Tag Archives: percentages

The falling number of adult men in the US workforce explained by absolute numbers and percentages

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What numbers would make it easier to understand what is happening to how many adult men are in the US workforce? This article starts with absolute numbers:

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The latest Bureau of Labor Statistics breakdown found that 44.07 million of 132.8 million eligible men older than 15 — or 33.2% — were not in the labor force last month. That’s 9 million more out-of-work men (29%) than in 2012.

The number of men opting not to work jumped by 891,000 over the preceding 12 months alone, as the economy sheds manufacturing and finance jobs.

Those numbers sound big. 9 million compared to fourteen years ago. Nearly 900,000 in just one year.

But how many adult men are in the workforce in the first place? Has this changed much between 2012 and 2026 or even in the last year? How many people live in the United States anyway?

Percentages are provided later in the article:

The share of eligible men participating in the workforce dropped from 77.5% in 1976 to 66.8% last month, the lowest nonpandemic reading since 1948. Meanwhile, the share of eligible women in the workforce has climbed from 47.3% in 1976 to 56.4%, boosted by growing fields, such as healthcare…

The recruiting industry trade group estimates that the number of men leaving the workforce after turning 65 has jumped by 99% since 2000, compared with a 71% increase among women. Currently, 53% of people entering the workforce are women and 47% are men.

The percentages suggest men in the workforce dropped over 10% between 1976 to 2026. And the percentage comparisons to women are interesting.

My guess is that the absolute numbers might catch people’s attention. The headline for the story provides evidence for this: “Millions of men are ditching the workforce.” Whoa, millions of men? What is happening? Something needs to be done.

Percentages are better for understanding the scope of the changes. An over 10% change over 60 years may not catch as much attention but it helps put the millions number in context. This is a change – but there are a lot of men and people in the United States.

Both sets of numbers may be accurate but I would vote for the percentages as they help put the changes in context.

The percentage of realtors under age 30 went up 400% (*from 1% to 4%)

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Some younger adults are moving into certain careers they feel offer them opportunities in an uncertain world. This includes becoming a realtor.

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Some Zoomers like Marmo are ditching four-year degrees in favor of work that unchains them from a desk, puts money in their bank accounts sooner, and — they hope — will survive the artificial intelligence boom that is already starting to change once-hot professions like software engineering, consulting, and marketing. Some are turning to blue collar work like HVAC servicing and wind turbine installation. Others are trying to start their own ventures via influencing and side hustles. And some see the lure in the licensed white-collar job, including working in real estate or insurance.

That shift in licensed jobs is slow, but growing. The share of Realtors younger than 30 grew from 1% to 4% in 2024, according to NAR’s member profile, and sits at 3% in 2025. Among insurance agents, the median age of an insurance principal who owns 20% or more of their agency is 55, with 22% of principals over the age of 66, according to a 2024 study of agencies conducted by the Big “I,” an association for independent insurance agents. Many are likely eying retirement, which could open up a huge amount of demand for young people to take up the trade.

Several Gen Zers I spoke to for this story told me they find appeal in working in real estate because there’s no ceiling on what they can earn. Rather than invest tens or hundreds of thousands of dollars in a four-year degree, they can spend a few weeks or months training to receive licenses and start working in fields where their hustle correlates to their payday…

Because it’s still something of a rarity to see a baby-faced real estate agent or teenager selling life insurance, the young people in licensure jobs I spoke to say that succeeding means not just learning the trade but competing against ageist stereotypes. The median age of a first-time home buyer has risen to an all-time-high of 38, according to NAR. That’s up from an average age of 33 a decade ago, according to a Zillow analysis. The idea of having a newly minted, 18-year-old real estate agent guide you through the biggest financial decision of your life is jarring. Katie Kenny, a 24-year-old Realtor in Chicago’s suburbs, says people meet her and are surprised, as they “expect the real estate agent to be like double my age,” she tells me. “They’re like, ‘oh, you’re young.’ And then when I open my mouth and start talking, they’re actually surprised because I do know a lot more, and I sound a lot more mature than what a normal 24-year-old would sound like.”

This article, like many articles, is trying to get a handle on a possible trend: younger people are pursuing different fields due to the world around them. There are numerous ways to report on this phenomena. This article uses a mix of statistics and interviews, considering broader patterns and hearing people describe their choices.

In the headline to the post, I highlight one way to report the data cited above. 400% growth in young realtors! 400% of anything sounds like a lot of change. A 100% increase or decrease would be noteworthy so 400% must mean a lot.

Another way to do this would be to take the approach above: the percentage of young realtors increased from 1% to 4%. This is not a big jump as both are small percentages. The odds of having a realtor under 30 years old is still 1 in 25.

Both of these options are factually correct. I would argue the second option is a better representation of the full context. Change happened but it is small change. If the same trend continues for 5 to 10 years, then there might be big change to report. Imagine the 30% of realtors under age 30 or 50%.

Someone will continue to track this data. It makes for interesting stories: “In an age of AI, college debt, and global crisis, more young adults in the United States are choosing to be realtors.” How big of a story it becomes partly depends on how it is told.

Small N and big percentage change, Paul McCartney and Wings edition

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I saw this headline earlier this week: “Paul McCartney’s Wings Album Soars More Than 5,000% In Sales.” For an artist who has sold millions of albums over 60 years of making music, this sounded important. But here are the details of the story:

According to Luminate, Venus and Mars sold 2,500 copies in the U.S. in the most recent tracking week. That’s a strong number for a reissue of an album that’s been around for decades — and especially notable given how little it moved just a week prior. In the previous frame, the set couldn’t even manage 100 copies. That means that from one span to the next, the Wings title enjoyed a sales spike of 5,435%.

The Venus and Mars surge can be attributed to a recent reissue that targets McCartney’s most devoted supporters. The full-length was re-released on vinyl in a half-speed remastered form, which may not sound like a major change, but it was enough to grab the attention of collectors and audiophiles alike. While the music remains largely the same, the format offers improved sound quality and a what must be a unique listening experience.

What happened is that this album was reissued on vinyl. This pushed sales of the record up. But it went from under 100 copies sold to 2,500 copies sold. This is a big percentage increase but not a big figure. 2,500 records moved in one week is less than a drop in the bucket in numbers of popular music sold after World War Two.

The headline is technically correct. Sales jumped over 5,000%! Sales spiked for Paul McCartney! Is it a meaningful change? No. Barely any records were sold in either week. Maybe plenty of people will click on this story because of the shocking statistic in the headline – I did – but there is not much news here.

This is what happens when you have a small number of cases overall. A small shift in numbers either way, up or down, can lead to a really big percentage change.

City voters changed more for Trump in 2024 compared to support in suburbs and elsewhere

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An analysis of voting data for president by county suggests Trump picked up more support from cities this election compared to changes in suburban voting:

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Let’s start with geography. Urban counties showed a bigger swing toward Trump than suburban and exurban counties, smaller metros, and rural areas. Of course, Harris did best — as did Biden four years earlier — in urban counties, but the 10-point swing toward Trump in urban counties was larger than swings in other places.

A more refined county classification from the American Communities Project, which groups counties based on their demographic, economic, and other factors, confirmed that Trump did better in 2024 than in 2020 in all types of communities, with larger swings in some places than others. Big cities, Hispanic centers, and Native American lands swung most toward Trump in 2024. The reddest communities — aging farmlands, evangelical hubs, and working class country — swung less, as did still-blue college towns and LDS (i.e. Mormon) enclaves, where Trump has repeatedly gotten smaller margins than previous Republican presidential candidates.

Going one step more granular to individual metros, many swung more than 10 points toward Trump in 2024 versus 2020, including New York, Los Angeles, Chicago, San Francisco, and Miami, as well as heavily Hispanic/Latino metros in Texas, California, and the Southwest. Just a handful of metros swung a bit bluer in 2024, mostly in the Mountain West and Pacific Northwest, including Salt Lake City, Tucson, and Colorado Springs. 

Looking across all counties that have reported election data, the geographic pattern of the 2024 vote was less polarized than in 2020 in some ways. Most notably, counties with a higher share of Hispanic residents were more likely to vote for Harris than for Trump, but by smaller margins than for Biden in 2020. Same with higher density counties: there was a very strong correlation between county density and Harris vote share, though not as strong as in 2020. In contrast, the correlation between county education level and Harris vote share strengthened further in 2024. Density and education are themselves highly correlated, with residents of more urban counties more likely to have a college degree than those of more rural counties, but higher-density counties swung toward Trump, while highly educated counties did not.

This is a different kind of analysis than looking at percentages of urban, suburban, and rural voters and who they voted for. This considers which places changed the most between 2020 and 2024.

One question about this is whether the electoral college outcomes changed if one candidate picked up more votes in cities. If the election came down to key states, were these swings in urban areas enough to win the state? Or maybe they did prove consequential in purple states. Looking at these swings in particular places could help address this. In Pennsylvania, did changes in metropolitan Philadelphia and Pittsburgh decide this or in Wisconsin, changes in metropolitan Milwaukee and Madison?

Additionally, it is less clear what this all means for considering suburban voters. The American Communities Project typology includes multiple suburban settings, Urban Burbs, Middle Suburbs, and Exurbs, in addition to suburban areas that might fit into other categories because of unique traits (such as a college town in a suburban county). Just looking at the three with suburbs in their title in one form or another, the 2020 patterns held: exurbs leaned Republican, suburbs near cities leaned Democratic, and middle suburbs leaned Republican. But voters in each three categories moved toward Trump. Was this shift substantive? Did suburban voters decide the 2024 election?

I am sure there is more analysis to come on this subject and I will keep looking for it.

How much land or how many homes should one actor be allowed to own?

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A recent fact check highlighted how much property several American actors owned:

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“Bill Gates is buying up the majority of American farmland and BlackRock is buying the majority of single family houses but I’m supposed to believe the biggest threat to us is Elon Musk buying Twitter?,” read a Twitter post that was liked or shared more than 250,000 times.

But Gates doesn’t own more than 50% of U.S. farmland, according to The Associated Press. Even with recent purchases, he owns less than 1% of the nation’s farmland.

Gates, with 269,000 acres, is considered the largest private owner of farmland in the country. But his share is a small percentage of the nearly 900 million acres of U.S. farmland, according to the Department of Agriculture…

Also, BlackRock does not own a majority of U.S. single-family homes, the AP said.

How much property ownership is too much? Putting the amount of land or property into percentages is one way to think about it. Gates owns less than 1% of the farmland, BlackRock owns under 50% of the homes. The first figure suggests Gates barely owns anything while the second number is not a great one to note since I suspect owning 49% would not assuage those who retweeted this (and the likely figure is way under 10%).

Putting the ownership in absolute numbers might make a different argument. Gates owns 269,000 acres. That sounds like a lot, even in a big country in the United States. Or, if someone said BlackRock owns 60,000 homes, that would sound like a lot, even in a country with many more homes than that.

But, before we decide what numbers to use, we have to know what the concern is: should someone own 1% of the farmland? Should a company own tens of thousands of homes? The numbers can help illuminate the situation but they cannot answer the moral and ethical questions of just how much should one person or organization own? Using big or shocking numbers (even if they are incorrect) to suggest people should pay attention to a particular social problem is not new.

Example of problems with statistics “nearly 1,500 millionaires” (out of more than 235,000) “paid no federal taxes”

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Statistics can be used well and they can be used not so well. Here is an example where the headline statistic suggests something different from the rest of the story:

Of an already small pool of millionaires and billionaires, 1,470 didn’t pay any federal income taxes in 2009, according to the Internal Revenue Service.

Just over 0.1% of taxpayers — or 8,274 out of 140 million total — made more than $10 million in 2009, according to the agency. More than 235,000 taxpayers earned $1 million or more, according to a recent report from the agency.

But of the high earners who avoided paying income taxes, many did so due to heavy charity donations or foreign investments.

About 46% of all American households won’t pay federal income tax in 2011, many due to low income, tax credits for child care and exemptions, according to the nonpartisan Tax Policy Center.

The headline makes it sound like there are a lot of millionaires who are avoiding paying taxes. The actual percentage hinted at it in the story suggests something else: less than 0.63% of all millionaires (1,470/235,000 – less than 1 in a 100)) paid no taxes. In the midst of a political debate about whether to raise taxes for the wealthy in America, each side could grab on to factual yet different figures: the 1,500 figure sounds high like the country is missing out on a lot money while the 0.63% figure suggests almost all pay some taxes. It wouldn’t take much to include both figures, the actual number and the percentage in the story.

Examples like this help contribute to the reaction some people have when they see statistics in the media: how can I trust any of them if they will just use the figures that suit them? All statistics become suspect and it is then hard to get a handle on what is going on in the world.