History

Messy Disability Records in the Historical Censuses

Zachary Bartsch1 Comment

The historical US Census roles of disability among free persons are a mess. Specifically for the 1850-1870 censuses, the census bureau was not professionalized and the pay was low (a permanent office wasn’t founded until 1902). So, the enumerators were temporary employees and weren’t experts of their art. To boot, their handwriting wasn’t always crystal clear. Second, training for disability enumeration was even less complete and enumerators did their best with whom they encountered and how they understood the instructions. Finally, the digitized data in IPUMS doesn’t perfectly match the census reports. What a mess.

Guilty by Association

Disabled people and their families often misreported their status out of embarrassment or shame. Given that enumerators had quotas to fill, they were generally not inclined to investigate claimed statuses strenuously. Furthermore, disabled people were humans and not angels. Sometimes they themselves didn’t want to be associated with other types of disabled people. In particular, the disability designation in question (13) on the 1850 census questionnaire asked  “Whether deaf and dumb, blind, insane, idiotic, pauper or convict”. Saying “yes” may put you in company that you don’t prefer to keep.

Summer censuses also sometimes missed deaf students who were traveling to or from a residential school.

Enumerator Discretion

The enumerator’s job was to write the disability that applied. What counts as deaf and dumb? That’s largely at the enumerator’s discretion. Some enumerators wrote ‘deaf’ even though that wasn’t an option. Was that shorthand for ‘Deaf and Dumb’? Or were they specifying that the person was deaf only and not dumb? We don’t know. But we do know that they didn’t follow the instructions. What if a person was both insane and blind? Then what should be written? “Blind/Insane” or “Blind and Insane” or “In-B” and any number of combinations were written. Some of them are easier to read than others.

Data Reading Errors

IPUMS is the major resource for using census data. The historical data was entered by foreign data-entry workers who didn’t always speak English. So, the records aren’t perfect. Some of the records are corroborated with Optical Character Recognition (OCR), but the historical script is sometimes hard to read. Finally, the fine folks at familysearch.org and Brigham Young University have used Church of Latter Day Saints (LDS) volunteers to proof data entries. Regardless, we know that the IPUMS data isn’t perfect and that the disability data is far from perfect. Usually, reports don’t dwell on it. They simply say that the data is incomplete.

The disability data is incomplete for a lot of reasons related to the respondent, the enumerator, the instructions, and the digital data creation. What a mess.

Podcast Recommendation: Acquired

Jeremy HorpedahlLeave a comment

For your upcoming summer road trips, even with a family, I recommend you check out the Acquired podcast. Each episode is the history (or partial history) of one business, told in a way that is entertaining and informative on many levels.

I was first introduced to the podcast when someone recommended the episode on Costco. It’s 3 hours long. I thought to myself “Really? I’m interested in Costco, but isn’t 3 hours a bit much?” But I had a long road trip, so I gave it a try. I was floored by how much I learned about Costco, the history of retail in the US, and the connections to other businesses. For example, Sam’s Club, which I thought was just kinda doing the same thing as Costco in different geographic areas, but no — Sam Walton copied Costco, as well as many other ideas from Sol Price (what a great name for a retailer!), the man behind the companies that would eventually become Costco today.

If you are at all interested in the history of business (especially mid-to-late Twentieth century businesses, though they do have one on Standard Oil), you will love this podcast. But I have found that the podcast is also great for children — well, at least if you have a roughly eleven-year-old boy. They will have many questions, so you may stop the podcast often, but that’s OK with me.

I think the reason some of the episodes appeal to children is because many of the stories focus on a single entrepreneur that started a business, and the hosts always spend a little bit of time on the childhood of those entrepreneurs. Often, they were entrepreneurial or innovative in some way as a child. For example, Warren Buffett in the first Berkshire Hathaway episode (there are 3 episodes on BH, totaling over 9 hours!), selling sticks of gum and cans of Coke door-to-door. Or Ingvar Kamprad (founder of IKEA, told in a 3-hour episode) selling matchboxes and fountain pens. Or the young Bill Gates being privileged enough in middle school to have access to computers, but also turning this into a business in high school (told in the first of two episodes on Microsoft, totaling once again over 9 hours).

As I mentioned in the above paragraph, if you thought that 3 hours on Costco was a lot, just wait until you listen to some of the others. You probably can’t imagine yourself listening to 9 hours on the history of a single company, much less your kids following along too. But I highly recommend that you give it a shot.

Optimal Protein Consumption in the 21st Century: A Model

Zachary Bartsch1 Comment

I’ve discussed complete proteins before. I’ve talked about the ubiquity of protein, animal protein prices, vegetable protein prices, and a little but about protein hedonics. My coblogger Jeremy also recently posted about egg prices over the past century. Charting the cost of eggs is great for identifying egg affordability. But a major attraction of eggs is that they are a ‘complete protein’. So how much of that can we afford?

Here I’ll outline a model of the optimal protein consumption bundle. What does this mean? This means consuming the quantities of protein sources that satisfy the recommended daily intake (RDI) of the essential amino acids and doing so at the lowest possible expenditure. Clearly, this post includes a mix of both nutrition and economics.  Since a comprehensive evaluation that includes all possible foods would be a heavy lift, here I’ll just outline the method with a small application.

Consider a list of prices for 100 grams of Beef, Eggs, and Pork.* We can also consider a list that identifies the quantity that we purchase in terms of hundreds of grams. Therefore, the product of the two yields the total that we spend on our proteins.

Of course, not all proteins are identical. We need some characteristics by which to compare beef, eggs, and pork. Here, I’ll use the grams of essential amino acids in 100 grams of each protein source. Because there are different RDIs for each amino acid, I express each amino acid content as a proportion of the RDI (represented by the standard molecular letter).

Then, we can describe how much of the RDI of each amino acid that a person consumes by multiplying the amino acid contents by the quantities of proteins consumed.

Our goal is to find the minimum expenditure, B, by varying the quantities consumed, Q, such that the minimum of C is equal to one. If the minimum element of C is greater than one, then a person could consume less and spend less while still satisfying their essential amino acid RDI. If the minimum element is less than one, then they aren’t getting the minimum RDI.

How do we find such a thing? Well, not algebraically, that’s for sure. I’ll use some linear programming (which is kind of like magic, there’s no process to show here).

The solution results in consuming only 116.28 grams of Pork and spending $1.093 per day. The optimal amino acid consumption is also below. Clearly, prices change. So, if eggs or beef became cheaper relative to pork, then we’d get different answers.

In fact, we have the price of these protein sources going back almost every month to 1998. While pork is exceptionally nutritious, it hasn’t always been most cost effective. Below are the prices for 1998-2025. See how the optimal consumption bundle has changed over time – after the jump.

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A Forgotten Data Goldmine: Foreign Commerce and Navigation Reports

Zachary BartschLeave a comment

Economists rely on trade data. The historical Foreign Commerce and Navigation of the United States reports detailed monthly figures on imports, exports, and re-exports. This dataset spans decades, providing a crucial resource for researchers studying price movements, consumption patterns, and the effects of war on global trade.

The U.S. Department of Commerce compiled these reports to track the nation’s commercial activity. The data cover a vast range of commodities, including coffee, sugar, wheat, cotton, wool, and petroleum. Officials recorded trade flows at a granular level, enabling economists to analyze seasonal fluctuations, wartime distortions, and postwar recoveries. Their inclusion of re-export figures allows for precise estimates of domestic consumption. Researchers who ignore re-exports risk overstating demand by treating imports as goods consumed rather than goods in transit.

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Women Have Always Worked More Than Men: Hours of Work Since 1900

Jeremy Horpedahl3 Comments

This chart shows the average number of hours worked in the US, by gender, for those in their prime working ages (25-54), from 1900 to 2023. It includes both paid market work and household production (which includes activities like cooking, cleaning, shopping, and taking care of children):

Most of the data (from 1900-2005) comes from a 2009 paper by Valerie Ramy and Neville Francis, which looks at lots of trends in work and leisure in the twentieth century. I extend the data past 2005 using an update from Ramey through 2012, and then attempting to replicate their methods using the CPS (for market work) and the BLS ATUS (for home production).

A few things to notice. First, there is no data for 2020, as the ATUS didn’t publish any tables due to incomplete data from the pandemic. And even if we had data, it would have been a huge outlier year.

More importantly, there is an obvious long-term trend of declining market work and rising household production for men, and the opposite for women. In 1900 women worked over 6 times as many hours in the household as they did in the market, but by 2023 they worked almost the exact same number of hours in each sector.

Male hours in market work declined by about 16 hours per week (using 10-year averages, as there is a slight business-cycle effect on hours), but the total number of hours they worked declined much more modestly, by about 3 hours per week (note: these numbers include all men, whether they are working or not). Women saw similar changes, but in the opposite direction, with total hours worked only falling by about 4 hours per week, even though hours working at home fell by almost 22 hours.

Americans do have more leisure time than in 1900, but not dramatically so: perhaps 3-4 hours per week. This is an improvement, but less of an improvement than you might suspect by looking at hours of market work alone.

Ramey and Francis do try to carefully distinguish between household production and leisure. For example, yardwork and changing diapers are household production, while gardening and playing with your children are leisure. For some respondents to surveys, they may feel differently about whether gardening is “really” work or not, and some may enjoy changing baby’s diapers, but in general their distinctions seem reasonable to me.

Finally, we can say pretty confidently with this data that women have almost always worked more hours than men — the one exception in the 20th century being WW2 — and the gender gap was about 4 hours per week in both the early 1900s and the most recent decade (though it did fluctuate in between).

Information Regarding Russia

Joy BuchananLeave a comment

2004: In September 2004, Ukrainian presidential candidate Viktor Yushchenko was poisoned while running against pro-Russian candidate Viktor Yanukovych. After a dinner meeting, Yushchenko fell severely ill and his face became dramatically disfigured with cysts and lesions (chloracne). Medical tests in Vienna confirmed extreme dioxin poisoning.
https://www.bbc.com/news/av/world-europe-43611547
The American liberal mind struggles to understand the difficulty of using elections under these conditions.

2018: “On March 4, 2018, British authorities say Russian agents poisoned Sergei Skripal—a former Russian military intelligence officer and U.K. double agent—and his daughter using a Novichok nerve agent…. With the immediate attack area isolated and the cleanup underway, the nation was shocked once again when two British nationals were poisoned by the same nerve agent nearly three months later in the neighboring town of Amesbury. One of the two, Dawn Sturgess, fell ill within 15 minutes of contact with the agent and died just over a week later. ” https://mwi.westpoint.edu/modern-day-nerve-agent-attack-military-lessons-salisbury/

If you get news from the internet and social media, be aware that some online participants are paid trolls from foreign governments.

Another pillar of this strategy involves botnets: swarms of fake, automated accounts created and controlled by Russian agents. These botnets hijack trending algorithms on social media platforms and thereby expose Western audiences to particular messages. They often share precisely worded posts to ensure that certain phrases—such as #WelcomeRefugees or #EndNetZero—trend in people’s news feeds. And they incessantly ‘like’ and repost content from pro-Kremlin influencers and trolls.

The aim here is twofold. First, it is an attempt to expand the reach of what would otherwise remain fringe opinions. They expose ever more people to Russian propaganda, and help create an illusion of popularity that serves to normalise pro-Kremlin talking points. But this is not merely intended to convert people into passionate Putinistas. The second goal is to promote the most inflammatory and divisive voices on either side of a given political issue. This helps spread the distrust and disillusionment that are so corrosive to liberal democratic society—and which have reached record levels on social media.

That is from https://quillette.com/2024/11/24/the-kremlins-bots-trolls-and-influencers-russia-disinformation/ , and if you would like a different news source then https://www.cnn.com/2024/10/30/europe/russian-disinformation-harris-walz-us-election-intl/index.html

Adam Smith and broadening horizons

Joy Buchanan1 Comment

Last week I had the honor of hosting Vernon Smith at Samford University and then being with him on his second day of the tour in Tuscaloosa, AL.

To introduce Vernon Smith’s new book about Adam Smith, I articulated a point that I had taken from reading Tyler Cowen’s GOAT book. Not all undergraduates have read Adam Smith, so I explained that Adam Smith was one of the first people to have a vision of a growing economy on a global scale. Afterward, I wondered if I had stated everything entirely correctly in my bold assertion. I went to consult with the source material via https://econgoat.ai/en/chat/gpt.

Joy: Does Tyler say that Adam Smith was one of the first people to imagine economic life on a globalized scale and how great the gains from trade could be?

EconGOAT GPT-4: Indeed, Tyler suggests that Adam Smith was one of the pioneering thinkers in envisioning economic life on a global scale and highlighting the immense gains from trade. In discussing Smith’s contributions, Tyler notes how Smith saw trade as a process by which nations could exchange their surplus or “superfluities” for goods they value more. While Smith didn’t quite articulate the theory of comparative advantage—later developed by Ricardo and Torrens—he was certainly heading in the right direction with his understanding of trade. This insight pointed towards a broader, more interconnected economic worldview that has since become central to economic theory (Chapter 8).

Tyler also gives Smith credit for recognizing issues with mercantilist views of trade, which often focused on stockpiling precious metals. Instead, Smith emphasized the expansion of consumption opportunities as the real benefit of trade, emphasizing its potential to enhance global prosperity. Smith’s multifaceted intellectual approach laid the groundwork for thinking about economies beyond just national borders, making him a key figure in the development of global economic thought.

Joy: When I think of a grand global vision prior to Smith, I think about religious leaders and military conquerors. Was Adam Smith the first to think of a grand global vision that fundamentally rests on individual freedom within a tolerant framework of laws and protections from harm?

EconGOAT GPT-4: Tyler acknowledges that Adam Smith played a pivotal role in developing the idea of economic globalization and the gains from trade. However, noting Smith as the absolute first might overlook other contributors. Before Smith, there were philosophers like the Scholastics and early mercantilists who considered economic ideas on a substantial, if not global, scale. The physiocrats, for example, were very much aware of how agriculture and trade could lead to prosperity for nations.

One could argue against Smith’s primacy by pointing out how people have always been aware of trade’s benefits, even if they didn’t articulate it quite as elegantly as Smith did. There’s historical evidence of trade routes as old as human civilization itself, such as the Silk Road or the trade networks of the Phoenicians. These early systems relied on a rudimentary understanding of economies of scale and specialization, even if they weren’t formalized.

Regarding your second point about religious leaders and conquerors, Smith’s vision indeed differs markedly. While others dreamt of unification through conquest or religious means, Smith’s framework empowered individuals to pursue their self-interest within a system of natural laws. This wasn’t just a vision of economic prosperity, but a moral and social vision as well. His “invisible hand” concept implies that individuals, left to their own devices within a safe legal framework, can contribute to the common good more efficiently than any central directive. This is highlighted in Chapter 8, where Tyler discusses Smith’s broader social and philosophical contributions. Smith’s ideas paved the way for modern market economies and significantly influence contemporary thought on economic freedom and globalization.

Joy: Would it be accurate to say that most people in Smith’s time had a very narrow view of the world, indeed hardly thinking beyond the borders of their own regions?

EconGOAT GPT-4: That’s a fair assessment. During Adam Smith’s time in the 18th century, most people indeed had a much narrower view of the world than we do today. Many individuals’ perspectives were limited to their immediate surroundings—villages, towns, or regions. The vastness of the globe, with its diverse cultures, economies, and possibilities for trade, wasn’t as accessible or imaginable to the everyday person as it is now.

Smith’s work in “The Wealth of Nations” was revolutionary in part because it broadened this horizon, not just for economists and policymakers but for anyone interested in economic activity. Smith’s ideas about the division of labor, specialization, and free markets opened up the concept of international trade as a means to prosperity beyond the local economy. His ability to foresee the potential for global interconnectedness in economies was ahead of his time.

I won’t excerpt our entire conversation. I eventually asked how to broaden one’s horizons.

EconGOAT GPT-4: While traveling Europe might seem like a grand adventure ripe for expanding one’s horizons (cue the “Eat, Pray, Love” montage), Adam Smith had reservations about the educational value of the “grand tour,” as it was then known. In Smith’s view, travel often led to “frivolous dissipation” rather than genuine intellectual or moral growth. Instead, he believed that real learning happened through competitive and commercial constraints—the kind you experience when you’re not just sightseeing but actively engaging with a community (Chapter 8).

That was when the bot made a genuinely funny joke about a silly modern book.

Was the US at Our Richest in the 1890s?

Jeremy Horpedahl2 Comments

Donald Trump has repeatedly said that the US was at our “richest” or “wealthiest” in the high-tariff period from 1870-1913, and sometimes he says more specifically in the 1890s. Is this true?

First, in terms of personal income or wealth, this is nowhere near true. I’ve looked at the purchasing power of wages in the 1890s in a prior post, and Ernie Tedeschi recently put together data on average wealth back to the 1880s. As you can probably guess, by these measures Trump is quite clearly wrong.

So what might he mean?

One possibility is tax revenue, since he often says this in the context of tariffs versus an income tax. Broadly this also can’t be true, as federal revenue was just about 3% of GDP in the 1890s, but is around 16% in recent years.

But perhaps it is true in a narrower sense, if we look at taxes collected relative to the country’s spending needs. Trump has referenced the “Great Tariff Debate of 1888” which he summarized as “the debate was: We didn’t know what to do with all of the money we were making. We were so rich.” Indeed, this characterization is not completely wrong. As economic historian and trade expert Doug Irwin has summarized the debate: “The two main political parties agreed that a significant reduction of the budget surplus was an urgent priority. The Republicans and the Democrats also agreed that a large expansion in government expenditures was undesirable.” The difference was just over how to reduce surpluses: do we lower or raise tariffs?

It does seem that in Trump’s mind being “rich” in this period was about budget surpluses. Let’s look at the data (I have truncated the y-axis so you can actually read it without the WW1 deficits distorting the picture, but they were huge: over 200% of revenues!):

It is certainly true that under parts of the high-tariff period, we did collect a lot of revenue from tariffs! In some years, federal surpluses were over 1% of GDP and 30% of revenues collected. But notice that this is not true during Trump’s favored decade, the 1890s. Following the McKinley Tariff of 1890, tariff revenue fell sharply (though probably not likely due to the tariff rates, but due to moving items like sugar to the duty-free list, as Irwin points out). The 1890s were not a decade of being “rich” with tariff revenue and surpluses.

Finally, also notice that during the 1920s the US once again had large budget surpluses. The income tax was still fairly new in the 1920s, but it raised around 40-50% of federal revenue during that decade. By the Trump standard, we (the US federal government) were once again “rich” in the 1920s — this is true even after the tax cuts of the 1920s, which eventually reduced the top rate to 25% from the high of 73% during WW1.

If we define a country as being “rich” when it runs large budget surpluses, the US was indeed rich by this standard in the 1870s and 1880s (though not the 1890s). But it was rich again by this standard in the 1920s. This is just a function of government revenue growing faster than government spending. And the growth of revenue during the 1870s and 1880s was largely driven by a rise in internal revenue — specifically, excise taxes on alcohol and tobacco (these taxes largely didn’t exist before the Civil War).

1890 was the last year of big surpluses in the nineteenth century, and in that year the federal government spent $318 million. Tariff revenue (customs) was just $230 million. There was only a surplus in that year because the federal government also collected $108 million of alcohol excise taxes and $34 million of tobacco excise taxes. In fact, throughout the period 1870-1899, tariff revenues are never enough to cover all of federal spending, though they do hit 80% in a few years (source: Historical Statistics of the US, Tables Ea584-587, Ea588-593, and Ea594-608):

One more thing: in some of these speeches, Trump blames the Great Depression on the switch from tariffs to income taxes. In addition to there really being no theory for why this would be the case, it just doesn’t line up with the facts. The 1890s were plagued by financial crises and recessions. The 1920s (the first decade of experience with the income tax) was a period of growth (a few short downturns) and as we saw above, large budget surpluses. The Great Depression had other causes.

After the Fall: What Next for Nvidia and AI, In the Light of DeepSeek

Scott Buchanan1 Comment

Anyone not living under a rock the last two weeks has heard of DeepSeek, the cheap Chinese knock-off of ChatGPT that was supposedly trained using much lower resources that most American Artificial Intelligence efforts have been using. The bearish narrative flowing from this is that AI users will be able to get along with far fewer of Nvidia’s expensive, powerful chips, and so Nvidia sales and profit margins will sag.

The stock market seems to be agreeing with this story. The Nvidia share price crashed with a mighty crash last Monday, and it has continued to trend downward since then, with plenty of zig-zags.

I am not an expert in this area, but have done a bit of reading. There seems to be an emerging consensus that DeepSeek got to where it got to largely by using what was already developed by ChatGPT and similar prior models. For this and other reasons, the claim for fantastic savings in model training has been largely discounted. DeepSeek did do a nice job making use of limited chip resources, but those advances will be incorporated into everyone else’s models now.

Concerns remain regarding built-in bias and censorship to support the Chinese communist government’s point of view, and regarding the safety of user data kept on servers in China. Even apart from nefarious purposes for collecting user data, ChatGPT has apparently been very sloppy in protecting user information:

Wiz Research has identified a publicly accessible ClickHouse database belonging to DeepSeek, which allows full control over database operations, including the ability to access internal data. The exposure includes over a million lines of log streams containing chat history, secret keys, backend details, and other highly sensitive information.

Shifting focus to Nvidia – – my take is that DeepSeek will have little impact on its sales. The bullish narrative is that the more efficient algos developed by DeepSeek will enable more players to enter the AI arena.

The big power users like Meta and Amazon and Google have moved beyond limited chatbots like ChatGPT or DeepSeek. They are aiming beyond “AI” to “AGI” (Artificial General Intelligence), that matches or surpasses human cognitive capabilities across a wide range of cognitive tasks. Zuck plans to replace mid-level software engineers at Meta with code-bots before the year is out.

For AGI they will still need gobs of high-end chips, and these companies show no signs of throttling back their efforts. Nvidia remains sold out through the end of 2025. I suspect that when the company reports earnings on Feb 26, it will continue to demonstrate high profits and project high earnings growth.

Its price to earnings is higher than its peers, but that appears to be justified by its earnings growth. For a growth stock, a key metric is price/earnings-growth (PEG), and by that standard, Nvidia looks downright cheap:

Source: Marc Gerstein on Seeking Alpha

How the fickle market will react to these realities, I have no idea.

The high volatility in the stock makes for high options premiums. I have been selling puts and covered calls to capture roughly 20% yields, at the expense of missing out on any rise in share price from here.

Disclaimer: Nothing here should be considered as advice to buy or sell any security.

How FRASER Enhances Economic Research and Analysis

Zachary BartschLeave a comment

Most of us know about FRED, the Federal Reserve Economic Data hosted by the Federal Reserve of St. Louis. It provides data and graphs at your fingertips. You can quickly grab a graph for a report or for a online argument. Of course, you can learn from it too. I’ve talked in the past about the Excel and Stata plugins.

But you may not know about the FRED FRASER. From their about page, “FRASER is a digital library of U.S. economic, financial, and banking history—particularly the history of the Federal Reserve System”. It’s a treasure trove of documents. Just as with any library, you’re not meant to read it all. But you can read some of it.

I can’t tell you how many times I’ve read a news story and lamented the lack of citations –  linked or unlinked.  Some journalists seem to do a google search or reddit dive and then summarize their journey. That’s sometimes helpful, but it often provides only surface level content and includes errors – much like AI. The better journalists at least talk to an expert. That is better, but authorities often repeat 2nd hand false claims too. Or, because no one has read the source material, they couch their language in unfalsifiable imprecision that merely implies a false claim.

A topical example would be the oft repeated blanket Trump-tariffs. That part is not up for dispute. Trump has been very clear about his desire for more and broader tariffs. Rather, economic news often refers back to the Smoot-Hawley tariffs of 1930 as an example of tariffs running amuck. While it is true that the 1930 tariffs applied to many items, they weren’t exactly a historical version of what Trump is currently proposing (though those details tend to change).

How do I know? Well, I looked. If you visit FRASER and search for “Smoot-Hawley”, then the tariff of 1930 is the first search result. It’s a congressional document, so it’s not an exciting read. But, you can see with your own eyes the diversity of duties that were placed on various imported goods. Since we often use the example of imported steel and since the foreign acquisition of US Steel was denied, let’s look at metals on page 20 of the 1930 act. But before we do, notice that we can link to particular pages of legislation and reports – nice! Reading the Smoot-Hawley Tariff Act’s original language, we can see the diverse duties on various metals. Here are a few:

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