Back in April I wrote about 4 different estimates of GDP growth and how well they have performed since 2023. With the 2nd quarter of 2025 GDP data coming out next week, what do the best performing predictors currently say?
In that last post, I showed that the Atlanta Fed GDPNow model and the Kalshi betting market were generally the best performers. And furthermore, averaging these two improves the predictive power a little more. As of today, the GDPNow model is predicting 2.4% growth and Kalshi is… also predicting 2.4%!
There will be a few more updates to GDPNow over the next week, and of course Kalshi is constantly updating as more people bet. But as of right now, 2.4% growth seems like a reasonable prediction. That may surprise some people, especially given all of the pessimism surrounding tariffs and policy uncertainty generally. But despite all of this, the US economy appears to be just continuing to chug along.
Here’s a somewhat niche measure of inflation: 6-month CPI excluding food, shelter, and energy. It might seem like a weird measure, as it excludes over half of the CPI. But there is a logic to at least considering it along with other measures.
Food and energy are both volatile, so they can give us a lot of noise. That’s why “core CPI” and other core measures are followed closely by the Fed and inflation watchers. But excluding shelter might also make sense, because increasing housing prices are largely due to supply constraints, and will move independently of monetary policy to some extent. Six-month inflation is also useful for a more timely measure than 12 months, the headline number.
As you can see in the chart above, this niche measure of inflation has been stuck for two and a half years. It has oscillated between about 0.5% and 1.5% since December 2022. And right now it’s almost exactly in the middle of that range. It has come down from 6 months ago, but higher than 1 year ago.
As you can see in the pre-2020 years, it generally oscillated between 0% and 1%. So 6-month inflation is stuck about 0.5% higher than we had become used to, which translates into roughly 1% higher annually.
In the grand scheme of things, 1% higher inflation isn’t the end of the world. But we do seem to be stuck at a slightly elevated rate of inflation relative to the decade before 2020.
The 23 blue-shaded MSAs in this map produce half of US GDP:
You might be tempted to think this map, like so many maps, is just a map of US population. It kind of is, but not completely. These 23 MSAs have 133 million people (as of the 2020 Census), or about 40% of the US population. That’s a lot, but it’s much less than half, which the GDP proportion they account for. In other words, these MSAs also tend to have above-average per capita income.
The three largest MSAs by population (NY, LA, Chicago) are also the three largest by GDP. But after the first three there are some interesting discrepancies. The San Francisco MSA is the 4th largest by GDP, but only the 12th largest by population — San Fran has a population similar to the Phoenix MSA, but almost double the GDP. San Francisco MSA has a very high GDP per capita (the third highest).
The San Jose MSA is also among these 23 largest MSAs for GDP, and also sticks out — it is the 13th largest by total GDP, but only the 36th largest by population. San Jose has a population similar to Cleveland and Nashville, but well over double the GDP of these two MSAs individually. In fact, there are 12 MSAs larger in population than San Jose, but that aren’t among these 23 MSAs that produce half of US GDP: places like St. Louis, Orlando, San Antonio, Pittsburgh, and Columbus. Silicon Valley really pulls up San Jose: it has the 2nd largest GDP per capita among MSAs, only beaten by much smaller Midland, Texas and its oil income.
I recently spent a week in Norway with my family. Highly recommended overall. While we were mostly able to get around the country by train, we needed to rent a car to get to a small, remote village where my great grandfather came from, and where I still have relatives. Prior to the drilling of several massive car tunnels in the 1980s and 1990s, Fjaerland was only accessible by boat.
And if you are renting a car in Norway today, it’s highly likely you will be renting an electric car (unless you specifically ask for a gas-powered car, as the older German couple in front of me at the rental counter did). The vast majority of new cars sold in Norway (over 90%) are electric, and since most rentals are new cars, that’s what they have.
Norway has made the biggest push in the world through public policy to encourage EV adoption, both for buying cars and for building up a charging infrastructure. In this post I will primarily focus on the consumer experience of renting an EV, though the public policy surrounding it is worth a discussion too.
The chart originates from Statista, as you can see from the label in the image. But it is very frequently shared on social media, Reddit, and elsewhere (often with the Statista label clipped), occasionally generating millions of views and lots of heated comments.
But it’s a bad graph. In so many ways. Let’s break them down.
The data comes from BLS’s Consumer Expenditures Survey. I use this data frequently, as regular readers probably know. The data in the viral chart is from 2021 (more on that in a moment), but if I create a similar chart using the most recent data in 2023 but also include spending by those older than Baby Boomers (primarily the Silent Generation), you will notice a curious thing:
Last week I tried to address whether rising wealth for younger generations was primarily driven by rising home values. My analysis suggested that it was a cause, but not the only cause. Here’s another chart on that topic, showing median net worth excluding home equity for recent generations:
Two things are notable in the chart. For millennials, even excluding home equity they are well ahead of past generations, though of course their net worth is much smaller excluding this category of wealth (the total median net worth for millennials in 2022 was $93,800). But for Gen X in 2022 (last data in that chart), they are slightly behind Boomers, never having recovered from the decline in wealth after 2007 (primarily from the stock market decline, since we’re excluding housing).
But today I want to address another general objection to the wealth data found in the Fed’s SCF and DFA programs. That objection has to do with household formation. Specifically, these surveys are calculated for households, and the age/generation indicators are for the household head (or “householder” as it is now called). And we know that household formation has been declining over time, as more young people live with parents, with roommates, etc. So the Millennial data we see in the chart above is excluding any Millennials that have not yet formed their own household.
Here’s a general picture of the decline, which has been happening gradually since about 1980. Note: I use the age group 26-41, because this is the age of Millennials in 2022 (the most recent SCF survey year). The highlighted years on the chart are when the Silent, Baby Boomer, Gen X, and Millennial generations were about the same age (26-41).
What this means is that when we are looking at households in these wealth surveys (or any survey that focuses on households) we aren’t quite comparing apples to apples. Does this mean the surveys are worthless? No! With the microdata in the SCF, we can look at not only the median value, but the entire distribution. Since the household formation rate has fallen by about 11 percentage points between Boomers in 1989 and Millennials in 2022, one solution is to look up or down the distribution for a rough comparison.
For example, if we assume all of the 11 percent of non-householders among Millennials have wealth below the median, we can make a rough correction by looking at the 39th percentile for Millennials — the 39th percentile would be the median if you included all of those 11 percent of non-householders as households. Similarly, for Gen X would move down 5 percentage points in the distribution to the 45th percentile in 2007.
The household-formation-adjusted chart does paint a more pessimistic picture than just looking at the median for each generation: the 39th percentile Millennial has about 20% less wealth than the median Boomer did at roughly the same age. Seems like generational decline! Is there any silver lining?
First, you should interpret the chart above as a worst case scenario for Millennial wealth. It assumes all non-householders have low wealth. But likely not all of them do. If instead we use the 43rd percentile of Millennials in 2022, their net worth is $61,000, slightly above Boomers at the same age. (The household formation problem isn’t going away anytime soon as generations age — even if we look at Gen Xers, with a median age of 50 in 2022, their household formation is still 6 percentage points behind Boomers at that age.)
Second, my worst case scenario almost certainly overstates the problem. If all of those 11 percent fewer Millennials not yet forming households were to get married to other millennials, it would only add half of that many households to the aggregate distribution (when two non-householders get married, it becomes one household). So instead of moving down 11 percentage points to the 39th percentile, we should only move down 5 or 6 percentiles. The 44th percentile of Millennial net worth in 2022 was $63,060 — again, compare this to Boomers in the chart above.
Finally, if we combine both of the adjustments discussed in this post, looking at wealth excluding home equity and also adjusting for the decline in household formation, we get the following chart (here I once again use the 39th percentile for Millennials and the 45th percentile for Gen X, i.e., the worst case scenario):
With this final adjustment, we get a slightly different picture. The wealth of these three generations is roughly the same at the same age. No increase in wealth, but no decline either. You could read this as pessimistic, if your assumption is that wealth should rise over time, but the general vibes out there are that young people are worse off than in the past. This wealth data suggests, once again, that the kids are doing all right.
As I have discussed in many previous blog posts, young people today have a lot more wealth than past generations at the same point in their life. But we also know that housing prices have increased dramatically in recent years, and that for most families their home is their largest source of wealth.
Does this imply that the increase in wealth young Americans have seen is primarily driven by increased housing prices? If so, this would paint a less optimistic picture of the wealth of young people today, since the value of your home that you usually can’t easily convert into other consumption.
If we look at the past 5 years (2019Q4 to 2024Q4), the total wealth US households under the age of 40 increased by $5 trillion, in nominal terms. That’s not adjusted for inflation, but we don’t need to do so because we can look at how much each asset class increased in nominal terms as well. The total value of assets for households under age 40 increased by $5.86 trillion.
Here’s how the various classes of assets have increased since 2019Q4:
We all know that homicides spiked in the US in 2020 and we all (hopefully) know that homicides have been falling across most of the country dramatically since the end of 2021. But have homicides started to get back to, or even below, pre-pandemic levels? Or is it merely reversing the 2020 increases?
The answer depends on the city and the pre-pandemic baseline! The chart below shows the 10 largest cities (with Fort Worth instead of Jacksonville, because the Real-Time Crime Index doesn’t include the latter) in the US, using a base of either January 2018 (the first month in the RTCI) or December 2019 (just before the pandemic, and murders had fallen nationally between these two dates):
The murder data comes from the Real-Time Crime Index, and it is a 12-month total so we shouldn’t have to worry about seasonality even though the months are different. I use Census annual city population estimates to calculate the rates (and estimate 2025 based on the growth from 2023-24).
As you can see, depending on the base timeframe used, about half of the cities saw declines, a few were roughly flat, and some definitely saw increases. New York, Houston, and Fort Worth are definitely still elevated. Los Angeles, Philly, Phoenix, and San Diego are definitely down. The others are either close to even or mixed depending on your baseline.
Keep in mind these data are only through March 2025. As both Billy Binion at Reason and Jeff Asher have both recently emphasized, if we use the most recent data for many cities, it’s entirely possible that 2025 will end up having some of the lowest homicide rates ever recorded for many US cities. The declines in early 2025 have definitely been big, but mostly they are just a continuation of the post-2021 decline.
Again, for clarification, all of these cities are down from their 2020-21 peaks: using September 2021 as the base (when the national murder rate roughly peaked), these 10 cities are down between 31% and 58%. Big improvements!
SPOILER ALERT if you are watching the TV Series Yellowstone: at the start of Season 5, John Dutton (played by Kevin Costner) is sworn in as Governor of Montana. One of his first proposals in his inaugural address is that the state legislature “double property taxes for non-residents” who have been buying up vacation homes in the state, and contributing to the increase in property values in the state (a fact which drives many plotlines throughout the series). This episode aired in November 2022.
This week, the real governor of Montana signed a pair of bills which effectively did what the fictional governor John Dutton proposed: significantly increasing property taxes on non-residents. Starting in tax year 2026, the property taxes for non-primary residences (which will include non-Montana residents and Montanans who own vacation homes) will be based on 1.9% of market value, while Montana residents will pay a graduated rate structure for their primary residence: 0.76% for property up to the state median (currently about $340,000), 0.9% up to two times the state median, 1.1% for the value between 2 and 4 times the state median, and 1.9% (the same as non-residents) for the value of homes above 4 times the state median ($1.36 million currently). Currently residential property is taxed at 1.35% of market value, meaning that while the rate hasn’t fully doubled for non-residents, most non-residents will be paying twice or more in property taxes than Montana residents.
I was a non-resident member of the Montana Property Tax Task Force, and served on the “Tax Fairness” subcommittee where the plan for HB 231 originated, so I have somewhat of a unique perspective on these changes to property tax rates. I will offer a few thoughts, some of which are critical, but let me first say that it was a great honor to be asked to serve on the Task Force by Montana’s Governor. Also, everyone on the Task Force was very friendly and receptive to ideas from outsiders (I was one of three non-Montanans on the Task Force), and so my comments here are not critical of the Task Force process nor anyone on it. As I did when I served on the Task Force, my goal in this post is to try, as best as I can, to objectively analyze how this proposal (now law) will impact Montana.
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