Economics

An Engineer in 1910 Didn’t Earn $450,000

Jeremy Horpedahl1 Comment

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.

  1. The listed salary was not one of an “ordinary man” — far from it.
  2. 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.

Are Imports Bad for GDP?

Zachary BartschLeave a comment

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.

Continue reading →

The Toyota Camry is Much More Affordable Than 30 Years Ago

Jeremy Horpedahl3 Comments

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?

I am not a car expert, so I can’t speak to the first, though I will note that there are Facebook groups dedicated to people that have cars with hundreds of thousands of miles on their odometers.

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.

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Circular AI Deals Reminiscent of Disastrous Dot.Com Vendor Financing of the 1990s

Scott BuchananLeave a comment

Hey look, I just found a way to get infinite free electric power:

This sort of extension-cord-plugged-into-itself meme has shown up recently on the web to characterize a spate of circular financing deals in the AI space, largely involving OpenAI (parent of ChatGPT). Here is a graphic from Bloomberg which summarizes some of these activities:

Nvidia, which makes LOTS of money selling near-monopoly, in-demand GPU chips, has made investing commitments in customers or customers of their customers. Notably, Nvidia will invest up to $100 billion in Open AI, in order to help OpenAI increase their compute power. OpenAI in turn inked a $300 billion deal with Oracle, for building more data centers filled with Nvidia chips.  Such deals will certainly boost the sales of their chips (and make Nvidia even more money), but they also raise a number of concerns.

First, they make it seem like there is more demand for AI than there actually is. Short seller Jim Chanos recently asked, “[Don’t] you think it’s a bit odd that when the narrative is ‘demand for compute is infinite’, the sellers keep subsidizing the buyers?” To some extent, all this churn is just Nvidia recycling its own money, as opposed to new value being created.

Second, analysts point to the destabilizing effect of these sorts of “vendor financing” arrangements. Towards the end of the great dot.com boom in the late 1990’s, hardware vendors like Cisco were making gobs of money selling server capacity to internet service providers (ISPs). In order to help the ISPs build out even faster (and purchase even more Cisco hardware), Cisco loaned money to the ISPs. But when that boom busted, and the huge overbuild in internet capacity became (to everyone’s horror) apparent, the ISPs could not pay back those loans. QQQ lost 70% of its value. Twenty-five years later, Cisco stock price has never recovered its 2000 high.

Beside taking in cash investments, OpenAI is borrowing heavily to buy its compute capacity. Since OpenAI makes no money now (and in fact loses billions a year), and (like other AI ventures) will likely not make any money for several more years, and it is locked in competition with other deep-pocketed AI ventures, there is the possibility that it could pull down the whole house of cards, as happened in 2000.  Bernstein analyst Stacy Rasgon recently wrote, “[OpenAI CEO Sam Altman] has the power to crash the global economy for a decade or take us all to the promised land, and right now we don’t know which is in the cards.”

For the moment, nothing seems set to stop the tidal wave of spending on AI capabilities. Big tech is flush with cash, and is plowing it into data centers and program development. Everyone is starry-eyed with the enormous potential of AI to change, well, EVERYTHING (shades of 1999).

The financial incentives are gigantic. Big tech got big by establishing quasi-monopolies on services that consumers and businesses consider must-haves. (It is the quasi-monopoly aspect that enables the high profit margins).  And it is essential to establish dominance early on. Anyone can develop a word processor or spreadsheet that does what Word or Excel do, or a search engine that does what Google does, but Microsoft and Google got there first, and preferences are sticky. So, the big guys are spending wildly, as they salivate at the prospect of having the One AI to Rule Them All.

Even apart from achieving some new monopoly, the trillions of dollars spent on data center buildout are hoped to pay out one way or the other: “The data-center boom would become the foundation of the next tech cycle, letting Amazon, Microsoft, Google, and others rent out intelligence the way they rent cloud storage now. AI agents and custom models could form the basis of steady, high-margin subscription products.”

However, if in 2-3 years it turns out that actual monetization of AI continues to be elusive, as seems quite possible, there could be a Wile E. Coyote moment in the markets:

MapGDP to teach economic growth

Joy Buchanan2 Comments

Economist Craig Paulsson has made a simple game free to all.

When you go to MapGDP.com you will find a real picture from Google Maps and a simple question. Guess the GDP/capita in the country where this picture was taken.

Watch his YouTube introduction

See Craig’s announcement about the game on his Substack

Many economics teachers will at some point visit the topic of “what is GDP” or “economic growth.” This web game is great for both topics. I put the website on my classroom projector and called on students to take the guess. We then could do the reveal together. I rate this high value for low effort from a teacher’s perspective.  No login or account creation required.

If you are an EWED reader and not an econ teacher, you might have fun playing the game yourself. Almost as satisfying as Wordle…

All of the Prices

Zachary BartschLeave a comment

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.

Go have a look around. You won’t regret it.

https://libraryguides.missouri.edu/pricesandwages/1870-1879

Purchasing Power in 1868: Guinness Edition

Jeremy HorpedahlLeave a comment

When reading an old novel or watching a period drama movie or TV show, it is almost inevitable that some historical currency amounts will be mentioned. This is especially true when the work is dealing with money and wealth, for example the series “The Gilded Age” is about rich people in late 19th century America. So money comes up a lot. I wrote a post a few weeks ago trying to contextualize a figure of $300,000 from 1883 for that show.

A new Netflix series “The House of Guinness” is another period piece that spends a lot of time focusing on rich people (the family that produces the famous beer), as well as their interactions with poorer folks. So of course, there are plenty of historical currency values mentioned, this time denominated in British pounds (the series is primarily set in Ireland, where the pound was in use). On this series, though, they have taken the interesting approach of giving the viewers some idea of what historical currency values are worth today, by overlaying text on the screen (the same way they translate the Gaelic language into English).

For example, in Episode 4 of the first season, one of the Guinness brothers is attempting to negotiate his annual payment from the family fortune. He asks for 4,000 pounds per year. On the screen the text flashes “Six Hundred Thousand Today.”

The creators of the show are to be commended for giving viewers some context, rather than leaving them baffled or pausing the show to Google it. But is 600,000 pounds today a good estimate? Where did they get this number? As with the “Gilded Age” estimate, it’s complicated, but it is probably more than you think.

Continue reading →

The “Lost World” of 2% Inflation

Scott BuchananLeave a comment

Here is a chart of the Core Personal Consumer Index for inflation (Core PCE), which is the Fed’s favorite measure on inflation, from 1970 through early 2024:

This chart is from an article by the Richmond Fed, The Origins of the 2 Percent Inflation Target. That article has a long discussion of how and why the Fed decided to name an explicit inflation target of 2% in 2012. Although controlling inflation has been formally part of the Fed’s “dual mandate” since the Federal Reserve Reform Act of 1977, it had traditionally not set a single numerical target. After years of discussions within the Fed, it was decided that the benefits of a clear single target outweighed the potential downsides. 2% was though to be about the lowest you could run, while still giving the Fed some room to cut short term rates in a recession without running up against the dreaded zero lower bound. It was understood that 2% was a loose target, with some years a little over or under to be allowed to balance each other out.

That Richmond Fed article was published in early 2024. At that point, inflation was falling quickly and steadily from its post-Covid high, as consumers finished spending down their gigantic stimulus package windfalls.

Unsurprisingly, this article concludes that “Even during this period, long-run inflation expectations have remained anchored, rising no higher than 2.5 percent, according to the Cleveland Fed.”

That was about 18 months ago. The actual path of inflation since then has not be a descent to 2-2.5%. Between gigantic peacetime deficits by two administrations, and the results of tariffs, inflation seems to have leveled out at around 3%:

Source

The sub-2% inflation that was normal for twenty years (2000-2020) may now be a lost world.   This puts the Fed in an awkward spot. Even ignoring the irresponsible squawking from some quarters of the government, it will not be an easy decision to keep cutting rates (to address soft employment) if inflation stays this high. The Fed’s mantra this time around is that the current inflation is just a transient response to tariffs and so can be largely discounted. But I recall similar verbiage in 2021, as the Fed dismissed the ramping inflation back then as merely a transitory effect of pandemic supply chain restrictions. They were wrong then, and I suspect it would be wrong now to be too complacent. The 1970s-80’s showed that once the inflation genie gets out of the bottle, it can be very costly to subdue it. Whether 2.0 % is still the right target, however, may be open to debate.

Now Published: Prohibition and Percolation

Zachary Bartsch2 Comments

My new article, “Prohibition and Percolation: The Roaring Success of Coffee During US Alcohol Prohibition”, is now published in Southern Economic Journal. It’s the first statistical analysis of coffee imports and salience during prohibition. Other authors had speculated that coffee substituted alcohol after the 18th amendment, but I did the work of running the stats, creating indices, and checking for robustness.

My contributions include:

  • National and state indices for coffee and coffee shops from major and local newspapers.
  • A textual index of the same from book mentions.
  • I uncover that prohibition is when modern coffee shops became popular.
  • The surge in coffee imports was likely not related to trade policy or the end of World War I
  • Both demand for coffee and supply increased as part of an intentional industry effort to replace alcohol and saloons.
  • An easy to follow application of time series structural break tests.
  • An easy to follow application of a modern differences in differences method for state dry laws and coffee newspaper mentions.
  • Evidence from a variety of sources including patents, newspapers, trade data, Ngrams, naval conflicts, & Wholesale prices.

Generally, the empirical evidence and the main theory is straightforward. I learned several new empirical methods for this paper and the economic logic in the robustness section was a blast to puzzle-out. Finally, it was an easy article to be excited about since people are generally passionate about their coffee.

Bartsch, Zachary. 2025. “Prohibition and Percolation: The Roaring Success of Coffee During US Alcohol Prohibition.” Southern Economic Journal, ahead of print, September 22. https://doi.org/10.1002/soej.12794.

Economic Freedom of the World 2025

James Bailey1 Comment

The Fraser Institute released their latest report on the Economic Freedom of the World today, measuring economic policy in all countries as of 2023. They made this excellent Rosling-style graphic that sums up their data along with why it matters:

In short: almost every country with high economic freedom gets rich, and every country that gets rich either has high economic freedom or tons of oil. This rising tide of prosperity lifts all boats:

This greater prosperity that comes with economic freedom goes well beyond “just having more stuff”:

The full report, along with the underlying data going back to 1970, is here. The authors are doing great work and releasing it for free, so no complaints, but two additional things I’d like to see from them are a graphic showing which countries had the biggest changes in economic freedom since last year, and links to the underlying program used to create the above graphs so that readers could hover over each dot to identify the country (I suppose an independent blogger could do the first thing as easily as they could…).

FRDM is an ETF that invests in emerging markets with high economic freedom (I hold some), I imagine they will be rebalancing following the new report.