placestats

Vacancy rate and Mean income of arriving households

Where Vacancy rate is higher, Mean income of arriving households tends to be higher. The link is moderate: +0.41 across 3,063 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 40 states, the middle value of the link is -0.04.

Holds after adjusting

Every place, plotted

One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.

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What each measure is

Vacancy rate

The percentage of all homes and apartments that nobody lives in. The middle county is 15%, which surprises people. It counts vacation and seasonal homes, so the top of the list is resort and outdoor-recreation areas, such as Daggett County, Utah at 77%, not abandoned towns. A high number can tell two very different stories, and this measure cannot tell them apart.

Census ACS 5-year · ACS table B25002_003, divided by housing units

Mean income of arriving households

The average income on the tax returns of people who moved in.

IRS county migration flows · IRS SOI migration, county aggregates

Highest and lowest

Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.

Counties

By vacancy rate

Vacancy rateMean income of arriving households
Highest
Daggett County, UT77.3%$65,733
Rich County, UT74.6%$85,104
Hamilton County, NY73.3%$89,929
Forest County, PA72.1%$47,503
Alpine County, CA70.2%$96,591
Lowest
Somerset County, NJ2.54%$114,070
Scott County, MN2.6%$80,971
Kendall County, IL2.73%$73,199
Dakota County, MN2.73%$75,745
Loudoun County, VA2.75%$118,600

By mean income of arriving households

Vacancy rateMean income of arriving households
Highest
Collier County, FL31.5%$283,470
Summit County, UT44.8%$267,830
Marin County, CA7.74%$234,840
Greene County, GA25.3%$215,010
Wasatch County, UT22.4%$188,850
Lowest
Sioux County, ND16.4%$21,793
Taliaferro County, GA34.6%$25,212
Madison Parish, LA31.2%$26,014
Sharkey County, MS16.3%$26,580
Quitman County, MS12.9%$27,679
States

By vacancy rate

Vacancy rateMean income of arriving households
Highest
Maine21.1%$85,089
Vermont20.1%$81,842
Alaska18.2%$63,208
West Virginia16.1%$58,478
Florida15.2%$121,230
Lowest
Washington7.42%$90,288
Oregon7.46%$74,875
Connecticut7.54%$110,950
California7.55%$95,714
New Jersey7.88%$102,350

By mean income of arriving households

Vacancy rateMean income of arriving households
Highest
Florida15.2%$121,230
Connecticut7.54%$110,950
New Hampshire14.4%$108,990
New Jersey7.88%$102,350
California7.55%$95,714
Lowest
North Dakota13.3%$54,547
Mississippi15.1%$56,877
Louisiana14.8%$58,224
West Virginia16.1%$58,478
Oklahoma12.5%$58,984
Metro areas

By vacancy rate

Vacancy rateMean income of arriving households
Highest
Nantucket, MA59.5%$132,250
Vineyard Haven, MA58.4%$167,880
Ocean Pines, MD57.9%$88,802
Breckenridge, CO57.3%$124,140
Kill Devil Hills, NC52.7%$92,935
Lowest
Lancaster, PA3.36%$68,101
Appleton, WI3.77%$62,389
Provo-Orem-Lehi, UT3.82%$69,204
Andrews, TX4.01%$60,569
Greeley, CO4.01%$73,503

By mean income of arriving households

Vacancy rateMean income of arriving households
Highest
Naples-Marco Island, FL31.5%$283,470
Heber, UT36.5%$246,880
Key West-Key Largo, FL36.4%$170,380
Jackson, WY-ID29.2%$169,430
Vineyard Haven, MA58.4%$167,880
Lowest
Greenville, MS17.6%$31,187
Deming, NM21.5%$33,527
Forrest City, AR17.8%$33,747
Kennett, MO17%$34,168
Greenwood, MS19.4%$34,844
Cities and towns — Mean income of arriving households is not published for cities and towns

By vacancy rate

Vacancy rateMean income of arriving households
Highest
Clemson University CDP, SC100%—
Ocean City town, MD87%—
Big Bear Lake city, CA76.7%—
Orange Beach city, AL73.9%—
Ocean City city, NJ73.1%—
Lowest
Severance town, CO0%—
Mead town, CO0%—
South Monrovia Island CDP, CA0%—
Salida CDP, CA0%—
Dos Palos city, CA0%—
ZIP codes — Mean income of arriving households is not published for ZIP codes

By vacancy rate

Vacancy rateMean income of arriving households
Highest
ZIP 29634 (Clemson University CDP, SC)100%—
ZIP 79406 (Lubbock city, TX)100%—
ZIP 43210 (Columbus city, OH)84.6%—
ZIP 21842 (Ocean City town, MD)82.3%—
ZIP 08008 (Ocean County, NJ)80.1%—
Lowest
ZIP 08886 (Warren County, NJ)0%—
ZIP 08823 (Pleasant Plains CDP, NJ)0%—
ZIP 08502 (Somerset County, NJ)0%—
ZIP 07738 (Lincroft CDP, NJ)0%—
ZIP 07630 (Emerson borough, NJ)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 3,079 counties: the five with far more mean income of arriving households than their vacancy rate would suggest, and the five with far less.

Vacancy rateMean income of arriving households
Above the line
Collier County, FL31.5%$283,470
Summit County, UT44.8%$267,830
Marin County, CA7.74%$234,840
Greene County, GA25.3%$215,010
Wasatch County, UT22.4%$188,850
Below the line
Sioux County, ND16.4%$21,793
Taliaferro County, GA34.6%$25,212
Madison Parish, LA31.2%$26,014
Sharkey County, MS16.3%$26,580
Lee County, AR28.8%$27,986

Two series, one county

Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.

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Every version of the link

Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.

Before adjusting for anything+0.0543,063 counties reporting both
After adjusting for density, income and education+0.411the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.427size taken out as well as density
Also comparing only within each state+0.379each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.456the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 287 equally weighted counties
Middle value inside single states-0.044the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.346uses each county’s rank, not its value, so a few extreme counties cannot create the link

How much to believe it

Could it be chance?

The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 6.3e-125. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 4.5e-12. The site tested 20,910 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 5.7e-124.

Do nearby places look alike?

Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.25 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.

Did they change together?

The figures above compare counties at one moment. This asks a different question: where vacancy rate rose most, did mean income of arriving householdsmove too? Each county’s change is compared with the average change in its own state. That takes out ups and downs that hit a whole region at once. Each change is the gap between two estimates that both contain some error. That error pulls these links towards zero, so a weak one is weak partly for that reason. The q column shows whether a link could be a fluke, allowing for the many pairs tested: 0.05 or less means it is unlikely to be chance.

PeriodCountiesChange togetherWithin statesq
2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic————
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,060-0.05-0.060.027

Not measurable over the main period, so only the second period is shown. How change is measured.

Related pairs

Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Vacancy rate and Mean income of arriving households