Economics

Tall poppies don’t get the calls

mdmakowsky1 Comment

Ask anyone who grew up playing basketball as the tallest player on the court and they will, each and every one of them, tell you that players were allowed to foul them harder and more often. If you were tall you didn’t get the calls, full stop. Why? We could sort through a host of mechanisms, but they all boil down to “Being tall is an unfair advantage. It’s only fair that I, the shorter opposing player, am allow to slap you, chop you, kick you, trip you, grab you.” To be honest, I don’t think this is a particularly shocking phenomenon. “Tall poppies get cut down” is a cultural cliche for a reason. What is interesting is that it persists even amidst billions of dollars in market incentives pushing in the other direction.

The latest version is happening right now as the Oklahoma City Thunder are currently doing their best to end Victor Wembanyama’s nascent career each and every night, and the referees seem uninterested in realigning the incentives otherwise. At the moment the Spurs are currently up 65-43 in game 4 of the series. If the series goes 7, there’s at least a 20% change Wembanyama doesn’t make it to the end. Will they break his foot smashing down on it, break his leg tripping him, or dislocate his shoulder yanking down on it from a leveraged position? Don’t know, but they’re doing their best to make it happen.

Caitlin Clark came into the WNBA as the single greatest talent prospect in the history of women’s basketball. The abuse she suffers is well documented. Wayne Gretzky was the greatest hockey player of all time, but he was arguably only allowed to reach his potential because Bobby Orr’s careers was cut in half by a league that allowed teams to abuse him with little to know punishment. Bobby Orr’s sin was that he was such a better skater than everyone else that, if allowed to play without constant grabbing, hooking, and abuse tantamount to aggravated assault, he would have walked away with too many goals, wins, and Stanley Cups. It wasn’t fair that he was so much better, so they let the players even the odds. Having watched him limp away after only 7.5 seasons, the NHL took the unofficial position that Gretzky’s teammates (specifically, Dave Semenko and Marty McSorley) held carte blanche to assault anyone who touched Gretzkey. While perhaps not a culture-shifting solution, Gretzky did have a 20 year career that brought hockey to new heights of popularity, so it was ostensibly effective.

But none of that gets at the underlying economics. Elite players bring big audiences to sporting events, which in turn, brings in big money for everyone. The owners, players, and everyone in between gets richer when elite players shine under the biggest lights. So why chop them down? Well, first we have a collective action problem to solve, because, yes, the entire market benefits from superstars, but their opposition during the course of play in any one game have the individual incentives to do whatever they can get away with to win. That’s why we have referees, commissioners, and a players union: to solve those collective action problems. All of those rules and institutions are in place specifically to align incentives and bargain for outcomes that maximize welfare. So why aren’t they working?

When you find cliches at the front of your mind, decent chance you’re running up against psychology and behavioral economics. And as Victor Wembanyama is learning each and every night of the playoffs, “tall poppies get cut down”. It’s not fair that he’s the first 7’5″ player with elite NBA level skills to ever play the game. You know, I was never a fan of watching Shaq play basketball per se, but I always knew he should have scored at least 40 points every night. Yes, he committed 7 offensive fouls every game, but he also received 25 fouls that went uncalled. Players were allowed to maul him because it was unfair he was so much bigger, stronger, and more athletic. His career was only as long as it was because his body could endure the abuse. There has never been another player in NBA history who could have survived even 3 seasons receiving the abuse he did.

Putting aside simple behavioral explanations, we also should consider the possibility that NBA team owners and players are so far down the diminishing marginal returns to wealth, that the median participant would actually prefer to earn less money in order to maximize their own chance at winning a championship. They want parity, of a sort. Parity, but only once the playoffs arrive. The regular season is too long and everyone does, in fact, want to make money, so the abuse is minimal, but once the playoffs arrive, the collective preference is for parity delivered via weaker rule enforcement. There are only so many elite players, but everyone is capable of low-level violence. This preference for postseason parity may also explain why Oklahoma City’s best player, Shai Gilgeous-Alexander, has the reputation for simulating being fouled on every play. If you’re going to get fouled no matter what, you might was well maximize the probability of getting a foul call by forcing the referee to be observed observing the incident.

And, to be clear, parity may in fact be revenue maximizing. Just look at the NFL – the entire structure is designed to maximize the number of franchises who believe at the beginning of the season that their team has a chance to win it all. The players are relatively anonymous compared to NBA superstars, but fans are mostly there to root for laundry, and in the NFL, so long as that laundry doesn’t say NY Jets on it, there’s at least a glimmer of hope. Counter point, just look at the NFL. They understood that each team, especially once the playoffs started, had strong incentives to try to end the opposing quarterbacks career on each and every play. So the NFL introduced a battery of rules to protect quarterbacks, and it seems to have worked.

So maybe I’ve come full circle. Maybe this is what the NBA wants. But I really, really it’s hope not. Wemby is special. I’d like to see the very most of what he can become.

Someone I Know is Taking Wegovy

Joy BuchananLeave a comment

This person is buying the pills direct from the supplier, in consultation with a doctor. It is amazing. Resurrection. The Great Stagnation is over. Go get this stuff. It’s funny how many people are already on it, but it doesn’t come up until you initiate a conversation.

As a behavioral economist… it’s pretty wild. Folks were eating things that part of themselves wanted to eat and part of themselves did not want to eat. And, instead of getting rid of the junk food, or somehow training people out of overeating, we’ve chemically quieted the desires.

I feel like the healthy people could have done more on choice architecture, in the old days (pre-2025). It was hard for the people trying to lose weight to avoid junk food. I’m not trying to introduce the boot of the state into kids’ birthday cakes but just pausing to reflect on how many people died because of our choices. Humans are supposed to just walk past an aisle of candy bars? (My parents explicitly and intentionally trained me from a young age to never buy anything at the “check out aisle” because it’s always going to be a stupid impulse purchase. As an adult, I buy a chocolate bar at check out about once a year and feel like I’m getting away with robbing a children’s hospital.)

Here’s Paul pondering these issues 2000 years ago (shortened by me):
Romans 7:15-19
15 I do not understand what I do. For what I want to do I do not do, but what I hate I do. 16 And if I do what I do not want to do, I agree that the law is good. … For I have the desire to do what is good, but I cannot carry it out. 19 For I do not do the good I want to do, but the evil I do not want to do—this I keep on doing.

Joy: I think on net glp1 will increase fertility relative to not having it. It seems like good news for folks reaching their (reportedly) desired number of children. But I would not count on it to turn any country around to get back to replacement.

The Welfare-Productivity Tradeoff in US-China Trade

James BaileyLeave a comment

Who benefits from trade between the US and China? If China subsidizes their exporting industries, should the US see this as a threat that undermines our industries, or thank China for lowering prices for US consumers? Does it matter that China runs a persistent trade surplus (exporting more than they import), while the US runs a persistent trade deficit?

Everyone has a take on these questions, but the answers I hear even among economists rarely draw from the leading modern models in the international trade literature. Krugman (1980) (10k citations) shows how large home markets matter for industries with increasing returns to scale. In a simple increasing returns model, unlike with Econ 101 comparative advantage, temporary subsidies can permanently flip which country an industry efficiently operates in.

Melitz (2003) (20k citations) extends the Krugman model to include firm-level productivity differences. Rubini (2014) extends the Melitz model to include innovation. Now Xiao (2025) has extended the Rubini model to include unbalanced trade, then calibrated the model with data from the US and China. Now that the mathematical models are able to incorporate more and more features of the real world, what do they show?

China’s trade surplus and the US trade deficit have tradeoffs. Specifically, China’s trade surplus leads them to be more productive than they otherwise would be, but have lower welfare, because so much of the fruit of their production is enjoyed by other countries. Conversely the US trade deficit leads us to produce less than we otherwise would, but to have higher welfare thanks to consumers enjoying the cheaper foreign goods.

In one sense this recapitulates some of the same debates people had without the math. Some people like trade because it benefits US consumers and overall present-day US wellbeing. Some don’t like it because it harms US manufacturing and our resiliency in any potential future conflict.

One advantage of the models is that it puts numbers on the tradeoffs. In this case, the welfare benefit to the US may be small relative to China’s welfare loss and relative to both countries’ productivity changes:

the average productivity increase caused by trade surplus ranges from 1.2 percentage points to 5.46 percentage points when the innovation cost changes. These results explain China’s long-term export promotion policies and align with its new policy goal of developing “new productivity forces”. I also identify a negative effect on China’s trade partners’ productivity (namely, the US), of between -2.74 percentage points and -5.89 percentage points. This comes at a welfare cost, equivalent to between 3 percentage points and 5.7 percentage points of consumption units. Correspondingly, China’s cheaper goods increase welfare in the US by between 0.26 percentage points and 1.22 percentage points

In addition to the big complex model, Xiao’s paper shares nice background on the sheer size of Chinese export subsidies, noting that they account for 2/3 of all manufacturing subsidies in G20 countries, and that export tax rebates are almost 2/3 as large as Chinese net exports. In short, China’s trade surplus is not simply driven by differing preferences and production capabilities across countries, but is largely driven by deliberate policy choices.

P.S. The paper’s author, Aochen Xiao, is on the econ job market.

Fuel Costs Are Way Up, But It’s Still Pretty Affordable to Fill Up Your Tank (relative to wages)

Jeremy HorpedahlLeave a comment

Two months ago I wrote about gasoline prices and tried to give the current prices some historical context. Gas prices have, of course, only continued to increase since then. Here’s a chart I created to give a bit more context, using an idea from Ryan Radia: how much does it cost to drive a car 250 miles? Since fuel efficiency has increased over time, we might be understating how much it costs to drive today relative to the past. And of course, to give the “cost” proper context I have stated in terms of hours worked at the average wage (note: the final data point is from April 2026, as we don’t have wage data for May yet):

In April 2026 it took about 1.4 hours of work at the average wage ($32.23) to purchase enough gasoline to drive 250 miles (10.7 gallons) at the average fuel efficiency (23.4 miles per gallon). That average fuel efficiency figure is from 2024, the latest available, so it could be a bit higher today. Maybe it’s a little easier than 1.4 hours of work to buy it, but even if fuel efficiency had crept up to 25 mpg (that would be a big increase in 2 years, historically speaking), it would still be 1.3 hours of work.

1.4 hours of work is certainly a big jump from earlier in 2026, but you’ll notice it is still on the low end in this chart, and well below the peak we saw in June 2022 of just over 2 hours of work to buy 250 miles worth of gasoline.

But 23.4 miles per gallon is pretty low, as this is includes lots of trucks and SUVs with pretty bad fuel efficiency. What if we looked at some more fuel efficient vehicles?

Here’s a few I checked on (all for 2026 models, with gas and electricity at current national averages):

  • Toyota Camry: 0.71 hours of work
  • Chrysler Pacifica Hybrid: 0.61 hours on electric, 1.18 hours on gasoline
  • Tesla Model Y: 0.37 hours of work

It will probably not surprise you that the all-electric Tesla Model Y is cheaper than the average car to operate at current prices, but you may not have realized that it is almost four times cheaper. But the Toyota Camry, with all models operating as hybrids now, also comes in pretty good at about half the cost of the average vehicle to operate (and the Camry is a very affordable car to purchase). The Chrysler Pacifica hybrid minivan does pretty well too, though even operating only on electricity (30 miles at a time), it’s only slightly more fuel efficient than the Camry.

PhD Chemical Engineer Finds New Career Booty Hooping

Scott Buchanan1 Comment

I read Straw Dogs, a critique of modern society by English political philosopher John Gray, shortly after it was published in 2002. (No relation to the movie with the same name). Wikipedia summarizes the author’s view as, “Gray blames humanism, and its central view of humanity, for much of the destruction of the natural world, and sees technology as just a tool by which humans will continue destroying the planet and each other.”  I cannot recommend the book as a whole – the reader is left in a state of despairing passivity. My AI justly notes, “Critiques of John Gray’s Straw Dogs: Thoughts on Humans and Other Animals generally center on its extreme pessimism, logical inconsistencies, and rhetorical excesses.”  

All that said, the book did contain many interesting observations. One line of thought that struck me at the time was that, with increasing efficiencies in the production of basic goods and services, more and more human effort will go into simply entertaining or “distracting” each other:

The days when the economy was dominated by agriculture are long gone. Those of industry are nearly over. Economic life is no longer geared chiefly to production. To what then is it geared? To distraction. Contemporary capitalism is prodigiously productive, but the imperative that drives is not productivity. It is to keep boredom at bay. With wants so quickly sated, the economy soon comes to depend on the manufacture of ever more exotic needs.

I was reminded of that line of thought when, at a recent gathering of PhD chemical engineers, I heard that one of our number has become somewhat well-known for a late-career shift. She goes by the name Andrea Hulamyhoop these days. (I happen to know her real last name and approximate age, but she wishes to keep those private).

Her father was a chemical engineering professor, and she earned a PhD in the discipline at Princeton University. She was just going along living a fairly normal sort of life, with a regular job, when without warning, it happened:

Then one day, she saw a girl hula hooping. “She looked really free and happy, and I thought, interesting, maybe I’ll try it.” A few minutes at a time quickly became an obsession. Turns out, there are whole online communities of hula hoopers who share tips and support. Conferences. And many shows and events looking for a pro to dazzle and inspire audiences.

“The hula hoop has changed everything in my life,” she says. “I didn’t know I could become a fit, sporty person. I didn’t know I was one. I love performing, and I love people, and I love parties.

“I always thought my life was a bit OK. My kids were grown up. I was enjoying my job,” she says. “But you know, we kind of think, is this all there is? And then to realize there’s this whole world — it’s been incredible. I’m happier than I’ve ever been in my life.”

Andrea Hulamyhoop doesn’t just swirl a hoop around her waist. She can twirl multiple hoops around multiple body parts, with style. She is perhaps best known for her appearance on America’s Got Talent in 2025, where she smashed previous records by bending over and twirling a hoop around her rear end for just over an hour and fifteen minutes. The crowd went wild.

The physics of this feat seem almost impossible, but seeing is believing. Andrea gives a gracious tutorial here.

When I asked who is the most famous holder of a Princeton chemical engineering PhD, both ChatGPT and Claude insisted that former GE president Jack Welch is more well-known than Andrea the butt-hooper, but I doubt that is true below a certain audience age bracket. She has some 17,000 Instagram followers. I’d be willing to bet that in a crowd of under-40’s today, if you asked “Have you heard about the guy who was president of GE in the 1980’s and 90’s?” or “Have you heard about the gal who can twirl a hula hoop on her butt?”, Andrea Hulamyhoop would win.

All this brought back to my mind the notion that as a society we are able to afford to devote a great deal of time to sheer entertainment, rather than growing potatoes.   A comment by a certain @petesounds9321 on Andrea’s epic 2025 AGT YouTube showed he had evidently not read Straw Dogs:

“I’d say we need more scientists than hula hoopers but hey…maybe I’m way off.”

Economic history as it’s happening is alway relative

mdmakowskyLeave a comment

This is the chart that I’ve been thinking about today.

The US government has been able to borrow on the cheap for most of it’s existence, with the exception of 70s and 80s when stagflation put the clamp down. Treasury rates are soaring right now…or at least, it feels that way because for most of my adult life the United States has been viewed as arguably the safest borrower in history. What follows are in some ways the only two questions that matter for the US economy. Is the US government a reliable institution? Is economic growth going to keep pace with inflation? The answer to each question (and their subcomponents) is, of course, unknown, but the market seems to think the net of that question is going in the wrong direction.

That said, for all of the neverending parade of (sometimes unintential) nostalgia that seems to pollute the discourse, wow, 1975-1985 was not exactly macroeconomically “aspirational”.

Which Business Programs Require Economics?

Zachary Bartsch2 Comments

Disclaimer: This post might throw shade.

The vast majority of business majors across the US are required to take two or more Economics courses. You can look across the spectrum. All of the top 20 business schools require two or more econ classes. In fact, Wharton is the top-ranked business school and their business program is actually an *economics* program. They don’t have finance/accounting/business degrees. Instead, they have an Economics degree with the various business concentrations. Again – the top business school in the country is an Economics program.

What about at the other end of the spectrum? I live in Florida. Every single Florida state school requires both Micro and Macroeconomics for business majors. These schools include everything from Florida State University to the local Florida state college down the road. I didn’t look at other state-run higher education systems in other states. There are a lot of states…

I teach at a private Catholic university. We’re listed in something called ‘The Newman Guide’ which recommends 17 Catholic schools. Many of these are liberal arts schools, but the list also includes Catholic University of America, which is an R1. Most of these schools also require two or more Economics classes in their Business major programs. The only exception is University of Dallas, which has Economics in the core curriculum.*

So, overwhelmingly undergraduate business programs across the country require two economics courses. But, why? The students are often not happy to be there, and I’ve even heard business professors demean the math as performatively rigorous and superfluous. They argue that plenty of people get rich or are otherwise successful without all of the quantitative skills that economics leverages.

I think that the fear of math is both a red herring and a scapegoat. Rather, Economics confronts students with the liberal arts – whether they like it or not. Be careful. Liberal Arts are not the same as Humanities. They include argumentation, the ability to write and communicate, clear and consistent logic, and, yes, even math. Accounting can tell you how to keep track of the money, but it doesn’t include a theory for when you should produce more or less in contrast to your competitors. Finance does better since it has the time value of money and ‘with vs without’ analysis. That’s closer to marginal thinking. But finance lacks a theory of markets outside of portfolio theory and arbitrage.**

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The Day the Cloud Evaporated: Life After the Data Center Collapse (A Guest Post by AI)

Jeremy Horpedahl3 Comments

This is a “guest” blog post that I asked Google Gemini Pro to write. Data centers are increasingly becoming a political issue in communities across America. People are asking questions like: “Why do we need these things? How much water will this use?” Because these are sometimes referred to as “AI Data Centers,” people might assume that data centers are primarily about creating cat memes and fake videos. And it’s true that’s a part of AI, and it’s true that much of the new data center construction is for AI.

But… data centers have been around for a while. People are only now taking notice of them, for the most part. To better understand this issue, I asked — what else? — AI to explain how much data centers are used in our daily lives. AI in this case means Google Gemini Pro.

I’ll paste the full guest post below, but I want to point something out first: this blog post makes no mention of AI. Instead, it talks about: GPS and mapping apps; almost everything you do if you work in an office; credit cards and digital banking; news and social media. All of these things rely on data centers and would cease to function without data centers. That’s not because I asked Gemini to leave out AI from the guest post — when I followed up on this omission, Gemini said “It was a calculated omission—partly to keep the focus on the immediate ‘analog’ shock to daily life.” Most people probably wouldn’t care of they lost the ability to create funny images with AI. They would care if they lost all of their photos, access to their Dropbox account, and the ability to send email.

You could interpret all of this as saying we are “too dependent” on data centers and the modern Internet. You could also say we are “too dependent” on electricity. Or modern plumbing. Or modern supply chains. Or agriculture. Modern life is based on modern technology. I don’t know if it really makes sense to say we are “dependent” on these things, other than that we use them and they are beneficial.

Anyway, on to the guest post from Google Gemini Pro:

The Day the Cloud Evaporated: Life After the Data Center Collapse

Imagine waking up tomorrow morning in your suburban home in Ohio, or your apartment in Seattle. You reach for your smartphone to silence the alarm, but the screen is a stubborn, glowing rectangle of error messages. You try to check the weather, but the app’s spinning wheel never stops. You try to text your partner, but the message stays “Sending…” until it eventually fails.

This isn’t just a bad Wi-Fi connection. Every data center on Earth—those massive, humming warehouses filled with silicon and cooling fans—has vanished. In an instant, the “brain” of the modern world has been lobotomized. For the average person in the United States, life wouldn’t just slow down; it would fundamentally reset to 1950, but without the physical infrastructure of 1950 to catch the fall.

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Will AI kill the research paper?

mdmakowsky1 Comment

Will AI kill the research paper?. I don’t know, probably not. But I do know that what has constituted a research paper has changed many times before and will change many times again.

Before the the 1940’s, economics research papers were largely prose. Analytic in nature, sure, but prose. Some graphs, maybe a box. A little math, but math largely for the sake of demonstrating logical relationships. Then Samuelson hit, reframed economics as thermodynamics and differential calculus. What was previously a research paper was was now a polemic, a monograph at best. Thought experiments were out, high theory was in.

This era of high theory flourished in the 70s, the math changed, and at some point computers arrived with the possibility of data sufficiently rich and numerous you couldn’t just plot all of the observations in Figure 1. That data couldn’t stand on its own, though. To be a credible publication you really needed to bundle your analysis with some theory that generated testable predictions. Pure theory papers gave way to an era of applied imperialism as economic models found themselves applied to every quantified context under the social scientific sun.

Causal identification became a thing of interest, and we got really good at telling stories again. Specifically, stories about instrumental variables. You needed a story to convince anyone, but we told so many that some folks started to notice that these stories were often pretty weak. That, in part, turned up the heat on a credibility revolution that was already in swing, which meant now you needed even better data and you needed to defend you identification strategy to the death. What was a paper before was now an embarassment you should probably consider retracting (nb: no one retracted anything, but that doesn’t mean people were suggesting it behind their backs).

Which kept rolling in data set after data set until we woke up one day and realized you either need to go out in the world and create your own actual experiment (nothing quasi- about it) or you needed to cultivate access to better…no, better…no, the very best-est, most detailed and granular administrative data ever, preferably a universe if possible. Data so perfect as to allow for contributions unassailable in their legitimacy. Do you have friends at the Danish Census? If you want tenure you should probably start flirting with someone at the Danish Census.

So a paper was a paper. Until it wasn’t a paper anymore. Until that wasn’t a paper anymore. Until that wasn’t a paper. The Recursive Dundee Theory of Research*, if you will. They all met the criteria of a contribution, until they didn’t.

So what does this mean for AI and research papers now? Well, if we look to thermodynamics in the 40s and cheap computing power in the 90’s for analogues, then I’d say it’s going to reshape the criteria for a contribution in no small part because it lowers the cost of mediocrity. Mediocre analysis will no doubt persist, but it will shift over into blog posts and journals no one ackowledges as legitimate. Do remember, please, that mediocrity is a relative concept. The quality of blog posts and publications in scam journals will likely massively improve as what can be accomplished in an afternoon’s work is radically increased. Don’t worry, I have no intention of improving beyond my current warm bath of blogging unremarkableness, but others will likely cave in to the pressure.

What about the papers in top journals, though? The papers Tyler is presumably talking about. Will AI kill those economic research papers? Probably not, but it will likely improve it significantly. Why? For the same reason that Michael Kremer says that technology and quality of life improve with the size of the human population. More people means more ideas, and there is nothing more important to economic growth than the sheer number of ideas. And no, I do not mean ideas generated by AI’s. I mean the raw number of researchers with the capacity to make major contributions is increasing dramatically because we’re all getting research assistants. We’re all getting copy editors. We’re all getting support. That’s how AI is going to change the research paper: by giving more ideas the support they need to reach the light of publication. The bar is going to get higher for the same reason that the level of sports improve as you widen the geography they pull from. There’s someone at a directional state school who didn’t get the placement they deserved out of grad school. Sure they have to teach a 3-3 load, but they’re licking their chops right now because they don’t need an army of grad assistants. Summer is here and they’ve got everything they need to make a contribution.

Or I don’t know. Maybe AI will do all of our thinking in 50 years. Forecasting technology beyond 5 years is like forecasting weather beyond 5 days: I can’t do it and neither can you.**

*Apologies to Justin Wolfers and all my Aussie friends for a bit of cultural appropriation. I promise to put some Vegemite on toast while enjoying a flat white and explaining Aussie Rules Football to a friend within 90 days.

**Except for Neal Stephenson. That guy’s the Warren Buffet of Sci Fi forecasting. Maybe he’s the one in a billion person actually experiencing one in a billion level luck, but that doesn’t make it any less impressive.

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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