MR Podcast: Insurance!

In our new Marginal Revolution Podcast Tyler and I talk insurance, the history of insurance, the economics of insurance, the prospects for new types of insurance and more. Did you know that life insurance was once considered repugnant and was often illegal?

Tyler and I were both surprised how little good work there is on insurance. Here’s Tyler:

[Y]ou look at microeconomic theory. You feel all insurance should be a simple thing. There is risk aversion. You buy the contract. You look at the actual history. It’s very hard to make sense of it. The more I learned, I found the more questions I had. I didn’t fall into some, oh, now I understand what was happening kind of pattern. And the second is simply, I had been underrating Charles Ives. He was more than a great composer. Those are my takeaways.

Here’s one more bit:

COWEN: I want to get to the big, big question about insurance and see what you think. This is my worry. My worry is the agency problems behind insurance never have been solved.

….TABARROK: It is a peculiar market in the sense that all of your revenues come early.

COWEN: That’s right.

TABARROK: You’re selling all of this insurance, and everything is great because all of the money is coming in and your costs don’t come until much, much later. Your customers need to be convinced that you’re going to be around for a long time and are going to fulfill these implicit debts. Which is one reason insurance companies like to have big buildings with giant columns, like banks, to make them look solid. How do we guarantee that? I absolutely agree that’s a huge problem. I hate to say, but, there is a lot of insurance regulation which is precisely meant to deal with this problem.

COWEN: At the state level, you can choose the state. There’s reinsurance through Bermuda or other locales….[But] the problem is not just the company, it’s the person buying the insurance. You could have an insurance company. They advertise, we hold only T-bills and you know they’re safe. People don’t want that. It’s not what I would want. I want the riskier life insurance to get a higher return on the package.

The fact that it’s not for me, makes it really easy to spend for something that promises higher return. They don’t pay it all off, or oh, whatever, but I’ll be dead then, and you don’t think that explicitly. But your ability to monitor the true safety is maybe fairly weak. Maybe it’s efficient to have a bunch of these not pay off, and you get the higher yields on average. You don’t want full safety in most spheres of human existence. The real risk is that you die, right?

TABARROK: If anything, the insurance markets have becoming safer over time because as they get larger, law of large numbers does mean that the risk falls.

COWEN: Assets are more and more correlated over time, I would say.

TABARROK: Well, so we have reinsurance…

COWEN: It’s not that everyone’s going to die at once. The problem is the assets all go crazy at the same time. The world’s more globalized, the gains in the S&P 500 have been concentrated in seven or eight stocks lately. There’s a lot of worrying signs on the asset side, this higher correlation and the law of large numbers is working against you. Fewer publicly traded companies. A place like China is not really somewhere you’re going to be investing in. Maybe you would have thought that 15 years ago. It seems to me going in the wrong direction.



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Will Trump Appoint a Great FDA Commissioner?

A German newspaper asked for my take on the nomination of RFK Jr. to head HHS. Here’s what I said:

Operation Warp Speed stands as the crowning achievement of the first Trump administration, exemplifying the impact of a bold public-private partnership. OWS accelerated vaccine development, production, and distribution beyond what most experts thought possible, saving hundreds of thousands of American lives and demonstrating the power of American ingenuity in a time of crisis.

By nominating Robert F. Kennedy Jr., a prominent anti-vaccine activist, President Trump undermines his own legacy, and casts doubt on his administration’s commitment to protecting American lives through science-driven health policy.

Many better choices are available. Here is my 2017 post on potential people to head the FDA, many of which would also be great at HHS. No indent. Key points remain true.

As someone who has written about FDA reform for many years it’s gratifying that all of the people whose names have been floated for FDA Commissioner would be excellent, including Balaji SrinivasanJim O’NeillJoseph Gulfo, and Scott Gottlieb. Each of these candidates understands two important facts about the FDA. First, that there is fundamental tradeoff–longer and larger clinical trials mean that the drugs that are approved are safer but at the price of increased drug lag and drug loss. Unsafe drugs create concrete deaths and palpable fear but drug lag and drug loss fill invisible graveyards. We need an FDA commissioner who sees the invisible graveyard.

Each of the leading candidates also understands that we are entering a new world of personalized medicine that will require changes in how the FDA approves medical devices and drugs. Today almost everyone carries in their pocket the processing power of a 1990s supercomputer. Smartphones equipped with sensors can monitor blood pressure, perform ECGs and even analyze DNA. Other devices being developed or available include contact lens that can track glucose levels and eye pressure, devices for monitoring and analyzing gait in real time and head bands that monitor and even adjust your brain waves.

The FDA has an inconsistent even schizophrenic attitude towards these new devices—some have been approved and yet at the same time the FDA has banned 23andMe and other direct-to-consumer genetic testing companies from offering some DNA tests because of “the risk that a test result may be used by a patient to self-manage”. To be sure, the FDA and other agencies have a role in ensuring that a device or test does what it says it does (the Theranos debacle shows the utility of that oversight). But the FDA should not be limiting the information that patients may discover about their own bodies or the advice that may be given based on that information. Interference of this kind violates the first amendment and the long-standing doctrine that the FDA does not control the practice of medicine.

Srinivisan is a computer scientist and electrical engineer who has also published in the New England Journal of Medicine, Nature Biotechnology, and Nature Reviews Genetics. He’s a co-founder of Counsyl, a genetic testing firm that now tests ~4% of all US births, so he understands the importance of the new world of personalized medicine.

The world of personalized medicine also impacts how new drugs and devices should be evaluated. The more we look at people and diseases the more we learn that both are radically heterogeneous. In the past, patients have been classified and drugs prescribed according to a handful of phenomenological characteristics such as age and gender and occasionally race or ethnic background. Today, however, genetic testing and on-the-fly examination of RNA transcripts, proteins, antibodies and metabolites can provide a more precise guide to the effect of pharmaceuticals in a particular person at a particular time.

Greater targeting is beneficial but as Peter Huber has emphasized it means that drug development becomes much less a question of does this drug work for the average patient and much more about, can we identify in this large group of people the subset who will benefit from the drug? If we stick to standard methods that means even larger and more expensive clinical trials and more drug lag and drug delay. Instead, personalized medicine suggests that we allow for more liberal approval decisions and improve our techniques for monitoring individual patients so that physicians can adjust prescribing in response to the body’s reaction. Give physicians a larger armory and let them decide which weapon is best for the task.

I also agree with Joseph Gulfo (writing with Briggeman and Roberts) that in an effort to be scientific the FDA has sometimes fallen victim to the fatal conceit. In particular, the ultimate goal of medical knowledge is increased life expectancy (and reducing morbidity) but that doesn’t mean that every drug should be evaluated on this basis. If a drug or device is safe and it shows activity against the disease as measured by symptoms, surrogate endpoints, biomarkers and so forth then it ought to be approved. It often happens, for example, that no single drug is a silver bullet but that combination therapies work well. But you don’t really discover combination therapies in FDA approved clinical trials–this requires the discovery process of medical practice. This is why Vincent DeVita, former director of the National Cancer Institute, writes in his excellent book, The Death of Cancer:

When you combine multidrug resistance and the Norton-Simon effect , the deck is stacked against any new drug. If the crude end point we look for is survival, it is not surprising that many new drugs seem ineffective. We need new ways to test new drugs in cancer patients, ways that allow testing at earlier stages of disease….

DeVita is correct. One of the reasons we see lots of trials for end-stage cancer, for example, is that you don’t have to wait long to count the dead. But no drug has ever been approved to prevent lung cancer (and only six have ever been approved to prevent any cancer) because the costs of running a clinical trial for long enough to count the dead are just too high to justify the expense. Preventing cancer would be better than trying to deal with it when it’s ravaging a body but we won’t get prevention trials without changing our standards of evaluation.

Jim O’Neill, managing director at Mithril Capital Management and a former HHS official, is an interesting candidate precisely because he also has an interest in regenerative medicine. With a greater understanding of how the body works we should be able to improve health and avoid disease rather than just treating disease but this will require new ways of thinking about drugs and evaluating them. A new and non-traditional head of the FDA could be just the thing to bring about the necessary change in mindset.

In addition, to these big ticket items there’s also a lot of simple changes that could be made at the FDA. Scott Alexander at Slate Star Codex has a superb post discussing reciprocity with Europe and Canada so we can get (at the very least) decent sunscreen and medicine for traveler’s diarrhea. Also, allowing any major pharmaceutical firm to produce any generic drug without going through a expensive approval process would be a relatively simply change that would shut down people like Martin Shkreli who exploit the regulatory morass for private gain.

The head of the FDA has tremendous power, literally the power of life and death. It’s exciting that we may get a new head of the FDA who understands both the peril and the promise of the position.

Signaling Quality in Crowdfunding Projects with Refund Bonuses

My latest paper, Signaling Quality: How Refund Bonuses Can Overcome Information Asymmetries in Crowdfunding (with the excellent Tim Cason and Robertas Zubrickas) is just published in Management Science.

Many promising crowdfunding projects fail due to a fundamental issue: trust. Potential backers often hesitate because they lack confidence in the credibility or viability of the projects. This gap is natural, as traditional bank financing involves a bank acting as an intermediary, vetting the project, assessing its risk, and effectively endorsing it with their reputation. In contrast, crowdfunding operates without such intermediaries. Backers rely on limited, often one-sided information provided by project creators, making it challenging to assess risks or validate claims. Unlike banks, which can access financial records, credit histories, and industry expertise, individual backers typically lack the time, resources, or skills to conduct rigorous due diligence. Moreover, assessing risk is expensive. So how can we convey information about the true value of a crowdfunding project to investors?

Here my co-authors and I turn to refund bonuses. We have previously shown in lab experiments that refund bonuses can dramatically increase the rate of success of crowdfunding contracts and, more generally, make it possible to produce public goods privately. The idea of a refund bonus is simple. In an ordinary Kickstarter-like contract, if a project fails to raise enough funds to reach its threshold, the funds are returned to the investors. In a refund bonus contract, if a project fails to reach its threshold the investors get their money back plus a refund bonus. The effect of the refund bonus is to make investing in socially valuable projects a no-lose proposition. Either the project succeeds which is great because the project is worth more than its cost or it fails and you get a refund bonus. The investor is better off either way.

Now consider the refund bonus from the point of view of the entrepreneurs. An entrepreneur who offers a refund bonus has a special reason to want their project to succeed, namely, if the project succeeds they don’t have to pay the refund bonus. Entrepreneurs know more about the quality of their project than investors. The entrepreneurs, for example, know the truth about their advertising campaign. Does the cool demo really work or was it puffery or worse? Entrepreneurs who offer refund bonuses are thus implicitly offering a kind of testament or bond–I am so confident that this project will succeed that I am willing to offer a refund bonus if it doesn’t succeed. As with a warrantee, the point of the warrantee is not that consumers will use it but that they won’t. The warrantee is a signal of quality. Similarly, we show that offering refund bonuses can signal quality.

Working out the equilibrium requires some game theory because if refund bonuses 100% guaranteed high-quality (i.e. if only entrepreneurs with high quality projects offered refund bonuses) then every project that offered refund bonuses would succeed but then entrepreneurs with lower quality projects wouldn’t fear offering refund bonuses. Thus, the equilibrium is mixed, all entrepreneurs with high quality projects offer refund bonuses but some entrepreneurs with low quality projects also offer refund bonuses. Nevertheless, the equilibrium is such that on average refund bonuses signal quality. We test the theory in a lab experiment and it works. Investors were significantly more likely to put their money into projects where the  entrepreneurs chose to offer refund bonuses (n.b. this is in comparison to experiments where refund bonuses were imposed, i.e. we specifically test the signaling role of refund bonuses.)

Thus, refund bonus for crowdfunding provide a decentralized method of reducing asymmetric information. The refund bonus credibly allows information about quality to be transmitted from the entrepreneur to the investors. The bottom line is that refund bonuses increase the power of crowdfunding finance making it more competitive with intermediated finance.

Addendum: Here is an excellent podcast on refund bonuses and crowdfunding. “Refund bonuses could revolutionize crowd funding!”

The 1970s Crime Wave

Tyler and I wrap up our series of podcasts on the 1970s with The 1970s Crime Wave. Here’s one bit:

TABARROK: …people think that mass incarceration is a peculiarly American phenomena, or that it came out of nowhere, or was due solely to racism. Michelle Alexander’s, The New Jim Crow, takes his view. In fact, the United States was not a mass incarceration society in the 1960s.

It became one in the 1980s and 1990s due to the crime wave of the 1970s. It was not simply due to racism. It is true Blacks do commit more crimes relative to their population than whites, but Blacks are also overrepresented as victims. The simple fact of the matter is that Black victims of crime, the majority group, demanded more incarceration of Black criminals. In 1973, the NAACP demanded that the government lengthen minimum prison terms for muggers, pushers, and first-degree murders.

The Black newspaper, the Amsterdam News, advocated mandatory life sentences for “the non-addict drug pusher of hard drugs.” The Black columnist, Carl Rowan, wrote that “locking up thugs is not vindictive.” Eric Holder, under Obama, he was the secretary of—

COWEN: Of something.

TABARROK: Yes, of something. He called for stop and frisk. Eric Holder called for stop and frisk. Back then, the criminal justice system was also called racist, but the racism that people were pointing to was that Black criminals were let back on the streets to terrorize Black victims, and that Black criminals were given sentences which were too light. That was the criticism back then. It was Black and white victims together who drove the punishment of criminals. I think this actually tells you about two falsehoods. First, the primary driver of mass imprisonment was not racism. It was violent crime.

Second, this also puts the lie, sometimes you hear from conservatives, to this idea that Black leaders don’t care about Black-on-Black crime. That’s a lie. Many Black leaders have been, and were, and are tough on crime. Now, it’s true, as crime began to fall in the 1990s, many Blacks and whites began to have misgivings about mass incarceration. Crime was a huge problem in the 1970s and 1980s, and it hit the United States like a brick. It seemed to come out of nowhere. You can’t blame people for seeking solutions, even if the solutions come with their own problems.

A lot of amazing stuff in this episode. Here’s our Marginal Revolution Podcast 1970s trilogy

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Info Finance

Excellent post by Vitalik on prediction markets and the broader category of what he calls info finance:

Now, we get to the important part: predicting the election is just the first app. The broader concept is that you can use finance as a way to align incentives in order to provide viewers with valuable information.

…Similar to the concept of correct-by-construction in software engineering, info finance is a discipline where you (i) start from a fact that you want to know, and then (ii) deliberately design a market to optimally elicit that information from market participants.

Info finance as a three-sided market: bettors make predictions, readers read predictions. The market outputs predictions about the future as a public good (because that’s what it was designed to do).

One example of this is prediction markets: you want to know a specific fact that will take place in the future, and so you set up a market for people to bet on that fact. Another example is decision markets: you want to know whether decision A or decision B will produce a better outcome according to some metric M. To achieve this, you set up conditional markets: you ask people to bet on (i) which decision will be chosen, (ii) value of M if decision A is chosen, otherwise zero, (iii) value of M if decision B is chosen, otherwise zero. Given these three variables, you can figure out if the market thinks decision A or decision B is more bullish for the value of M.

Importantly, Vitalik notes that AI agents can make decision and prediction markets more liquid at much lower cost.

One technology that I expect will turbocharge info finance in the next decade is AI (whether LLMs or some future technology). This is because many of the most interesting applications of info finance are on “micro” questions: millions of mini-markets for decisions that individually have relatively low consequence. In practice, markets with low volume often do not work effectively: it does not make sense for a sophisticated participant to spend the time to make a detailed analysis just for the sake of a few hundred dollars of profit, and many have even argued that without subsidies such markets won’t work at all because on all but the most large and sensational questions, there are not enough naive traders for sophisticated traders to take profit from. AI changes that equation completely, and means that we could potentially get reasonably high-quality info elicited even on markets with $10 of volume. Even if subsidies are required, the size of the subsidy per question becomes extremely affordable.

China’s Libertarian Medical City

You’ve likely heard of Prospera, the private city in Honduras established under the ZEDE (Zone for Employment and Economic Development) law, which has drawn global investment for medical innovation. The current Honduran government is trying to break its contracts and evict Prospera from Honduras. The libertarian concept of an autonomous medical hub, free to attract top talent, pharmaceuticals, medical devices, ideas, and technology from around the world is, however, gaining traction elsewhere—most notably and perhaps surprisngly in the Boao Hope Lecheng Medical Tourism Pilot Zone in Hainan, China.

Boao Hope City is a special medical zone supported by the local and national governments. Treatments in Boao Hope City do not have to be approved by the Chinese medical authorities as Boao Hope City is following the peer approval model I have long argued for:

Daxue: Medical institutions within the zone can import and use pharmaceuticals and medical devices already available in other countries as clinically urgent items before obtaining approval in China. This allows domestic patients to access innovative treatments without the need to travel abroad…. The medical products to be used in the pilot zone must possess a CE mark, an FDA license, or PMDA approval, which respectively indicate that they have been approved in the European Union, the US, and Japan for their safe and effective use.

Moreover, evidence on the new drugs and devices used within the zone can be used to support approval from the Chinese FDA–this seems to work similar to Bartley Madden’s dual track procedure.

Daxue: Since 2020, the National Medical Products Administration has introduced regulations on real-world evidence (RWE), with the pilot zone being the exclusive RWE pilot in China. This means that clinical data from licensed items used within the zone can be transformed into RWE for registration and approval in China. Consequently, medical institutions in the zone possess added leverage in negotiations with international pharmaceutical and medical device manufacturers seeking to enter the Chinese market.

… This process significantly reduces the time required for approval to just a few months, saving businesses three to five years compared to traditional registration methods. As of March 2024, 30 medical devices and drugs have been through this process, among which 13 have obtained approval for being sold in China.

The zone also uses peer-approval for imports of health food, has eliminated tariffs on imported drugs and devices and waived visa requirements for many medical tourists

To be sure, it’s difficult to find information about Boao Hope medical zone beyond some news reports and press releases so take everything with a grain of salt. Nevertheless, the free city model is catching on. There are already 29 hospitals in the zone including international hospitals and hundreds of thousands of medical tourists a year. The medical zone is part of a larger free port project.

Prospera is ideally placed for a medical zone for North and South America. The Honduran government should look to China’s Boao Hope Medical Zone to see what Prospera could achieve for Honduras with support instead of oppositon.

Hat tip: MvH.

Prediction Markets for the Win

The prediction markets predicted the election outcome more accurately and more quickly than polls or other forecasting methods, just as expected from decades of research. In this election, however, many people discounted the prediction markets because of large trades on Polymarket. Paul Krugman, for example, wrote:

Never mind the prediction markets, which are thin and easily manipulated.

None of that was true but perhaps that was par for the course. Even some prediction market experts, however, began to wobble under the influence of “whale” manipulation theories. But this story was always shaky. What was the supposed logic?

Few directly articulated the theory—perhaps because it sounds absurd when spelled out. The idea seems to be that whales shifted market odds from 50:50 to 40:60, hoping this would drive more people to vote for Trump. Really? Were voters in Pennsylvania watching Polymarket to decide who to vote for? In a decision market, manipulation might be desirable to a whale (albeit unlikely to succeed), but in prediction markets, this scenario seems dubious: a) people would need to know about these markets, b) they’d need to care about probability shifts on these markets (as opposed to voting say the way their family and neighbors were voting), and c) this would have to be an effective way to spend money to influence votes compared to the myriad other ways of influencing voting. Each step seems dubious.

Alternatively, maybe whales were simply wasting money, “memeing” away millions of dollars? Is that something that whales do? The memeing theory is more plausible with many small traders, not a few whales. Or maybe the whales aimed to spark excitement among the minnows, hoping to build momentum before cashing out. However, exciting small traders to inflate prices and then exiting is risky; the same power that whales have to drive up prices can drive prices down just as quickly, making a profitable exit challenging. In short, while not impossible, the idea of whale-driven manipulation in prediction markets was far-fetched.

In fact, we now know that the biggest whale was moving the markets towards accuracy (against his own interest by the way). In an excellent WSJ article we learn:

The mystery trader known as the “Trump whale” is set to reap almost $50 million in profit after running the table on a series of bold bets tied to the presidential election.

Not only did he see Donald Trump winning the presidency, he wagered that Trump would win the popular vote—an outcome that many political observers saw as unlikely. “Théo,” as the trader called himself, also bet that Trump would win the “blue wall” swing states of Pennsylvania, Michigan and Wisconsin.

Now, Théo is set for a huge payday. He made his wagers on Polymarket, a crypto-based betting platform, using four anonymous accounts. Although he has declined to share his identity, he has been communicating with a Wall Street Journal reporter since an article on Oct. 18 drew attention to his bets.

In dozens of emails, Théo said his wager was essentially a bet against the accuracy of polling data. Describing himself as a wealthy Frenchman who had previously worked as a trader for several banks, he told the Journal that he began applying his mathematical know-how to analyze U.S. polls over the summer. 

Here’s the most remarkable bit. Theo commissioned his own polls using a different methodology!

Polls failed to account for the “shy Trump voter effect,” Théo said. Either Trump backers were reluctant to tell pollsters that they supported the former president, or they didn’t want to participate in polls, Théo wrote.

To solve this problem, Théo argued that pollsters should use what are known as neighbor polls that ask respondents which candidates they expect their neighbors to support. The idea is that people might not want to reveal their own preferences, but will indirectly reveal them when asked to guess who their neighbors plan to vote for.

…In an email, he told the Journal that he had commissioned his own surveys to measure the neighbor effect, using a major pollster whom he declined to name. The results, he wrote, “were mind blowing to the favor of Trump!”

Théo declined to share those surveys, saying his agreement with the pollster required him to keep the results private. But he argued that U.S. pollsters should use the neighbor method in future surveys to avoid another embarrassing miss.

Thus, a big win for prediction markets, for Polymarket and for GMU’s Robin Hanson, the father of prediction markets, whose work directly influenced the creation of Polymarket.

What is the Best-Case Scenario for a Trump Presidency?

The economy is strong and Trump has a significant opportunity to simply take credit for that if he avoids major disruptions. While he must fulfill some of his campaign promises, people voted for Trump not for his policies per se. Trump has leeway. No one will accuse him of flip-flopping. While these are not my first-best policies, Trump won against astounding media and elite opposition and an attempted assassination. The people have spoken, so here’s a best-case outline for following through on Trump’s policies without cratering the economy:

  1. Trade Policy: Moderate tariff increases on China. No Chinese electric cars for us. But drop the “tariffs on everything” language. He can always say his rhetoric was a threat to get other countries to lower their tariffs. Let’s instead talk tough against our enemies but shift toward “friend-shoring”, maintaining or even lowering tariffs with allied nations, such as Canada, Europe, and possibly India, as part of a broader strategy to contain China’s influence.
  2. Border Control: Trump must strengthen the border. But let’s limit deportations to individuals who arrived in the past four years. Control the border, throw some illegals out but minimize human misery by not deporting long-term residents and their US-citizen families. Declare a win while avoiding economic disruption and strengthening the police state.
  3. Vaccine and Health Policy: Appoint Robert F. Kennedy Jr. to head a committee on vaccine policy and, after several years of investigation, write a report. Take medical freedom more seriously.
  4. Crypto Regulation: Appoint Hester M. Peirce to head the SEC. Stabilize the regulatory environment for cryptocurrency. Simplify tax rules for crypto. Support digital dollar growth and treat stablecoins as what they are, namely, the US dollar dominating world electronic payments.
  5. Space and Innovation: U.S. Space Force! Commit to Mars exploration and position the U.S. as a leader in space innovation. Get advice from Elon.
  6. US AI. Immediately approve Meta for its nuclear-AI program. Swat the bees. Approve Amazon as well. Tell the FERC that their job is to increase the supply of energy. Keep the Chip Act but make it clear that the goal is to dominate the space not make jobs or social policy. We are the world leaders in AI. Let’s keep it that way.
  7. Kill Bureaucracy: Let Elon Musk take the chainsaw to a few bureaucracies like Javier Milei. Afuera! Afuera! Afuera! Streamline bureaucratic processes, cut red tape and invigorate tech and infrastructure initiatives.
  8. Respect Meritocracy: End race and gender based discrimination in government programs.
  9. Expand Housing Supply: Build baby build! Trump is a natural to lead this. Trump the developer! Incentivize states and localities to streamline zoning laws and reduce restrictions that hamper new housing developments. Increase housing supply.

Each of these policies is consistent with Trump’s priorities and rhetoric and has broad appeal for voters who value economic opportunity, accountability, and national resilience. The economy is strong. Trump has the wind at his back. If he is sensible, all of this would make for a successful presidency. If Trump wants the judgment of history, the path is open should he choose to walk it.

Increasing the Supply of Very High-IQ Workers

I have argued that there are on the order of just 164 thousand very high-IQ workers in the United States. How do we get more? Ian Calaway on the job market from Stanford has an interesting paper arguing that early math mentors can be a force multiplier for students with superior math abilities. Calaway estimates that having a math mentor at a school, someone who runs a math club and organizes entry into top math competitions, increases the number of students earning PhDs and pursing careers as scientists and professors. Not every school has such a math mentor but Calaway estimates (after taking into account underlying abilities, he’s not naive) that over 27 years, math mentors identified 9,092 American Math Competitions students (the cream of the crop) but there were 11,168 missing students of very high ability.

These 11,168 additional students represent the missing exceptional math talents who would have participated in the AMC and been identified as exceptional if they had access to a mentor…these mentors would have increased the number of these students attending selective universities (3,017 students), majoring in STEM (3,465 students), earning PhDs (1,652 students), and pursuing careers as scientists and professors (1,850 students) during this twenty-seven year period.

11,168 missing students of very high ability over 27 years may not sound like much but we are talking about the very top talent level. A footnote illustrates:

Sergey Brin (Google), Mark Zuckerberg (Meta), Peter Thiel (PayPal), and Sam Altman (OpenAI) were all top AMC scorers (Committee on the American Mathematics
Competitions, 1980–2023)

High-IQ individuals don’t simply vanish without mentorship; they likely still have decent careers. However, even if you are skeptical about the social value of earning a PhD, the number of mentored individuals who go on to start firms or earn patents appears substantial. Just as athletic talent can wither without guidance, it seems that intellectual talent may also be underutilized without proper mentorship, with many high-IQ individuals failing to reach their full potential.

The Immigration Rap Battle

From the team that brought you Hayek v. Keynes we have the immigration rap battle featuring “George Borjas,” “Garett Jones” and “Stephen Miller” on team build the wall and “Bryan Caplan” and “Alex Nowrasteh” on open the border. I wouldn’t say the actors (AI?), look very much like their real world counterparts but much respect to the author of the rap lyrics who has brilliantly captured the essence of the ideas economically and thematically.

Sugar Babies

Science: We examined the impact of sugar exposure within 1000 days since conception on diabetes and hypertension, leveraging quasi-experimental variation from the end of the United Kingdom’s sugar rationing in September 1953. Rationing restricted sugar intake to levels within current dietary guidelines, yet consumption nearly doubled immediately post-rationing. Using an event study design with UK Biobank data comparing adults conceived just before or after rationing ended, we found that early-life rationing reduced diabetes and hypertension risk by about 35% and 20%, respectively, and delayed disease onset by 4 and 2 years. Protection was evident with in-utero exposure and increased with postnatal sugar restriction, especially after six months when solid foods likely began. In-utero sugar rationing alone accounted for about one third of the risk reduction.

Pregnant women might want to ration their sugar intake, as well as alcohol, during pregnancy.

Hat tip: Kevin Lewis.

Principles of Economics Textbooks and the Market for Ice Cream

Rey Hernández-Julián and Frank Limehouse writing in the Journal of Economics Teaching write that very few principles of economics textbooks deal with modern information and digital tech industries:

The main takeaways of our review are highlighted by two stand-alone textboxes found in Mankiw’s (2023) textbook. This textbook has been regarded as one of the most dominant players in the principles of economics textbook market for over 20 years. In the introductory chapter of the 10th Edition (2023), “Ten Principles of Economics” there is a stand-alone textbox with the Netflix logo with the following caption: “Many movie streaming services set the marginal cost of a movie equal to zero”. However, there is no further explanation of this statement in the chapter and no presentation of the concept of zero marginal cost pricing in the remainder of the entire textbook. In Chapter 2 (“Thinking Like an Economist”), there is an In the News article from the New York Times, “Why Tech Companies Hire Economists”, but very little coverage in the text on how to apply microeconomic concepts to the tech industry. These two discussions of the tech industry in Mankiw’s text exemplify many of our findings from other texts….updated examples from the modern economy seem to be afterthoughts and detached from the central discussion of the text.

…There are some notable exceptions. The most significant coverage of these questions is in Chapter 16 of Cowen and Tabarrok’s Modern Principles of Microeconomics, 5th edition (2021). In this chapter, the authors discuss platform service providers, such as Facebook, Amazon, Google, Visa, and Uber, and the role they play in competing “for the market,” instead of “in the market.” They also discuss why the prevailing product is not necessarily the best one, how music is a network good, and why these platform services may give away goods for ‘free’.

I would also point out that our example of a constant-cost industry (flat long-run supply curve) is domain name registration! As we write in Modern Principles:

Now consider what happens when the demand for domain names increases. In 2005, there were more than 60 million domain names. Just one year later, as the Internet exploded in popularity, there were more than 100 million domain names. If the demand for oil nearly doubled, the price of oil would rise dramatically, but despite nearly doubling in size, the price of registering a domain name did not increase…the expansion of old firms and the entry of new firms quickly pushed the price back down to average cost.

In short, it’s called Modern Principles for a reason! Tyler and I are committed to keeping up with the times and not just adding the occasional box and resting on our laurels.

See Hernández-Julián and Limehouse for some further examples of how to introduce modern industries into principles of economics.

The MR Podcast–Oil Shocks, Price Controls and War

Our second podcast on the 1970s titled Oil Shocks, Price Controls and War is now available! Here’s one bit:

Tabarrok: …Sheikh Ahmed Yamani, in a famous statement, he was the oil minister for the Kingdom of Saudi Arabia, he’s a leader of OPEC, he says on October 16th, this is 10 days after the war begins, “This is a moment for which I have been waiting for a long time. The moment has come. We are masters of our own commodity.” They raise the price of oil. Oil production falls by about 9 percent to 10 percent. That doesn’t seem on the surface to be a huge amount, but it reveals something which people had not been prepared for, and that was the inelasticity of oil demand.

I would put it this way. I think this is the key idea here. Almost accidentally, the exporting countries had discovered that the demand for oil was more inelastic than anyone had ever realized. The main lesson they drew before 1973, the oil exporting countries thought that the only way to increase revenues was to produce more. After 1973, they learned that an even better way to increase revenues was to produce less.

Here’s another:

COWEN: Since the 1980s, economists, for a number of reasons, have underrated real shocks as a source of business cycles and downturns. You have the Keynesians who didn’t want to talk about it, and then you had the Monetarists, Milton Friedman, who wanted to promote their own recipe, and people just stopped talking about it. Even 2008, which clearly had a lot to do with a major negative shock to aggregate demand, but the price of oil is quite high at the time when that’s breaking, and it was a major factor behind the downturn.

TABARROK: Absolutely.

COWEN: No one wants to talk about that.

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