Data

arXiv will ban authors who submit papers with LLM mistakes

Joy BuchananLeave a comment

In the world of academic preprints, arXiv has long been the go-to platform for researchers to share work quickly. But with the explosion of generative AI tools, the repository is drawing a line in the sand.

On May 14, 2026, arXiv moderator Thomas Dietterich announced a clarified enforcement policy. If a submission contains incontrovertible evidence that authors didn’t properly check LLM-generated content, all listed authors face serious consequences.

What counts as “Incontrovertible Evidence”? The policy targets clear signs of unchecked AI output, including:

  • Hallucinated or fake references
  • Meta-comments left by the model (e.g., “Here is a 200-word summary; would you like me to make any changes?” or placeholder instructions like “fill in the real numbers from your experiments”)
  • Other obvious errors, plagiarized text, biased content, or misleading claims generated by AI

arXiv’s Code of Conduct already holds every author fully responsible for the entire paper’s contents.

The Penalty

  • One-year ban from submitting new papers to arXiv.
  • After the ban, future submissions must first be accepted at a reputable peer-reviewed venue before arXiv will host them.

At first researchers discussing the policy online seemed happy about the one-year ban, but when I pointed out that it is essentially a ban for life to use it at a pre-print venue, some people became nervous.

Why now? arXiv has been overwhelmed by low-effort “AI slop.” These papers are marked by fabricated citations and shallow summaries. This erodes trust in the entire preprint ecosystem.

In response to the complaints (someone like me would be worried that I’ll somehow let an error slip through and then be banned for life from posting working papers), Scientific Director Steinn Sigurðsson shared:

on the whole @arxiv flap about hallucinated references etc

you don’t see the stuff we reject… some of it is really really egregious

the decision to impose additional consequences is largely to throttle that stuff so n00bs and bad actors don’t trash us trying repeatedly

This is the problem that we face with every internet forum. A few bad actors ruin it for good people.

In 2022 I wrote Content moderation strategy

Elon Musk buying Twitter is the big news this week. He wants to enhance free speech on the site and, according to him, make it more open and fun. Some fans are hoping that he will make the content moderation and ban policy more transparent. Maybe that’s possible. 

If no one can be banned, then bad actors will bring the whole platform down. Inevitably, good people get caught in the net, and it’s devastating to be locked out of a platform where your peers are sharing.

However, if you want to be taken seriously by tech folk then ask for a system that is possible. A substantially better experience might be incompatible with the site being free to users.

Part of the problem that I don’t hear people talking about is that a free platform is not easily compatible with good customer service.

For some not-fake work and citations: Buchanan et al. (2024) provided early clear evidence that a mark of LLM-written work is fake citations. And, Buchanan and Hickman (2024) show that certain framings can prompt people to be more suspicious of AI-generated writing, such that they are pushed toward doing a fact-check before believing all claims.

Buchanan, Joy, and William Hickman. “Do people trust humans more than ChatGPT?.” Journal of Behavioral and Experimental Economics 112 (2024): 102239.

Buchanan, Joy, Stephen Hill, and Olga Shapoval. “ChatGPT hallucinates non-existent citations: Evidence from economics.” The American Economist 69.1 (2024): 80-87.

How do Income Tax Brackets Work?

Zachary Bartsch1 Comment

I was listening to an episode of The Deduction, a podcast by the Tax Foundation. As if that first sentence isn’t evident enough, I was reminded of how confusing taxes are – period. Even experts disagree and see grey areas. As I was listening, I thought “man, they need a graph”. So, here we are.

Income Tax Vocabulary

The money that you are paid by your employer is your gross income. Not all of it is taxable. You can deduct money from your gross income to get your taxable income. Most people subtract the ‘standard deduction’ from their gross income, which is how I’ll proceed in this post. Since the standard deduction for 2026 is $16,100 for a single earner, that means that your taxable income is $16,100 less than your gross income. By following a formula, one can calculate the amount of money that they must pay the government. These payments can be all at once, throughout the year, or even directly from your paycheck. The total that’s due to the government by April 15 is called the total tax liability. Finally, the money that the government doesn’t take, and that you get to keep, is called your net income. It’s your income net of taxes.

If you’ve had a job, then you are probably most familiar with your gross income, what your employer pays you, and your net income, what you get to take home. The steps in between might include some hand-waving.

Marginal Tax Rates

One of the most confusing pieces of the income tax code is marginal income taxes. Below are the brackets for 2026.

Marginal Tax rates work like this: Every dollar that you earn faces a tax rate. If your taxable income would be below zero, then you pay zero in taxes. But if your taxable income is $5k, then it gets taxed at a rate of 10%. That part should be pretty straightforward. But what if your taxable income is $15k? According to the table, you face a tax rate of 10% for dollars earned up to $12,400. That would be a tax liability of $1,240. But the remainder of your $15k in taxable income exists in the next tax bracket. That portion of your taxable income faces a tax rate of 12%. Sticking with the example, $2,600 is in the 12% tax bracket, so the tax liability for that portion of your taxable income is $312 (=$2.6k*0.12). Therefore, your total tax liability would be the sum of your tax liabilities across all applicable tax brackets: $1,552 (=$1,240+$312).

There are some features of marginal tax rates that are worth mentioning. Since the tax rates on the lower taxable income brackets don’t change, earning more gross income never reduces your net income unless the tax rate exceeds 100% (which it doesn’t here). So, when someone says that their taxable income is in the 35% tax rate bracket, they probably just mean that their last dollar earned is there. They’re only paying 35% on the taxable income that’s above $256,225. They’re not paying 35% of all earned dollars to the Internal Revenue Service (IRS).

Below is a graph that details the different marginal tax rates with shaded areas. The blue line is the average tax rate. It’s calculated by dividing the tax liability by the gross income. Even though one might earn an income that’s greater than $257k where the marginal tax rate is 35% or greater, the average tax rate remains lower, topping out at about 30% in this figure. The average tax rate is lower than an earner’s top marginal tax rate because the income in those lower brackets never disappears or get taxed at a higher rate.

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Most Published Research Findings Are Directionally Correct

James BaileyLeave a comment

As a new quick rule of thumb inspired by the Nature papers, you could do worse than “cut estimated effect sizes in half”. If a published paper says that a college degree raises wages 100%, then chances are the degree really does raise wages, but more like 40–50%. In 2005, John Ioannidis said that “most published research findings are false”. By 2026, we seem to have improved to “most published research findings are exaggerated.”

That’s the conclusion of my piece out today at Econlog: “Is Economics Finally Becoming Trustworthy?“

There’s plenty of both good and bad news for economics and the social sciences in both my piece and the Nature special issue it describes. It’s kind of like the Our World in Data motto:

In short, our attempt to replicate hundreds of papers showed that published social science results shouldn’t be trusted precisely today, but they seem to be getting more reliable over time, and they are much more reliable than chance. Economics and political science look the best, though we are still very far from perfect:

You can read the full piece here.

Gerrymandering Doesn’t Give an Obvious Edge to Either Party in the US House

Jeremy HorpedahlLeave a comment

Congressional districts must be redrawn after each US Census. In fact, that is one of the main functions the Census: to determine how many seats of the US House of Representatives that each state is allotted. A related function is to give states information about the distribution of the population in their state. Even if a state doesn’t gain or lose seats after a Census, the population in their state may have grown, shrank, or simply moved around within the state. If each Congressional district is to represent roughly the same number of people, district boundaries will still need to be redrawn even absent a change in the state’s total share of the US House seats.

That much is clear. However, given that historically and still largely today Congressional districts are drawn by state legislatures, there is a temptation and a real possibility that the party in power of a state legislature will draw boundaries in a way that benefits that party. There is nothing illegal about doing this as far as the federal Constitution is concerned (that I am aware of), but it does seem a bit unsporting. But I guess much of politics might be deemed “unsporting.”

Nonetheless, sometimes the shape of districts is so obviously weird and not representing an cohesive group of citizens or communities that it gets the derisive term “Gerrymander,” which derives from a historical example of a very odd looking district. But even if a district doesn’t look weird, it may still give one party an advantage that some deem unfair, such as by diluting one party’s supporters into multiple districts so they get no seats, or alternatively cramming all the supporters into one district so they have a very lopsided victory in just one district, rather than controlling multiple districts. This practice is known as “partisan Gerrymandering,” and it will be my focus in this post today (there are other forms, such as racial Gerrymandering, which are also important but are beyond the scope of this post).

Surely this practice occurs. Some states have tried to avoid it the problem of Gerrymandering by using non-partisan commissions, though this is a minority of states (less than a dozen), and when push-comes-to-shove they don’t actually seem that committed to the idea (both California and Virginia have essentially abandoned these commissions in 2025-26 to attempt to, once again, gain a partisan advantage). But lately a particular question has come up: does partisan Gerrymandering benefit one major party more?

In total for the US House, whatever Gerrymandering at the state level that is happening seems to roughly wash out in national representation: in the 2024 election, Republicans received about 51.7% of the two-party share of votes totaled over all House elections, and Republicans have about 50.6% of the seats in the House. Perhaps you could say that the GOP effectively loses 5 seats to what they “should” have in a truly proportional sense, but this ignores many factors, some of which I will discuss below. But even so, the GOP has a slim majority in the House and they won a slim total of national House votes. It’s about right.

But that “washing out” at the national level ignores some very large disparities at the state level. In some states, one party has all the House seats, even though they got nowhere near 100% of the House vote. Many of these are states with 1 or 2 House seats, which are less interesting because either there is no possibility of Gerrymandering (1 seat) or there is no obviously “fair” division, but it is not only those small states. For examples, Massachusetts gives all 9 seats to the Democrats, even though Republicans received 31.5% of the two-party vote share. Do Republicans deserve 3 of the seats? Is the fact that they don’t have 1/3 of the seats evidence of Gerrymandering? Conversely, in Oklahoma Republicans hold all 5 seats, even though Democrats got 30% of the vote. Should Democrats get a seat or two in Oklahoma?

(Note: for all vote data, I have queried Google Gemini Pro. I found multiple errors along the way, but I am fairly confident the numbers are all correct now. Please let me know if you spot any errors).

Neither Massachusetts nor Oklahoma’s Congressional representation is an obvious case of Gerrymandering on its face. It’s possible that 1/3 opposition party support in both states is perfectly even distributed across the state, such that it would not be possible to draw any “fair” districts that give the opposition roughly 1/3 of the seats. But it could be the result of Gerrymandering, or at least an indication we should look deeper. We can tally up all of the differences across states in the following chart:

Chart 1

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GDP Forecasts for the First Quarter of 2026

Jeremy Horpedahl1 Comment

Forecast models, betting markets, and surveys of experts all drastically overstated the actual growth of GDP in the last quarter of 2025. They were off in the initial release, which was just 1.4 percent, but this was even further revised down to 0.5 percent. All four of the sources I track were forecasting over well over 2 percent, with some over 3 percent.

Does that mean we shouldn’t trust the forecasts? Perhaps, but last quarter was largely pulled down by government spending cuts, which the models completed missed. You can see this very clearly in the Atlanta Fed GDPNow model. Perhaps they shouldn’t have been surprised by this drop in government spending, but that is where the major error was.

So what do these forecasts think about the first quarter data for 2026, which comes out tomorrow? The two best predictors historically, GDPNow (Atlanta Fed) and Kalshi, are pretty far apart on this one, over a percentage point difference, with GDPNow being the only forecast under 2 percent:

Price Level: Noise vs Signal

Zachary Bartsch2 Comments

My university recently hosted a guest speaker. Among their content, they included some nominal macroeconomic values from pre-2020, back in the era when inflation was very low. That roughly includes the years 2012-2019. Truly, inflation stayed below 2% through February of 2021, but I think that we can all agree that the economy was different in a few ways beginning in 2020.

I asked the speaker why not express the nominal values in real terms. They were emphatic that the low rates of inflation at the time implied that the signal-to-noise ratio was too low. Therefore, the ‘real’ inflation adjusted values would not be more precise because excessive noise would be introduced into the series during a period when not much deflating was necessary in the first place.

My answer to this is a firm ‘maybe’. It makes sense and it’s plausible (Jeremy has written about error and revisions in the past). We can think about the noise in price indices in a few ways.

1) It may be information is incomplete and becomes more complete as time passes. This sort of noise only exists in the short-run and is resolved as more information becomes available later in time. Revisions tend to happen each month for prior months, as well as each year for prior years. There are also big revisions after methodological, consumption weight, and data source changes.

2) Another type of noise is due to incomplete information that is never resolved. After all, the government statisticians can’t see literally all of the transactions. Those unobserved transactions will never make it into the official inflation measures and we’ll never get a perfect picture.  

3) Methodological artifacts may also include known biases. This type of noise doesn’t get corrected except after major changes to the series. If those changes never happen, then we just sort of live with imprecision. Luckily, so long as the bias is consistent, then percent change in the price indices will approximate the underlying true levels. However, if there are non-random biases in the percent change, then it can cause some trouble.

One way to get an idea for the amount of noise in the data is to observe the magnitude of revisions. Of course, this only helps us with the first type of noise above that eventually gets resolved with more information. It’s much harder to get a handle on the imprecision that is not identifiable. The Philadelphia Federal Reserve Bank provides an easy-to-use database that puts all of the archival and revised numbers for many macro series in a single place: the Real-Time Data Set (RTDS). It includes every historical PCE price index value for each publication month. Let’s limit our sample to the 21st century.

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Are Americans Thriving Under Trump? No, According to the Cost of Thriving Index

Jeremy HorpedahlLeave a comment

The Cost of Thriving Index from Oren Cass’s American Compass is an attempt to calculate how well US families are doing financially, but without using traditional inflation adjustments to income. Instead, Cass and crew have chosen 5 categories of goods and services, and tracked those over time relative to median earnings for men ages 25 and older (in the baseline model — it can also be applied to different categories of workers).

Scott Winship and I wrote a detailed critique of the COTI, which I summarized in a previous blog post. Our critique comes from several angles, including correcting several major errors in COTI, as well as arguing that standard inflation adjustments to median income are superior to this new approach.

Based on our critique, I don’t think COTI is a very good measure of how well US families are doing financially. But the COT Index still has many fans. And Cass seems to think Trump is in large part pursuing many policies that should help out US workers and families, such as Trump’s tariff policies. Thus, it will be useful to see if Trump’s policies are leading to American workers “thriving” in the first year of Trump’s presidency.

Unfortunately, even using Cass’s preferred approach, Americans don’t appear to be thriving under Trump.

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The United States Has A Progressive Tax System

Jeremy Horpedahl5 Comments

For Tax Day 2026, here are some estimates of how progressive the US tax system is, drawing primarily from published academic work. While there is disagreement about exactly how progressive the tax system is (and should be), these papers all agree that as income rises, average tax rates rise. These estimates attempt to include, as best as possible, all federal, state, and local taxes, and to take account of tax incidence.

From Auten and Splinter in the Journal of Political Economy:

Piketty, Saez, and Zucman in the Quarterly Journal of Economics (Figure IX):

And here is a chart that I created, which comes from the appendix data for PSZ (2018), which is roughly comparable to the Auten-Splinter chart above. Note that it isn’t perfectly comparable: the income groups on the x-axis aren’t exactly the same, and the latest year in PSZ is 2014 rather than 2019 (they do have estimates for later years in updates to the work, but I am trying to stick with the published academic work). But they are roughly comparable:

Auerbach, Kotlikoff, and Koehler in the Journal of Political Economy take the additional step of computing lifetime average tax rates, rather than for a single year, showing the US tax system is even more progressive when considered this way. Note: they also include the value of transfers, which makes these results not directly comparable to the papers above:

Finally, here are two estimates from think tanks that work on tax policy. Even though the Tax Foundation is considered more right-leaning and ITEP is considered more left-leaning, both agree that the overall US tax code is progressive.

A Canticle for Aadam Jacobs

mdmakowsky2 Comments

For the talk of the future of generating art, let’s not forget the task of remembering the art we’ve already made. Behold: more than 10,000 cassette recorded concerts, from as far back as 1984, recorded in community centers, church basements, taverns, all-ages clubs, and hundreds of other unsung “venue” owners who let then (and often always) unknown bands play shows for a a couple dozen attendees, all in the hopes that door money and beverages might keep the owner out of the red on a random weeknight while.

I have a couple bootlegs from concerts I attended, but it never occurred to me that I might get to listen to a 1995 Blonde Redhead show at The Empty Bottle or The Blow Pops playing 1991 show at a Milwaukee spot I’ve never heard of. These shows have always had an ephemeral quality to them, existing far more in the stories of those who claimed to be there that night than the actual direct artistic footprint.

But maybe not. Maybe the internet can and does, in fact, remember. Because while there is a lot to be absorbed from the finished product, but there is often so much more learn from the imperfect and unpolished early stages. A band before they slowed down or ventured beyond their first 3 chords, a writer still stuck in the first person, a disseratation chapter still haunted by the writing of the insecure graduate student we all were. The awkard phases when an artist (or artists) are still finding their voice. Perhaps, more than ever, we need to remember the importance of not skipping over the embarassing, exhausting, and, yes, often futile work at the beginning and middle. There are more shortcuts than ever to making a thing, but no shortcut to becoming the version of yourself that can make the thing that only you can make.

Hungary is A Free Trading Nation Relative to the US

Jeremy HorpedahlLeave a comment

Vice President Vance’s recent trip to Hungary to stump for Viktor Orban was interesting for a number of reasons, but is not totally surprising. In many ways Orban’s “illiberal democracy” (his self-applied term) has many overlaps with MAGA Republican policy. Johan Norberg recently wrote a very good critique of Orban’s policies, and why the US should not follow further down the path or Orbanism.

I agree completely with Norberg’s analysis completely, though his focus is mostly on the decline in democracy, the rule of law, and personal freedoms in Hungary under Orban. Norberg does have several criticisms of Orban’s economic policies, but on the whole economic policy under Orban has been relatively unchanged: in the Human Freedom Index report Norberg cites, the “personal freedom” portion of the index declined 1.5 points on a 10-point scale under Orban, while the “economic freedom” portion only declined by 0.3 points.

What’s really interesting is that within the Economic Freedom of the World Index, Hungary’s highest scoring area of the five areas is “freedom to trade internationally,” where they ranked the 25th best country in the world in 2023. While MAGA Republicans might like the US to copy many of Hungary’s policies, they clearly do not in this case, as trade restrictions one of the signature economic policies of Trump (possibly his most important economic policy).

To be clear, the high ranking on free trade in Hungary is not due to any conscious policy choice of Orban’s administration. Instead, it is because Hungary is a member of the European Union, and therefore is part of the single market (meaning they have free trade with most of their trading partners) and part of the customs union (meaning they can’t set their own external trade policy). Indeed, it appears if Orban had his way, they would have much less free trade, as he is trying to hold up the EU-Mercosur trade agreement. Nonetheless, Orban’s hands are largely tied on trade policy.

Not only was Hungary ranked quite high on free trade in 2023, they were ranked higher than the US, as they have been for most of the past decade:

While the EFW data is generally only available with a significant lag, and therefore only through 2023 in the chart above, they did provide a special update for the US in mid-2025, given the radical changes in trade policies by the second Trump administration. That’s the blue dot you see floating down below with a score of 7.4. While that isn’t the final ranking for 2025 (they still don’t have the scores for 2024!), it gives an indication of roughly where the US will land in 2025, making it much less free trading than Hungary.

The EFW Area 4 score includes not just tariff rates, but also non-tariff barriers to trade, as well as capital controls and labor movement. What if we only focus on the tariff sub-score, since this is the part of trade policy Trump has altered the most?

On tariff policy alone, there wasn’t much difference between the US and Hungary in 2023 (indeed, if we look solely at tariff rates, the US was slightly better, with an average rate of 3.3% compared with 5.0% in Hungary). But with the radical change in rates in 2025, Fraser estimates that the US will drop significantly, giving it one of the highest average tariff rates in the world. This would be a massive difference between Hungary and the US on trade policy. We’ll have to wait for the complete data before making a final judgement, and indeed given that average tariff rates have changed more than 50 times under the second Trump administration already, it’s not even clear what our score will be for 2025. But it will almost certainly be worse than Hungary.