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Mean adjusted gross income per return and Poverty rate (model-based)

Across 3,102 counties, Mean adjusted gross income per return and Poverty rate (model-based) have a link of -0.57, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and what is left could easily be chance. 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

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

Poverty rate (model-based)

The percentage of people in poverty, as an estimate from a statistical model, not a direct count. The Census Bureau combines survey answers with tax and food-assistance records, to get figures that small counties' survey answers cannot give on their own.

Census SAIPE · Census SAIPE SAEPOVRTALL_PT

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 mean adjusted gross income per return

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
Teton County, WY$509,1506.2%
Pitkin County, CO$280,7306.4%
Summit County, UT$265,7205.1%
New York County, NY$257,31016.5%
Blaine County, ID$252,8806.9%
Lowest
Kusilvak Census Area, AK$27,08330.8%
Holmes County, MS$37,01535.6%
Zapata County, TX$38,81230.4%
Quitman County, MS$39,00332.1%
Starr County, TX$39,52328.8%

By poverty rate (model-based)

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
Issaquena County, MS$46,64749.6%
Martin County, KY$53,34648.1%
East Carroll Parish, LA$44,00446.5%
Ziebach County, SD$51,38246.2%
Bolivar County, MS$56,68438.7%
Lowest
Lincoln County, SD$127,8303.3%
Douglas County, CO$148,6203.7%
Los Alamos County, NM$138,5903.8%
Loudoun County, VA$156,2704.1%
Morgan County, UT$145,7404.3%
States

By mean adjusted gross income per return

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
District of Columbia$143,63015.2%
Connecticut$121,89010.2%
Massachusetts$121,20010.5%
Washington$114,94010.3%
New Jersey$112,2309.7%
Lowest
Mississippi$65,73218.3%
West Virginia$68,20116.4%
New Mexico$69,65016.9%
Louisiana$73,39618.9%
Kentucky$73,74816.1%

By poverty rate (model-based)

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
Louisiana$73,39618.9%
Mississippi$65,73218.3%
New Mexico$69,65016.9%
West Virginia$68,20116.4%
Kentucky$73,74816.1%
Lowest
New Hampshire$108,1507.3%
Utah$94,5199%
Minnesota$94,4709.2%
Colorado$101,5209.4%
New Jersey$112,2309.7%
Metro areas

By mean adjusted gross income per return

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
Jackson, WY-ID$387,5506.34%
Naples-Marco Island, FL$224,46010.5%
Hailey, ID$220,6607.84%
Heber, UT$220,3805.05%
San Jose-Sunnyvale-Santa Clara, CA$211,9507.65%
Lowest
Zapata, TX$38,81230.4%
Rio Grande City-Roma, TX$39,52328.8%
Deming, NM$41,04026.4%
Raymondville, TX$43,30027.8%
Gallup, NM$44,62934.3%

By poverty rate (model-based)

Mean adjusted gross income per returnPoverty rate (model-based)
Highest
Cleveland, MS$56,68438.7%
Greenville, MS$50,17635.5%
Forrest City, AR$48,48434.3%
Gallup, NM$44,62934.3%
Selma, AL$50,29631.4%
Lowest
Los Alamos, NM$138,5903.8%
Heber, UT$220,3805.05%
Appleton, WI$88,2295.93%
Jackson, WY-ID$387,5506.34%
Nantucket, MA$154,0806.5%

Counties furthest from the pattern

Compared with the straight line that best fits all 3,124 counties: the five with far more poverty rate (model-based) than their mean adjusted gross income per return would suggest, and the five with far less.

Mean adjusted gross income per returnPoverty rate (model-based)
Above the line
Teton County, WY$509,1506.2%
Issaquena County, MS$46,64749.6%
Martin County, KY$53,34648.1%
Ziebach County, SD$51,38246.2%
East Carroll Parish, LA$44,00446.5%
Below the line
Manassas Park city, VA$62,3047.7%
Daggett County, UT$65,7617.6%
Calumet County, WI$89,5724.6%
King County, TX$52,0009.7%
Franklin County, ID$71,3737.1%

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-0.5693,102 counties reporting both
After adjusting for density, income and education-0.002the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.003size taken out as well as density
Also comparing only within each state-0.021each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.158the 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-0.644the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting-0.228uses 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 = 0.910. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.960. 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 0.920.

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 +0.44 (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 mean adjusted gross income per return rose most, did poverty rate (model-based)move 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 pandemic3,003-0.28-0.169.3e-12
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,015-0.14-0.090.002

In counties where one changed more, the other tended to move the opposite way, compared with other counties in the same state (r = -0.16). 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 Mean adjusted gross income per return and Poverty rate (model-based)