placestats

Share foreign-born and Labour force

Where Share foreign-born is higher, Labour force tends to be higher. The link is weak: +0.38 across 2,447 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 39 states, the middle value of the link is +0.54.

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 foreign-born

The percentage of residents born outside the United States, whether or not they are citizens. The middle county is 2.7%, and the numbers are very uneven: Miami-Dade is 54% and Queens 48%, while half of all counties are under 3%. The count alone mostly ranks counties by size, which is why this percentage is shown next to it.

Census ACS 5-year · ACS table B05002_013, divided by total population

Labour force

Everyone who is working or actively looking for work. People who have stopped looking are not included. So a falling unemployment rate can mean either more jobs or fewer people looking.

BLS LAUS · BLS LAUS county annual averages

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 foreign-born

Share foreign-bornLabour force, per 1,000 residents
Highest
Miami-Dade County, FL54.3%530.07
Queens County, NY47.6%505.30
Aleutians West Census Area, AK44.1%671.11
Hudson County, NJ42.6%590.98
Santa Clara County, CA41%537.70
Lowest
Comerío Municipio, PR0%318.51
Niobrara County, WY0%378.88
Roberts County, TX0%472.61
Cottle County, TX0%889.40
Mellette County, SD0%354.38

By labour force

Share foreign-bornLabour force, per 1,000 residents
Highest
Cottle County, TX0%889.40
Upton County, TX7.62%847.85
Yakutat City and Borough, AK18.2%739.13
Garfield County, MT0%728.14
Aleutians East Borough, AK32.4%712.53
Lowest
Chattahoochee County, GA5.17%133.86
McDowell County, WV1.83%196.22
Greene County, MS0.89%215.01
Forest County, PA1.92%228.15
Lake County, TN2.29%232.55
States

By share foreign-born

Share foreign-bornLabour force, per 1,000 residents
Highest
California26.7%497.29
New Jersey23.5%526.52
New York22.6%495.66
Florida21.4%502.62
Nevada19%512.07
Lowest
West Virginia1.71%442.04
Montana2.29%517.85
Mississippi2.39%423.83
Puerto Rico2.72%369.17
Wyoming3.51%506.36

By labour force

Share foreign-bornLabour force, per 1,000 residents
Highest
District of Columbia13.3%602.83
Colorado9.58%555.88
New Hampshire6.2%549.19
Massachusetts17.7%546.89
Minnesota8.56%543.87
Lowest
Puerto Rico2.72%369.17
Mississippi2.39%423.83
West Virginia1.71%442.04
Louisiana4.73%450.25
Kentucky4.43%456.09
Metro areas

By share foreign-born

Share foreign-bornLabour force, per 1,000 residents
Highest
Miami-Fort Lauderdale-West Palm Beach, FL41.9%529.40
San Jose-Sunnyvale-Santa Clara, CA40.3%543.49
Nogales, AZ34.1%422.76
Los Angeles-Long Beach-Anaheim, CA32.5%521.67
San Francisco-Oakland-Fremont, CA31.6%551.50
Lowest
Wapakoneta, OH0.517%520.67
Coshocton, OH0.548%416.26
Pikeville, KY0.62%341.31
Lewistown, PA0.697%505.71
Escanaba, MI0.711%445.50

By labour force

Share foreign-bornLabour force, per 1,000 residents
Highest
Guymon, OK23.9%687.55
Jackson, WY-ID11.3%679.02
Los Alamos, NM11.1%676.66
Breckenridge, CO9.47%652.13
Edwards, CO16%631.07
Lowest
Wildwood-The Villages, FL5.85%220.33
Susanville, CA6.03%279.48
Cañon City, CO2.2%304.52
Zapata, TX22.9%321.13
Homosassa Springs, FL5.65%321.14
Cities and towns — Labour force is not published for cities and towns

By share foreign-born

Share foreign-bornLabour force, per 1,000 residents
Highest
Sweetwater city, FL75%—
Hialeah city, FL74.7%—
Fountainebleau CDP, FL73.7%—
Hialeah Gardens city, FL71.3%—
Doral city, FL70.7%—
Lowest
Kayenta CDP, AZ0%—
Odenville city, AL0%—
Monroeville city, AL0%—
Margaret town, AL0%—
Nitro city, WV0%—
ZIP codes — Labour force is not published for ZIP codes

By share foreign-born

Share foreign-bornLabour force, per 1,000 residents
Highest
ZIP 33010 (Hialeah city, FL)78.5%—
ZIP 33012 (Hialeah city, FL)75.8%—
ZIP 33126 (Miami city, FL)75.6%—
ZIP 33135 (Miami city, FL)74.3%—
ZIP 33013 (Hialeah city, FL)74.1%—
Lowest
ZIP 00782 (Comerío Municipio, PR)0%—
ZIP 00780 (Ponce Municipio, PR)0%—
ZIP 72416 (Craighead County, AR)0%—
ZIP 71328 (Rapides Parish, LA)0%—
ZIP 71225 (Ouachita Parish, LA)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,453 counties: the five with far more labour force than their share foreign-born would suggest, and the five with far less.

Share foreign-bornLabour force, per 1,000 residents
Above the line
Cottle County, TX0%889.40
Upton County, TX7.62%847.85
Garfield County, MT0%728.14
Yakutat City and Borough, AK18.2%739.13
Grand County, UT7.29%704.65
Below the line
Chattahoochee County, GA5.17%133.86
McDowell County, WV1.83%196.22
Greene County, MS0.89%215.01
Forest County, PA1.92%228.15
Lake County, TN2.29%232.55

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+0.4942,447 counties reporting both
After adjusting for density, income and education+0.384the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.332size taken out as well as density
Also comparing only within each state+0.296each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.446the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 279 equally weighted counties
Middle value inside single states+0.535the link worked out inside each of 39 states with at least 20 counties reporting
Using ranks, after adjusting+0.181uses 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 = 7.3e-87. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 3.2e-6. 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 5.5e-86.

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 +0.16 (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 foreign-born rose most, did labour forcemove 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 pandemic2,362-0.01-0.010.866
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years2,320+0.10+0.140.001

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 foreign-born and Labour force