Gini index of income inequality and Homicide rate
Where Gini index of income inequality is higher, Homicide rate tends to be higher. The link is weak: +0.31 across 1,143 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 22 states, the middle value of the link is +0.42.
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
Gini index of income inequality
How unequally household income is shared, on a scale from 0 to 1. Zero would mean every household has the same income. One would mean a single household has all of it. US counties run from about 0.32 to 0.60. It is measured on money income before taxes and government payments, so US figures sit above countries that measure it after taxes and payments.
Census ACS 5-year · ACS table B19083_001
Homicide rate
Deaths recorded as homicide per 100,000 people. It comes from death certificates, not police reports.
County Health Rankings · County Health Rankings v015
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 gini index of income inequality
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| Macon County, GA | 0.611 | 19 |
| Holmes County, MS | 0.609 | 44.3 |
| New York County, NY | 0.596 | 2.85 |
| Lee County, AR | 0.571 | 22.6 |
| Humphreys County, MS | 0.567 | 25.1 |
| Lowest | ||
| Paulding County, GA | 0.354 | 5.62 |
| Kendall County, IL | 0.356 | 3.62 |
| Stafford County, VA | 0.378 | 3.16 |
| Charles County, MD | 0.385 | 8.12 |
| Canadian County, OK | 0.387 | 3.23 |
By homicide rate
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| Phillips County, AR | 0.504 | 57.4 |
| St. Louis city, MO | 0.495 | 50.6 |
| Leflore County, MS | 0.538 | 48.4 |
| Washington County, MS | 0.506 | 46.9 |
| Lowndes County, AL | 0.537 | 46 |
| Lowest | ||
| Morris County, NJ | 0.455 | 0.658 |
| Rockingham County, NH | 0.428 | 0.827 |
| Davis County, UT | 0.391 | 0.922 |
| Delaware County, OH | 0.416 | 0.951 |
| York County, ME | 0.42 | 0.958 |
States
By gini index of income inequality
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| New York | 0.515 | 3.65 |
| District of Columbia | 0.514 | 23 |
| Connecticut | 0.498 | 3.36 |
| Louisiana | 0.494 | 15.9 |
| California | 0.489 | 5.32 |
| Lowest | ||
| Utah | 0.428 | 2.49 |
| Alaska | 0.433 | 8.64 |
| New Hampshire | 0.441 | 1.52 |
| Wisconsin | 0.443 | 4.57 |
| Idaho | 0.444 | 2.19 |
By homicide rate
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| District of Columbia | 0.514 | 23 |
| Mississippi | 0.484 | 16 |
| Louisiana | 0.494 | 15.9 |
| Alabama | 0.478 | 12.7 |
| Missouri | 0.465 | 11 |
| Lowest | ||
| New Hampshire | 0.441 | 1.52 |
| Maine | 0.457 | 1.59 |
| Vermont | 0.452 | 2.04 |
| Idaho | 0.444 | 2.19 |
| Rhode Island | 0.461 | 2.29 |
Metro areas — Gini index of income inequality is not published for metro areas
By homicide rate
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| Greenville, MS | — | 46.9 |
| Selma, AL | — | 41.5 |
| Greenwood, MS | — | 40.9 |
| Pine Bluff, AR | — | 37.3 |
| Clarksdale, MS | — | 33.1 |
| Lowest | ||
| Portland-South Portland, ME | — | 1.07 |
| Provo-Orem-Lehi, UT | — | 1.22 |
| State College, PA | — | 1.24 |
| Iowa City, IA | — | 1.41 |
| Barnstable Town, MA | — | 1.44 |
Cities and towns — Homicide rate is not published for cities and towns
By gini index of income inequality
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| Darlington city, SC | 0.692 | — |
| Hazard city, KY | 0.683 | — |
| Milledgeville city, GA | 0.676 | — |
| Arroyo zona urbana, PR | 0.668 | — |
| Dyersburg city, TN | 0.666 | — |
| Lowest | ||
| Margaret town, AL | 0.249 | — |
| Bangor Base CDP, WA | 0.259 | — |
| Harrisburg city, SD | 0.266 | — |
| Brookshire city, TX | 0.266 | — |
| Moorefield CDP, VA | 0.266 | — |
ZIP codes — Homicide rate is not published for ZIP codes
By gini index of income inequality
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Highest | ||
| ZIP 00913 (San Juan zona urbana, PR) | 0.834 | — |
| ZIP 08609 (Trenton city, NJ) | 0.683 | — |
| ZIP 00901 (San Juan zona urbana, PR) | 0.67 | — |
| ZIP 39095 (Holmes County, MS) | 0.67 | — |
| ZIP 92590 (Riverside County, CA) | 0.664 | — |
| Lowest | ||
| ZIP 98315 (Bangor Base CDP, WA) | 0.259 | — |
| ZIP 23801 (Fort Lee CDP, VA) | 0.271 | — |
| ZIP 34753 (Mascotte city, FL) | 0.272 | — |
| ZIP 99703 (Fairbanks city, AK) | 0.275 | — |
| ZIP 85613 (Sierra Vista city, AZ) | 0.28 | — |
Counties furthest from the pattern
Compared with the straight line that best fits all 1,144 counties: the five with far more homicide rate than their gini index of income inequality would suggest, and the five with far less.
| Gini index of income inequality | Homicide rate | |
|---|---|---|
| Above the line | ||
| Phillips County, AR | 0.504 | 57.4 |
| Petersburg city, VA | 0.446 | 46 |
| St. Louis city, MO | 0.495 | 50.6 |
| Macon County, AL | 0.479 | 44.8 |
| Washington County, MS | 0.506 | 46.9 |
| Below the line | ||
| New York County, NY | 0.596 | 2.85 |
| Western Connecticut Planning Region, CT | 0.543 | 1.51 |
| Collier County, FL | 0.533 | 2.17 |
| Westchester County, NY | 0.535 | 2.37 |
| Marin County, CA | 0.523 | 1.87 |
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 | +0.445 | 1,143 counties reporting both |
| After adjusting for density, income and education | +0.313 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | +0.319 | size taken out as well as density |
| Also comparing only within each state | +0.282 | 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 | +0.186 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 219 equally weighted counties |
| Middle value inside single states | +0.423 | the link worked out inside each of 22 states with at least 20 counties reporting |
| Using ranks, after adjusting | +0.269 | 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 = 2.6e-27. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 4.8e-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 1.0e-26.
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 +0.35 (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 gini index of income inequality rose most, did homicide ratemove 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.
| Period | Counties | Change together | Within states | q |
|---|---|---|---|---|
| 2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic | 879 | +0.09 | +0.08 | 0.343 |
| 2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years | 989 | +0.02 | +0.03 | 0.768 |
Measured over the nearest years published: Homicide rate: 2013–2019 for the 2014–2019 row; Homicide rate: 2019–2022 for the 2019–2023 row.
Over the main period, any link between the changes could easily be chance. How change is measured.
Related pairs
- Share Black, not Hispanic and Homicide rate — +0.74
- Stroke and Homicide rate — +0.72
- Threat of utility shut-off and Homicide rate — +0.71
- Homicide rate and Children in single-parent households — +0.69
- Lack of reliable transportation and Homicide rate — +0.68
- Housing insecurity and Homicide rate — +0.68
- Food insecurity and Homicide rate — +0.67
- Child mortality and Homicide rate — +0.67
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 Gini index of income inequality and Homicide rate