panel Study of Income Dynamics (PSID) data, we link present day stock ownership to historical FSB branch locations. Own, paternal, and grandpaternal FSB-county exposure is associated with lower stock market participation among Black individuals. These effects persist after controlling for socioeconomic and geographic differences, migration, and broader patterns of racial exclusion. Our findings reveal intergenerational transmission of race-based financial trauma and a robust mechanism perpetuating the racial wealth gap.

Sep 4

10:20 am - 11:00 am PDT

Break

Sep 4

11:00 am - 11:40 am PDT

Deadly Stigma

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Presented by: Manasvini Singh (Carnegie Mellon University)

How harmful is stigma in the “real world”? Answers are elusive because stigma is difficult to measure in observational data, and isolating its effects requires exogenous variation in stigma without variation in the stigmatized trait. This study addresses these challenges by focusing on a widespread form of stigma — weight stigma — in the high-stakes setting of inpatient healthcare. BMI categories are displayed prominently to providers in electronic medical records, and obesity is heavily stigmatized socially. The “obese” cutoff may thus discretely shift stigma while keeping constant the underlying trait. Using a regression discontinuity design that exploits this institutional feature, I find a discontinuous increase in in-hospital mortality at this cutoff, though patient health does not change. Two patterns suggest stigma-based discrimination as the mechanism. First, just-obese patients receive lower diagnostic effort than almost-obese patients. Second, a physician-validated LLM identifies a rise in stigmatizing language in clinical notes at the cutoff — specifically, statements that impose moral judgment, undermine patient credibility, and stereotype patients — that closely tracks mortality effects. Overall, this paper establishes stigma as a powerful social force that can have life-or-death consequences.

Sep 4

11:40 am - 12:20 pm PDT

Opt in? Opt out?

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Presented by: Alex Chan (Harvard University)

Ayush Gupta (Boston University), Yetong Xu (Harvard University)

Cadaveric organ shortages leave thousands without life-saving transplants each year. Countries differ in using opt-in (informed consent) or opt-out (presumed consent) systems for donor registration. Using newly assembled cross-country panel data and an event-study design, this paper provides evidence that presumed-consent laws increase organ donation only when strictly enforced and family veto power is limited; weak opt-out regimes show negligible or even negative effects. A theoretical signaling model provides a plausible mechanism when opt-in or opt-out yields more donations, emphasizing the roles of donation propensity, signaling costs, and the family’s ability to overturn defaults. A large laboratory experiment further tests these mechanisms, showing that opt-in generally produces equal or higher donation rates unless signaling is costly and family veto power is minimal. The results underscore that defaults alone rarely increase donations unless paired with strong institutional enforcement.

Sep 4

12:20 pm - 2:00 pm PDT

Lunch

Sep 4

2:00 pm - 2:40 pm PDT

State Dependence and Commitment: Experimental Evidence from Crop Insurance in Uganda

Presented by: Sili Zhang (Ludwig Maximilian University of Munich)

Lorenzo Casaburi (University of Zurich), Jack Willis (Sciences Po)

According to standard economic arguments, state dependence generates the value of flexibility. This paper proposes that it can instead generate demand for commitment when individuals anticipate that future states will distort their decisions. A conceptual framework models two broad channels—state-dependent valuations (e.g., projection bias) and state-dependent decision mistakes (e.g., scarcity effects)— and shows that sophistication about such future distortions can generate demand for commitment. We test this prediction in a field experiment in Uganda, where we exclude present bias as a source of commitment demand by design. Farmers are offered pay-at-harvest crop insurance for two seasons and can choose upfront whether to commit to second-season insurance or maintain flexibility. Forty percent of farmers choose commitment. An intervention increasing sophistication raises commitment by 11 percentage points. Additional evidence suggests that both channels matter with substantial heterogeneity across farmers. Our results highlight the importance of individuals’ sophistication about future state dependence for welfare analysis and policy design, particularly in environments with high state variability.

Sep 4

2:40 pm - 3:20 pm PDT

Behavioral Inequality: The Contribution of Decision-Making Frictions to Inequality

Presented by: Stefano DellaVigna (University of California, Berkeley)

Tim de Silva (Stanford University), Rohan Jha (University of California, Berkeley)

We provide the first systematic quantification of how decision-making frictions—such as failing to claim government benefits, choosing dominated insurance plans, not saving for retirement, and not quitting smoking—aggregate to affect inequality in income, consumption, and wealth. We review the existing literature and combine it with original analysis of survey data to estimate the prevalence and financial impact of 18 frictions across the income distribution. To make these frictions comparable, we develop a framework in which each friction is characterized by three parameters: the share of the population at risk, the share affected by the friction, and the average loss conditional on being affected. Aggregating across the frictions with dollar-loss estimates, the estimated impact on annual income is 7.8% for the bottom quartile of the income distribution relative to 4.2% for the top quartile; the total loss for low-income households is approximately 7.5 times larger than the impact of a major EITC expansion. We then incorporate these frictions into a life cycle model with realistic institutional features, including tax-advantaged retirement accounts, progressive taxation, portfolio choice, and a social insurance system. The model reveals that removing frictions tends to reduce inequality in lifetime consumption, with the largest effects coming from smoking and attending for-profit colleges. Our results suggest that decision-making frictions are a quantitatively important contributor to inequality in income, consumption, and wealth.

Sep 4

3:20 pm - 4:00 pm PDT

Break

Sep 4

4:00 pm - 4:40 pm PDT

A Practical Approach to Robust Policy Evaluation with Behavioral Agents

Presented by: Dmitry Taubinsky (University of California, Berkeley)

B. Douglas Bernheim (Stanford University)

Sep 4

4:40 pm - 5:20 pm PDT

What Motivates Partisan Selective Exposure? Experimental Evidence from the 2024 US Presidential Election

Presented by: Matt Gentzkow (Stanford University)

Peter Robertson (Stanford University), Michael Thaler (University College London)

Why do partisans prefer like-minded information sources? They may want to learn the truth and believe these sources are the most accurate. Or, they may prefer them for non-accuracy psychological forces such as confirmation bias. We evaluate these motives in two large-scale experiments in which 3,785 participants choose sources to help them predict swing-state winners in the 2024 US presidential election. Partisans exhibit substantial selective exposure, choosing like-minded sources both among real news outlets and among synthetic sources we construct. This behavior remains essentially unchanged under two treatments: (i) increasing incentives for accuracy and (ii) shutting down confirmation motives by having participants delegate their predictions to sources without seeing sources' content. In contrast, participants respond strongly to experimentally-varied source accuracy, even absent incentives. Our results, interpreted in reduced form and through a discrete-choice model, suggest the selective exposure in our experiment can be almost entirely explained by demand for accuracy.

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A pelican riding a bicycle with GPT-6 Astra

Creating a skill

So what happened?

UseMod wikis inherit CGI.pm's original sin

The other sandbox escape that allowed POST requests

How did the investigating team figure this out?

Did OpenAI try and cover this up?

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U.S. models are still better than Chinese models

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Do you disavow and denounce and denunciate?

Hate the game

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Bonus Quibble

If you want to support my work, please take out a premium subscription (just $6 per month).

Please support my work by taking out a premium subscription—just $6 per month.

Building for the ages

The math starts to shift

Where we're at

Where does that leave us?

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The Galileo Fallacy

To the stars! (But why?)

The wrong energy revolution

Why don’t we have flying cars?

Carmaggedon never comes

Portland’s own experience shows there’s no Autopocalypse

Why this happens: Traffic evaporation and induced demand

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Downloads

September 1, 2026

References & Resources

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Title IV — Accessing the American Dream

Title V — Program Reform

Title VI — Veterans and Housing

Title VII — Oversight and Accountability

Title VIII — Accountability, Coordination, Studies, and Reporting

Title IX — Strengthening Community Banks’ Role in Housing

Title X — Home-Ownership for Main Street America

Title XI — Central Bank Digital Currency

Title XII — Miscellaneous

Conclusion

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