placestats

Share Asian, not Hispanic and Mean income of departing households

Across 2,001 counties, Share Asian, not Hispanic and Mean income of departing households have a link of +0.52, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and a very weak link of +0.16 remains. Most of the first figure came from both measures following how urban, rich and educated a place is, not from a link with each other.

Mostly gone 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

Share Asian, not Hispanic

The percentage of residents who are Asian alone and not Hispanic.

Census ACS 5-year · ACS table B03002_006, divided by total population

Mean income of departing households

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

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 share Asian, not Hispanic

Share Asian, not HispanicMean income of departing households
Highest
Honolulu County, HI42%$70,570
Aleutians West Census Area, AK40.7%$75,076
Santa Clara County, CA39.3%$176,300
San Francisco County, CA34.7%$197,250
Alameda County, CA32%$130,900
Lowest
Yuma County, CO0%$50,861
Lincoln County, CO0%$46,977
Kiowa County, CO0%$30,160
Jackson County, CO0%$58,667
Dolores County, CO0%$49,344

By mean income of departing households

Share Asian, not HispanicMean income of departing households
Highest
San Francisco County, CA34.7%$197,250
San Mateo County, CA30.5%$186,430
New York County, NY12.3%$184,460
Santa Clara County, CA39.3%$176,300
Marin County, CA6.09%$166,660
Lowest
Liberty County, MT0%$16,132
Buffalo County, SD0%$21,857
Comanche County, KS0%$25,222
Glascock County, GA0%$25,283
Hamilton County, KS0%$26,690
States

By share Asian, not Hispanic

Share Asian, not HispanicMean income of departing households
Highest
Hawaii36.7%$70,932
California15.1%$103,240
New Jersey9.83%$107,090
Washington9.31%$101,370
New York8.83%$106,890
Lowest
West Virginia0.747%$60,437
Wyoming0.798%$69,134
Montana0.809%$64,963
Mississippi0.965%$53,459
Maine1.1%$73,852

By mean income of departing households

Share Asian, not HispanicMean income of departing households
Highest
District of Columbia4.01%$117,230
Massachusetts7.03%$116,360
Connecticut4.71%$107,280
New Jersey9.83%$107,090
New York8.83%$106,890
Lowest
Mississippi0.965%$53,459
Arkansas1.53%$59,308
West Virginia0.747%$60,437
Oklahoma2.31%$60,452
Louisiana1.71%$62,595
Metro areas

By share Asian, not Hispanic

Share Asian, not HispanicMean income of departing households
Highest
Urban Honolulu, HI42%$70,570
San Jose-Sunnyvale-Santa Clara, CA38.1%$175,160
Kapaa, HI29%$75,335
San Francisco-Oakland-Fremont, CA27.4%$156,960
Hilo-Kailua, HI20.9%$62,523
Lowest
Raymondville, TX0%$41,400
Mitchell, SD0%$56,196
Las Vegas, NM0%$47,795
Iron Mountain, MI-WI0%$51,429
Hailey, ID0%$107,940

By mean income of departing households

Share Asian, not HispanicMean income of departing households
Highest
San Jose-Sunnyvale-Santa Clara, CA38.1%$175,160
San Francisco-Oakland-Fremont, CA27.4%$156,960
Nantucket, MA1.78%$156,720
Gardnerville Ranchos, NV-CA2.64%$148,660
Bridgeport-Stamford-Danbury, CT5.28%$133,340
Lowest
Moultrie, GA0.841%$36,372
Cleveland, MS0.952%$38,442
Logansport, IN1.54%$39,639
Eufaula, AL-GA0.507%$39,775
McComb, MS0.558%$39,897
Cities and towns — Mean income of departing households is not published for cities and towns

By share Asian, not Hispanic

Share Asian, not HispanicMean income of departing households
Highest
Cupertino city, CA71.7%—
Milpitas city, CA71.5%—
South San Gabriel CDP, CA69.5%—
San Marino city, CA68.9%—
Waipahu CDP, HI67.1%—
Lowest
Terryville CDP, CT0%—
Woodland Park city, CO0%—
Lochbuie town, CO0%—
Eagle town, CO0%—
Mecca CDP, CA0%—
ZIP codes — Mean income of departing households is not published for ZIP codes

By share Asian, not Hispanic

Share Asian, not HispanicMean income of departing households
Highest
ZIP 94539 (Fremont city, CA)78.4%—
ZIP 11355 (New York city, NY)74.5%—
ZIP 94555 (Fremont city, CA)73.2%—
ZIP 95035 (Milpitas city, CA)71.3%—
ZIP 95014 (Santa Clara County, CA)71.3%—
Lowest
ZIP 08734 (Ocean County, NJ)0%—
ZIP 08533 (Ocean County, NJ)0%—
ZIP 08059 (Mount Ephraim borough, NJ)0%—
ZIP 07524 (Paterson city, NJ)0%—
ZIP 06331 (Windham County, CT)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,009 counties: the five with far more mean income of departing households than their share Asian, not Hispanic would suggest, and the five with far less.

Share Asian, not HispanicMean income of departing households
Above the line
Irion County, TX0%$155,190
Nantucket County, MA1.78%$156,720
New York County, NY12.3%$184,460
Marin County, CA6.09%$166,660
Douglas County, NV2.64%$151,080
Below the line
Honolulu County, HI42%$70,570
Aleutians West Census Area, AK40.7%$75,076
Kauai County, HI29%$75,335
Maui County, HI27.8%$77,405
Hawaii County, HI20.9%$62,523

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+0.5172,001 counties reporting both
After adjusting for density, income and education+0.156the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.138size taken out as well as density
Also comparing only within each state+0.112each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.219the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 259 equally weighted counties
Middle value inside single states+0.570the link worked out inside each of 38 states with at least 20 counties reporting
Using ranks, after adjusting+0.115uses 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 = 2.2e-12. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.047. 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 5.4e-12.

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 +0.22 (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 share asian, not hispanic rose most, did mean income of departing 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 years1,674+0.04+0.030.274

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 Share Asian, not Hispanic and Mean income of departing households