Category: Political Science

Peter Coy on DOGE

by  Tyler Cowen in

The federal government doesn’t have the people it needs to adequately monitor and vet its enormous streams of payments to defense contractors, hospitals and individuals. For example, administrative expenses account for only half a percent of the budget of the Social Security Administration. Trying to squeeze down that half percent by cutting personnel could lead to misspending of the other 99.5 percent of the budget.

Here is more from the NYT, interesting throughout.  Here is another bit:

To fix such problems, [Brian] Riedl said, “you need G.A.O. and other government experts and others who have done auditing to do most of the legwork.” There is no single easily repeatable fix: “Every program, every program failure and example of mismanagement has its own story.”

You may recall that private health insurance companies have fairly high “overhead,” perhaps a misleading term but nonetheless relevant for these debates.  There are hundreds of billions of “lost” funds at DOD and in Medicare.  Does the plan to improve on that performance involve more staff or less staff?

*Is Inequality the Problem?*

by  Tyler Cowen in

Lane Kenworthy has a book coming out next year, I have read it, and it is superb (rooftops) and also very important.  Here is a brief excerpt:

Rich democratic nations with higher levels of income inequality or larger increases in income inequality haven’t tended to have slower economic growth, lower or slower-growing household income, or worse household balance sheets…

The notion that income inequality is harmful for health has recieved substantial attention from researchers, and some now take it for granted that inequality reduces longevity.  But the country evidence offers very little support for this conclusion.

I will let you know when a pre-order is possible.  In the meantime, it shouldn’t matter, but I can also report that Kenworthy is very much a left-leaning thinker, as you can adduce from his policy recommendations toward the end of the book.

How to make DOGE work

by  Tyler Cowen in

That is the topic of my latest Bloomberg column, here is one excerpt:

Another priority should be to deregulate medical trials. America is now in a golden age of medical discovery, with mRNA vaccines, anti-malaria vaccines, GLP-1 weight loss drugs and new treatments against cancer all showing great promise. AI may bring about still more advances.

Unfortunately, the US system of clinical trials remains a major obstacle to turning all this science into medicine. There are regulations concerning hospital protocols, the design of the trials, FDA requirements, the procedures of universities and institutional review boards, and the handling of data, among other barriers. America can have better and speedier approval procedures without lowering its standards.

Of all the tasks I’ve outlined, this is by far the most difficult, because it involves changes in so many different kinds of institutions. Yet it has one of the highest possible payoffs, because more treatments might be developed and made available if the clinical trial process weren’t so onerous. Reforming clinical trials should also appeal to older Americans, who are especially likely to vote and who think the most about their medical care. The goal should be an America where most people live to 90.

Many Republicans are very excited about DOGE. But its governance structure is undefined and untested. It does not have a natural home or an enduring constituency. It cannot engage in much favor-trading. Its ability to keep Trump’s attention and loyalty may prove limited. And it’s not clear that deregulation is a priority for many voters.

The more I read about DOGE from Vivek and Musk, the more I feel it needs a greater sense of prioritization.

Where are incumbents still popular?

by  Tyler Cowen in

From my email, here is your Switzerland fact of the day:

The media is awash with stories about western countries incumbent parties losing elections in the last two years:

The exception no one seems to remember: Switzerland. In the october 2023 election, 3 out of the 4 governing parties increased their vote share. And it wasn’t just parties that are formally in government but effectively act as an opposition: The right wing Swiss People’s Party won. The left wing Social Democrats one. And the moderate Centre party one. The losers: The centre right Liberal Party (in government) and two different green parties (both outside of government).

Possible cause: Low inflation (https://marginalrevolution.com/marginalrevolution/2022/10/the-polity-or-is-it-culture-that-is-swiss.html)?

From Johann C.

Info Finance

by  Alex Tabarrok in

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

by  Alex Tabarrok in

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.

Do you want a Democratic or Republican doctor?

by  Tyler Cowen in

Political polarization is increasingly affecting policymaking, but how is it influencing professional decision-making? This paper studies the differences in medical practice between Republican and Democratic physicians over 1999-2019. It links physicians in the Medicare claims data with their campaign contributions to determine their partyalignment. In 1999, there were no partisan differences in medical expenditure perpatient. By 2019, Republican physicians are now spending 13% more, or $70 annually per patient. We analyze four potential sources of this partisan difference: practice characteristics (i.e., specialization and location), patient composition, preferences for financial gain, and beliefs about appropriate care. Even among physicians in the same specialty and location treating patients for the same condition, Republican physicians spend 6% more, especially on elective procedures. Using a movers design, we also find large partisan differences for treating the same patient. We find no evidence that these partisan differences are driven by profit incentives. Instead, the evidence points to diverging beliefs. Republican physicians adhere less to clinical guidelines, consistent with their reported beliefs in prior surveys. The timing of the divergence matches the politicization of evidence-based medicine in Congress. These results suggest that political polarization may lead to partisan differences in the beliefs and behavior of practitioners.

That is from the job market paper of Woojin Kim from UC Berkeley.  I found this one of the most interesting job market papers of this year.

Prediction Markets for the Win

by  Alex Tabarrok in

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?

by  Alex Tabarrok in

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.

Political Sorting in the U.S. Labor Market

by  Tyler Cowen in

That is the central topic of the job market paper of Sahil Chinoy from Harvard University.  Here is the abstract:

We study political sorting in the labor market and examine its sources. Merging voter file data and online résumés to create a panel of 34.5 million people, we show that Democrats and Republicans choose distinctive career paths and employers. This leads to marked segregation at the workplace: a Democrat or Republican’s coworker is 10% more likely to share their party than expected. Then, we ask whether segregation arises because jobs shape workers’ politics or because workers’ politics shape their job choices. To study the first, we use a quasi-experimental design leveraging the timing of job transitions. We find that uncommitted workers do adopt the politics of their workplace, but not workers who were already registered Democrats or Republicans. The average effect is too small to generate the segregation we document. To study the second, we measure the intensity of workers’ preferences for politically compatible jobs using two survey experiments motivated by the observational data. Here, we find that the median Democrat or Republican would trade off 3% in annual wages for an ideologically congruent version of a similar job. These preferences are strong enough to generate segregation similar to the observed levels.

Co-authored with Martin Koenen, also a job market candidate from Harvard.  Koenen’s other papers, at the link, look very interesting too.

Does the internet limit immigrant assimilation?

by  Tyler Cowen in

This paper documents the effects of new communication technologies on immigrants’ socio-economic integration, spatial and job segregation, and networking behavior. Combining data on home-country Internet expansion shocks with data on immigrants’ linguistic skill, naturalization, location choice, and employment in the US, I find that home-country Internet slows down immigrants’ social and economic integration. The effect is driven by lower-skilled and younger immigrants. On the other hand, home-country Internet decreases spatial and job segregation with co-nationals, and increases immigrants’ subjective well-being. For the mechanisms, I use the American Time Use Survey data to show that home-country Internet changes networking behavior of immigrants. I also explore the role of (i) return intentions, (ii) international phone calls, and (iii) Facebook usage. The evidence is consistent with a simple Roy model, augmented with a choice between destination- and origin-country ties. Overall, this paper shows how new ICTs transform the links between immigration, diversity, and social cohesion.

That is from the job market paper of Alexander Yarkin from Brown University.

My Conversation with the excellent Christopher Kirchhoff

by  Tyler Cowen in

Here is the audio, video, and transcript.  Here is the intro:

Christopher Kirchhoff is an expert in emerging technology who founded the Pentagon’s Silicon Valley office. He’s led teams for President Obama, the Chairman of the Joint Chiefs of Staff, and CEO of Google. He’s worked in worlds as far apart as weapons development and philanthropy. His pioneering efforts to link Silicon Valley technology and startups to Washington has made him responsible for $70 billion in technology acquisition by the Department of Defense. He’s penned many landmark reports, and he is the author of Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War.

Tyler and Christopher cover the ascendancy of drone warfare and how it will affect tactics both off and on the battlefield, the sobering prospect of hypersonic weapons and how they will shift the balance of power, EMP attacks, AI as the new arms race (and who’s winning), the completely different technology ecosystem of an iPhone vs. an F-35, why we shouldn’t nationalize AI labs, the problem with security clearances, why the major defense contractors lost their dynamism, how to overcome the “Valley of Death” in defense acquisition, the lack of executive authority in government, how Unit X began, the most effective type of government commission, what he’ll learn next, and more.

Excerpt:

COWEN: Now, I never understand what I read about hypersonic missiles. I see in the media, “China has launched the world’s first nuclear-capable hypersonic, and it goes 10x the speed of sound.” And people are worried. If mutual assured destruction is already in place, what exactly is the nature of the worry? Is it just we don’t have enough response time?

KIRCHHOFF: It’s a number of things, and when you add them up, they really are quite frightening. Hypersonic weapons, because of the way they maneuver, don’t necessarily have to follow a ballistic trajectory. We have very sophisticated space-based systems that can detect the launch of a missile, particularly a nuclear missile, but right then you’re immediately calculating where it’s going to go based on its ballistic trajectory. Well, a hypersonic weapon can steer. It can turn left, it can turn right, it can dive up, it can dive down.

COWEN: But that’s distinct from hypersonic, right?

KIRCHHOFF: Well, ICBMs don’t have the same maneuverability. That’s one factor that makes hypersonic weapons different. Second is just speed. With an ICBM launch, you have 20 to 25 minutes or so. This is why the rule for a presidential nuclear decision conference is, you have to be able to get the president online with his national security advisers in, I think, five or seven minutes. The whole system is timed to defeat adversary threats. The whole continuity-of-government system is upended by the timeline of hypersonic weapons.

Oh, by the way, there’s no way to defend against them, so forget the fact that they’re nuclear capable — if you want to take out an aircraft carrier or a service combatant, or assassinate a world leader, a hypersonic weapon is a fantastic way to do it. Watch them very carefully because more than anything else, they will shift the balance of military power in the next five years.

COWEN: Do you think they shift the power to China in particular, or to larger nations, or nations willing to take big chances? At the conceptual level, what’s the nature of the shift, above and beyond whoever has them?

KIRCHHOFF: Well, right now, they’re incredibly hard to produce. Right now, they’re essentially in a research and development phase. The first nation that figures out how to make titanium just a little bit more heat resistant, to make the guidance systems just a little bit better, and enables manufacturing at scale — not just five or seven weapons that are test-fired every year, but 25 or 50 or 75 or 100 — that really would change the balance of power in a remarkable number of military scenarios.

COWEN: How much China has them now? Are you at liberty to address that? They just have one or two that are not really that useful, or they’re on the verge of having 300?

KIRCHHOFF: What’s in the media and what’s been discussed quite a bit publicly is that China has more successful R&D tests of hypersonic weapons. Hypersonic weapons are very difficult to make fly for long periods. They tend to self-destruct at some point during flight. China has demonstrated a much fuller flight cycle of what looks to be an almost operational weapon.

COWEN: Where is Russia in this space?

KIRCHHOFF: Russia is also trying. Russia is developing a panoply of Dr. Evil weapons. The latest one to emerge in public is this idea of putting a nuclear payload on a satellite that would effectively stop modern life as we know it by ending GPS and satellite communications. That’s really somebody sitting in a Dr. Evil lair, stroking their cat, coming up with ideas that are game-changing. They’ve come up with a number of other weapons that are quite striking — supercavitating torpedoes that could take out an entire aircraft carrier group. Advanced states are now coming up with incredibly potent weapons.

Intelligent and interesting throughout.  Again, I am happy to recommend Christopher’s recent book Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War, co-authored with Raj M. Shah.

New report on nuclear risk

by  Tyler Cowen in

Phil Tetlock is part of the study, from the Forecasting Research Institute.  Obviously this is very importnt.  From Tetlock’s email to me:

“In brief, this study is the largest systematic survey of subject matter experts on the risk posed by nuclear weapons. Through a combination of expert interviews and surveys, 110 domain experts and 41 experienced forecasters predicted the likelihood of nuclear conflict, explained the mechanisms underlying their predictions, and forecasted the impact of specific tractable policies on the likelihood of nuclear catastrophe.

Key findings include:

  1. We asked experts about the probability of a nuclear catastrophe (defined as an event where nuclear weapons cause the death of at least 10 million people) by 2045, the centenary of the bombings of Hiroshima and Nagasaki. Experts assigned a median 4.5% probability of a nuclear catastrophe by 2045, while experienced forecasters put the probability at 1%.

a.       Respondents thought that a nuclear conflict between Russia and NATO/USA was the adversarial domain most likely to be the cause of a nuclear catastrophe of this scale, however risk was dispersed relatively evenly among the other adversarial domains we asked about: China/USA, North Korea/South Korea, India/Pakistan, and Israel/Iran.

  1. We asked participants about their beliefs on the likely effectiveness of several policy options aimed at reducing the risk of a nuclear catastrophe. Two policies emerged as clear favorites for most participants: a crisis communications network and nuclear-armed states implementing failsafe reviews. The median expert thought that a crisis communications network would reduce the risk of a nuclear catastrophe by 25%, and failsafe reviews would reduce it by 20%.”

You will find the report here.