Household Formation and Generational Wealth

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.

Manufacturing Jobs of the Past

This post is co-written with John Olis, History major at Ave Maria University.

There is a popular myth that manufacturing jobs of the past provided a leg-up to young people. The myth goes like this. Manufacturing jobs had low barriers to entry so anyone could join. Once there, the job paid well and provided opportunities for fostering skills and a path toward long-term economic success. There is more to the myth, but let’s stop there for the moment. Is the myth true?

One of my students, John Olis, did a case study on Connecticut in 1920-1930 using cross sectional IPUMS data of white working age individuals to evaluate the ‘Manufacturing Myth’. We are not talking causal inference here, but the weight of the evidence is non-zero. The story above has some predictions if not outright theoretical assertions.

  1. Manufacturing jobs paid better than non-manufacturing jobs for people with less human capital.
  2. Manufacturing jobs yielded faster income growth than non-manufacturing jobs.
  3. Implicitly, manufacturing jobs provided faster income growth for people with less human capital.

Using only one state and two decades of data obviously makes the analysis highly specific. Expanding the breadth or the timescale could confirm or falsify the results. But historical Connecticut is a particularly useful population because 1) it had a large manufacturing sector, 2) existed prior to the post WWII boom in manufacturing that resulted from the destruction of European capacity, and 3) had large identifiable populations with different levels of human capital.

Who had less human capital on average? There are two groups who are easy to identify: 1) immigrants and 2) illiterate people. Immigrants at the time often couldn’t speak English with native proficiency or lacked the social norms that eased commercial transactions in their new country (on average, not always). Illiterate people couldn’t read or write. Therefore, having a comparative advantage in manual labor, we’d expect these two groups to be well served by manufacturing employment vs the alternative.

Being cross-sectional, the individuals are not linked over time, so we can’t say what happened to particular people. But we can say how people differed by their time and characteristics. Interaction variables help to drill-down to the relevant comparisons. There are two specifications for explaining income*, one that interacts manufacturing employment with immigrant status and one that interacts the status of illiteracy. The baseline case is a 1920 non-operative native or literate person. Let’s start with the below snapshot of 1920. The term used in the data is ‘operative’ rather than ‘manufacturer’, referring to people who operate machines of one sort or another. So, it’s often the same as manufacturing, but can also be manufacturing-adjacent. The below charts illustrate the effect of lower human capital in pink and the additional subpopulation impacts of manufacturing in blue.

In the left-hand specification, native operatives made 2.2% less than the baseline population. That is, being an operative was slightly harmful to individual earnings. Being an immigrant lowered earnings a substantial 16.8%, but being an operative recovered most of the gap so that immigrant operatives made only 6.1pp less than the baseline population and only 3.9pp less than native operatives. In the right-hand specification, unsurprisingly, being illiterate was terrible for one’s earnings to the tune of 23.4pp. And while being an operative resulted in a 1.2% earnings boost among natives, being an operative entirely eliminated the harm that illiteracy imposed on earnings.

Both graphs show that manufacturing had tiny effects for a typical native or literate individual. But manufacturing mattered hugely for people who had less human capital. So, prediction 1) above is borne out by the data: Manufacturing is great for people with less-than-average human capital.

But what about earnings *growth*? See below.

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Spending on Necessities Has Declined Dramatically in the United States

Has it gotten easier or harder for Americans to afford the basic necessities of life? Part of the answer to this question depends on how you define “basic necessities,” but using the common triad of food, clothing, and housing seems like a reasonable definition since these composed over 80% of household spending in 1901 in the United States.

If we use that definition of necessities, here is what the progress has looked like in the US since 1901:

The data comes from various surveys that the Bureau Labor Statistics has collected over the years, collectively known as the Consumer Expenditure Surveys. The surveys were conducted about once every 1-2 decades from 1901 up until the 1980s, and then annually starting in 1984. Some of these are multi-year averages, but to simplify the chart I’ll just state one year (e.g., “1919” is for 1918 and 1919). The categories are fairly comprehensive: “food” includes both groceries and spending at restaurants; “housing” includes either mortgage or rent, plus things like utilities and maintenance; and “clothing” includes not only the cost of the clothes themselves, but services associated with them such as repairs or alterations (much more important in the past).

We can see in the chart that over time the share spent on these three areas of spending has declined dramatically, taken as a group. Housing is different, but it has been fairly stable over time, mostly staying between 22% and 29% of income (the Great Depression being an exception). There are two time periods when these costs rose: the Great Depression and the late 1970s/early 1980s. Both are widely recognized as bad economic times, but they are aberrations. The jump from 1973 to 1985 in spending on necessities was fully offset by 2003, and today spending on necessities is well below 1973 — even though for housing, it is a few percentage points greater.

A chart like this shows great progress over time, but it will inevitably raise many questions. Let me try to answer a few of them in advance.

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Anti-Tariff Declaration

The Smoot-Hawley Tariff of 1930 was opposed by a thousand economists, but passed anyway, exacerbating the Great Depression. Now that the biggest tariff increase since 1930 is on the table, the economists are trying again. I hope we will find a more receptive audience this time.

The Independent Institute organized an “Anti-Tariff Declaration” last week that now has more signatures than the anti-Smoot-Hawley declaration, including many from top economists. One core argument is the sort you’d get in an intro econ class:

Overwhelming economic evidence shows that freedom to trade is associated with higher per-capita incomes, faster rates of economic growth, and enhanced economic efficiency.

But I thought the Declaration made several other good points. Intro econ textbooks say that tariffs at least benefit domestic producers (at the expense of consumers and efficiency), but in practice these tariffs have been mainly hurting domestic producers, because:

The American economy is a global economy that uses nearly two thirds of its imports as inputs for domestic production.

I get asked to sign a petition of economists like this every year or so, but this is the first one I have ever agreed to sign onto. Most petitions are on issues where there are good arguments on each side, like whether to extend a particular tax cut, or which Presidential candidate is better for the economy. But the argument against these tariffs is as solid as any real-world economic argument gets.

The full Declaration is quite short, you can read the whole thing and consider signing yourself here.

The Best Investments of the 1970s

The tariffs still have me thinking about buying VIX calls and stock puts (especially when policy changes loom on certain dates like July 8th), and on the bigger question of finding the sort of investments that did well in the 1970’s, another decade of stagflation that was kicked off by a President who broke America’s commitment to an international monetary system that he thought no longer served us.

That’s how I concluded last week. So this week I’ll answer the question- what were the best investments of the 1970’s? When the dollar is losing value both at home and abroad, holding dollars or bonds that pay off in dollars does poorly:

Source: My calculations using Aswath Damodaran’s data

Stocks can do alright with moderate inflation, but US stocks lost value in the stagflation of the 1970’s. Foreign stocks and commodities generally performed better. Real estate held its value but didn’t produce significant returns; gold shone as the star of the decade:

Source: My calculations using Aswath Damodaran’s data

Gold is easy to invest in now compared to the 1970s; you don’t have to mess with futures or physical bullion, there are low-fee ETFs like IAUM available at standard brokerages.

Of course, while history rhymes, it doesn’t repeat exactly; this time can and will be different. I doubt oil will spike the same way, since we have more alternatives now, and if it did spike it wouldn’t hurt the US in the same way now that we are net exporters. Inflation won’t be so bad if we keep an independent Federal Reserve, though that is now in doubt. At any time the President or Congress could reverse course and drop tariffs, sending markets soaring, especially if they pivot to tax cuts and deregulation in place of tariffs ahead of the midterms.

Things could always get dramatically better (AI-driven productivity boom) or worse (world war). But for now, “1970s lite” is my base case for the next few years.

When Genius Failed

Myron Scholes was on top of the world in 1997, having won the Nobel Prize in economics that year for his work in financial economics, work that he had applied in the real world in a wildly successful hedge fund, Long Term Capital Management. But just one year later, LTCM was saved from collapse only by a last-minute bailout that wiped out his equity (along with that of the other partners of the fund) and cast doubt on the value of his academic work.

Roger Lowenstein told the story of LTCM in his 2001 book “When Genius Failed“. I finally got around to reading this classic of the genre this year, and I’d say it is still well worth picking up. The story is well-told, and the lessons are timeless-

  • Beware hubris
  • Beware leverage
  • Bigger positions are harder to get out of (especially once everyone knows you are in trouble)
  • In a crisis, all correlations go to one
  • Past results don’t necessarily predict future performance
  • Sometimes things happen that are very different from anything that happened in your backtest window.

The book came out in 2001 but it presages the 07 financial crisis well- not about mortgage derivatives specifically, but the dangers of derivatives, leverage, using derivatives to avoid regulations restricting leverage, and over-relying on mathematical models of risk based on past behavior. If Fed had let LTCM fail, could we have avoided the next crisis? Perhaps so, as their counterparties (most major Wall Street banks) who got burned would have been more careful about the leverage and derivatives used by themselves and their counterparties, and regulators may have taken stronger stances on the same issues.

Perhaps some more recent well-contained blowups foreshadow the next big crisis in the same way, like FTX or SVB?

Some more specific highlights about LTCM:

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Now published: Human capital of the US deaf Population, 1850-1910

Myself and a student coauthor worked hard on our article that is now published in Social Science History. It’s the first modern statistical analysis of the historical deaf population. We bring an economic lens and statistical treatment to a topic that previously included much anecdotal evidence and case study. We hope that future authors can improve on our work in ways that meet and surpass the quantitative methods that we employed.

Our contributions include:

  • A human capital model of deafness that’s agnostic about its productivity implications and treats deaf individuals as if they made decisions rationally.
  • A better understanding of school attendance rates and the ages at which they attended.
  • Deaf children were much more likely to be neither in school nor employed earlier in US history.
  • The negative impact of state ‘school for the deaf’ availability on subsequent economic outcomes among deaf adults. We speculate that they attended schools due to the social benefits of access to community.
  • Deaf workers did not avoid occupations where their deafness would be incidentally detectable by trade partners, implying that animus discrimination was not systemically important for economic outcomes.
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Trump’s National Sales Tax

Tariffs are going up to levels last seen in the 1930 Smoot-Hawley tariffs that helped kick off the Great Depression:

Tariffs are taxes- roughly, a national sales tax with an exemption for domestically-produced goods and services. I think the words make a difference here- “raising tariffs on countries who we run a trade deficit with” just sounds abstruse to most people, while “raising taxes on goods bought from firms in net-seller countries” sounds negative, but they are the same thing.

Of course, in this case the plan is to raise taxes to at least 10% on goods from all other countries even if they aren’t net-sellers, and raise taxes up to 49% on those that are. This is not a negotiating tactic. We know this from the math- the new tax formula uses net imports from a country rather than a country’s tariff rates, so a country could cut their tariffs on US goods to zero today and it wouldn’t necessarily reduce our “reciprocal” tariffs at all; at best it would reduce them to 10%. We also know it isn’t about negotiating because the administration says it isn’t. Their goal, obviously, is to reduce trade, not to free it.

They say they are doing this to bring manufacturing back to America and to promote national defense. But American manufacturers don’t seem happy. Even before the latest huge tax increase, trade war was their biggest concern:

The National Association of Manufacturers Q1 2025 Manufacturers’ Outlook Survey reveals growing concerns over trade uncertainties and increased raw material costs. Trade uncertainties surged to the top of manufacturers’ challenges, cited by 76.2% of respondents, jumping 20 percentage points from Q4 2024 and 40 percentage points from Q3 of last year.

The National Association of Manufacturers responded to the latest tax increase with a negative statement; so even the one major group that might have benefitted from tariffs is unhappy. Foreign producers and US consumers will of course be very unhappy. I think Trump is making a huge political blunder alongside the economic one- he got elected largely because Biden allowed inflation to get noticeably high, but now Trump is about to do the same thing.

I also see this as a huge national security blunder. For tariffs on China, I at least see their argument- we should take an economic hit today in order to become less reliant on our peer-competitor and potential adversary. But the tariffs on allies make no sense- they are hitting the very countries that are most valuable as economic and/or military partners in a conflict with China, like Canada, Mexico, Japan, South Korea, Vietnam, India, and Taiwan (!!!). One of our biggest advantages vs. China has been that we have many allies and they have few, and we appear to be throwing away this advantage for nothing.

What can you or I do about this? Stock up on durable goods before the price increases hit. Picking investment winners is always hard, but things this makes me consider are gold, stocks in foreign countries that trade little with the US, and companies whose stocks took a big hit today despite not actually being importers. Finally, we can try nudging Congress to do something. The Constitution gives the power to levy taxes to the legislative branch, but in the 20th century they voted to delegate some of this power to the executive. Any time they want, Congress could repeal these tariffs and take back the power to set rates. I have some hope they actually will- just yesterday the Senate voted to repeal some tariffs on Canada, and more votes are planned. The alternative is to risk a recession and a wipeout in the midterms:

Messy Disability Records in the Historical Censuses

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

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.