Revenue Road Trip: Taxpayers Fleeing Urban Counties for Smaller-Government Counterparts

Following Tax Day, Open the Books is releasing a set of deep dives into data released by the Internal Revenue Service, synthesized with additional public datasets. These findings come straight from Uncle Sam’s own ledger. Read the previous story here.

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Last week the American Legislative Exchange Council (ALEC) released its seminal, annual Rich States, Poor States report, which ranks all 50 states on their economic competitiveness using metrics like total tax burden, labor laws and the cost of debt service. Open the Books did a complimentary analysis, digging into county-level statistics.

We usually measure migration by counting how many people leave. But that’s only part of the picture. When people move, they don’t just relocate, they take their income, spending power, and economic impact with them.

A survey of 2,315 counties using data published by the IRS demonstrates billions of dollars of dollars in adjusted gross income (AGI) have been leaving counties that house major urban centers.

Counties experiencing the largest net income outflows due to migration (IRS SOI Data, 2022–2023)

The data reveals a striking pattern.

Cook County, Illinois lost more than $4.3 billion in adjusted gross income (AGI) through migration. Los Angeles County follows closely, with losses exceeding $4.2 billion.

Other major economic centers are not far behind:

Santa Clara County lost nearly $2.8 billion. New York County, Manhattan, has lost roughly $2.8 billion. King County, WA (home to Seattle) saw nearly $2 billion leave.

These are not marginal shifts. They represent massive economic outflows from some of the country’s most productive regions.

As people pack up and move, their taxable income is headed elsewhere. More spending power is disappearing. More long-term economic capacity is being relocated.

Many of the counties experiencing the largest losses share common traits. They are large urban centers, high-cost regions, and major economic hubs.

In many cases, they’re also dense with government employees. In our previous report, we detailed how high-government counties suffered higher poverty rates and lower median household incomes. Conversely, low-government counties were more prosperous.

San Francisco County has a massive 133 government workers per 1,000 residents, 73 more than the average county. New York County has even more at 136 per thousand. King County has 76 per thousand, still 17 more than average.

Just a bit further down the list of losers is another usual suspect: Washington, DC with a predictably high 335 government employees per thousand residents and net negative $702,074 in AGI.

Not only do places like these tend to fare worse by key economic indicators of wellbeing, but they’re bleeding revenue.

Income loss at this scale has real implications. Counties losing billions in AGI face shrinking tax bases, increased pressure on public services where they may be most needed and reduced long-term economic resilience.

From Urban Centers to Smaller Government Counties

Take a look at where the revenue was headed. These are the counties that enjoyed the biggest net gain in AGI, year over year.

Many of these counties also share something in common: the density of government employees is below average there.

Palm Beach County has just 39 government workers per 1,000 residents. Pasco County has an even lower count at 25. Per our previous report, Pasco was also among the top five counties for net taxpayers gained. It was joined by Williamson and Montgomery counties in Texas; they respectively have 39 and 46 government workers per thousand residents, both well below average.

Fewer People, More Money: Where Income Is Gathering Despite Population Loss

When we compare total income across places like Los Angeles County, New York County, and Cook County we assume that tells us where economic prosperity is abundant. But that assumption hides more than it reveals. Large counties almost always dominate these rankings simply because they have more people. It does not follow that the average household in those places is wealthy. In fact, some of the most populated counties in America look far less affluent once you shift the lens.

This is where AGI per return becomes essential. Adjusted Gross Income, or AGI, measures total income reported on tax returns. But total AGI alone tells us very little about how people actually live. AGI per return, which captures income per household, changes the question entirely. Instead of measuring economic size, it measures economic reality.

In fact, a deeper and more surprising pattern emerges when we look at how income moves alongside people.

In several counties, fewer households arrived than left, yet total income still rose. In places like Miami-Dade and Palm Beach County, population decline coincided with income growth.

As discussed, Palm Beach County benefits from a low density of government workers in addition to the state’s sunny skies and lack of an income tax. Nearby Miami-Dade County, despite being a major urban hub, still manages to have a relatively low number of government workers per thousand residents (49, or about 10 below the average county).

These results are not a contradiction. They demonstrate a shift in who lives there. Lower- or middle-income households are being replaced by higher-income ones, changing the economic structure of these regions even as the number of residents falls.

Indeed, the Los Angeles Times reported the area has attracted an “unusually large number of the disaffected California tech moguls” fleeing a potential 5% wealth tax on billionaires.

“This extraordinary wealth migration is reshaping south Florida: spurring development…and amplifying demand for nannies, private chefs, exclusive golf club memberships and private schools,” wrote reporter Stacy Perman.

The logic should follow that some of the net migration out of these counties can be reversed, and household incomes can rise, as a fresh support economy springs up around the new neighbors.

Conclusion

Some counties are becoming more economically selective, with rising barriers to entry and a growing concentration of wealth among fewer households. At the same time, other counties may appear prosperous in aggregate terms while many of their residents do not experience that prosperity. Frequently, they appear in pairs. While New York County generates massive total income, tax revenue is hemorrhaging and some of it is pooling in Western Connecticut just outside the city. The same story is true even in the environs of progressive bastion San Francisco: nestled in the cliffside, neighboring Marin County managed to hover just 1 above the national average of government workers per thousand residents (60) while minimizing outflow of taxpayers and getting slightly wealthier.

In the end, the way we measure inequality shapes the story we tell about it. The real question is not how big a local economy is, but how much of its benefits are captured by dense government rather than truly reaching the people who live there.

Methodology

This analysis uses the most recent publicly available data from each federal source. Employment and population data run through 2024. Poverty and income estimates run through 2023. Migration data runs through 2021-2022, reflecting the additional processing time required for IRS tax return address matching at the county level. These timelines are consistent with how federal statistical agencies publish county-level data.

Click here to interact with more county-level data.

Source Data: BLS QCEW 2024 · USDA SAIPE 2023 · IRS SOI 2021-2022 · U.S. Census Bureau 2024

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