Data

What is $300,000 from “The Gilded Age” Worth Today?

Jeremy Horpedahl2 Comments

SPOILER ALERT FOR THE THIRD SEASON OF THE GILDED AGE

In Season 3 of the drama series “The Gilded Age,” one of the servants (Jack, a footman) earns a sum of $300,000 by selling a patent for a clock he invented (the total sum was $600,000, split with his partner, the son of the even wealthier neighbor to the house Jack works in). In the series, both the servants and Jack’s wealthy employers are shocked by this amount. Really shocked. They almost can’t believe it.

How can we put that $300,000 from 1883 in New York City in context so we can understand it today?

A recent WSJ article attempts to do that. They did a good job, but I think more context could help. For example, they say “Jack could buy a small regional bank outside of New York or bankroll a new newspaper.” Probably so, but I don’t think that quite conveys the shock and awe from the other characters in the show (a regional bank? Ho-hum).

First, the WSJ states that the “figure nowadays would be between $9 and $10 million.” That’s just doing a simple inflation adjustment, probably using a calculator such as Measuring Worth (it’s a good tool, and they mention it later in the story). But as the WSJ goes on to note, that probably isn’t the best way to think about that figure.

Here’s my best attempt to contextualize the $300,000 figure: as a footman, Jack probably made $7 to $10 per week. Or let’s call it $1 per day. That means Jack’s fellow servants would have had to work 300,000 days to earn that same amount of income — in other words, assuming 6 days of work per week, they would have had to work for almost 1,000 years to earn that much income. Jack appears, to his co-workers, to have earned that income almost in one fell swoop (though in reality, he spent months of his free time toiling away at the clock).

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The 2018 Tariffs in Many Graphs

Zachary Bartsch2 Comments

Did president Trump’s first term tariffs, enacted in 2018, increase manufacturing employment or even just manufacturing output? Let’s set the stage.

Manufacturing employment was at its peak in 1979 at 19.6 million. That number declined to 18m by the 1980s, 17.3m in the 1990s. By 2010, the statistics bottom out at 11.4m. Since then, there has been a rise and plateau to about 12.8m if we omit the pandemic.

Historically, economists weren’t too worried about the transition to services for a while. After all, despite falling employment in manufacturing, output continued to rise through 2007. But, after the financial crisis, output has been flat since 2014, again, if we omit the pandemic. Since manufacturing employment has since risen by 5% through 2025, that reflects falling productivity per worker. That’s not comforting to either economists or to people who want more things “Made in the USA”.

https://fred.stlouisfed.org/graph/?g=1LxMV

Looking at the graphs, there’s no long term bump from the 2018 tariffs in either employment or output. If you squint, then maybe you can argue that there was a year-long bump in both – but that’s really charitable. But let’s not commit the fallacy of composition. What about the categories of manufacturing? After all, the 2018 tariffs were targeted at solar panels, washing machines, and steel. Smaller or less exciting tariffs followed.

Breaking it down into the major manufacturing categories of durables, nondurables, and ‘other’ (which includes printed material and minimally processed wood products),  only durable manufacturing output briefly got a bump in 2018. But we can break it down further.

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Initial Jobs Reports from BLS are Very Good At Identifying Downturns in the Labor Market

Jeremy HorpedahlLeave a comment

Yesterday I showed that BLS jobs reports from the CES aren’t getting worse over time, if we judge them by how much they are later revised. In fact, they are much better than decades past, with the last 20 years or so standing out as much better than the past.

Today I want to address a related but separate topic: are the initial jobs reports good at telling us when a downturn in the labor market is beginning? This is actually the strongest argument for releasing this survey data in a timely manner, even though the data often goes through significant revisions later. The report typically comes out the first Friday of a new month, so it is very current data. Given that the likely new BLS Commissioner has signaled he prefers the more accurate quarterly release, even though it is 7-9 months after the fact, it is useful to ask if these initial reports have any value in telling us when labor market declines (and recessions) are beginning.

That’s right: you are getting two posts from me this week, on essentially the same topic. Because it’s very important right now.

The short answer: the report is very good for the purpose of identifying downturns, especially the start of the downturns. Let’s walk through the past few recessions.

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BLS Has Been Getting Better at Estimating Jobs, and They are Not More Favorable to Democrats

Jeremy Horpedahl3 Comments

You’ve probably heard a lot about BLS data recently (or at least more than usual) with Trump firing the BLS Commissioner after a bad monthly revision to the nonfarm payroll jobs figures. But this didn’t come out of the blue, as there was plenty of criticism of the jobs numbers during the Biden term as well, mostly coming from the political right.

The two main criticisms leveled at the BLS, in my reading of it are:

  1. The BLS is getting worse at estimating jobs numbers over time, leading to larger revisions
  2. The revisions are done in a way that is favorable to Democrats

I think both of those claims can be analyzed with the following chart, which also shows those claims to be incorrect:

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Hayek on The Volatility Pie

Zachary Bartsch4 Comments

In the Road to Serfdom, Friedrich Hayek uses some basic quantitative logic to make an important point about employment and political economy.

Hayek starts by assuming that government jobs are stable relative to those in the private sector. This might seem obvious, but let’s just start by checking the premises. Below are the percent change in total compensation and total employment for government employees and for the private sector. From year to year, private employment and total compensation is more volatile. So, Hayek’s initial premise is correct.

https://fred.stlouisfed.org/graph/?g=1LcUK
https://fred.stlouisfed.org/graph/?g=1LcOu

From there, he proceeds to say that if any part of income or employment is guaranteed or stabilized by the government, then the result must be that the risk and volatility is borne elsewhere in the economy. He reasons that if there is a decline in total spending, then stable government pay and employment implies that the private sector must have a deeper recession than the overall economy. Looking at the above graphs, both government employment and the total compensation are much less volatile.

But can’t governments intervene in macroeconomic stabilization policies effectively? Yes! They can and do stabilize the economy, especially with monetary policy. But Hayek is referring to individual stabilizations. For any individual to be guaranteed an income, all others must necessarily experience greater income volatility. How’s that?

Consider two individuals. Person #1 has an average income of $100. In any given year, his income might be $10 – or 10% – higher or lower than average. For the moment, person #2 is not employed and has income volatility of zero. If the government provides a job with a constant pay rate to person #2, then they still have zero income volatility. But instead of earning a consistent $0, person #2 earns a consistent $50. Nice.

Of course, person #2 gets his pay from somewhere. By one means or another, it comes from person #1. Let’s be generous and assume the tax on person #1 has no resulting behavioral effect. His new average income is $50, being $10 higher or lower in any given year. But now, that $10 deviation is over a base of $50 rather than $100. Person #1’s income varies by 20% relative to his new average!

Reasoning through this, we can consider that a person has a stable portion of their income and a volatile portion. If someone takes a part of your stable portion and leaves you with all of your volatile portion, then your remaining income is now more volatile on average. I think that this point is interesting enough all by itself.

IRL, many of our taxes are not lump sum. Rather, progressive taxation causes a negative incentive for production & earnings. The downside is that we produce less. The upside is that the government takes a higher proportion of our volatile income than of our stable income (because income changes are always on the margin and those marginal dollars are taxed at a higher rate). So, the government shares the income volatility of the private sector. By continuing to pay government employees a stable salary, the government is effectively absorbing some of that year-to-year income volatility on behalf of its employees.* The government is, in a sense, providing income insurance to a subgroup.

What does this have to do with The Road to Serfdom? Hayek argues that, as the government employs an increasing proportion of the population, the remaining private sector experiences increasing income and employment volatility. Such volatility increases private risk exposure so much that people begin to fawn over and increasingly compete for the stability found in government work. He gets anthropological and argues that the economic attraction to government jobs will introduce greater competition for those jobs and subsequently greater esteem and respect for those who are able to get them. This process makes the government jobs even more attractive.

My own two cents is that there is nothing internally unstable about this process. Total real income would fall compared to the alternative. However, such a state of affairs might be externally unstable as other governments/economies compete with the increasingly socialist one.

*An important analogue is that firms behave in a similar way. An individual may receive a relatively constant salary so long as they are employed. But the result must be that the firm bears more of the net-profit volatility. So, as more people want stable private sector jobs, the profit volatility of firms would increase and result in greater [seemingly windfall] profits and losses.

GDP Predictions: Pretty Good!

Jeremy HorpedahlLeave a comment

Last week I wrote about the GDP predictions from Kalshi and the GDPNow Model. They were both showing 2.4% for Q2 of 2025 last week. They both changed slightly by yesterday, up to 2.8% and 2.9%. The final result (technically, the “advanced” result, but the final one for purposes of this comparison) was 2.97%. The Atlanta Fed GDPNow model continues to be a top performer, and you can’t do much better than averaging these two estimates. And you can pretty consistently do better than the median result from the WSJ/Dow Jones survey of economists.

Here’s the updated table:

And here is the original post explaining the data.

Is A Music Major Worth It?

James Bailey2 Comments

Our new paper concludes that the answer is a resounding “It Depends”.

It depends on your answer to the following questions:

  1. If you didn’t major in music, would you major in something else, or not finish college?
  2. How dead set are you on a career in music?
Source: Figure 1 of Bailey and Smith (2025)

We found that

  1. Music majors earn more than people who didn’t graduate from college, even if they don’t end up working as musicians
  2. Among musicians, music majors earn more than other majors
  3. But among non-musicians, other majors earn much more than music majors

So on average a music major means higher income if you would be a musician anyway, or if you wouldn’t have gone to college for another major, but lower income than if you majored in something else and worked outside of music. The exact amounts depend on what you control for; this gets complex but this table gives the basic averages before controls:

Source: Table 2 of Bailey and Smith (2025), showing wage plus business income for respondents to the 2018-2022 American Community Survey

For better or worse, a music major also means you are much more likely to be a musician- 113 times more likely, in fact (this is just the correlation, we’re not randomizing people into the major). Despite that incredible correlation, only 9.8% music majors report being professional musicians, and only 22.3% of working musicians were music majors.

Sean Smith had the idea for this paper and wrote the first draft in my Economics Senior Capstone class in 2024. After he graduated I joined the paper as a coauthor to get it ready for journals, and it was accepted at SN Social Sciences last week. We share the data and code for the paper here.

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Second Quarter GDP Predictions

Jeremy Horpedahl1 Comment

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.

Inflation Is Stuck

Jeremy HorpedahlLeave a comment

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.