Author: James Bailey

Credit Card Limits for Men and Women

James Bailey1 Comment

Yesterday Federal Reserve researcher Nathan Blascak presented a paper at my Economics Seminar Series that was a surprise hit, with the audience staying over 40 minutes past the end to keep asking questions. So today I’ll share some highlights from the paper, “Decomposing Gender Differences in Bankcard Credit Limits”. 

The challenge here is that its hard to get data that includes both gender and credit card limits (its illegal to use gender as a basis for allocating credit, so credit card companies don’t keep data on it, as they don’t want to be suspected of using it). The paper is original for managing to do so, by merging three different datasets. But even this merged data only lets them do this for a fairly specific subgroup- Americans who hold a mortgage solely in their name (not jointly with a spouse). Even this limited data, though, is quite illuminating.

Their headline result is that men have 4.5% higher credit limits than women. Women actually have slightly more credit cards (3.38 vs 3.22), but have lower limits on each card; summing up their total credit limit across all cards yields an average of $28,544 for women vs $30,079 for men.

Source: Table 1 of this paper

Two of the big factors that determine limits, and so could cause this difference, are credit scores and income. The table above shows that men and women have remarkably similar credit scores, while men have higher incomes. Still, when the paper tries to predict credit limits, controlling for credit scores, incomes, and other observables explains only about 13% of the gender gap.

Men have 4.5% higher credit limits on average, but this difference varies a lot across the distribution. For credit scores, the gap is narrow in the middle but bigger at the extremes. For income, we see that men get higher limits at higher incomes, but women actually get higher limits at lower incomes- and not just “low incomes”, women do better all the way up to $100,000/yr:

The papers data covers 2006-2018, so they also show all sorts of interesting trends. The average number of credit cards held by men and women plunged after the 2008 recession and remains well below the peak. Total credit limits plunged too, though they were almost totally recovered by 2018.

There’s lots more in the paper, which is a great example of the value of descriptive work with new data. If anything I’d like to see the authors push even harder on the distribution angle. Its nice to see how limits vary across all incomes and credit scores, but why not show the full distribution of credit card limits by gender? My guess is that the 1st and 99th percentiles are very interesting places, because there’s all sorts of crazy behavior at the extremes. Finally, I wonder if higher limits are actually a good thing once you get beyond a relatively low amount- do you know of anyone who ever had a good reason to get their personal credit card balances over $20,000?

The Shrinking Allied Social Science Association

James Bailey4 Comments

For many decades the Allied Social Science Association (ASSA) meetings, anchored by the American Economic Association, have been by far the world’s largest gathering of economists each year, typically attracting well over ten thousand. But the meetings went virtual-only for the past two years, and when they finally return in-person in 2023 they will likely be substantially diminished.

Some of this is due to potentially one-off factors; some people don’t want to travel to Louisiana because of its state laws, some still want to avoid large conferences because of Covid, others want to avoid the ASSA’s response to Covid:

All registrants will be required to be vaccinated against COVID-19 and to have received at least one booster to attend the meeting…. High-quality masks (i.e., KN-95 or better) will be required in all indoor conference spaces.

But the AEA made one big, apparently permanent change that means it could be a long time before we see a meeting as big as January 2020’s in San Diego- they gave up the job market. Prior to Covid the vast majority of first-round interviews to be a full-time US economics professor took place at ASSA. Naturally interviews moved online during Covid, but surprisingly the AEA has asked that they stay online, and in fact has specifically asked schools NOT to schedule interviews during ASSAs. This removes a huge source of demand for the meetings- the ~1200 new PhDs looking for their first jobs, the thousands of people there to recruit them (each hiring school typically sends 2-4 interviewers), and everyone trying to switch jobs. This was THE big thing that made AEAs special, that other conferences didn’t really have.

I’ll let everyone else debate whether this makes the job market better or worse; I’m agnostic there, but I’m sure it will shrink the conference. One silver lining to a smaller conference is that it is much easier to find a hotel room. Like usual I was waiting on the AEA website this Tuesday to book a hotel room on the first minute the AEA’s deeply discounted hotel blocks opened, because the good hotels tend to fill up near-instantly. But it appears this was unnecessary this year- two days later and even the headquarters hotel is still wide open:

I got the room I wanted at the Hotel Monteleone; I’ll be looking to grab a spot on the Carousel Bar, maybe see some of you there. I’ll present a poster at AEA, but mostly I’m just looking forward to spending real time in New Orleans for the first time since I moved away in 2017.

Yes, it rotates while you sit and drink

So I’m still looking forward even to a diminished AEA, but it does make me wonder- which other conferences will benefit most from AEA’s decline? I don’t know that anyone has put together the numbers for all the conferences enough to know what the 2nd-largest is, but my bet both for the 2nd-largest and most likely to benefit is the Southern Economic Association; I’ll be there too, in Ft. Lauderdale this November.

McDouble vs Big Mac: Why Inflation Hits the Bottom Harder

James Bailey1 Comment

Since they were first introduced as part of the Dollar Menu in 1997, the McDouble and the McChicken have been my go-to choices when I visit Mcdonald’s. It was always hard to justify getting one of the fancier sandwiches like a Big Mac or Quarter Pounder, since they were 4-5x the cost of a McDouble but only about twice the size. This is part of why the McDouble has been called “the greatest food in human history“. But as we’ve seen with the plagues and wars of the 2020s, history doesn’t always progress in the direction you’d hope.

I hadn’t been to a McDonald’s for a while until last weekend, when I was shocked to see the McDouble and McChicken listed at $2.99. This wasn’t at an airport restaurant either, or even in an expensive big city; I stopped in Keene, New Hampshire on a drive home from Vermont. The price is up 200% from the days of the Dollar Menu! Meanwhile, the Big Mac has also got more expensive, but much less dramatically; it was $5.89, compared to the ~$5 I expect. So, 200% price increases at the bottom, vs 18% at the top.

This location may be a bit of an anomaly, but the big picture is clear; a typical McDouble now costs well over $2 in most of the US, while a typical Big Mac is still well under $6. You used to be able to get 4-5 McDoubles for the price of a Big Mac; now you typically get less than 3 and sometimes, as in Keene, less than 2.

What’s going on here? First, the McDouble was always absurdly cheap. Second, prices rise most quickly where demand is inelastic, and demand is less elastic for goods that are cheaper and goods that are more like “necessities” than “luxuries”.

This is why I think the McDouble is worth highlighting- its part of a more general trend of where inflation hits. I’ve noticed this in the grocery store as well; the price of standard ground beef is up much more than grass-fed organic beef, likewise with standard eggs vs free-range organic. How different would the Economist’s Big Mac Index look if it used the McDouble instead?

With falling inflation we may see the end of this necessity vs luxury price compression. But I doubt we’ll ever see the glory of the standard $1 McDouble again.

The New Hampshire McDonalds was disappointing, but Vermont was nice

Series 65 for Economists

James Bailey7 Comments

Financial discussions often give the disclaimer “this is not investment advice” for legal reasons. I would always see this and wonder, is anyone ever willing to say “this *is* investment advice”?

The answer is, yes, licensed investment advisers do when speaking to their clients. How do people become licensed investment advisers? They start by taking the Series 65 exam.

I decided to take the Series 65 because I thought it would be a good learning opportunity, that it could be fun to tell people “this is investment advice”, and because it also provides the fast track to becoming an accredited investor. I’d like to have the option to invest in startups or hedge funds, but the SEC doesn’t let people do that unless they are rich (consistently over $300k/yr HH income, or $1mil in assets) or a licensed financial professional. I didn’t want to wait years to pass the income or asset tests, and so decided to pass the literal test instead.

I hoped that as a PhD economist who sometimes reads about finance for fun, I could pass the Series 65 without studying. This turned out not to be true, but it also wasn’t wildly wrong. You need to get at least 72% of questions correct to pass; taking a practice test cold I got 62%. I decided to first take the slightly easier Security Industry Essentials exam as a warmup. For both exams, I passed after spending ~ 2 weeks reading through the ~500 page study guides from the Securities Institute of America in my spare time.

For someone with an economics background, the exams will feature a few true econ questions you’ll know cold, a lot of “common sense” finance questions you probably know, some more specific finance questions you probably don’t know, and some specific questions about laws and regulations for investment advisers you almost certainly don’t know. This means you can speed through some parts of the study guide, but will need to slow way down in others. I found myself learning a roughly equal mix of things I’m happy to know for their own sake, things that would only be helpful to the extent I actually work as an investment adviser, and things that seem completely pointless.

Overall this seems like a decent way to spend a bit of time and money. Economists love to complain about people asking us for financial advice, and we tend to either reply “I don’t know, that’s not what economics is about” or give uninformed answers. But it doesn’t take that much time to educate yourself enough to be able to give people good, informed answers, so I think we should do so, especially when the alternatives people turn to tend to either be uninformed (friends or internet randos) or biased (advisers who get paid for steering them to high-fee investments).

That said, if your goal is actually to make money as an adviser or as an accredited investor, the Series 65 exam is only the first hoop to jump through. You still need to get licensed, which means either starting an investment advisory firm or joining one. I haven’t tried to do this yet despite passing the Series 65 in June, as I’ve been busy with my main job. I’d be interested to hear from anyone who has done this, especially anyone who got a part-time or consulting role just to get licensed to make accredited investments. How hard was it, how long did it take, what did you think of the actual work?

The Future of Student Debt

James Bailey2 Comments

Yesterday the Biden administration announced that is forgiving up to $20k per person in student debt. So far we’ve seen lots of debate over whether this was a good/fair idea; as an economist who paid back his own debt early, you can probably guess what I have to say about that, so I’ll move on to the more interesting question of what happens now.

…after sharing one tweet
OK one more, but I promise its relevant

The above is a quote from Thomas Sowell as a political commentator, but he was also a great economist. His book Applied Economics says that the essence of the economic approach to policy analysis is to not just consider the immediate effect, but instead to keep asking “and then what?” So let’s try that here.

We’ll start with the immediate effects. Those whose debt just fell will be happy, and will have more money to spend or save in other ways. The federal government is on the other side of this, they’ll receive less in debt payments and so will have to fund themselves in other ways like borrowing money or raising taxes. People are still trying to estimate how big this transfer from the government to student debtors is, but let’s take the Penn Wharton Budget Model estimate of $330 billion (the actual cost is likely higher, since that estimate is for $10k of loan forgiveness, but the actual program forgives up to $20k for those who had Pell grants). Dividing by US population tells you the cost is roughly $1000 per American; dividing by $10,000 tells you that roughly 33 million debtors benefit.

OK, what happens next? The big question is: is this a one-time thing, or does it make future loan forgiveness more or less likely? Later I’ll make the argument for why the answer could be “less”. But right now most people seem to think the answer is “more”, and that belief is what will be driving decisions.

If current and future students think loan forgiveness is likely, they have an incentive to take out more loans than they otherwise would, and to pay them off more slowly (particularly since income-based repayment was just cut from 10% to 5% of income). This higher willingness to pay from students gives colleges an incentive to raise tuition; historically about 60% of subsidized loans to students end up captured by colleges in the form of higher prices:

We find a pass-through effect on tuition of changes in subsidized loan maximums of about 60 cents on the dollar, and smaller but positive effects for unsubsidized federal loans. The subsidized loan effect is most pronounced for more expensive degrees, those offered by private institutions, and for two-year or vocational programs.

Source: https://www.newyorkfed.org/research/staff_reports/sr733.html

To the extent that you think student debt is a national problem, this action didn’t solve the problem so much as push it back 6 years; wiping out roughly 20% of all student debt brings us back to 2016 levels. So we could end up right back here in 2028, possibly faster to the extent that students borrow more as a result.

Source: https://fred.stlouisfed.org/series/SLOAS#

That, together with the “normalization” of student loan forgiveness, is why people think a similar action in the future is likely. But I’ll give two reasons it might not happen.

First, this action may have only reduced student debt by about 20%, but it reduced the number of student debtors much more (at least 36%), because most debtors owed relatively small amounts. It will take more than 6 years for the number of voters who’d benefit from loan forgiveness to get back to what it was in 2022, reducing support for forgiveness in the mean time.

Source: https://www.valuepenguin.com/average-student-loan-debt

That also gives Congress plenty of time to do something, even by their lethargic standards. Part of what bothers many people about this loan forgiveness is that it not only doesn’t solve the underlying issue of the Department of Education signing kids up for decades of debt, it will likely worsen the underlying issue through the moral hazard effect I describe above. Forgiveness would be much more popular if it were paired with reforms to solve the underlying issue. While we aren’t getting real reform now, I do think forgiveness makes it more likely that we’ll see reform in the next few years. What could that look like?

Let’s start with the libertarian solution, which of course won’t happen:

More realistic will be limits on where Federal loan money can be spent, and shared responsibility for colleges. Colleges and the government have spent decades pushing 18 year olds to sign up for huge amounts of debt. While I’d certainly like to see 18-year-olds act more responsibly and “just say no” to the pushers, the institutions bear most of the blame here. The Department of Education should raise its standards and stop offering loans to programs with high default rates or bad student outcomes. This should include not just fly-by-night colleges, but sketchy masters degree programs at prestigious schools.

Colleges should also share responsibility when they consistently saddle students with debt but don’t actually improve students’ prospects enough to be able to pay it back. Economists have put a lot of thought into how to do this in a manner that doesn’t penalize colleges simply for trying to teach less-prepared students.

I’d bet that some reform along these lines happens in the 2020’s, just like the bank bailouts of 2008 led to the Dodd-Frank reform of 2010 to try to prevent future bailouts. The big question is, will this be a pragmatic bipartisan reform to curb the worst offenders, or a Republican effort to substantially reduce the amount of money flowing to a higher ed sector they increasingly dislike?

A Theory of Certificate of Need Laws and Health Care Spending

James Bailey1 Comment

I just published a paper on CON laws and spending in Contemporary Economic Policy. As frequent readers of this blog will know, CON laws in 34 states require healthcare providers in 34 US states to get permission from a state board before opening or expanding, and one goal of the laws is to reduce health care spending. The contribution we aim for in this paper is to lay out a theoretical framework for how these laws affect spending.

There have been many empirical papers on this, typically finding that CON laws increase spending, but the only theory explaining why has been simple supply and demand. Health care markets are hard to model for a few reasons, but one big one is that most spending is done through insurers, so the price consumers pay is typically quite a bit lower than the price producers receive. This leads to “moral hazard”- i.e. overuse and overspending by consumers. Normally economists hate monopolies because they lead to underproduction, so in a market with overuse its fair to ask (as Hotelling did about nonrenewable resources)- could two market failures (moral hazard overuse and monopoly underuse) cancel each other out?

Continue reading →

CFTC Orders PredictIt Shut Down- Can Political Betting Survive?

James Bailey8 Comments

Political betting has long been in a legal grey area. It seems that the Commodities Futures Trading Commission wants to make everything black and white, but at least for now it has simply made everything murkier.

PredictIt is the largest political betting site in the US; if you want to know who is likely to win an upcoming election, its the best place to find a quick answer. Prediction markets have two great virtues- they are usually right about what’s going to happen, and if they aren’t you can bet, making money and improving their accuracy at the same time.

PredictIt has operated since 2014 under a “no-action letter” from the CFTC. Effectively, the regulators told them “we’re not saying what you’re doing is definitely legal, but we know about it and have no plans to shut you down as long as you stick to the limits described in this letter”. But last week the CFTC withdrew their letter and ordered PredictIt to shut down by February 2023.

My first question was, why? Why shut them down now after 8 years when all their operations seem to be working as usual? The CFTC said only that “DMO has determined that Victoria University has not operated its market in compliance with the terms of the letter and as a result has withdrawn it”, but did not specify which of the terms PredictIt violated, leaving us to speculate. Did the scale simply get too big? Did they advertise too heavily? Did Victoria University, the official operator, let too much be handled by a for-profit subcontractor? Did some of their markets stray too far from the “binary option contracts concerning political election outcomes and economic indicators” they were authorized for?

PredictIt hasn’t been much clearer about what happened, simply putting a notice on their site. Their CEO did an interview on the Star Spangled Gamblers podcast where he said there was no one thing that triggered the CFTC but did mention “scope” as a concern- which I interpret to mean that they offered some types of markets the CFTC didn’t like, perhaps markets like “how many times will Donald Trump tweet this month”.

The other big question here is about PredictIt’s competitors. In 2021 it seemed like we were entering a golden age of real-money prediction markets, with crypto-based PolyMarket and economics-focused Kalshi joining PredictIt. I looked forward to seeing this competition play out in the marketplace, but it now seems like we’re headed toward a Kalshi-only monopoly where they win not by offering the product users like best, but by having the best relationship with regulators. Polymarket had offered markets without even a no-action letter, based on the crypto ethos of “better to ask forgiveness than permission”; this January the CFTC hit them with a $1.5 million fine and ordered them to stop serving US customers.

If the CFTC doesn’t reverse their decision to shut down PredictIt, then February 2023 will see a Kalshi monopoly. This has led to speculation that Kalshi is behind the attack on PredictIt; their cofounder issued this not-quite-a-denial. But it certainly looks bad for the CFTC that they are effectively giving a monopoly to the company that hires the most ex-CFTC members.

For now you can still bet on PredictIt or Kalshi (or even Polymarket if you’re outside the US). If you’d like to petition the CFTC about PredictIt you can do so here. It might actually work; while the CFTC’s recent actions certainly look cronyistic, they’ve been reasonable compared to other regulators. They’re giving PredictIt no fines and several months to wind down, and even Polymarket gets to keep serving non-US customers from US soil. I’d likely make different decisions if I were at CFTC but the ideal solution here is a change in the law itself, as we’ve seen recently in sports betting. Prediction markets are impressive generators and aggregators of information, and politics and policy are at least as valuable an application as sports. To go meta, suppose we want to know- will PredictIt survive past February? There’s a prediction market for that, and its currently saying they’ve got a 20% chance.

Boutique Science

James Bailey1 Comment

Science keeps getting bigger- more researchers, more funding, and of course more publications. Scientific progress is much harder to measure, but there are good arguments that it’s roughly flat over time. This implies that productivity per researcher is plummeting.

Source

There’s been a lively debate about what drives this falling productivity- is it that the easy discoveries got made first, leaving only harder ones for today’s scientists? Or is something else tanking scientific productivity, like the bureaucratic way we organize scientific research today?

A recent paper, “Slowed canonical progress in large fields of science“, suggests that the growth in the number of researchers and publications could itself be part of the problem. Comparing scientific fields over time, they find that:

When the number of papers published per year in a scientific field grows large, citations flow disproportionately to already well-cited papers; the list of most-cited papers ossifies; new papers are unlikely to ever become highly cited, and when they do, it is not through a gradual, cumulative process of attention gathering; and newly published papers become unlikely to disrupt existing work. These findings suggest that the progress of large scientific fields may be slowed, trapped in existing canon.

What is driving this? They argue:

First, when many papers are published within a short period of time, scholars are forced to resort to heuristics to make continued sense of the field. Rather than encountering and considering intriguing new ideas each on their own merits, cognitively overloaded reviewers and readers process new work only in relationship to existing exemplars. A novel idea that does not fit within extant schemas will be less likely to be published, read, or cited. Faced with this dynamic, authors are pushed to frame their work firmly in relationship to well-known papers, which serve as “intellectual badges” identifying how the new work is to be understood, and discouraged from working on too-novel ideas that cannot be easily related to existing canon. The probabilities of a breakthrough novel idea being produced, published, and widely read all decline, and indeed, the publication of each new paper adds disproportionately to the citations for the already most-cited papers.

Second, if the arrival rate of new ideas is too fast, competition among new ideas may prevent any of the new ideas from becoming known and accepted field wide.

Supposing they are correct, it’s not totally clear what to do. At the biggest level we could fund fewer researchers in large fields, or push more fields to be like economics, where the quality of each researcher’s publications is valued much more than the quantity. But what can an individual researcher do differently? One idea is “boutique science” or “hipster science”, trying to find the smallest or newest field you could reasonably attach yourself to.

Another idea is that the role of generalists and synthesizers is becoming more valuable, as Tyler Cowen often says and David Esptein applies to science in his book Range. When papers are coming out faster than anyone can read, we need more people to sift through them and explain which few are actually important and which are forgettable or wrong. There are lots of ways to do this- review articles, meta-analysis, replication at scale, and of course blogs. But the junk pile is going to keep growing, so we’ll need new and better ways of finding the hidden gems.

Recession or not, the biggest GDP political football is 3 months away

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US GDP fell for the second straight quarter according to statistics released this week by the Bureau of Economic Analysis. This means that by one common definition we’re now in a recession, which has ignited a debate about whether “two consecutive quarters of negative GDP growth” is the best definition (as opposed to ‘when the NBER says there’s one’, like I generally teach and Jeremy argued for here, or something else).

Naturally this debate has political overtones, since the party in power would be blamed for a recession, so we’ve seen the White House CEA argue that we’re not in a recession, many on the other side argue that we are, and plentiful hypocrisy from people who should know better.

But in political terms, the fight over the binary “are we in a recession” call won’t be the big economic factor in November’s elections- that will be inflation and GDP, especially 3rd quarter GDP. One of the oldest and best predictors of US elections is the Fair Model, which uses inflation and the number of recent “strong growth quarters”. Fair’s update following the recent Q2 GDP announcement states:

the predicted vote share for the Democrats is 46.70, which compares to 48.99 in October. The smaller predicted vote share for the Democrats is due to two fewer strong growth quarters and slightly higher inflation

By Election Day we’ll have 3 more months of economic data making it clear whether inflation is getting under control and whether economic activity is picking back up or continuing to decline. Monthly data releases on inflation and unemployment will be closely watched, but the most discussed release will likely be third quarter GDP. It will summarize 3 months instead of just one, it will be of huge relevance to the debate over how severe the recession is or whether we’re even in one, and it will likely be released less than two weeks before election day. The NBER almost certainly won’t weigh in by then; they tend to take over a year to date recessions, not adjudicate debates in real time.

So when BEA does release their Q3 GDP estimate in late October, what will it say? Markets currently estimate at least a 75% chance it will be positive (they had estimated a 36% chance of positive Q2 GDP just before the latest announcement). That sounds high to me, the yield curve is still inverted and I bet investment will continue to drag, but forecasting exact GDP numbers is hard. Its a much easier bet that whatever the number turns out to be will loom large in political debates just before the elections. Perhaps we’ll get the Q3 GDP growth number that would make for the most chaotic debate: 0.0%.

Trial Updates: Novavax Approved, Potatoes Work

James Bailey2 Comments

I’m usually the one writing the papers, but I recently did two studies as a participant / guinea pig. Both just released major positive updates.

I joined the Novavax trial in late 2020 to have the chance to get a Covid vaccine sooner; at the time Pfizer had just got emergency approval but wasn’t available to the general public. The smart bio people on Twitter also seemed to think it was likely to be safer, and perhaps more effective, than other Covid vaccines (it delivers relevant proteins directly, rather than using mRNA or a viral vector). The trial results were published over a year ago now, and were in fact excellent:

Results from a Phase 3 clinical trial enrolling 29,960 adult volunteers in the United States and Mexico show that the investigational vaccine known as NVX-CoV2373 demonstrated 90.4% efficacy in preventing symptomatic COVID-19 disease. The candidate showed 100% protection against moderate and severe disease

As usual the FDA dragged its feet, even as other agencies around the world like the European Medical Agency and the World Health Organization approved the US-made Novavax. But last week it finally gave emergency authorization, and yesterday the CDC recommended Novavax. Of course, by now almost everyone who wants a Covid vaccine has one, and this approval is only for adults. But this will be a great option for boosters, as well as for anyone who was genuinely just concerned with the new technologies in the other vaccines (rather than just afraid of needles, or preferring to cut off their nose to spite authority’s face). As the CDC put it:

Protein subunit vaccines package harmless proteins of the COVID-19 virus alongside another ingredient called an adjuvant that helps the immune system respond to the virus in the future. Vaccines using protein subunits have been used for more than 30 years in the United States, beginning with the first licensed hepatitis B vaccine. Other protein subunit vaccines used in the United States today include those to protect against influenza and whooping cough….

Today, we have expanded the options available to adults in the U.S. by recommending another safe and effective COVID-19 vaccine. If you have been waiting for a COVID-19 vaccine built on a different technology than those previously available, now is the time to join the millions of Americans who have been vaccinated

I’m glad I was in this trial- I got a Covid vaccine several months before I otherwise could have, I made a few hundred dollars, and I learned a lot. But it would have been much better if they found a way to do fewer blood draws, and if FDA approval had come quicker. I’ve been in a weird gray area with respect to vaccine mandates for the last year; almost everyone ended up accepting my vaccine card, but I never knew if they were going to say “no, you need an FDA approved one”. I ended up getting Pfizer for a booster even though I think it’s a worse vaccine, partly for this reason, and partly because Novavax said they’d only give me the booster if I did another blood draw and I was tired of that.

The all-potato diet trial I wrote about here also released its results this week. This trial was much less formal, much smaller, and had no control group, so the results aren’t a slam-dunk the way Novavax is. But I think they’re still impressive. I lost 8 pounds in the 4-week trial, but it turns out the average participant who did all 4 weeks did even better:

Of the participants who made it four weeks, one lost 0 lbs…. Everyone else lost more than that. The mean amount lost was 10.6 lbs, and the median was 10.0 lbs.

Their summary also explains other costs and benefits of the diet, showing lots of data as well as many quotes from participants, including two from me. They conclude with some fascinating speculation about potential mechanisms from the boring (literally, lower variety makes eating boring so you eat less) to the speculative (low lithium? high potassium? weird lithium-potassium interactions), check it out if you’re interested in why obesity rates keep rising or if you’re considering doing the potato diet.

I’m glad I was in these two trials- what to try next?