The Fastest-Shrinking Cities in America
When people talk about cities losing population, they usually tell one story. The good jobs left, the tax base followed, and the place hollowed out over a generation. But the Census data tells a more complicated version of that story. Right now the list of fast-shrinking large cities mixes two completely different things, and if you read them as the same trend you will misread both.
The numbers here come from the U.S. Census Bureau's American Community Survey, and they cover one recent period of change, not a full decade. That matters. A single ACS interval is noisier than a ten-year trend, so a city near the top of this list might be in real long-run decline, or it might be having one rough stretch that partly snaps back. I'll flag which is which where the data supports it.
One more filter. The very top of the full fastest-shrinking cities ranking is dominated by tiny towns, where losing a few hundred people swings the percentage hard. Those places are real, but the names don't tell you anything. So this piece sticks to cities above 120,000 people, where the labels are recognizable and the losses involve a lot of human beings.
Story one: people priced out of the expensive coasts
The single biggest drop on the large-city list belongs to San Francisco, down 5.0% to about 830,235 residents. New York fell 3.6% from a base of roughly 8,483,844, which is a small percentage attached to a very large number of departures. And a cluster of California cities sits right alongside them: Torrance at -3.4%, Berkeley at -3.3%, Glendale at -2.9%, and Palmdale at -2.8%.
These cities don't have a job-loss problem in the old sense. They have a cost problem that collided with remote work. When the pandemic decoupled a lot of high-earning jobs from any specific office, the people holding those jobs looked at coastal rents and mortgages and did the math. Some moved to cheaper metros. Some moved a couple hours out and kept the job. The result shows up as out-migration from the priciest places in the country.
The honest caveat is that this kind of decline is not the same as structural collapse, and it may partly reverse. Return-to-office pressure, a cooling in some rental markets, and the simple fact that people still want to be in these cities all push the other way. I would not bet that San Francisco keeps shedding 5% a year. A cost-and-remote-work outflow can slow or turn around in a way that disinvestment-driven decline almost never does.
Story two: the slow structural decline in the South and Midwest
The other cities on this list belong to a different category, and it's worth keeping them separate. Jackson, Mississippi fell 4.6% to about 146,631. St. Louis dropped 4.3% to roughly 288,512. Shreveport, Louisiana lost 3.5% to about 180,982, and New Orleans fell 3.2% to around 371,853.
What links these is not a one-time shock but a long arc of lost jobs and disinvestment. The work that built these cities (manufacturing, port and rail activity, regional industry) thinned out over decades, and the people followed the work elsewhere. When the employment base shrinks, the tax base shrinks with it, which strains schools, water systems, and basic services, which then pushes more people to leave. Jackson's water-system troubles are a recent, visible example of that loop.
This is the pattern people picture when they hear "shrinking city," and it has a longer history than one ACS period. If you want to see where it can lead when it runs for half a century, the clearest cases are documented at length: how Detroit lost half its population and how Youngstown, Ohio lost two-thirds of its population. Those cities are not on today's large-city list because the worst of their decline already happened. Jackson, St. Louis, Shreveport, and New Orleans are earlier in the same kind of story.
Why the two stories shouldn't be averaged together
Put San Francisco and Shreveport in the same column and you get a meaningless blend. One lost people because it's too expensive to stay and the jobs let you leave. The other lost people because the jobs themselves went away. A policy that helps one would do little for the other. Lower coastal housing costs would bring some people back to the Bay Area; it would not rebuild Shreveport's employment base.
The reversibility is different too. Out-migration driven by cost and remote work has a natural ceiling and a real chance of partly unwinding. Decline driven by a shrinking job base tends to compound, because each departure weakens the services that might have kept the next family in place. Same percentage on a chart, two very different futures.
One ACS period can't settle which cities are in trouble for good and which are just having a hard year. What it can do is show you the shape of the moment, as long as you don't flatten two stories into one.
If you want to see the full picture, the live fastest-shrinking cities ranking includes the smaller places this piece left out, and you can put any two of these cities side by side over time using the compare tool to judge for yourself whether a drop looks like a blip or a trend.
Sources
Population change figures are from the U.S. Census Bureau's American Community Survey, with the large-city list drawn from the CensusEasy fastest-shrinking cities ranking.
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What are the fastest-shrinking large cities in America right now?
Among cities over 120,000 people, San Francisco leads at -5.0%, followed by Jackson, Mississippi at -4.6% and St. Louis at -4.3%. New York, Shreveport, and New Orleans also appear, along with several California cities like Torrance, Berkeley, Glendale, and Palmdale.
Why are San Francisco and New York losing population if they have strong job markets?
These coastal cities aren't losing jobs in the old sense. They have high housing costs that collided with remote work, letting high earners keep their jobs while moving to cheaper places. This kind of cost-driven out-migration can slow or partly reverse, unlike decline tied to a shrinking job base.
How reliable is a single year of Census population change data?
A single American Community Survey period is noisier than a full ten-year trend, so one big drop can reflect a real long-run decline or just a rough stretch that partly snaps back. The compare tool lets you check whether a city's loss looks like a blip or a sustained pattern.