placestats

Republican share of the two-party vote, 2024 and Friending bias

A county is not a voter. Read either way, this says one thing and no more. Counties that voted more Republican also tend to differ on the other measure, and counties that voted less Republican tend to differ the other way. It does not follow that the people who voted that way are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of exactly this data. How a county votes also goes so closely with its density, age and education that much of what looks political here is really those. That is what the adjusted figures are for. The vote shares run from 2000 to 2024, and the links here are measured in 2023.

Where Republican share of the two-party vote, 2024 is higher, Friending bias tends to be lower. The link is weak: -0.32 across 2,979 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 39 states, the middle value of the link is -0.38.

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

Republican share of the two-party vote, 2024

The Republican share of the votes for the two main parties in the 2024 presidential election, by state. Third-party votes are left out, so this shows which way the two-party vote leaned and nothing about turnout. It describes how a state voted and does not judge it. No measure here treats either party as the better end.

MIT Election Data and Science Lab · MEDSL 2024 official state returns

Friending bias

How much less often low-income people make high-income friends than you would expect from how often they meet them. A high value means the chance to mix is there but is not taken.

Social Capital Atlas · Opportunity Insights bias_grp_mem_county

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 republican share of the two-party vote, 2024

Republican share of the two-party vote, 2024Friending bias
Highest
Sterling County, TX93.8-0.0051
Sherman County, TX93.80.088
Cameron Parish, LA93.30.0141
Armstrong County, TX93.1-0.0962
Wheeler County, TX93.10.0243
Lowest
District of Columbia, DC6.690.0467
Prince George's County, MD11.50.122
Baltimore city, MD12.50.148
Orleans Parish, LA14.90.0231
Clayton County, GA15.20.0968

By friending bias

Republican share of the two-party vote, 2024Friending bias
Highest
Todd County, SD240.335
Nantucket County, MA31.20.33
DeSoto County, FL71.60.308
Corson County, SD560.273
Marin County, CA17.20.271
Lowest
Clark County, KS87-0.108
Glascock County, GA92-0.106
Armstrong County, TX93.1-0.0962
Oldham County, TX93.1-0.0928
Cleveland County, AR84.3-0.0816
States — Friending bias is not published for states

By republican share of the two-party vote, 2024

Republican share of the two-party vote, 2024Friending bias
Highest
Wyoming73.5—
West Virginia71.3—
Idaho68.8—
North Dakota68.7—
Oklahoma67.5—
Lowest
District of Columbia6.69—
Vermont33.6—
Maryland35.2—
Massachusetts37—
Hawaii38.2—
Metro areas

By republican share of the two-party vote, 2024

Republican share of the two-party vote, 2024Friending bias
Highest
Cullman, AL90.5-0.0194
Pampa, TX89.60.113
Borger, TX89.30.0815
Gillette, WY88.90.11
Brownwood, TX87.50.0794
Lowest
Boulder, CO21.40.118
Santa Cruz-Watsonville, CA21.70.179
San Francisco-Oakland-Fremont, CA230.0639
Vineyard Haven, MA23.10.218
Ithaca, NY24.70.103

By friending bias

Republican share of the two-party vote, 2024Friending bias
Highest
Nantucket, MA31.20.33
Arcadia, FL71.60.308
Trenton-Princeton, NJ32.70.241
Napa, CA320.222
Bridgeport-Stamford-Danbury, CT40.60.219
Lowest
Harrison, AR83-0.0249
Urban Honolulu, HI39-0.0207
Cullman, AL90.5-0.0194
Rexburg, ID84-0.0125
Moscow, ID54.1-0.0123

Counties furthest from the pattern

Compared with the straight line that best fits all 2,986 counties: the five with far more friending bias than their republican share of the two-party vote, 2024 would suggest, and the five with far less.

Republican share of the two-party vote, 2024Friending bias
Above the line
DeSoto County, FL71.60.308
Nantucket County, MA31.20.33
Todd County, SD240.335
Jerome County, ID77.50.257
Corson County, SD560.273
Below the line
Alexandria city, VA20.5-0.0306
San Francisco County, CA16.2-0.0158
Clark County, KS87-0.108
Cook County, MN32.1-0.0271
Glascock County, GA92-0.106

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-0.4102,979 counties reporting both
After adjusting for density, income and education-0.321the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.287size taken out as well as density
Also comparing only within each state-0.234each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.233the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 285 equally weighted counties
Middle value inside single states-0.380the link worked out inside each of 39 states with at least 20 counties reporting
Using ranks, after adjusting-0.332uses 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 = 2.3e-72. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 1.9e-8. 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 1.6e-71.

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 +0.18 (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 Republican share of the two-party vote, 2024 and Friending bias