Threat of utility shut-off and Returns reporting capital gains
Where Threat of utility shut-off is higher, Returns reporting capital gains tends to be lower. The link is moderate: -0.51 across 2,287 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 30 states, the middle value of the link is -0.66.
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
Threat of utility shut-off
The estimated percentage of adults who received a notice threatening to shut off a utility in the past year. It is adjusted so places with older or younger populations can be compared fairly. It is an estimate from a statistical model, not a direct count from a local survey.
CDC PLACES · PLACES SHUTUTILITY, age-adjusted
Returns reporting capital gains
The percentage of tax returns reporting a capital gain: profit from selling something like stock or property.
IRS Statistics of Income · IRS SOI N01000 / 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 threat of utility shut-off
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| East Carroll Parish, LA | 27.8% | 5.83% |
| Madison Parish, LA | 25.5% | 5.25% |
| Greene County, AL | 25.5% | 5.46% |
| McKinley County, NM | 25% | 3.21% |
| Kusilvak Census Area, AK | 24.9% | 0.722% |
| Lowest | ||
| Falls Church city, VA | 3.7% | 41.9% |
| Ozaukee County, WI | 4.1% | 34.4% |
| Waukesha County, WI | 4.2% | 30.8% |
| Arlington County, VA | 4.3% | 33.7% |
| Loudoun County, VA | 4.4% | 31% |
By returns reporting capital gains
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| McPherson County, NE | 6.7% | 45% |
| Garfield County, MT | 7.5% | 44.4% |
| Carter County, MT | 7.7% | 44.1% |
| Marin County, CA | 5% | 43.9% |
| Blaine County, NE | 7% | 43.5% |
| Lowest | ||
| Kusilvak Census Area, AK | 24.9% | 0.722% |
| McDowell County, WV | 19.7% | 2.96% |
| McKinley County, NM | 25% | 3.21% |
| Northwest Arctic Borough, AK | 17.5% | 3.21% |
| Bethel Census Area, AK | 19.6% | 3.38% |
States — Threat of utility shut-off is not published for states
By returns reporting capital gains
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| District of Columbia | — | 23.9% |
| Washington | — | 23.4% |
| Massachusetts | — | 22.8% |
| New Jersey | — | 22.4% |
| Connecticut | — | 22.3% |
| Lowest | ||
| Mississippi | — | 10.1% |
| West Virginia | — | 11.2% |
| Alabama | — | 12.8% |
| Louisiana | — | 13.1% |
| New Mexico | — | 13.4% |
Metro areas
By threat of utility shut-off
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| Gallup, NM | 25% | 3.21% |
| Clarksdale, MS | 22.5% | 7.02% |
| Greenville, MS | 20.4% | 6.75% |
| Selma, AL | 20.4% | 6.88% |
| Forrest City, AR | 19.9% | 6.07% |
| Lowest | ||
| Los Alamos, NM | 4.8% | 31% |
| San Jose-Sunnyvale-Santa Clara, CA | 4.81% | 36.3% |
| Madison, WI | 4.9% | 26.2% |
| Heber, UT | 4.97% | 33.1% |
| Appleton, WI | 5.06% | 21.8% |
By returns reporting capital gains
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| San Jose-Sunnyvale-Santa Clara, CA | 4.81% | 36.3% |
| Jackson, WY-ID | 5.9% | 35.2% |
| Heber, UT | 4.97% | 33.1% |
| San Francisco-Oakland-Fremont, CA | 5.66% | 32.3% |
| Hailey, ID | 6.42% | 32% |
| Lowest | ||
| Gallup, NM | 25% | 3.21% |
| El Centro, CA | 13.3% | 3.72% |
| Lumberton, NC | 17.4% | 4.6% |
| Hinesville, GA | 12.1% | 5.81% |
| Forrest City, AR | 19.9% | 6.07% |
Cities and towns — Returns reporting capital gains is not published for cities and towns
By threat of utility shut-off
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Highest | ||
| Benton Harbor city, MI | 34.6% | — |
| Glasgow Village CDP, MO | 33.3% | — |
| Buena Vista CDP, MI | 33.2% | — |
| Tallulah city, LA | 32.3% | — |
| Jennings city, MO | 31.8% | — |
| Lowest | ||
| San Marino city, CA | 2.6% | — |
| Cupertino city, CA | 2.7% | — |
| Saratoga city, CA | 2.8% | — |
| Los Altos city, CA | 2.8% | — |
| Palos Verdes Estates city, CA | 2.9% | — |
Counties furthest from the pattern
Compared with the straight line that best fits all 2,298 counties: the five with far more returns reporting capital gains than their threat of utility shut-off would suggest, and the five with far less.
| Threat of utility shut-off | Returns reporting capital gains | |
|---|---|---|
| Above the line | ||
| Sioux County, NE | 9.4% | 42% |
| Garfield County, MT | 7.5% | 44.4% |
| Carter County, MT | 7.7% | 44.1% |
| McPherson County, NE | 6.7% | 45% |
| Blaine County, NE | 7% | 43.5% |
| Below the line | ||
| Aleutians West Census Area, AK | 7.6% | 5.7% |
| North Slope Borough, AK | 9.7% | 3.8% |
| Murray County, GA | 8.5% | 5.71% |
| Greenlee County, AZ | 8% | 7.06% |
| Itawamba County, MS | 7.8% | 7.55% |
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 | -0.704 | 2,287 counties reporting both |
| After adjusting for density, income and education | -0.513 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | -0.507 | size taken out as well as density |
| Also comparing only within each state | -0.316 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | -0.391 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 192 equally weighted counties |
| Middle value inside single states | -0.659 | the link worked out inside each of 30 states with at least 20 counties reporting |
| Using ranks, after adjusting | -0.573 | uses 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 = 2.2e-153. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.2e-8. 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 2.3e-152.
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 +0.43 (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
- Threat of utility shut-off and Returns claiming the earned income credit — +0.80
- Threat of utility shut-off and Homicide rate, annual — +0.72
- Threat of utility shut-off and Homicide rate — +0.71
- Threat of utility shut-off and Children in single-parent households — +0.69
- Threat of utility shut-off and Average test score — -0.65
- Threat of utility shut-off and Social connection score — -0.63
- Threat of utility shut-off and Years of potential life lost — +0.59
- Threat of utility shut-off and Premature mortality — +0.58
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 Threat of utility shut-off and Returns reporting capital gains