placestats

Homeownership rate and Violent crime rate

Where Homeownership rate is higher, Violent crime rate tends to be lower. The link is weak: -0.35 across 2,280 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 36 states, the middle value of the link is -0.54.

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

Homeownership rate

The percentage of lived-in homes that are owned, not rented. Empty homes are left out of the count entirely.

Census ACS 5-year · ACS table B25003_002, divided by occupied housing units

Violent crime rate

Murders, rapes, robberies and aggravated assaults in the year, per 100,000 residents, from the FBI. It counts only crimes reported to police or found by them, so crimes nobody reports are missing. For a state, the figure is the FBI's estimate, which fills in for police agencies that did not report. For a county, it is only what the agencies reported, and it is shown only where agencies that reported for all 12 months serve at least 90% of the people who live there.

FBI Uniform Crime Reporting program (Crime Data Explorer) · FBI Crime Data Explorer: states, estimated_crimes violent_crime; counties, Return A master file, actual offenses

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 homeownership rate

Homeownership rateViolent crime rate
Highest
Edwards County, TX94.5%492
Oliver County, ND93.4%0
Powhatan County, VA93.1%109
New Kent County, VA92.1%173
Keweenaw County, MI91.7%42.3
Lowest
Hudson County, NJ31.2%330
Suffolk County, MA36.6%629
Petersburg city, VA38.3%700
Emporia city, VA38.4%688
San Francisco County, CA38.5%730

By violent crime rate

Homeownership rateViolent crime rate
Highest
Shelby County, TN54.6%1,876
Crittenden County, AR56.6%1,764
Baltimore city, MD47.5%1,694
St. Louis city, MO45.4%1,457
Robeson County, NC65.6%1,421
Lowest
San Juan County, CO55.5%0
Kiowa County, CO69.7%0
Conejos County, CO74.5%0
Menominee County, WI73.5%0
Roberts County, TX85.5%0
States

By homeownership rate

Homeownership rateViolent crime rate
Highest
West Virginia74.3%269
Maine74%104
Michigan72.9%461
Vermont72.8%216
New Hampshire72.5%115
Lowest
District of Columbia41.1%1,142
New York54.3%391
California55.8%507
Nevada59.3%434
Hawaii62.6%232

By violent crime rate

Homeownership rateViolent crime rate
Highest
District of Columbia41.1%1,142
New Mexico69.3%747
Alaska66.6%734
Tennessee67%636
Arkansas66.1%623
Lowest
Maine74%104
New Hampshire72.5%115
Connecticut66.2%152
Rhode Island63.3%167
Wyoming71.9%194
Metro areas

By homeownership rate

Homeownership rateViolent crime rate
Highest
Wildwood-The Villages, FL88.1%117
Hemlock Farms, PA86.2%96.9
Holland, MI86.1%159
DeRidder, LA83.2%229
Punta Gorda, FL83.2%115
Lowest
Pullman, WA46.6%166
Los Angeles-Long Beach-Anaheim, CA48.6%555
Carbondale, IL49.3%457
Laramie, WY49.4%163
Lawrence, KS49.5%164

By violent crime rate

Homeownership rateViolent crime rate
Highest
Memphis, TN-MS-AR60.6%1,453
Lumberton, NC65.6%1,421
Orangeburg, SC65.9%1,414
Forrest City, AR55.2%1,324
Albuquerque, NM68.7%1,152
Lowest
Quincy, IL-MO73%0
Lexington, NE66.1%0
Columbus, IN69.9%16.1
Pikeville, KY74%31.1
Moscow, ID60.6%35.7
Cities and towns — Violent crime rate is not published for cities and towns

By homeownership rate

Homeownership rateViolent crime rate
Highest
East Hills village, NY100%—
White Rock CDP, NM99.6%—
Hooper city, UT99.4%—
Marvin village, NC99.3%—
Todd Creek CDP, CO99.2%—
Lowest
Fort Carson CDP, CO0%—
Air Force Academy CDP, CO0%—
Camp Pendleton Mainside CDP, CA0%—
North Fort Lewis CDP, WA0%—
Lackland AFB CDP, TX0%—
ZIP codes — Violent crime rate is not published for ZIP codes

By homeownership rate

Homeownership rateViolent crime rate
Highest
ZIP 29207 (Columbia city, SC)100%—
ZIP 08056 (Gloucester County, NJ)100%—
ZIP 48380 (Oakland County, MI)99.7%—
ZIP 87547 (White Rock CDP, NM)99.6%—
ZIP 06419 (Middlesex County, CT)99.5%—
Lowest
ZIP 01003 (Amherst Town city, MA)0%—
ZIP 99703 (Fairbanks city, AK)0%—
ZIP 99505 (Anchorage municipality, AK)0%—
ZIP 93106 (University of California-Santa Barbara CDP, CA)0%—
ZIP 92136 (San Diego city, CA)0%—

Counties furthest from the pattern

Compared with the straight line that best fits all 2,287 counties: the five with far more violent crime rate than their homeownership rate would suggest, and the five with far less.

Homeownership rateViolent crime rate
Above the line
Shelby County, TN54.6%1,876
Crittenden County, AR56.6%1,764
Baltimore city, MD47.5%1,694
Robeson County, NC65.6%1,421
Orangeburg County, SC65.9%1,414
Below the line
Madison County, ID40.2%68.6
Sioux County, ND46%27.4
San Juan County, CO55.5%0
Harrisonburg city, VA39.9%224
Riley County, KS44.9%174

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-0.4602,280 counties reporting both
After adjusting for density, income and education-0.355the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.325size taken out as well as density
Also comparing only within each state-0.286each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.430the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 237 equally weighted counties
Middle value inside single states-0.536the link worked out inside each of 36 states with at least 20 counties reporting
Using ranks, after adjusting-0.354uses 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 = 1.1e-68. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 8.6e-10. The site tested 29,403 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 9.0e-68.

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 +0.30 (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 homeownership rate rose most, did violent crime 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.

PeriodCountiesChange togetherWithin statesq
2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic1,966+0.03+0.020.663
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years1,845-0.03-0.030.422

Over the main period, any link between the changes could easily be chance. How change is measured.

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 Homeownership rate and Violent crime rate