placestats

Private jobs and Motor vehicle theft rate

Where Private jobs is higher, Motor vehicle theft rate tends to be higher. The link is weak: +0.32 across 2,276 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 +0.60.

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

Private jobs

Private-sector jobs, averaged over the year, as employers report them to the state's unemployment insurance program. Jobs are counted where the job is, not where the worker lives.

BLS Quarterly Census of Employment and Wages · BLS QCEW annual averages, private, all industries, annual_avg_emplvl

Motor vehicle theft rate

Thefts of cars, trucks, motorcycles and other vehicles 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 motor_vehicle_theft; 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 private jobs

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
King County, TX1809.520
Bristol Bay Borough, AK1268.79227
Upton County, TX941.4364.8
Teton County, WY885.3530.1
Montour County, PA842.5233.2
Lowest
Long County, GA30.4922.6
Menominee County, WI37.830
Elliott County, KY40.3527.4
Sioux County, ND47.770
Corson County, SD49.7522.5

By motor vehicle theft rate

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
St. Louis city, MO676.372,219
Baltimore city, MD467.541,966
Shelby County, TN463.201,873
Orleans Parish, LA429.451,842
Alameda County, CA415.081,842
Lowest
San Juan County, CO465.220
Sierra County, CA99.600
Wrangell City and Borough, AK263.060
Menominee County, WI37.830
Lexington city, VA548.650
States

By private jobs

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
District of Columbia781.991,061
Massachusetts457.75120
North Dakota446.89222
Minnesota442.04267
New Hampshire432.6064.2
Lowest
West Virginia308.9991.7
Mississippi315.82191
New Mexico320.93519
Oklahoma336.12265
Alabama336.39221

By motor vehicle theft rate

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
District of Columbia781.991,061
Nevada431.30681
Washington387.95680
Colorado418.69659
Maryland355.13557
Lowest
New Hampshire432.6064.2
Idaho379.0877.3
Maine392.7679.9
West Virginia308.9991.7
Vermont394.3692.5
Metro areas

By private jobs

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
Jackson, WY-ID691.0423.4
Port Lavaca, TX601.5494.7
Williston, ND599.75301
Elkhart-Goshen, IN595.57191
Jasper, IN587.8234.4
Lowest
Zapata, TX123.840
Susanville, CA128.10228
Shelton, WA131.51230
Rio Grande City-Roma, TX136.0191.2
Picayune, MS141.74131

By motor vehicle theft rate

Private jobs, per 1,000 residentsMotor vehicle theft rate
Highest
Memphis, TN-MS-AR404.191,420
Pueblo, CO300.941,235
Seattle-Tacoma-Bellevue, WA446.841,008
San Francisco-Oakland-Fremont, CA462.52979
Denver-Aurora-Centennial, CO462.08940
Lowest
Zapata, TX123.840
Lexington, NE374.480
Columbus, IN530.180.701
Crestview-Fort Walton Beach-Destin, FL339.092.27
Lewisburg, PA351.678.75

Counties furthest from the pattern

Compared with the straight line that best fits all 2,283 counties: the five with far more motor vehicle theft rate than their private jobs would suggest, and the five with far less.

Private jobs, per 1,000 residentsMotor vehicle theft rate
Above the line
St. Louis city, MO676.372,219
Baltimore city, MD467.541,966
Shelby County, TN463.201,873
Alameda County, CA415.081,842
Orleans Parish, LA429.451,842
Below the line
King County, TX1809.520
Teton County, WY885.3530.1
Upton County, TX941.4364.8
Montour County, PA842.5233.2
Bristol Bay Borough, AK1268.79227

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+0.4202,276 counties reporting both
After adjusting for density, income and education+0.320the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.254size taken out as well as density
Also comparing only within each state+0.251each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.187the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 227 equally weighted counties
Middle value inside single states+0.604the link worked out inside each of 36 states with at least 20 counties reporting
Using ranks, after adjusting+0.339uses 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 = 3.2e-55. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.000. 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 2.2e-54.

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 +0.24 (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 private jobs rose most, did motor vehicle theft 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 pandemic2,013+0.05+0.060.270
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years1,874-0.07-0.050.382

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 Private jobs and Motor vehicle theft rate