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Adult income rank of children raised poor here and Area in drought

Where Adult income rank of children raised poor here is higher, Area in drought tends to be higher. The link is weak: +0.32 across 3,119 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

Adult income rank of children raised poor here

Where children who grew up here with poor parents ended up as adults, ranked against everyone in the country by income, on a scale from 0 to 1. A value of 0.5 would mean that on average they reached the middle of the national income ladder.

Opportunity Atlas · Opportunity Insights kfr_pooled_pooled_p25

Area in drought

The share of the area in moderate drought or worse, averaged over the year's weekly Drought Monitor maps. A county half in drought all year and a county fully in drought for half the year both score 50%. Experts draw the maps each week from rain, soil, stream and crop data, so they are a judgment, not a direct measurement.

US Drought Monitor · USDM data services GetDroughtSeverityStatisticsByAreaPercent, statisticsType=1, D1

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 adult income rank of children raised poor here

Adult income rank of children raised poor hereArea in drought
Highest
Harding County, SD0.6889.27
Bowman County, ND0.67538.1
Grant County, ND0.6678.69
Billings County, ND0.66639.9
Golden Valley County, ND0.66240.4
Lowest
Kusilvak Census Area, AK0.2160
Hoonah-Angoon Census Area, AK0.2370
Northwest Arctic Borough, AK0.2420
Bethel Census Area, AK0.2450
Oglala Lakota County, SD0.24835.8

By area in drought

Adult income rank of children raised poor hereArea in drought
Highest
Crawford County, IA0.516100
Monona County, IA0.466100
Barton County, KS0.464100
Ellis County, KS0.528100
Graham County, KS0.503100
Lowest
Northwest Hills Planning Region, CT0.4380
Summit County, CO0.5180
Pitkin County, CO0.4580
Lake County, CO0.4060
Grand County, CO0.5070
States — Adult income rank of children raised poor here is not published for states

By area in drought

Adult income rank of children raised poor hereArea in drought
Highest
Kansas—74.2
Nebraska—68.8
Iowa—65.2
New Mexico—57.5
Texas—55.7
Lowest
New Hampshire—0
Alaska—0.0508
Massachusetts—0.0746
Maine—0.302
Rhode Island—0.884
Metro areas

By adult income rank of children raised poor here

Adult income rank of children raised poor hereArea in drought
Highest
Dickinson, ND0.62530.6
Carroll, IA0.5996.5
Williston, ND0.58631.4
Le Mars, IA0.55179.5
Heber, UT0.54325.1
Lowest
Laurinburg, NC0.31115.9
Greenville, MS0.31926.7
Lumberton, NC0.32114.8
Henderson, NC0.3249.94
Clarksdale, MS0.32532.4

By area in drought

Adult income rank of children raised poor hereArea in drought
Highest
Columbus, NE0.508100
Fredericksburg, TX0.464100
Fremont, NE0.482100
Great Bend, KS0.464100
Hays, KS0.528100
Lowest
Worcester, MA0.4410
Watertown-Fort Drum, NY0.4150
Utica-Rome, NY0.4290
Trenton-Princeton, NJ0.3860
Torrington, CT0.4380

Counties furthest from the pattern

Compared with the straight line that best fits all 3,138 counties: the five with far more area in drought than their adult income rank of children raised poor here would suggest, and the five with far less.

Adult income rank of children raised poor hereArea in drought
Above the line
Douglas County, NE0.399100
Bexar County, TX0.39899.4
Jefferson County, OR0.39198.3
Burnet County, TX0.409100
Bandera County, TX0.411100
Below the line
Oliver County, ND0.6370
Harding County, SD0.6889.27
Grant County, ND0.6678.69
Edmunds County, SD0.6315.81
Crook County, WY0.6052.39

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+0.4053,119 counties reporting both
After adjusting for density, income and education+0.320the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.321size taken out as well as density
Also comparing only within each state+0.060each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.089the 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+0.036the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.267uses 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 = 2.9e-75. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.000. The site tested 24,090 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 2.1e-74.

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 +0.80 (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?

Not measurable: at least one of these is published for too few of the years a change needs (2014–2019 or 2019–2023), or for too few counties in both.

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 Adult income rank of children raised poor here and Area in drought