placestats

Share Asian, not Hispanic and Gross domestic product

Where Share Asian, not Hispanic is higher, Gross domestic product tends to be higher. The link is weak: +0.34 across 1,973 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 38 states, the middle value of the link is +0.60.

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

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

Gross domestic product

Gross domestic product: the value of everything produced in the area, in dollars of that year (not adjusted for inflation).

BEA Regional Accounts · BEA CAGDP2 line 1

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 HispanicGross domestic product, per 1,000 residents
Highest
Honolulu County, HI42%82,257
Aleutians West Census Area, AK40.7%188,791
Santa Clara County, CA39.3%212,515
San Francisco County, CA34.7%309,451
Alameda County, CA32%106,347
Lowest
Yuma County, CO0%62,810
San Juan County, CO0%79,007
Lincoln County, CO0%94,582
Kiowa County, CO0%105,745
Jackson County, CO0%111,512

By gross domestic product

Share Asian, not HispanicGross domestic product, per 1,000 residents
Highest
Glasscock County, TX0%4.4m
McMullen County, TX0%3.2m
Martin County, TX0%2.8m
Borden County, TX0%1.3m
Irion County, TX0%789,455
Lowest
Glascock County, GA0%14,046
Elliott County, KY0%14,710
Nicholas County, KY0%15,817
Owsley County, KY0%16,330
Crawford County, GA0%16,887
States

By share Asian, not Hispanic

Share Asian, not HispanicGross domestic product, per 1,000 residents
Highest
Hawaii36.7%77,294
California15.1%97,521
New Jersey9.83%87,071
Washington9.31%103,535
New York8.83%109,826
Lowest
West Virginia0.747%56,869
Wyoming0.798%88,571
Montana0.809%67,588
Mississippi0.965%51,334
Maine1.1%68,059

By gross domestic product

Share Asian, not HispanicGross domestic product, per 1,000 residents
Highest
District of Columbia4.01%259,270
New York8.83%109,826
Massachusetts7.03%105,525
Washington9.31%103,535
Delaware4.08%102,727
Lowest
Mississippi0.965%51,334
West Virginia0.747%56,869
Arkansas1.53%58,731
Alabama1.41%61,244
Kentucky1.5%62,799
Metro areas

By share Asian, not Hispanic

Share Asian, not HispanicGross domestic product, per 1,000 residents
Highest
Urban Honolulu, HI42%83,443
San Jose-Sunnyvale-Santa Clara, CA38.1%209,413
Kapaa, HI29%71,948
San Francisco-Oakland-Fremont, CA27.4%166,505
Hilo-Kailua, HI20.9%55,049
Lowest
Raymondville, TX0%35,295
Mitchell, SD0%80,490
Las Vegas, NM0%34,828
Iron Mountain, MI-WI0%61,939
Hailey, ID0%89,638

By gross domestic product

Share Asian, not HispanicGross domestic product, per 1,000 residents
Highest
Borger, TX0.671%418,460
Big Spring, TX1.01%385,154
Midland, TX2.1%302,341
Port Lavaca, TX5.29%240,937
San Jose-Sunnyvale-Santa Clara, CA38.1%209,413
Lowest
Winchester, VA-WV1.98%3470.05
Charlottesville, VA4.93%11,224
Lynchburg, VA1.37%15,532
Blacksburg-Christiansburg-Radford, VA4.07%17,826
Picayune, MS0.393%25,165
Cities and towns — Gross domestic product is not published for cities and towns

By share Asian, not Hispanic

Share Asian, not HispanicGross domestic product, per 1,000 residents
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 — Gross domestic product is not published for ZIP codes

By share Asian, not Hispanic

Share Asian, not HispanicGross domestic product, per 1,000 residents
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 1,984 counties: the five with far more gross domestic product than their share Asian, not Hispanic would suggest, and the five with far less.

Share Asian, not HispanicGross domestic product, per 1,000 residents
Above the line
Glasscock County, TX0%4.4m
McMullen County, TX0%3.2m
Martin County, TX0%2.8m
Borden County, TX0%1.3m
Irion County, TX0%789,455
Below the line
Honolulu County, HI42%82,257
Queens County, NY25.9%58,830
Fort Bend County, TX21.6%53,591
Kauai County, HI29%72,183
Hawaii County, HI20.9%56,111

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+0.4801,973 counties reporting both
After adjusting for density, income and education+0.337the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.310size taken out as well as density
Also comparing only within each state+0.307each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.299the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 254 equally weighted counties
Middle value inside single states+0.598the link worked out inside each of 38 states with at least 20 counties reporting
Using ranks, after adjusting+0.363uses 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 = 2.0e-53. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.002. 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 1.2e-52.

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 +0.08 (p = 0.001). Once the adjustment is made, little map pattern is left.

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 gross domestic productmove 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 pandemic1,575+0.05+0.050.683
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years1,659+0.05+0.090.066

Over the main period, any link between the changes could easily be chance. 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 Gross domestic product