Economic Growth

Yes, Americans Probably Are About 46 (or Maybe 65) Times Richer Than in 1776

Jeremy HorpedahlLeave a comment

My post and chart from last week showed the phenomenal growth of average income in the US since the Founding. Using GDP per capita historical estimates and adjusting for inflation, this figure is about 46 times greater today than right around the time we declared independence.

It will probably not surprise you that some folks were skeptical. Could this really be true? Two major objections were raised to using GDP per capita. First, wouldn’t it be better to use a median income value rather than a mean (simple average)? Second, wouldn’t a measure of wages be better than GDP per capita?

I really would like to show you an annual series of median income data back to 1776, but unfortunately it just doesn’t exist. Good median income data are hard to find much before the 1950s, much less the 1770s. However, while median values are often better for showing levels, the growth rates of median wages and mean wages aren’t that different for periods when we have comparable data. Consider the following chart, which compares median wages (as calculated by EPI using CPS data) and mean wages (from BLS’s series for non-supervisory workers) since 1973. I have stated these in nominal terms, so don’t take this as real growth rates, but rather it is a raw comparison of two series (we could apply the same inflation adjustment to both, but that won’t change the picture, only the numbers).

Median wages increased by 667% and mean wages increased by 657%, almost identical. Again, these aren’t inflation adjusted, but that’s not the point of this exercise. The point is that whether you use mean or median wages, at least since 1973, the growth rates are the same. Was this true if we went back another 200 years? We can’t say for sure. But many people have this same skepticism about mean wages in recent decades. I think it is better to use median values when you have them, but we shouldn’t throw up our hands and claim we know nothing if all we have is mean wages.

Next, consider the following chart. It begins in 1790, but instead of using GDP per capita, as I did last week, it uses a measure of average wages from economic historian Lawrence Officer. This measure is for “production workers in manufacturing,” and it is a total compensation measure, meaning that it will include the value of fringe benefits as well — though these aren’t noticeable in the data until the 1930s. This is still an average value, but because it is for manufacturing laborers, it won’t be distorted by the wages of managers and owners in that industry, and it won’t be affected by the growth of new industries that might require more years of education (indeed, manufacturing wages are lowering than overall average wages today, so this is taking the hard case). I have also included a second line, which only includes manufacturing wages (not benefits) that I have blended with Officer’s compensation series starting in the 1930s, in case you think including benefits is somehow “cheating.” (Note the log scale again, as in last week’s chart.)

The trends here are very much in the ballpark from the GDP per capita chart I created last week. Using total compensation, wages are 65 times higher than in 1790. Using only wages, they are 49 times higher. Notice that these are both better than the 46 times multiplier using GDP per capita. How is that possible, since I am using the same price deflator in both cases? First, average hours of work have fallen significantly since the 18th century, so incomes haven’t risen quite as much as wages. Second, there was a bit of a decline in GDP per capita during the Revolutionary War, and if we use 1790 as the baseline for GDP per capita, the multiplier is 63. But again, these numbers are all in the ballpark: whether the true figure for a typical American is 46x, 49x, 63x, or 65x, this is a tremendous amount of economic growth.

If you want to look at that chart pessimistically, you will see that there is some reduction in growth rates in the past few decades. That’s true whether we use wages or compensation. This is a well known issue, and has been discussed endlessly in academic papers and on social media. I don’t want to glaze over it here, but I mostly will: the long-run trend of growth in the US is amazing. That’s true whether you use GDP per capita, or wages or compensation for production workers.

So once again, Happy 250th Birthday to the USA and all of you living in the wake of that amazing 250 years of economic growth!

Happy Birthday, USA

Jeremy Horpedahl4 Comments

For America’s 250th birthday, my present to all of you is this chart showing our economic history. Average income in the US has increased dramatically since the country was founded. This chart attempts to provide one, continuous series, using the best available income data and inflation adjustments (well, mostly continuous — before 1790 there are just a few estimates). Sources are listed at the bottom of the chart. The y-axis is a log scale.

The Day the Cloud Evaporated: Life After the Data Center Collapse (A Guest Post by AI)

Jeremy Horpedahl3 Comments

This is a “guest” blog post that I asked Google Gemini Pro to write. Data centers are increasingly becoming a political issue in communities across America. People are asking questions like: “Why do we need these things? How much water will this use?” Because these are sometimes referred to as “AI Data Centers,” people might assume that data centers are primarily about creating cat memes and fake videos. And it’s true that’s a part of AI, and it’s true that much of the new data center construction is for AI.

But… data centers have been around for a while. People are only now taking notice of them, for the most part. To better understand this issue, I asked — what else? — AI to explain how much data centers are used in our daily lives. AI in this case means Google Gemini Pro.

I’ll paste the full guest post below, but I want to point something out first: this blog post makes no mention of AI. Instead, it talks about: GPS and mapping apps; almost everything you do if you work in an office; credit cards and digital banking; news and social media. All of these things rely on data centers and would cease to function without data centers. That’s not because I asked Gemini to leave out AI from the guest post — when I followed up on this omission, Gemini said “It was a calculated omission—partly to keep the focus on the immediate ‘analog’ shock to daily life.” Most people probably wouldn’t care of they lost the ability to create funny images with AI. They would care if they lost all of their photos, access to their Dropbox account, and the ability to send email.

You could interpret all of this as saying we are “too dependent” on data centers and the modern Internet. You could also say we are “too dependent” on electricity. Or modern plumbing. Or modern supply chains. Or agriculture. Modern life is based on modern technology. I don’t know if it really makes sense to say we are “dependent” on these things, other than that we use them and they are beneficial.

Anyway, on to the guest post from Google Gemini Pro:

The Day the Cloud Evaporated: Life After the Data Center Collapse

Imagine waking up tomorrow morning in your suburban home in Ohio, or your apartment in Seattle. You reach for your smartphone to silence the alarm, but the screen is a stubborn, glowing rectangle of error messages. You try to check the weather, but the app’s spinning wheel never stops. You try to text your partner, but the message stays “Sending…” until it eventually fails.

This isn’t just a bad Wi-Fi connection. Every data center on Earth—those massive, humming warehouses filled with silicon and cooling fans—has vanished. In an instant, the “brain” of the modern world has been lobotomized. For the average person in the United States, life wouldn’t just slow down; it would fundamentally reset to 1950, but without the physical infrastructure of 1950 to catch the fall.

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The Declining Cost of Adam Smith

Jeremy HorpedahlLeave a comment

Last week I had the opportunity to see (and touch!) some first edition copies of Adam Smith’s books, including The Wealth of Nations and The Theory of Moral Sentiments.

For an economist, of course this was a very cool experience. The books from the Remnant Trust were still in great condition, despite people like me handling these copies from time-to-time. The books were also beautiful editions, which got me thinking: how much did these cost to purchase when originally published?

According to John Rae’s Life of Adam Smith, the original price for The Wealth of Nations was 1 pound, 16 shillings. Average wages per day in England were somewhere around 15 pence per day (1 pence is 1/12 of a shilling), it would take close to 30 days of labor to purchase the book. But that’s assuming you spent all of your wage on books, which of course would have been impossible: a common laborer would have been spending 80-90% of their wages on food, beer, and rent. And that’s assuming no unexpected expenses or sickness. In reality, it might take a common laborer months, years, or maybe his entire life to save up for that book.

Today, of course we can read this book online for free, but what if you want a nice hardcover version? Amazon has several nice hardback versions available for just under $30. These are not quite as beautiful as the 1776 edition, but they would look nice in any library. Given that the average wage in the US today is close to $32, it would take less than one hour of labor to purchase the book. And thankfully the cost of necessities today is much lower than 1776, indeed much lower than 1900, so it would be much easier to set aside that one hour of wages relative to the past, and purchase yourself a little treat like a book written 250 years ago.

Most Married Women with Children Were Working By the Late 1970s

Jeremy Horpedahl2 Comments

A recent essay by Jeffrey Tucker asks “Has Life Really Improved in Half a Century?” Specifically, Mr. Tucker is interested in measuring median income of families (he uses household income, but families are clearly what he is interested in).

Tucker grants that real median household income has increased by about 40 percent from 1984 to 2024 (if he had used family income instead, the increase is almost 50 percent). But… he says this is illusory. That’s because it now takes two incomes to achieve that median income, whereas it only took one income in the past:

“Adding another income stream to the household is a 100 percent rise in work expectations but it has yielded only a 20-plus percent rise in material income. The effective pay per hour of work for the household has fallen by 40 to 50 percent!”

(He makes a data error by saying that in 1976 real median household income was $68,000-$70,000, when it was actually $59,000 in 2024 dollars in 1976 — real income didn’t fall from 1976 to 1984!)

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Which Economies Grow with Shrinking Populations?

Zachary Bartsch5 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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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…

One-Third of US Families Earn Over $150,000

Jeremy Horpedahl15 Comments

This is from the latest Census release of CPS ASEC data, updated through 2024 (see Table F-23 at this link). In 1967, only 5 percent of US families earned over $150,000 (inflation adjusted).

Addendum: Several comments have asked how much of these trends can be explained by the rise of dual-income households. The answer is some, but not all of it, which I have written about before. Dual-income households were already the most common family structure by the 1980s. There hasn’t been an increase in total hours worked by married households since Boomers were in their 30s. You can explain some of the increase up until the Boomers by rising dual-income households, but this doesn’t explain the continued progress since the 1980s. And as Scott Winship and I have documented, even if you look just at male earnings, there has been progress since the 1980s.

Even more data on this question in a new post!

The American Middle Class Has Shrunk Because Families Have Been Moving Up

Jeremy Horpedahl8 Comments

In 1967, about 56 percent of families in the US had incomes between $50,000 and $150,000, stated in 2023 inflation-adjusted dollars. In 2023, that number was down to 47 percent. So the American middle class shrunk, but why? (Note: you can do this analysis with different income thresholds for middle class, but the trends don’t change much.)

The data comes from the Census Bureau, specifically Table F-23 in the Historical Income Tables.

As you can see in the chart, the proportion of families that are in the high-income section, those with over $150,000 of annual income in 2023 dollars, grew from about 5 percent in 1967 to well over 30 percent in the most recent years. And the proportion that were lower income shrunk dramatically, almost being cut in half as a proportion, and perhaps surprisingly there are now more high-income families than low-income families (using these thresholds, which has been true since 2017). The number is even more striking when stated in absolute terms: in 1967 there were only about 2.4 million high-income households, while in 2023 there were 11 times as many — over 26 million.

Is this increase in family income caused by the rise of two-income households? To some extent, yes. Women have been gradually shifting their working hours from home production to market work, which will increase measured family income. However, this can’t fully explain the changes. For example, the female employment-population ratio peaked around 1999, then dropped, and now is back to about 1999 levels. Similarly, the proportion of women ages 25-54 working full-time was about 64 percent in 1999, almost exactly the same as 2023 (this chart uses the CPS ASEC, and the years are 1963-2023).

But since the late 1990s, the “moving up” trend has continued, with the proportion of high-income families rising by another 10 percentage points. Both the low-income and middle-income groups fell by about 5 percentage points. Certainly some of the trend in rising family income from the 1960s to the 1990s is due to increasing family participation in the paid workforce, but it can’t explain much since then. Instead, it is rising real incomes and wages for a large part of the workforce.

Is Everyone Going to Europe This Summer?

Jeremy Horpedahl6 Comments

I had planned to write about the Trump-BLS fight today. But considering that two of my co-bloggers have already written about this (Mike on Monday and Scott on Tuesday) and that I have written about supposedly “fake” jobs numbers before several times (see January 2024 and August 2024), I will hold off on that topic until all of the dust settles. But this is a very important topic, and I believe Trump is clearly in the wrong (as is Kevin Hassett, see my tweets from this week), so please do continue to follow this topic and sane voices on it (see a Tweet from Ernie Tedeschi and from me for a long-run perspective on data accuracy).

But now, on to something a little more light-hearted: is everyone traveling to Europe these days?

Judging by my Facebook feed, it seems that Yes, lots of people are traveling to Europe. But this could be a result of selection bias in at least two ways: the people I am friends with on Facebook, and what people choose to post about on Facebook.

So what does the hard data say? We actually have pretty good long-run data on this question. In short: yes, lots more Americans are traveling to Europe (and overseas generally). Though don’t worry: not everyone went to Europe this summer, despite what social media might have you believe.

For starters, here’s a chart showing three decades of US overseas travel:

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