Jerome Powell’s term as Fed Chair ends in late May 2026. President Trump has said that he will nominate a new chair and the US senate will confirm them. It may take multiple nominations, but that’s the process. The new chair doesn’t govern monetary and interest rate policy all by their lonesome, however. They have to get most of the FOMC on board in order to make interest rate decisions. We all know that the president wants lower interest rates and there is uncertainty about the political independence of the next chair. What will actually happen once Jerome is out and his replacement is in?
The treasury markets can give us a hint. The yields on government debt tend to follow the federal funds rate closely (see below). So, we can use some simple logic to forecast the currently expected rates during the new Fed Chair’s first several months.
Here’s the logic. As of October 16, the yield on the 6-month treasury was 3.79% and the yield on the 1-year treasury was 3.54%. If the market expectations are accurate, then holding the 1-year treasury to maturity should yield the same as the 6-month treasury purchased today and then another one purchased six months from now. The below diagram and equation provide the intuition and math.
Since the federal funds rate and US treasury yields closely track one another, we can deduce that the interest rates are expected to fall after 6 months. Specifically, rates will fall by the difference in the 6-month rates, or about 49.9 basis points (0.499%). This cut is an expected value of course. Given that the cut is between a half and a zero percent, we can back out the market expectation of for a 0.5% vs 0.0% cut where α is the probability of the half-point cut.* Formally:
One of the likely effects of the federal government shutdown is that recipients of SNAP benefits (what used to be officially called “food stamps,” a term still used by the general public, especially those that dislike the program) may lose their benefits next month. This would obviously be a hardship for those that depend on this program, but it has also led to bad claims being made about the program, from both supporters and opponents of the program.
Let’s start from the political right: Matt Walsh makes the claim that by subsidizing food consumption “obviously drives up the cost” of groceries.
The number one thing that artificially inflates the price of groceries is the food stamp program. The federal government is subsidizing groceries for 40 million people which obviously drives up the cost. That's why the increase in the cost of groceries tracks exactly with the…
As with all bad claims, there is a nugget of truth baked into them. If the government subsidizes anything, we would expect demand to increase, and thus unless supply is perfectly elastic, there will be some effect on prices. However, we need to think more carefully about the nature of the subsidy.
The way SNAP works is that beneficiaries receive an electronic voucher to spend at the grocery store, which is about $300 per month on average for a household. That $300 must be spent on groceries. However, if that household had already planned to spend $300 or more on groceries, it is unlikely they will spend all of the additional $300 on food. In the limit, it’s entirely possible they will spend no additional money on groceries, merely reducing their out-of-pocket spending on groceries by $300. They will then effectively have $300 more to spend on other goods. More likely is that they will spend some of the additional $300 on groceries, and some of it on other goods.
Many studies have tried to look at the extent to which SNAP benefits affect household spending, but these were mostly observational studies. There was no treatment and control group. But a 2009 paper titled “Consumption Responses to In-Kind Transfers: Evidence from the Introduction of the Food Stamp Program” has a better approach to studying the question. Since the original Food Stamp program was slowly rolled out across the country over more than a decade, you can compare counties that entered the program first to counties that entered it later. By doing so, Hilary Hoynes and Diane Schanzenbach find out some first interesting things about the causal effects of SNAP benefits.
For the claim by Walsh in his Tweet, the most relevant result from the paper is that food stamps impact household spending similarly to a cash transfer. Yes, the program increases household spending on groceries, but it also increases spending on other goods and services. And it does so almost identically to how cash transfers impact household spending. In other words, while pitching the program as assistance for buying groceries may make it more politically palatable, SNAP benefits are no different from a similarly-sized cash transfer for the average recipient. If they do cause any inflation, they do so in the same way as a cash transfer would, and thus there is no specific impact on food inflation.
A second bad claim about SNAP comes from the political left, in this case Minnesota Governor Tim Walz:
Talk to some economists and they’ll tell you that exchange rates aren’t economically important. They say that exchange rates between countries are a reflection of supply and demand for one another’s stuff. So, at the macro, it’s a result and not a determinant of transnational economic activity.
For individual firms at the micro level, it’s the opposite. They don’t affect the exchange rate by their lonesome and are instead affected by it. If you have operations in a foreign country, then sudden changes to the exchange rate can cause your costs to be much higher or lower than you had anticipated. The same is true when you sell in a foreign country, but for revenues. This type of risk is called ‘exchange rate risk’ since it’s possible that none of the prices in either country changed and yet your investment returns change merely because of an appreciated currency.
Supply & Demand
Exchange rates are determined by supply and demand for currencies. Demand is driven by what people can do with a currency. If a country’s goods become more attractive, then demand for those goods rise and demand for the currency rises. After all, most retailers and wholesalers in the US require that you pay using US dollars. Importantly, it’s not just manufacturing goods that drive demand for currency. Demand for services, real estate, and financial assets can also affect the supply and demand for currency. In fact, many foreigners are specifically interested in stocks, bonds, US treasuries, and other investments. The more attractive all of those things are, the more demand there is for them.
Of course, the market for currency also includes suppliers. Who does that? Answer: Anyone who holds dollars and might buy something. Indeed, all buyers of goods or financial products are suppliers of their medium of exchange. In the US, we pay in dollars. Especially since 1972, suppliers have also included other central banks and governments. They treat the US currency as if it’s a reserve of value, such as gold, that can be depended upon if they need a valuable asset (hence the name, “Federal Reserve”). This is where the term ‘reserve currency’ comes from – not from the dollar-denominated prices of some internationally traded commodities. Though, that’s come to be an adopted meaning.
Another major supplier of currency is the US central bank. It has the advantage of being able to print US dollars. But it doesn’t have an exchange rate policy. So, it’s not targeting a particular price of the US dollar versus any other currency. The Fed does engage in some international reserve lending, but it’s not for the purpose of supplying currency to foreign exchange markets.
The US Exchange Rate in 2025
One of the reasons that the US has such popular financial assets is that we have highly developed financial markets and the rule of law. People trust that, regardless of the individual performance of an asset, the rules of the game are mostly known and evenly applied. For example, we have a process to follow when bond issuers default. So, our popularity is not merely because our assets have higher returns. Rather, US investment returns have dependably avoided political risk – relative to other countries anyway.
Inflation adjusting income and prices from the past is a common theme in my blog posts, including fact checking of other attempts to do these adjustments. But here is a really novel one, in a viral post from Facebook (which comes from this essay), which claims that a civil engineer earned the equivalent of $450,000 in today’s terms:
Can this be correct? If so, it would represent massive stagnation in incomes over time. Thankfully, there are two major errors, or at least misleading aspects to the calculation.
The listed salary was not one of an “ordinary man” — far from it.
Using gold prices to inflation adjust the incomes is very misleading.
First, the salary: $3,000 per year was definitely not what ordinary men earned. The average wage, for example, for a production worker in manufacturing was 18 cents per hour. You would need to work almost 17,000 hours to earn $3,000 at that wage, which of course is not possible. In reality, the average worker put in 57 hours per week — which means they earned about $500 if they were able to work 50 weeks per year (most probably didn’t). So already we see that the civil engineer working on the Panama Canal is making about 6 times as much as an “ordinary man.” Agricultural workers, the other main industry of 1910, earned about $28 per month ($22 if they also received board) — even less than manufacturing, and only about 1/10 of the engineer
Second, the gold price adjustment is misleading. Yes, in 1910, gold was how we defined currency in the US. But you can’t eat gold, and most people only keep a little gold on hand that can be described as providing services for them (such as jewelry). What people really wanted were real goods and services, and mostly goods. Around 1910, the average American household spent about 40% of their income on food, 23% on housing, and 15% on clothing. Comparing standards of living over time requires us to look at what people spend their money on, not what the currency is denominated in. And that’s what a good consumer price index does: it compares the prices of all consumer spending at different points in time, not just one thing like gold, allowing us to make rough comparisons of income over time.
Using the Measuring Worth historical CPI (which extends the BLS CPI back before 1913), we see that the index was 9.21 in 1910, and it stands at 323.364 in August 2025. So the 18-cent manufacturing wage from 1910 is roughly equivalent to $6.32 in current dollars. The average manufacturing wage today? Around $29. And of course, workers today have a whole range of fringe benefits, worth roughly another $13.58 for private sector workers. This means that an “ordinary man” today working in manufacturing can buy 5-7 times as many real goods and services as his 1910 counterpart for each hour he works. And the work is, of course, much safer today: BLS reports 23,000 industrial deaths in 1913 (61 deaths per 100,000 workers), but only 391 manufacturing deaths in 2023 (0.003 deaths per 100,000 workers).
But what about that extraordinary man in 1910, the civil engineer? How was he doing compared with today? Using the same historical CPI, we can see that $3,000 in 1910 is roughly equivalent to $105,000 today. Not bad! That’s almost exactly the median pay for civil engineers today. But keep in mind the civil engineer working in Panama was an unusually highly paid position. A 1913 report from the American Society of Civil Engineers suggests that most early career civil engineers were making closer to $1,500 per year — half of the Panama engineer. Engineers were also a highly skilled, very rare profession in 1910. And don’t forget that about 10% of the American workers on the Canal died in the construction, mostly from disease so the engineers were probably just as susceptible to death as the laborers.
Finally, we might ask a different question: what if you had held onto gold since 1910? Let’s say your great-great grandfather was a civil engineer, and managed over the course of a few years to save one year’s salary in gold. He even managed to hide it during the 1930s-1970s, when private holding of gold was generally illegal in the US.
How much would that 150 ounces of gold be worth today? That answer is simple: about $615,000 today (gold has gone up a bit just since that calculation was done in May!). But was that a good investment? Not really. A $3,000 investment in the stock market from 1910 to 2024 would be worth about… $120 million (it’s actually a bit more than that, since the market continued to rise after January 2024). Of course, that would have required a bit of active management, since index funds don’t come along until much later. But your great-great grandfather would have been much wiser to set up a trust for you and have it actively managed to approximate the entire US stock market, rather than to bury 150 ounces of gold in his backyard.
Even assuming you lost half the value to management fees, the stock portfolio today would be worth at least 100 times as much as the gold.
A periodically recurring conversation on social media is whether imports are bad for GDP. Everyone thinks they are clearly right, and then they lazily defer to brief dismissal of the opposing view. Some of this might be due to media format. Something just a tiny bit more thorough could help to resolve the painfully unproductive online interactions… And just maybe improve understanding.
It starts with the GDP expenditure identity:
The initial assertion is that imports reduce GDP. After all, M enters the equation negatively. So, all else constant, an increase in M reduces Y. It’s plain and simple.
Many economists reply that the equation is an accounting identity and not a theory about how the world works and that the above logic is simply confusing these two things. This reply 1) allows its employers to feel smart, 2) doesn’t address the assertion, & 3) doesn’t resolve anything. In fact, this reply erects a wall of academic distinction that prevents a resolution. What a missed opportunity to perform the literal job of “public intellectual”.
How are Imports Bad/Good/Irrelevant for GDP?
Let’s add a small but important detail to the above equation to distinguish between consumption of goods produced domestically and those produced elsewhere.
There are 62 songs called “Better Man” just on Ultimate Guitar (which doesn’t claim to be comprehensive), plus many more slight variations like “A Better Man” or “Better Man Blues”. Some of these are obscure, but many are from well-known artists including Taylor Swift, Oasis, Ellie Goulding, Justin Bieber, and Pearl Jam; one by Robbie Williams inspired a major motion picture also called Better Man.
Meanwhile there is only one song on Ultimate Guitar called “Better Woman”, plus one variation (“A Better Woman”), both from artists I hadn’t heard of (Sera Cahoone and Beccy Cole). Why such an extreme difference?
Is it that men are the ones who are terrible and need improvement? Or are men the ones who see hope for improvement, while women can’t change or don’t want to? Let’s consider what the lyrics have to say about this. Reading though them all I saw a few recurring categories of “Better Man”:
Wish I Were Better: I count 33 of the 62 songs in this category. A man singing about how he wishes he were better, usually because of a woman, the classic “You Make Me Want to Be a Better Man“. Sometimes this is hopeful that he will be, sometimes regretful that he hasn’t been or despairing that he won’t be. Occasionally the inspiration to be better comes from someone other than a woman he’s in love with, such as Jesus, his dad, or his kids.
You Make Me Better: 13/62. Same idea as the last category, except the man has already become better. Again usually because of a woman, but sometimes because of someone else like God or his kids or his friends. Another 3 are a variation of this, I Got Better, where the man changed without anyone’s help or for a woman who isn’t convinced he really changed.
Wish You Were a Better Man: 4/62, but includes the hit by Taylor Swift. A woman wishes a man she loved were better. Another 2 songs including the Pearl Jam hit are a variant of this, Can’t Find A Better Man, where a woman stays with a bad man because she doesn’t see a better choice. Steven Seagal (yes, that Steven Seagal) reverses things and sings that a woman should leave him because she can do better. Then there’s 1 example of the genre where Hellyeah wishes his father were a better man.
One-offs: There are a few 1-off “Better Man” songs that seem to be in a category of their own: Beth Hart’s celebration of finding a better man, Ellie Goulding‘s odd insistence that “I’m the better man” (even though she’s a woman), and Ryan Innes’ entry which is the closest anyone comes to saying they wish they were a worse man. By the way, there appear to be zero songs out there called “Worse Man”- perhaps some day I’ll write one, but its a free idea and I’d be happy to see one of you beat me to it.
What about our 2 “Better Women”?Sera Cahoone’s song (the only one with the exact title “Better Woman”) is a standard “Wish I Were Better” entry, just as a woman (though the person she wants to be better for might still be a woman as usual):
So I step on up and be a better woman in your eyes From now on I’m gonna love everything about you
Beccy Cole’s “A Better Woman” concludes that she doesn’t actually want or need to become a better woman:
I ain’t changin’ nothin’ Just to have your lovin’ Yeah, I’m alright with who I am I don’t need to be a better woman – I just need a better man
The boring explanation for the gender discrepancy is that “Better Man” just scans better rhythmically. But I don’t think can explain a 60-2 (or 60-1 if we’re being strict) difference, and there seems the be a big underlying difference in the prevalence of these themes for men and women, not just titles. This matches up with the classic sayings from Camille Paglia:
A woman simply is, but a man must become
Or this one often attributed (probably incorrectly) to Einstein:
Women marry hoping that the man will change. Men marry hoping the woman will stay the same. Both are usually disappointed.
Whatever the cause, you can find the playlist I made of all 60 “Better Man” songs I could find on Youtube Music here:
I liked most of them (surprisingly given the range of genres and the fact that I hadn’t heard of most of the artists), but my favorite in this vein is to forget being a Better Man or Better Woman, and instead be “A Better Son/Daughter” like Rilo Kiley says:
The following chart from Arbor Research shows that the average age of cars on the road in the US is 14.5 years. If we go back to 1995, it was almost half that, and the increase has been steady since over the past 30 years. Similar data from the Bureau of Transportation Statistics confirms these numbers.
Why would this be? I see two primary explanations that are possible. One is that cars are becoming more reliable (better quality), so consumers are happy to drive them longer. The other is that cars today are less affordable, so people are only hanging onto old cars because they are forced to. One of these is a happy explanation, one is consistent with a narrative of stagnation. Which is true?
On the affordability question, we do have some good data, but it points in the opposite direction: cars are much more affordable today than in 1995, or even before that.
Today I’m just sharing a truly awe-inspiring resource. The University of Missouri has what is essentially a central clearinghouse for prices and wages. If you want the price of anything, then they should be your first stop.
See the screenshot at the bottom. The website links to the original sources for household consumption prices, occupation wages, etc. They make it easy to cut the data by date, industry, location, etc. Because they cite their sources, you can see some data series that are not even available on FRED – without having to perform the painful sleuthing on a government website.
I especially like this site for its historical data. One of the challenges of historical US data is that individual cities may not have prices that are representative of the national levels or trends. Lower levels of market integration make representative samples even more important than in modern data. But really, that was more of a concern for 20th century researchers. Now, we love our panel data. So, the historically less integrated markets of the US provide ‘toy economies’ that include greater regionalism and local shocks.
Although David Jacks has loads of tabulated data, he doesn’t have it all. The Missouri library site links to PDFs of original statistical publications which, while digitized, have never been tabulated into useable data fit for modern researchers.
Datasets can be pulled offline for all sorts of reasons. As I wrote in February, this shows the value of being a data hoarder– just downloading now any data you think you might want later:
Several major datasets produced by the federal government went offline this week…. This serves as a reminder of the value of redundancy- keeping datasets on multiple sites as well as in local storage. Because you never really know when one site will go down- whether due to ideological changes, mistakes, natural disasters, or key personnel moving on.
The US Federal government shutdown this month provides another reminder of this. So far most datasets are still up, but I’ve seen some availability issues:
The good news is that a number of institutions have stepped up in 2025 to host at-risk datasets (joining those like IPUMS, NBER, and Archive.org that have been hosting datasets for many years, but are scaling up to meet the moment):
Restore CDC hosts all CDC data as it was in January 2025.
Harvard Library’s project is less user-friendly but more powerful, archiving all 16 terabytes of Data.gov.
Yesterday on Twitter I shared a chart showing the age at first marriage for white men and women in the US, with data going back to 1880. I pointed out an interesting fact: at least for men, the age was essentially the same in 1890 and 1990 (27), though for women it was a bit higher in 1990 than in 1890 (by about 1 year).
This Tweet generated quite a bit of interest (over 800,000 impressions so far), and (of course!) a lot of skeptical responses. One skeptical response is that I cut off the data in 1990, when trends since then have shown continuously rising ages at first marriage, and by 2024 the comparable figures were much higher than in 1890 (by about 4 years for men and 6.5 years for women). In one sense, guilty as charged, though I only came across this data when looking through the Historical Statistics of the US, Millennial Edition, and that was the most current data available when it was printed. Here is a more updated chart from Census:
But there is another interesting fact about that data: the massive decline age of first marriage in the first half of the 20th century. Between 1890 and 1960, the median age at first marriage fell by about 3 years for men and 2 years for women. For men, most of the decline (about 2 years) had already happened by 1940. Thus, if we start from the low-point of the 1950s and 1960s (as many charts do, such as this one), it appears marriage is continuously getting less common in US history, while the fuller picture shows a U-shaped pattern.
This same pattern shows up in another measure of marriage data: the percentage of people that never get married. If we look at White, Non-Hispanic Americans in their late 40s, the picture looks something like this (keen observers will note that the Hispanic distinction is a modern one dating from the 1970s, but Census IPUMS has conveniently imputed this classification back in time based on other demographic characteristics):
Looking at people in their late 40s is useful because, at least for women, they are past their childbearing years. And using, say, the late 50s age group doesn’t alter the picture much: even though some people get married for the first time in their 50s, it’s always been a small number.
Here we can see an even more dramatic pattern. 100 years ago, it was not super rare for people to never marry: over 1/10 of the population didn’t! But by 1980 (thus, for people born in the early 1930s), it was much rarer: less than 4% of women were never married (among White, Non-Hispanics). In fact, the peak in 1920 of 10% unmarried women wasn’t surpassed again until 2013! And it’s not substantially higher today than 1920 for women, especially when considering the full swing downward. Men are quite a bit higher today, though the 1920 peak of 13% wasn’t surpassed again until 2006.
For a measure that peaks in 1920, we might wonder if new immigrants are skewing the data in some way, given that this is right at the end of about 4 decades of mass immigration. But just the opposite: if we focus on native-born women, the 1920 level was even higher at 11.1%, which wasn’t surpassed until 2022, and even in the latest figures it is less than 1 percentage point higher than 1920.
Precisely why we observed this U-shaped pattern in marriage (both first age and ever married) is debated among scholars, though my sense among the general public is that it isn’t much thought about. Most people (from my casual observation) seem to assume that marriage rates and ages were always lower in the past, and that modern times are the outliers. But in reality, the middle part of the 20th century seems to be the outlier. The “Baby Boom” of roughly 1935-1965 is possibly better understood as a “Marriage Boom,” with more babies naturally following from more and younger marriages.
Economist Writing Every Day 