Women aged 15 to 50 and Local income tax as a share of income
Across 554 counties, Women aged 15 to 50 and Local income tax as a share of income have a link of +0.51, 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
Women aged 15 to 50
The number of women aged 15 to 50, the group the survey asks about recent births.
Census ACS 5-year · ACS table B13002_001
Local income tax as a share of income
Local income tax as a percentage of what residents earned. It is zero in most of the country. About 4,800 local governments in a dozen states charge one, and New York City's is the largest. When a city spans several counties, its tax is split between them by where its residents' income is.
Census local government finances · Census local government finances, item T40, every local government
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 women aged 15 to 50
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| District of Columbia, DC | 299.46 | 4.57 |
| Riley County, KS | 296.97 | 0.00731 |
| Athens County, OH | 288.02 | 0.388 |
| Monroe County, IN | 286.79 | 0.0146 |
| Boone County, MO | 286.24 | 0.000408 |
| Lowest | ||
| Forest County, PA | 81.36 | 0.38 |
| Jewell County, KS | 141.97 | 0.0151 |
| Noble County, OH | 147.07 | 0.0965 |
| Lyon County, KY | 147.89 | 0.181 |
| Wallace County, KS | 150.10 | 0.00422 |
By local income tax as a share of income
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| District of Columbia, DC | 299.46 | 4.57 |
| Bronx County, NY | 251.40 | 2.44 |
| New York County, NY | 277.51 | 2.44 |
| Kings County, NY | 259.40 | 2.42 |
| Queens County, NY | 236.47 | 2.42 |
| Lowest | ||
| Sedgwick County, KS | 233.91 | 0.00001 |
| Franklin County, MO | 207.20 | 0.000018 |
| Jasper County, MO | 233.80 | 0.000018 |
| Cole County, MO | 214.43 | 0.000046 |
| Dickinson County, KS | 206.26 | 0.000112 |
States
By women aged 15 to 50
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| District of Columbia | 299.46 | 4.16 |
| New York | 235.28 | 1.01 |
| Maryland | 234.62 | 1.69 |
| Oregon | 233.14 | 0.136 |
| Alabama | 232.68 | 0.0541 |
| Lowest | ||
| Pennsylvania | 222.74 | 0.735 |
| Iowa | 223.04 | 0.0602 |
| Michigan | 224.01 | 0.135 |
| Ohio | 225.36 | 0.992 |
| Kansas | 226.78 | 0.00054 |
By local income tax as a share of income
Metro areas — Local income tax as a share of income is not published for metro areas
By women aged 15 to 50
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| Rexburg, ID | 363.32 | — |
| Pullman, WA | 304.13 | — |
| Vermillion, SD | 296.48 | — |
| Mount Pleasant, MI | 294.46 | — |
| Ithaca, NY | 289.20 | — |
| Lowest | ||
| Wildwood-The Villages, FL | 68.73 | — |
| Punta Gorda, FL | 131.04 | — |
| Port Townsend, WA | 139.76 | — |
| Brookings, OR | 142.43 | — |
| Homosassa Springs, FL | 143.17 | — |
Cities and towns — Local income tax as a share of income is not published for cities and towns
By women aged 15 to 50
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| University of California-Davis CDP, CA | 578.70 | — |
| Isla Vista CDP, CA | 540.79 | — |
| Clemson University CDP, SC | 528.13 | — |
| Kingston CDP, RI | 522.94 | — |
| University of California-Santa Barbara CDP, CA | 506.96 | — |
| Lowest | ||
| Sun City West CDP, AZ | 6.63 | — |
| The Villages CDP, FL | 15.41 | — |
| Laguna Woods city, CA | 15.92 | — |
| Sun Lakes CDP, AZ | 18.04 | — |
| Green Valley CDP, AZ | 21.82 | — |
ZIP codes — Local income tax as a share of income is not published for ZIP codes
By women aged 15 to 50
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Highest | ||
| ZIP 36849 (Auburn city, AL) | 724.54 | — |
| ZIP 44243 (Kent city, OH) | 654.69 | — |
| ZIP 19717 (Newark city, DE) | 639.22 | — |
| ZIP 33620 (Tampa city, FL) | 630.00 | — |
| ZIP 32612 (Gainesville city, FL) | 599.26 | — |
| Lowest | ||
| ZIP 89070 (Clark County, NV) | 0.00 | — |
| ZIP 85734 (Tucson city, AZ) | 0.00 | — |
| ZIP 85375 (Sun City West CDP, AZ) | 8.68 | — |
| ZIP 32162 (The Villages CDP, FL) | 14.59 | — |
| ZIP 92637 (Laguna Woods city, CA) | 15.92 | — |
Counties furthest from the pattern
Compared with the straight line that best fits all 554 counties: the five with far more local income tax as a share of income than their women aged 15 to 50 would suggest, and the five with far less.
| Women aged 15 to 50, per 1,000 residents | Local income tax as a share of income | |
|---|---|---|
| Above the line | ||
| District of Columbia, DC | 299.46 | 4.57 |
| Queens County, NY | 236.47 | 2.42 |
| Richmond County, NY | 229.88 | 2.31 |
| Bronx County, NY | 251.40 | 2.44 |
| Kings County, NY | 259.40 | 2.42 |
| Below the line | ||
| Riley County, KS | 296.97 | 0.00731 |
| Boone County, MO | 286.24 | 0.000408 |
| Monroe County, IN | 286.79 | 0.0146 |
| Johnson County, IA | 284.55 | 0.102 |
| Tippecanoe County, IN | 270.64 | 0.00446 |
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 | +0.506 | 554 counties reporting both |
| After adjusting for density, income and education | +0.160 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | +0.172 | size taken out as well as density |
| Also comparing only within each state | +0.211 | 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 | +0.005 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 93 equally weighted counties |
| Middle value inside single states | +0.472 | the link worked out inside each of 8 states with at least 20 counties reporting |
| Using ranks, after adjusting | -0.112 | 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 = 0.000. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.088. 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 0.000.
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 +0.49 (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
- Loneliness and Local income tax as a share of income — +0.42
- Share foreign-born and Women aged 15 to 50 — +0.38
- Hearing disability and Local income tax as a share of income — -0.36
- Fine particulate matter and Local income tax as a share of income — -0.35
- Median home value and Local income tax as a share of income — +0.35
- Homeownership rate and Local income tax as a share of income — -0.32
- Local income tax as a share of income and Homicide rate, annual — +0.31
- Returns claiming charitable contributions and Local income tax as a share of income — +0.31
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 Women aged 15 to 50 and Local income tax as a share of income