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Gini index of income inequality and Mean income of departing households

Where Gini index of income inequality is higher, Mean income of departing households tends to be higher. The link is weak: +0.35 across 3,097 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

Gini index of income inequality

How unequally household income is shared, on a scale from 0 to 1. Zero would mean every household has the same income. One would mean a single household has all of it. US counties run from about 0.32 to 0.60. It is measured on money income before taxes and government payments, so US figures sit above countries that measure it after taxes and payments.

Census ACS 5-year · ACS table B19083_001

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 gini index of income inequality

Gini index of income inequalityMean income of departing households
Highest
Union County, NM0.637$57,295
Guadalupe County, NM0.619$33,085
Sherman County, TX0.615$56,030
Stonewall County, TX0.615$39,214
Macon County, GA0.611$40,516
Lowest
Crockett County, TX0.289$58,800
Dallam County, TX0.328$51,700
Beaver County, UT0.344$46,493
Aleutians West Census Area, AK0.346$75,076
Kearny County, KS0.349$48,228

By mean income of departing households

Gini index of income inequalityMean income of departing households
Highest
San Francisco County, CA0.518$197,250
Pitkin County, CO0.602$190,290
San Mateo County, CA0.496$186,430
New York County, NY0.596$184,460
Santa Clara County, CA0.474$176,300
Lowest
Liberty County, MT0.5$16,132
Buffalo County, SD0.49$21,857
Comanche County, KS0.404$25,222
Glascock County, GA0.415$25,283
Hamilton County, KS0.386$26,690
States

By gini index of income inequality

Gini index of income inequalityMean income of departing households
Highest
New York0.515$106,890
District of Columbia0.514$117,230
Connecticut0.498$107,280
Louisiana0.494$62,595
California0.489$103,240
Lowest
Utah0.428$75,046
Alaska0.433$70,755
New Hampshire0.441$88,031
Wisconsin0.443$74,261
Idaho0.444$64,130

By mean income of departing households

Gini index of income inequalityMean income of departing households
Highest
District of Columbia0.514$117,230
Massachusetts0.488$116,360
Connecticut0.498$107,280
New Jersey0.48$107,090
New York0.515$106,890
Lowest
Mississippi0.484$53,459
Arkansas0.481$59,308
West Virginia0.47$60,437
Oklahoma0.468$60,452
Louisiana0.494$62,595
Metro areas — Gini index of income inequality is not published for metro areas

By mean income of departing households

Gini index of income inequalityMean income of departing households
Highest
San Jose-Sunnyvale-Santa Clara, CA—$175,160
San Francisco-Oakland-Fremont, CA—$156,960
Nantucket, MA—$156,720
Gardnerville Ranchos, NV-CA—$148,660
Bridgeport-Stamford-Danbury, CT—$133,340
Lowest
Middlesborough, KY—$34,039
Forrest City, AR—$35,708
Moultrie, GA—$36,372
Kennett, MO—$36,678
Clarksdale, MS—$37,933
Cities and towns — Mean income of departing households is not published for cities and towns

By gini index of income inequality

Gini index of income inequalityMean income of departing households
Highest
Darlington city, SC0.692—
Hazard city, KY0.683—
Milledgeville city, GA0.676—
Arroyo zona urbana, PR0.668—
Dyersburg city, TN0.666—
Lowest
Margaret town, AL0.249—
Bangor Base CDP, WA0.259—
Harrisburg city, SD0.266—
Brookshire city, TX0.266—
Moorefield CDP, VA0.266—
ZIP codes — Mean income of departing households is not published for ZIP codes

By gini index of income inequality

Gini index of income inequalityMean income of departing households
Highest
ZIP 00913 (San Juan zona urbana, PR)0.834—
ZIP 08609 (Trenton city, NJ)0.683—
ZIP 00901 (San Juan zona urbana, PR)0.67—
ZIP 39095 (Holmes County, MS)0.67—
ZIP 92590 (Riverside County, CA)0.664—
Lowest
ZIP 98315 (Bangor Base CDP, WA)0.259—
ZIP 23801 (Fort Lee CDP, VA)0.271—
ZIP 34753 (Mascotte city, FL)0.272—
ZIP 99703 (Fairbanks city, AK)0.275—
ZIP 85613 (Sierra Vista city, AZ)0.28—

Counties furthest from the pattern

Compared with the straight line that best fits all 3,111 counties: the five with far more mean income of departing households than their gini index of income inequality would suggest, and the five with far less.

Gini index of income inequalityMean income of departing households
Above the line
San Francisco County, CA0.518$197,250
Pitkin County, CO0.602$190,290
San Mateo County, CA0.496$186,430
New York County, NY0.596$184,460
Santa Clara County, CA0.474$176,300
Below the line
Liberty County, MT0.5$16,132
Buffalo County, SD0.49$21,857
Holmes County, MS0.609$30,005
Glascock County, GA0.415$25,283
Comanche County, KS0.404$25,222

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+0.0593,097 counties reporting both
After adjusting for density, income and education+0.353the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.347size taken out as well as density
Also comparing only within each state+0.298each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.680the 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+0.222uses 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 = 1.0e-91. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 5.7e-10. 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 7.9e-91.

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 gini index of income inequality 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 years3,088-0.01-0.020.421

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 Gini index of income inequality and Mean income of departing households