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Gini index of income inequality and Mean adjusted gross income per return

Where Gini index of income inequality is higher, Mean adjusted gross income per return tends to be higher. The link is weak: +0.33 across 3,102 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 -0.01.

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 adjusted gross income per return

Average adjusted gross income (income after a few deductions, as reported to the IRS) per tax return. Business and farm losses are subtracted. It counts only people who file, and people who earn too little to have to file are missing, which makes the poorest places look better off.

IRS Statistics of Income · IRS SOI A00100 / N1

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 adjusted gross income per return
Highest
Harding County, NM0.71$65,610
Loving County, TX0.658$128,820
Guadalupe County, NM0.619$42,528
Sherman County, TX0.615$68,821
Stonewall County, TX0.615$65,193
Lowest
Crockett County, TX0.289$68,469
Clark County, ID0.324$49,945
Dallam County, TX0.328$69,631
Yakutat City and Borough, AK0.333$62,539
Beaver County, UT0.344$63,088

By mean adjusted gross income per return

Gini index of income inequalityMean adjusted gross income per return
Highest
Teton County, WY0.522$509,150
Pitkin County, CO0.602$280,730
Summit County, UT0.503$265,720
New York County, NY0.596$257,310
Blaine County, ID0.48$252,880
Lowest
Kusilvak Census Area, AK0.44$27,083
Holmes County, MS0.609$37,015
Zapata County, TX0.519$38,812
Quitman County, MS0.481$39,003
Starr County, TX0.529$39,523
States

By gini index of income inequality

Gini index of income inequalityMean adjusted gross income per return
Highest
New York0.515$107,450
District of Columbia0.514$143,630
Connecticut0.498$121,890
Louisiana0.494$73,396
California0.489$110,970
Lowest
Utah0.428$94,519
Alaska0.433$89,809
New Hampshire0.441$108,150
Wisconsin0.443$86,606
Idaho0.444$85,905

By mean adjusted gross income per return

Gini index of income inequalityMean adjusted gross income per return
Highest
District of Columbia0.514$143,630
Connecticut0.498$121,890
Massachusetts0.488$121,200
Washington0.466$114,940
New Jersey0.48$112,230
Lowest
Mississippi0.484$65,732
West Virginia0.47$68,201
New Mexico0.477$69,650
Louisiana0.494$73,396
Kentucky0.478$73,748
Metro areas — Gini index of income inequality is not published for metro areas

By mean adjusted gross income per return

Gini index of income inequalityMean adjusted gross income per return
Highest
Jackson, WY-ID—$387,550
Naples-Marco Island, FL—$224,460
Hailey, ID—$220,660
Heber, UT—$220,380
San Jose-Sunnyvale-Santa Clara, CA—$211,950
Lowest
Zapata, TX—$38,812
Rio Grande City-Roma, TX—$39,523
Deming, NM—$41,040
Raymondville, TX—$43,300
Gallup, NM—$44,629
Cities and towns — Mean adjusted gross income per return is not published for cities and towns

By gini index of income inequality

Gini index of income inequalityMean adjusted gross income per return
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 adjusted gross income per return is not published for ZIP codes

By gini index of income inequality

Gini index of income inequalityMean adjusted gross income per return
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 3,124 counties: the five with far more mean adjusted gross income per return than their gini index of income inequality would suggest, and the five with far less.

Gini index of income inequalityMean adjusted gross income per return
Above the line
Teton County, WY0.522$509,150
Pitkin County, CO0.602$280,730
Summit County, UT0.503$265,720
New York County, NY0.596$257,310
Blaine County, ID0.48$252,880
Below the line
Kusilvak Census Area, AK0.44$27,083
Holmes County, MS0.609$37,015
Zapata County, TX0.519$38,812
Starr County, TX0.529$39,523
Quitman County, MS0.481$39,003

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+0.0243,102 counties reporting both
After adjusting for density, income and education+0.327the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.327size taken out as well as density
Also comparing only within each state+0.321each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.620the 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-0.012the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.235uses 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 = 5.9e-78. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 4.8e-9. 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 4.1e-77.

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 +0.15 (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 adjusted gross income per returnmove 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 pandemic2,991+0.09+0.070.016
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,003+0.07+0.070.008

In counties where one changed more, the other tended to move the same way, compared with other counties in the same state (r = +0.07). The same holds in the second period. 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 adjusted gross income per return