placestats

Returns claiming the earned income credit and Black Protestant adherents

A county is not a congregation. Counties where more people are counted as adherents (members of a religious group) also tend to differ on the other measure, and that is all. It does not follow that the adherents are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is as easy to fall into here as with the voting pairs. Two things about the counting matter too. Adherents are counted where their congregation meets, not where they live, so thirty very small counties exceed 100%. And a denomination that did not report is missing, not zero. That undercounts membership most where churches are least formally organised.

Where Returns claiming the earned income credit is higher, Black Protestant adherents tends to be higher. The link is moderate: +0.41 across 3,121 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 +0.21.

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.

Loading every place…

What each measure is

Returns claiming the earned income credit

The percentage of tax returns claiming the earned income tax credit, which goes to working households with low incomes. It is a count from tax records of the working poor, not a survey estimate.

IRS Statistics of Income · IRS SOI N59660 / N1

Black Protestant adherents

Members of the historically Black Protestant churches, as a share of the population. Their central records are thinner than most, so this is the least complete of the six groups. Which of these churches reported also differs between the 2010 and 2020 studies, so part of any change between them is who reported, not real membership.

· Religion Census BPRTRATE (2010, 2020)

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 returns claiming the earned income credit

By black Protestant adherents

Returns claiming the earned income creditBlack Protestant adherents
Highest
Nevada County, AR27.8%34.6
Adams County, MS31.4%34
Northampton County, NC26.5%29.6
Macon County, AL29.7%29.2
Lowndes County, MS27.9%28.8
Lowest
Yuma County, CO14.3%0
Washington County, CO14.4%0
Teller County, CO9.54%0
Summit County, CO6.08%0
Sedgwick County, CO17.3%0
States

By returns claiming the earned income credit

Returns claiming the earned income creditBlack Protestant adherents
Highest
Mississippi26.7%8.7
Louisiana24%5.45
Georgia20.6%5.15
Arkansas20.5%6.31
Alabama20.3%7.65
Lowest
New Hampshire7.91%0.02
Massachusetts9.56%0.28
Washington9.82%0.39
Minnesota9.98%0.35
Vermont10.1%0

By black Protestant adherents

Returns claiming the earned income creditBlack Protestant adherents
Highest
District of Columbia12.6%10.4
Mississippi26.7%8.7
Alabama20.3%7.65
Arkansas20.5%6.31
Tennessee17%5.74
Lowest
Vermont10.1%0
New Hampshire7.91%0.02
North Dakota10.5%0.05
Montana11.7%0.06
Idaho12.6%0.07
Metro areas

By returns claiming the earned income credit

Returns claiming the earned income creditBlack Protestant adherents
Highest
Zapata, TX45.4%0
Rio Grande City-Roma, TX44.4%0
Clarksdale, MS42%18.2
Greenville, MS41.2%22.1
Greenwood, MS38.7%16.4
Lowest
Los Alamos, NM3.7%0
Jackson, WY-ID6.19%0.858
Heber, UT6.24%0
Edwards, CO6.39%0
Nantucket, MA6.55%0

By black Protestant adherents

Returns claiming the earned income creditBlack Protestant adherents
Highest
Columbus, MS29.8%26
Magnolia, AR25.3%25.7
Camden, AR23.6%25.5
El Dorado, AR24.9%22.5
Greenville, MS41.2%22.1
Lowest
Zapata, TX45.4%0
Yankton, SD11.5%0
Worthington, MN13.9%0
Wooster, OH10.7%0
Woodward, OK19.3%0

Counties furthest from the pattern

Compared with the straight line that best fits all 3,143 counties: the five with far more black Protestant adherents than their returns claiming the earned income credit would suggest, and the five with far less.

Returns claiming the earned income creditBlack Protestant adherents
Above the line
Nevada County, AR27.8%34.6
Adams County, MS31.4%34
Northampton County, NC26.5%29.6
Stonewall County, TX8.33%24.1
Lowndes County, MS27.9%28.8
Below the line
Kusilvak Census Area, AK48.7%0
Oglala Lakota County, SD45.5%0
Zapata County, TX45.4%0
Starr County, TX44.4%0
Buffalo County, SD43.1%0

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.

Loading…

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+0.5133,121 counties reporting both
After adjusting for density, income and education+0.407the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.415size taken out as well as density
Also comparing only within each state+0.233each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.359the 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+0.215the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting+0.435uses 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 = 1.7e-124. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 5.2e-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 1.5e-123.

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 +0.36 (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 Returns claiming the earned income credit and Black Protestant adherents