Economist Writing Every Day

Update on School Valentines

January 31, 2026January 30, 2026Joy BuchananLeave a comment

I have principles. One of them is that school Valentines are indulgent and bad for the environment.

I have written Markets in Everything for school Valentine’s

And here are some quotes from Do Less for Preschool

Just fail, people. Don’t even put “crazy sock day” on your work Outlook calendar…

Oh no. If AI lifts the constraint of time, then what we are going to get is more crazy sock days. To stay ahead in the status competition, families will have to do Bluey-Crazy Sock Day every week. The ocean will become a thick soup of polyester Bluey-crazy-socks, size 3T, worn only once.

On principle, I did low-effort Valentine’s last year. I spent as little of my own time and money as I could. My kids wrote their friends’ names on the paper things. Smugly, I imagined that I’d saved the dolphins in the tuna nets and helped some other mom feel like she was doing okay.

Who do you imagine is upset? Not the other moms. My kids. The older one especially feels in his body that failing this test in February of 2026 will result in expulsion from the tribe and death in the outer darkness beyond the reach of the campfire.

Guess what I care about more than dolphins? We will do more this year.

Preschool kids do not care and should not be asked to care. I still believe that parents and daycare directors should do less for preschool. Truly, I see no reason, at all, for a preschool dress up day or Valentine’s Day party. Can someone think of the dolphins before it’s too late and the kid grows up and starts caring about the status wars?

Drawbacks of Long Term Thinking

January 30, 2026January 30, 2026Zachary BartschLeave a comment

This post is just some thoughts about perspective. I apologize for any lack of organization.

My academic influences include North, Weingast, Coase, Hayek, the field of Public Choice, and others. I’m not an ‘adherent’ to any school of thought. Those guys just provided some insights that I find myself often using.

What lessons did they teach? Plenty. When I see the world of firms, governments, and other institutions, I maintain a sharp distinction between intention and outcome. Any given policy that’s enacted is probably not the welfare maximizing one, but rather must keep special interests relatively happy. So, the presence of special interests is a given and doesn’t get me riled up. When I see an imperfect policy outcome, I think about who had to be enticed to vote for it. We live in a world where ‘first bests’ aren’t usually on the table.

Historically, or in lower income countries, I think about violence. Their rules and laws are not operating in a vacuum of peaceful consent. There is always the threat of violence. Laws are enforced (or not) conditional on whether and what type of violence that may result. All of the ideal legislation is irrelevant if theft and fraud are the lay of the land.

I think about institutional evolution with both internal and external pressures. I’m a bit worried about the persistence of the US republic, or at least worried for its pro-growth policies. I’m not worried about China in the long run. I don’t think they have the institutions that get them to ‘high income’ status. I do think that they are a tactical concern in the short run and that the government does/will have access to great volumes of resources in the medium run. That’s a bit of a concern. But like I said, I’m not super worried in the long run.

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The Wealth Ladder

January 29, 2026January 25, 2026James BaileyLeave a comment

The Wealth Ladder is a 2025 personal finance book from data blogger Nick Maggiulli. The core idea is good: that the best financial strategies will be different based on your current wealth level. Maggiulli divides people into 6 net worth levels based on orders of magnitude, from less than $10K to over $100M. The middle of the book has separate chapters with advice for people in each level, so a book that is already a fairly quick and easy read as a whole could be even quicker if you skipped the chapters about levels other than your own.

The beginning of the book tries to develop some simple rules phrased in a way that they can apply across every level, because they are based on a percentage of your net worth. I like the idea but don’t think it really worked. His “1% Rule” says you should only accept an opportunity to earn money if it will increase your net worth by at least 1%. But in practice, whether an earning opportunity is worth your time depends less on how many absolute dollars in generates as a % of your net worth, and more on how many $ per hour it generates. The “0.01% Rule” (don’t worry about spending money on anything that costs less than 0.01% of your net worth) is better. But whether it is a good rule for you will depend on your age and income.

In short, while tailoring his advice in 6 different ways for the 6 wealth levels of his ladder is an improvement on one-size-fits all personal finance books, even this much tailoring isn’t enough. Having a $1 million net worth is normal for a household in their 60s but would be exceptional for one in their 20’s; and vice-versa for a household with under $10k net worth. Chapter 10 explains the data on this well, but it kind of undermines the ideas of the previous chapters. Households with the same net worth should be making very different decisions in their 20s vs 60s.

The strongest part of the book is the use of data from the Survey of Consumer Finances and the Panel Study of Income Dynamics to show how people differ by wealth level and how people move from one level to another. For instance, he shows that the poor have most of their wealth in cash and vehicles; the middle class in homes; the wealthy in retirement accounts and stocks; the very rich in private businesses. Americans tend to climb the wealth ladder slowly but steadily; over 10 years they are twice as likely to move up the ladder as to move down; over 20 years, 3 times as likely. The median person who made it to one of the top 3 rings (i.e. the median millionaire) is in their 60s.

If you get ahold of a copy of the book it’s definitely worthwhile to flip through all the tables and figures, but I won’t be adding to to my short list of the best personal finance books. The core metaphor of the ladder carriers the implicit assumption that everyone should be trying to get to the top of the ladder. But if someone is satisfied with less than $10 million, why should they take on lots of time and effort and risk to start a business for a small chance to go over $100 million?

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The US Homicide Rate in 2025 May Have Been the Lowest Ever

January 28, 2026Jeremy Horpedahl1 Comment

The following chart merges two data sources to create a long-run series on homicides in the US. Based on early estimates for 2025 from Jeff Asher, the homicide rate may be as low as 4.3 murders per 100,000 population. That would be the lowest since at least 1900, and possibly the lowest US homicide rate ever since the best evidence suggests it was even higher pre-1900. The current record low was 4.4 murders per 100,000, which the US saw in 1955, 1957, and 2014.

Economic Impacts of Weather Apps Exaggerating Storm Dangers

January 27, 2026January 27, 2026Scott Buchanan1 Comment

Snowmageddon!! Over 20 inches of snow!!! That is what we in the mid-Atlantic should expect on Sat-Sun Jan 24-25 according to most weather apps, as of 9-10 days ahead of time. Of course, that kept us all busy checking those apps for the next week. As of Wednesday, I was still seeing numbers in the high teens in most cases, using Washington, D.C. as a representative location. But my Brave browser AI search proved its intelligence on Wednesday by telling me, with a big yellow triangle warning sign:

Note: Apps and social media often display extreme snow totals (e.g., 23 inches) that are not yet supported by consensus models. Experts recommend preparing for 6–12 inches as a realistic baseline, with the potential for more.

“Huh,” thought I. Well, duh, the more scared they make us, the more eyeballs they get and the more ad revenue they generate. Follow the money…

Unfortunately, I did not log exactly who said what when last week. My recollection is that weather.com was still predicting high teens snowfall as of Thursday, and the Apple weather app was still saying that as of Friday. The final total for D.C. was about 7.5 inches for winter storm Fern. In fairness, some very nearby areas got 9-10 inches, and it ended up being dense sleet rather than light fluffy snow. But there was still a pretty big mismatch.

Among the best forecasters I found was AccuWeather. They showed a short table of probabilities that centered on (as I recall) 6-10”, with some chances for higher and for lower, that let you decide whether to prepare for a low probability/high impact scenario. It seems that the Apple weather app is notoriously bad: instead of integrating several different forecast models like some other apps (and like your local talking head meteorologist), it apparently just spits out the results of one model:

The core issue is that many weather apps, including Apple Weather, display raw data from individual forecast models without the context and analysis that professional meteorologists provide. While meteorologists at the National Weather Service balance multiple computer models, dozens of simulations and their own expertise to create forecasts, apps often pull from a single source and deliver it directly to users.

“Everything that catches attention is mostly nonsense,” said Eric Fisher, chief meteorologist for WBZ-TV in Boston. He points to the viral snowfall maps that spread on social media, noting that extreme forecasts generate the most attention even when they may not be the most accurate.

Anyway, I tried to poke around and find out in dollar terms how much it benefits the weather apps to exaggerate storm dangers. I was unsuccessful there, but by playing with query wording, I was able to coax out of ChatGPT some numbers on how much these exaggerations may cost the rest of us. (A more qualitative search noted, among other things, that the “crying wolf” cost of people becoming jaded to alarmist forecasts may lead them to discount genuine warnings; and I will add it is inconvenient to find the stores out of things because of panic buying).

Everything below the line of asterisks is just a straight dump from the AI, since I could not readily improve on its presentation:

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The economic impact of weather apps exaggerating storm dangers isn’t easy to quantify precisely because most formal studies focus on weather warnings overall (from official sources like the National Weather Service), not specifically on private weather apps exaggerating risk. However, economics research on false alarms, over-warning, and exaggerated alerts offers concrete dollar figures that we can use to approximate the kinds of costs involved. Below are the key economic impacts with as many dollar figures as available:

💸 1. Opportunity Costs of False or Overbroad Storm Warnings

Time cost of false warnings:

Traditional county-wide tornado warnings (over-broad alerts) have historically forced many people to shelter unnecessarily, resulting in ≈234 million person-hours per year spent under warnings (1996–2004) — valued at roughly $2.7 billion annually in lost time/productivity in the U.S. alone.
Improved storm-based warnings that reduce false warning area could save up to $750 million–$1.9 billion/year in avoided lost time.

This demonstrates that exaggerated alerts — such as those sometimes amplified or presented without clear context by weather apps — can force unnecessary economic shutdowns of work and business activity.

🏙️ 2. Evacuation and Preparedness Costs from False Alarms

Evacuation costs:

A NOAA analysis estimates that evacuation costs for hurricanes, when done broadly for storm-warnings, can reach about $1.4 billion annually in the U.S., with roughly $1 billion being unnecessary cost due to false alarms (people evacuating where no damaging winds ultimately occur).

Evacuations are one of the most expensive forms of response — from lost wages to lodging and fuel costs — and exaggerated risk messaging can trigger them prematurely or more frequently.

🏭 3. Business Productivity Losses from False Alerts

Example from private sector:

A building management firm reported that by reducing false storm alerts (better targeted data rather than broad app warnings), it saved ~$10 million in lost production time in one year alone.

This is a real dollar example showing how over-warning impacts businesses directly when they preemptively shut down operations.

💼 4. Broader Firm-Level Economic Avoidance

Cost avoidance from better warning info:

A study of nearly 500 firms found that switching from deterministic (binary “storm/no storm”) warnings to probabilistic information could produce $2.3 billion to $7.6 billion per year in avoided costs for businesses, thanks to better decision-making.

While this doesn’t measure exaggeration specifically, it underscores the economic penalty of imprecise or alarmist warnings, which many weather apps unintentionally echo.

📉 5. Insurance & Property Impacts

Although not directly about exaggerated warnings, inaccurate perceptions of storm danger influence behavior and pricing:

Insurance premiums rising: In storm-prone states (e.g., Florida), homeowners’ premiums have risen by ~57% or more because of risk perceptions and loss patterns tied to severe weather.
Losses from storms: Billion-dollar disasters are common; for example, Hurricane Milton in 2024 had estimated total costs of $21–$85 billion (depending on source).

While not directly caused by exaggeration, inflated perceptions of danger (from apps or media) can affect insurance markets and property values, contributing indirectly to economic impacts.

📈 6. Net Benefits vs. Exaggeration

It’s important to balance:

Early warnings overall clearly save money and lives. Improved forecasts and early alert systems have been estimated to avoid $300 million to $2 billion per year in asset losses and provide up to $32 billion/year in broader economic benefits (through optimized activities and prep).

This highlights that the problem isn’t warnings per se, but inaccurate or exaggerated warnings that cause over-response.

What is the price of obvious lying?

January 26, 2026January 26, 2026mdmakowskyLeave a comment

Pushing beyond the despair and doomerism of “Nothing matters”, the question has never been is there a price for lying in politics, but rather what is the price of lying in politics. Note that “in politics” is doing a lot of heavy lifting here. In day to day life, the price of lying is the threat to your reputation. A reputaton for being untrustworthy is always very costly in the long run. But politics, however, has different layers across which the price of lying is heterogeneous. And yes, there are contexts where that price can go negative.

Put simply, what is the cost here? Is Greg Bovino, head of US Border Patrol, worried about his reputation? Is he worried about future personal legal liability? Is he worried about maintaining cooperative alignment across the administration and within the ranks of the Border Patrol and ICE? There’s a saying in politics – the worst thing you can do is tell the truth at the wrong time. But that’s more relevant to “lying by omission”, about simply abstaining from speaking on a subject so that you are not forced to choose between lying and paying a high political cost. This is different. I’m picking on this one person in the administration because Alex Pretti was summarily executed in the street in cold blood by a thicket of federal agents for the apparent crime of being in attendance and trying to help a woman while she was being pepper sprayed, but it is the subsequent lying that I am concerned with here. It follows a pattern that continues to darkly fascinate me.

Rather than simply “say nothing”, this administration has committed to the broad tactic of stating things that are factually, obviously untrue. That, more important, it is highly likely they know are untrue. That’s not something we’ve seen a lot of before. Politicians were known for being “slick” and “slippery”. For bending the truth, torturing the facts, or managing to fill entire press conferences without saying or committing to anything of substance. This administration, as I’ve said before, is different.

I see two likely explanations:

The price of lying is zero because no one believes anything anymore. The truth is subjective and siloed.
The price of lying is negative because constant and consistent commitment to the party can only be demonstrated by bearing the personal cost of telling obvious lies. In doing so you maintain the group, save yourself from being purged, and everyone in the group lives to fight another day. The net of which is a negative price for lying.

So what is it? Are we through the lol-nothing-matters looking glass, or are we witnessing an administration circle the wagons and solidify their committment to one another by blatantly lying on national television? I’m (perhaps obviously) of the belief that everything matters, that lying does have a cost, but the need for unity is so strong within this administration and it is, in fact, the lying that is holding it together. Until, of course, it doesn’t. Remember the most important lesson of The Folk Theorem – you can sustain cooperation in the Prisoner’s Dilemma, but only until you learn when the game is going to end. Then all bets are off.

Casual Sourdough Baking

January 24, 2026January 25, 2026Joy BuchananLeave a comment

I have sourdough starter in my fridge and have tried making two rounds of bread. I write this as a civilian, for others who will never elevate baking above a hobby.

I will begin with a picture of my first bread:

That’s not very fluffy but not terrible. It was real bread to go with butter or soup. My neighbor’s starter was in great condition when she gave it to me, and I followed the standard recipe. I use 80% bread flour and 20% whole wheat flour to make it healthier.

Below I will speculate on whether sourdough projects are a good use of time or not. Call it home economics.

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Which Economies Grow with Shrinking Populations?

January 23, 2026January 23, 2026Zachary Bartsch4 Comments

If you didn’t know, China has had negative population growth for the past 4 years. Japan has had negative population growth for the past 15 years. The public and economists both have some decent intuition that a falling population makes falling total output more likely. Economists, however, maintain that income per capita is not so certain to fall. After all, both the numerator and denominator of GDP per capita can fall such that the net effect on the entire ratio is a wash or even increase. In fact, aggregate real output can still continue to grow *if* labor productivity rises faster than the rate of employment decline.

But this is a big if. After all, some of the thrust of endogenous growth theory emphasizes that population growth corresponds to more human brains, which results in more innovation when those brains engage with economic problems. Therefore, in the long run, smaller populations innovate more slowly than larger populations. Furthermore, given that information can cross borders relatively easily no one on the globe is insulated from the effects of lower global population. Because information crosses borders relatively well, the brains-to-riches model doesn’t tell us who will innovate more or experience greater productivity growth.

What follows is not the only answer. There are certainly multiple. For example, recent Nobel Prize winner Joel Mokyr says that both basic science *and* knowledge about applications must grow together. That’s not the route that I’ll elaborate.

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How to Make a Few Billion Dollars

January 22, 2026James Bailey1 Comment

The title is excellent, given that the author Brad Jacobs did in fact make a few billion dollars.

The book itself is fine to read, but also fine to skip if you aren’t yourself burning to build a billion dollar company through excellent management and mergers and acquisitions. I certainly don’t care to, which Jacobs says would make me a bad hire for one of his companies:

I only hire people who are motivated to make a lot of money…. If an candidate says to me ‘I’m not motivated by money’, I suspect either they’re not being candid or they lack the hunger that’s necessary to succeed

The book has plenty of hard-driving sentiments like this that you’d expect from a self-made billionaire:

Fire C players

For the first time ever, an American company, Exxon, had reported quarterly earnings in excess of $1 billion. The words “obscene profits” flashed on my TV screen, and I remember thinking “That sounds pretty good! Maybe I ought to check out the oil sector.” [This part I agree with, economic theory predicts that entrepreneurs will enter the sectors with the highest profits and its what I’d do if I wanted to make money, though in practice I think it is surprisingly rare for would-be entrepreneurs to choose this way -JB]

“The CEO trait most closely correlated with organizational success is high IQ” [specifically more important than EQ]

But Jacobs balances these ideas with some surprisingly hippy-like attitudes. Jacobs went to Bennington College and almost had a career as a jazz keyboardist. Chapter 1 is titled “How to Rearrange Your Brain”, and emphasizes the importance of meditation. Page 21 is basically “have you ever really looked at your hands, man… do it, it’s a trip”

I don’t want to spend even one hour around people who are unkind. An organization is like a party. You only want to invite people who bring the vibe up

Though perhaps this hippy/anti-hippy balance shouldn’t be surprising for someone who says one of the main things he asks about potential hires is “can this person think dialectically”.

Strongly recommend the book if you want to follow Jacobs’ path; weakly recommend it as a general management/self-help book or way to learn about markets.

The US Has One of the Highest Fertility Rates Among Peer Countries

January 21, 2026January 21, 2026Jeremy Horpedahl6 Comments

Declining fertility rates have been in the news a lot lately, and with good reason. Some countries, such as South Korea, have seen massive declines in fertility rates, and they face huge social problems and population decline resulting from these declining rates. But does the United States face the same problem?

To be clear, fertility rates are down in the US. Using the most common measure, the total fertility rate, births per woman in the US fell from a peak of over 3.5 births at the peak of the Baby Boom in the late 1950s and early 1960s, to around 2 births per woman in the 1990s and 2000s, and fell further to 1.6 births in 2023 (note: it had been around 2 births in the 1930s as well — the Baby Boom was a very real).

But the total fertility rate, or the number of births per woman of child-bearing age (usually 15-49) in a particular year is not a perfect measure. As Saloni Dattani clearly explains, if the timing of births is changing, this can make the TFR temporarily fluctuate. If women on average are delaying births to a later age, the TFR will fall initially even if women end up having the exact same number of children.

An alternative measure suggested by Dattani is the completed cohort fertility rate. This measure looks at the total number of children that women from a particular birth year in a country have throughout their child-bearing years. This rate also shows a decline for the US, but it is much more gradual: for women born in the 1930s (who would eventually become mothers during the Baby Boom), they peaked at about 3.25 births per woman, which declined to right at about 2.0 births in the 1950s (the Baby Boomers themselves), and has gradually risen since then to about 2.20 for women born in the early 1970s.

How does the US completed cohort fertility rate compare with other countries?

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