placestats

Unemployment rate and Expected yearly tornado loss

Where Unemployment rate is higher, Expected yearly tornado loss tends to be lower. The link is weak: -0.35 across 3,121 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 40 states, the middle value of the link is -0.19.

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

Unemployment rate

Unemployed people as a percentage of the labor force (people working or looking for work), not of the whole population. A place where few people look for work at all can have low unemployment and still have few people working.

BLS LAUS · BLS LAUS county annual averages

Expected yearly tornado loss

The damage tornadoes are expected to do to buildings in an average year, in dollars for every $100,000 that the buildings are worth. FEMA works it out from the tornadoes recorded from 1986 to 2023 and the damage they did.

FEMA National Risk Index · FEMA National Risk Index v1.20, NRI_Table_Counties / NRI_Table_States, TRND_ALRB

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 unemployment rate

Unemployment rateExpected yearly tornado loss
Highest
Imperial County, CA17.6%0.114
Kusilvak Census Area, AK14.8%0.00164
Yuma County, AZ12.4%0.144
Colusa County, CA12.4%0.817
East Carroll Parish, LA11.8%26.3
Lowest
Loving County, TX1.3%3.68
Brule County, SD1.3%13.6
King County, TX1.4%14
Sanborn County, SD1.4%22.4
Hand County, SD1.4%13.1

By expected yearly tornado loss

Unemployment rateExpected yearly tornado loss
Highest
Johnson County, IA2.4%62.9
Logan County, OK3%60.3
York County, NE2.4%47.5
Platte County, NE2%44.7
Sumter County, AL3.6%44.5
Lowest
Anchorage Municipality, AK3.5%0.000001
Sitka City and Borough, AK3%0.000003
Fairbanks North Star Borough, AK3.8%0.000005
Skagway Municipality, AK5.3%0.000005
Ketchikan Gateway Borough, AK3.5%0.000006
States

By unemployment rate

Unemployment rateExpected yearly tornado loss
Highest
Nevada5.13%0.0317
District of Columbia4.86%1.51
California4.72%0.502
Illinois4.49%12.3
New Jersey4.32%2.08
Lowest
South Dakota1.82%17.6
Vermont1.94%1.01
North Dakota2.05%11.5
Maryland2.24%1.98
New Hampshire2.28%1.94

By expected yearly tornado loss

Unemployment rateExpected yearly tornado loss
Highest
Nebraska2.3%27.4
Iowa2.97%22.6
Mississippi3.12%19.2
Oklahoma3.14%18.4
Alabama2.47%18.1
Lowest
Alaska4.26%0.000238
Nevada5.13%0.0317
Washington4.21%0.183
Hawaii2.85%0.196
Oregon3.79%0.219
Metro areas — Expected yearly tornado loss is not published for metro areas

By unemployment rate

Unemployment rateExpected yearly tornado loss
Highest
El Centro, CA17.6%—
Yuma, AZ12.4%—
Deming, NM10.3%—
Visalia, CA9.8%—
Rio Grande City-Roma, TX9.2%—
Lowest
Pierre, SD1.52%—
Yankton, SD1.6%—
Los Alamos, NM1.6%—
Burlington-South Burlington, VT1.61%—
Mitchell, SD1.63%—

Counties furthest from the pattern

Compared with the straight line that best fits all 3,143 counties: the five with far more expected yearly tornado loss than their unemployment rate would suggest, and the five with far less.

Unemployment rateExpected yearly tornado loss
Above the line
Johnson County, IA2.4%62.9
Logan County, OK3%60.3
York County, NE2.4%47.5
Sumter County, AL3.6%44.5
Platte County, NE2%44.7
Below the line
Los Alamos County, NM1.6%0.372
Chittenden County, VT1.5%0.576
Toole County, MT1.9%0.333
Washington County, VT2%0.21
Cumberland County, ME2.1%0.041

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-0.2583,121 counties reporting both
After adjusting for density, income and education-0.351the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.320size taken out as well as density
Also comparing only within each state-0.126each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.275the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 287 equally weighted counties
Middle value inside single states-0.192the link worked out inside each of 40 states with at least 20 counties reporting
Using ranks, after adjusting-0.375uses 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 = 2.5e-91. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 9.3e-6. 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 2.4e-90.

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 +0.77 (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

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 Unemployment rate and Expected yearly tornado loss