Author: James Bailey

The Novelist Paradox

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If novelists are so smart, why don’t they succeed at much besides writing fiction?

When I read a good novel I think “the author must be very smart to be able to write this and understand people so well”.

But novelists tend not to be very successful at things in life other than writing fiction, certainly not at anything like the rate of people who write good non-fiction books.

Just off the top of my head, people who wrote good / highly acclaimed non-fiction books while also being highly successful in other fields:

  • Julius Caesar
  • Marcus Aurelius
  • Benjamin Franklin
  • Richard Feynman
  • Winston Churchill
  • Barack Obama
  • JD Vance
  • Many top economists (Keynes, Hayek, Friedman)

While off the top of my head, novelists who reached anything like that level of success in other fields include:

… No one?

The best that comes to mind is people that started philosophical movements related to their writing, like Ayn Rand, Scott Alexander, or Eliezer Yudkowsky. But that’s clearly a different kind of success than for most non-fiction authors. Likewise when I ask Claude the best examples I get are doctors, lawyers, and academics, not world leaders. I’ve been kicking this idea around for years but was inspired to finally write it down because I found out that before Ben Hur was a movie it was a wildly successful novel, and the novel was written by former Civil War general Lew Wallace (not a great general as they go, but its still impressive to be a general at all). But I still think that is the exception.

In fact, worse than just “not being world-changingly successful”, some of my favorite living novelists sometimes seem crushed by the weight of everyday tasks like giving public talks, maintaining relationships, or completing their work anywhere close to on time.

Naming the living novelists I’m thinking of would be mean so here’s F Scott Fitzgerald

The paradox: if novelists are so smart, why aren’t they more broadly successful?

Potential resolutions:

  1. I’m wrong and novelists actually are broadly successful.
  2. Novelists are so smart, but tend to have other deficits that keep them from being broadly successful, or from wanting to try, e.g. being neurotic introverts
  3. Novelists aren’t so smart, it’s more of a narrow skill that we shouldn’t expect to indicate general intelligence, like being good at painting or football.

The question can be flipped: why can’t / won’t many very successful people write fiction? Are they more grounded in the real world when it treats them well? I’m not ‘very successful’ but I write a lot. In my case I’m not convinced I could even write a bad novel, much less a good one. Wouldn’t know where to start.

Cunningham’s Law Update: John Giebfried writes in with excellent counterexamples along the lines of resolution #1-

Making Friends In Politics Is Possible

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I knew getting involved in politics was a great way to make enemies, but it never occurred to me until I saw it in action that it can also be a way to make friends.

I’m still not very involved, even as academics go. I think many of us are a bit too eager to talk about political issues in general, but too slow to engage with the policy process in areas directly tied to our research. It’s hard to keep track of every relevant bill and proposed regulation, but I think we bring the most value when we’re the 3rd person to weigh in to share what the research says on an obscure topic, rather than the 3000th person to weigh in on a hot-button issue with a take that sounds just like everyone else on the same side.

My biggest surprise when testifying in state legislatures or public hearings has been that friends follow through while opponents don’t. People who disagree with me will say so at the time, then leave it at that. But people who agree with me will follow up afterwards with messages like “thanks for saying that” or “let’s get coffee”, or let me know when related issues come up.

Perhaps this is unusual, just some good luck in a small sample size, or a reflection of the fact that I only weigh in on relatively obscure issues far from the culture war. But again, I never even thought of this as a possibility. I still wouldn’t run for office any time soon. But if this wasn’t already obvious to everyone else, I encourage you to add this as one term in your own equation as you weigh the pros and cons of political engagement: “nudge the policy process in directions you like” + “engagement takes time and energy and makes enemies” + “maybe friends too”.

How Much To Trust Research Papers? My Rules Of Thumb

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  1. Trust literatures over single papers
  2. Common sense and Bayes’ Rule agree: extraordinary claims require extraordinary evidence
  3. Trust more when papers publicly share their data and code
  4. Trust higher-ranked journals more up to the level of top subfields (e.g. Journal of Health Economics, Journal of Labor Economics), but top general-interest journals can be prone to relaxing standards for sensationalist or ideologically favored claims (e.g. The Lancet, PNAS, Science/Nature when covering social science)
  5. More recent is better for empirical papers, data and methods have tended to improve with time
  6. Overall effects are more trustworthy than interaction or subgroup effects, the latter two are easier to p-hack and necessarily have lower statistical power
  7. Trust large experiments most, then quasi-experiments, then small experiments, then traditional regression (add some controls and hope for the best)
  8. The real effect size is half what the paper claims

That last is inspired by a special issue of Nature out today on the replicability of social science research. An exception to rule #4, this is an excellent project I will write more about soon.

Experimental Banking Reveals the Value of Leisure

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In 2014 India required banks to offer no-cost accounts. This led hundreds of millions of people to open bank accounts for the first time, and more than doubled the number of Indian women who had a bank account:

This increased households’ collective ability to save and borrow, but didn’t shift decision-making power towards women despite the larger change for them. That is the finding of a paper by Tarana Chauhan, a Brown University postdoc who is currently on the job market. The paper is a well-executed example of a difference-in-difference analysis of observational data- that is, carefully examining data that other people generated to examine events that help establish causality. But the validity of difference-in-difference strategies in separating correlation from causation can always be questioned, and always is in economics seminars.

So Dr. Chauhan, this time with coauthors Berber Kramer, Patrick Ward and Subhransu Pattnaik, followed up by directly running an experiment. They got a company to offer subsidized loans to hundreds of randomly selected Indian farmers, then surveyed the farmers to see if they behaved differently than a control group that didn’t get loans. The loans carried a 14% interest rate, which seems high to Americans but was apparently 10pp lower than the other options available in India. They wanted to know whether farmers would use the loans to improve farm productivity, and whether this would have any differential effects on women.

The first stage of the experiment worked: households took the loans and got more engaged with the financial system.

Some used the money for smartphones:

But for the most part they seem not to have spent the money on farming- they didn’t buy significantly more land, seeds, fertilizer, or farm equipment. They did spend more on “non-farm business equipment” and “large consumer durables”. Despite not producing more food themselves, they reported higher food security. Income stayed flat, but women were able to shift some time away from work and toward leisure:

I find these results surprising given how poor the households receiving the loans are. They earn the equivalent of about $1,000/yr, putting them around the global “extreme poverty” line. At that income level I’d think they would value additional income highly relative to leisure, and yet when they get the loan, work time goes down and leisure time increases. Could it really be the case that they’ve already hit their income target, and are on the backward bending part of the labor supply curve? Some other possibilities are that they don’t expect that investing in farming would increase yields enough to be worthwhile, or that they worry any increased income would be taken away through explicit or implicit taxes. But the households generally seem better off as a result of the loan.

The other surprise- enough of the loans were paid back that the lenders made a profit despite the research pushing the interest rate below-market.

Does Broadband Bring Jobs?

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No, according to a new paper from the University of Georgia’s Michael Kotrous.

Many people expected it to, partly by thinking about the jobs that could benefit from faster internet, and partly by looking at the experience of Chattanooga, Tennessee. Chattanooga was the first major city to get gigabit-speed broadband, and they did see a huge improvement in the labor market right afterwards:

But as the graph shows, the introduction of broadband there coincides with the end of the nationwide Great Recession. Was the boom in jobs after 2009 because of the broadband, or would it have happened anyway as party of the recovery from recession? A synthetic control strategy shows that Chattanooga’s recovery was pretty typical for cities like it, so the broadband angle probably didn’t do much:

This might seem like a historical curiosity about one city, but the federal government is currently trying to spend $42 billion to expand broadband to more places, partly motivated by the idea of bringing jobs. I thought the Broadband Equity Access and Deployment Program‘s big problem is how slow it is- Congress created with the Infrastructure Investment and Jobs Act of 2021, but money didn’t start getting sent out until late 2025, and it could be many more years before it leads to any useable broadband. Even then it now seems unlikely to bring jobs, though there could be other benefits.

This paper’s author Michael Kotrous is currently on the economics job market. As his former professor and coauthor, I recommend hiring him if your school gets the chance.

Is a US Oil Export Ban Coming?

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The Iran regime’s military strategy seems to be that by bombing the oil infrastructure of their neighbors and neutral shipping, US gasoline prices will go so high that Americans will demand an end to the war.

How many Americans would be willing to pay $6/gallon gas for months for a ~50% chance of toppling a regime that oppresses 90 million people and destabilizes its region on the other side of the world? Probably only a minority of voters, especially when the President didn’t make the case to the American people or Congress beforehand.

But the US produces more than enough oil for its own needs. Why does the Strait of Hormuz being closed mean higher gas prices here? Only because US oil companies can sell to global markets, and they won’t choose to sell a barrel of oil to a US refiner for $60 when they could sell it to a foreign refiner for $100. If the government took away the foreign option, US oil producers would sell to US refiners at prices consistent with pre-war sub-$3/gallon gasoline.

Naturally there would be costs to an export ban. US oil producers would miss out on windfall profits, while Russian producers would benefit. Foreign customers of US oil, many of them in allied countries, would be angered by the missed shipments and global oil prices would soar further.

But if the US administration wants to avoid a midterm wipeout driven by high gas prices, I see only 3 options:

  1. Get lucky and see the Iranian regime fall quickly
  2. Negotiate an end to the war quickly (which might itself be unpopular if they can’t get a good deal) or just declare victory and go home (but its not clear whether Iran would re-open the strait now just because the US stopped bombing)
  3. Restrict Exports

I say “restrict” not “ban” because I don’t think a complete export ban is necessary to stabilize US prices. You could instead do an export tax (high enough to stop many exports but low enough to allow the buyers with the highest values / fewest alternatives to stay in the market), or you could do a ban but allow a few export waivers for favored buyers or sellers (which seems like Trump’s style), or similarly a quota limiting exports to a certain number (say, limit each company’s monthly exports to 90% of their volume in the same month last year).

This has an obvious precedent: the Biden administration stopped issuing new permits to export liquified natural gas in 2024 to prevent prices spiking here during the Ukraine war (which led to even higher prices for our European allies). But a total ban on oil exports would be a much bigger deal.

Will the Trump administration actually try something like this? It will be an interesting test of US political economy to see what happens when the interests of the military-industrial complex conflict with the interests of oil producers.

Iran on Markets, Markets on Iran

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We’re bombing Iran, and Iran is now bombing most of its neighbors. Oil prices are up ~20% since the bombing began last weekend, and stocks are down.

Iranian “Supreme Leader” Khamenei is now dead. Prediction markets sort of saw this coming; I mentioned here a month ago that markets thought it more likely than not that Khamenei would be “out of office” this year.1

Real-money US-regulated exchanges can’t directly cover the war, but others can and do, such as the international Polymarket:

Polymarket’s argument for why they offer these markets

This market shows that regime change is likely, but will take time- a 51% chance by the end of the year, but only a 13% chance by the end of the month.

How would this be achieved? Markets see a 60% chance that there will be US troops in Iran this year, though this market could be triggered by just a few special forces operators, or by troops visiting for humanitarian purposes after domestically-driven regime change. There will likely be a US-Iran ceasefire by the end of May. It’s not clear at all who will be running Iran at the end of the year:

Iran is far from the only country whose future leadership is unclear. Last month I noted that the current leaders of Britain, Hungary, and Cuba would likely be out of office by year end. These are all now looking even more likely than they did a month ago:

So I’ll repeat:

Myself, I find most of these market odds to be high, and I’m tempted to make the “nothing ever happens” trade and bet that everyone stays in office. But even if all these markets are 10pp high, it still implies quite an eventful year ahead. Prepare accordingly.

  1. US-regulated exchanges can’t offer markets on death. Kalshi’s rules stated that if Khamenei died, the market would refund everyone at current prices rather than paying as if he were “out of office”. When he died many people got mad at Kalshi- some who had bet he’d be “out of office” and were mad that they weren’t paid at 100%, others that Kalshi was offering something too close to a death market- “how else would he lose power” (even though Maduro and Assad provide clear recent examples) ↩︎

Humanity’s Last Exam in Nature

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Last July I wrote here about “Humanity’s Last Exam”:

When every frontier AI model can pass your tests, how do you figure out which model is best? You write a harder test.

That was the idea behind Humanity’s Last Exam, an effort by Scale AI and the Center for AI Safety to develop a large database of PhD-level questions that the best AI models still get wrong.

The group initially released an arXiV working paper explaining how we created the dataset. I was surprised to see a version of that paper published in Nature this year, with the title changed to the more generic “A benchmark of expert-level academic questions to assess AI capabilities.”

One the one hand, it makes sense that the core author groups at the Center for AI Safety and Scale AI didn’t keep every coauthor in the loop, given that there were hundreds of us. On the other hand, I’m part of a different academic mega-project that currently is keeping hundreds of coauthors in the loop as it works its way through Nature. On the third, invisible hand, I’m never going to complain if any of my coauthors gets something of ours published in Nature when I’d assumed it would remain a permanent working paper.

AI is now getting close to passing the test:

What do we do when it can answer all the questions we already know the answer to? We start asking it questions we don’t know the answer to. How do you cure cancer? What is the answer to life, the universe, and everything? When will Jesus return, and how long until a million people are convinced he’s returned as an AI? Where is Ayatollah Khamenei right now?

My First Exit

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I invested in my first private company in 2022; my first opportunity to cash out of a private investment came this year when Our Bond did an IPO, now trading on Nasdaq as OBAI.

I’m happy to get a profitable exit less than 4 years after my first investment, given that I’m investing in early-stage companies. Venture funds tend to run for 10 years to give their companies time to IPO or get acquired, and WeFunder (the private investment platform I used) says that “On average, companies on Wefunder that earn a return take around 7 years to do so.” The speed here is especially striking given that I didn’t invest in Our Bond itself until April 2025.

Most private companies that raise money from individual investors are very early stage, what venture capitalists would call “pre-seed” or “seed-stage” companies looking for angel investors. Later-stage companies often find it simpler to raise their later stages (Series B, et c) from a few large institutional investors. But a few choose to do “community rounds” and allow individuals to invest later. This is what Our Bond did right before their IPO, allowing me to exit in less than a year.

This helps calm my biggest concern with equity crowdfunding- adverse selection:

The companies themselves have a better idea of how well they are doing, and the best ones might not bother with equity crowdfunding; they could probably raise more money with less hassle by going to venture funds or accredited angel investors.

My guess is that the reason some good companies bother with this is marketing. Why did Substack bother raising $7.8 million from 6000 small investors on WeFunder in 2023, when they probably could have got that much from a single VC firm like A16Z? They got the chance to explain how great their company and product is to an interested audience, and to give thousands of investors an incentive to promote the company. Getting one big check from VCs is simpler, but it doesn’t directly promote your product in the same way.

All this is enough to convince me that the equity crowdfunding model enabled by the 2012 JOBS Act will continue to grow.

Still, things could have easily gone better for me, as these markets are clearly inefficient and have complexities I’m still learning to navigate. Profitability is not just about choosing the right companies to invest in, but about managing exits. I expected the typical IPO roadshow would give me months of heads-up, but Our Bond surprised its investors with a direct listing. The first thing I heard about the IPO was a February 4th email from “VStockTransfer” that I thought was a scam at first, since it was a 3rd-party company I’d never heard of asking me to pay them money to access my shares. But Our Bond confirmed it was real- VStockTransfer was the custodian for the private shares, and charges $120 to “DRS transfer” them to a brokerage of your choice where they can be sold.

I submitted the request to move the shares to Schwab the same day, but Schwab estimated it would take a week to move them. Neither Schwab nor VStockTransfer ever sent me a notification that the shares had been transferred, and by the time I noticed they had moved a week later, the stock price had fallen dramatically:

As I write this on February 18th, the OBAI price represents a 1.3x return on the price I invested in the private company at last April. When I was first able to sell some stock on February 11th, the price represented a 3x return; if I’d been able to sell right away on the 4th without waiting for the brokerage transfer process, it would have been a 10x return.

By the Efficient Market Hypothesis this timing shouldn’t be so critical, but I knew there would be a rush for the exits as lots of private investors would want to unload their shares at the first opportunity, an opportunity some would have waited years for. Sometimes old-fashioned supply and demand analysis is a better guide to markets than the EMH: demand for OBAI stock had no big reason to change in February, but freely floating supply saw a big increase as private shares got unlocked and moved to brokerages.

Getting a 10x return vs a 1.3x return on one of your winners is the difference between a great early investor and a bad one. I always thought such differences would be driven by who picks the best companies to invest in, but at least in this case it could be driven by who is fastest on the draw with brokerage transfers.

If I ever find myself holding shares in another company that does a direct listing, I’ll be doing whatever I can to make sure the transfer goes as fast as possible (pick the fastest brokerage, check on the transfer status every day, et c). This process also seems like one reason to do fewer, larger private investments- a fixed $120 transfer fee is a big deal if the initial investment was in the low hundreds but wouldn’t matter much for a larger one.

Being accredited would help there, allowing access to additional later-stage, less-risky companies. But I’ll call OBAI a win for equity crowdfunding, and a big win for asset pricing theories based on liquidity and flows over efficient estimation of the present discounted value of future cashflows.

Disclaimer: I still hold some OBAI

Commodity Sports

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I’m trying to coin “Commodity Sports” as the term to refer to sports betting that takes place on exchanges regulated by the US Commodity Futures Trading Commission, as opposed to sports betting that takes place through casinos regulated by state gaming commissions. So far it seems to be working alright, I haven’t convinced Gemini but have got the top spot in traditional Google search:

That article- Will Commodity Sports Last?– is my first at EconLog. I’m happy to get a piece onto one of the oldest economics blogs, one where I was reading Arnold Kling’s takes on the Great Recession in real time, where I was introduced to Bryan Caplan’s writing before I read his books, and where Scott Sumner wrote for many years (though I started reading him at The Money Illusion before that).

The key idea of the piece, other than the legal oddity of sports betting sharing a legal category with corn futures, is that the Commodity Sports category is being pioneered by prediction markets like Kalshi. As readers here will know, I like prediction markets:

I love that CFTC-regulated exchanges like Kalshi and Polymarket are bringing prediction markets to the mainstream. The true value of prediction markets is to aggregate information dispersed across the world into a single number that represents the most accurate forecast of the future.

But I’m not so excited to see them expanding into sports:

Although I see huge value in prediction markets when they are offering more accurate forecasts on important issues that help policymakers, businesses, and individuals make more informed plans for our future (e.g., Which world leaders will leave office this year?, or Which countries will have a recession?)… I see much less value in having a more accurate forecast of how many receptions Jaxon Smith-Njigba will have.

Like Robin Hanson, I worry that the legal battles against Commodity Sports and the brewing cultural backlash against sports betting risk taking the most informative prediction markets down along with it.

The full piece is here.