# Precincts within counties: report

Chapter 6.3 of The Public Mind, by Vishal Singh (NYU Stern). Generated from the chapter's data files; the reading version is at https://vishalsingh.org/politics/precincts-within-counties. Table n of this report is figure n of the chapter.

## Identification

- Title: Precincts within counties
- Chapter: 6.3 (Part VI, Election results at different scales; Votes, giving and places)
- Question: How much do precinct margins vary inside a county, and which counties vary most?
- Dek: In 2024, 65.0% of two-party presidential votes in the sample were cast in precincts decided by 20 points or more, against 57.2% in counties decided by that margin.
- Grain: places
- Status: draft
- Published: 2026-09-30
- Updated: not revised
- Data sources:
  - Precinct presidential returns. MIT Election Data and Science Lab, 2024 presidential returns by precinct (Harvard Dataverse), two-party votes per reporting unit; years: 2016, 2020, 2024; weights: none (full counts); statistics weighted by two-party votes
  - County election returns. Certified 2024 county totals from the repaired county file, used to check each county's precinct rows; years: President 1868-2024 (40 elections); House and Senate 1990-2024; weights: none (full counts)
  - County demographics panel. County panel: ACS 2024 nonwhite share, rural share and Rural-Urban Continuum Code 2023; years: 2000-2024 (election years, interpolated between census and survey anchors); weights: none (county values; counties weighted by two-party votes in the correlations)
- Canonical URL: https://vishalsingh.org/politics/precincts-within-counties
- Report: https://vishalsingh.org/politics/precincts-within-counties/report
- Markdown: https://vishalsingh.org/politics/precincts-within-counties/report.md
- BibTeX key: singh2026precinctswithincounties

```bibtex
@misc{singh2026precinctswithincounties,
  author = {Singh, Vishal},
  title = {Precincts within counties},
  year = {2026},
  url = {https://vishalsingh.org/politics/precincts-within-counties},
  note = {In The Public Mind. Published 30 September 2026.}
}
```

## Principal estimates

The facts the dek and the opening prose cite, in order of appearance.

| Estimand | Population | Period | Value | Interval | n | Weights | Source | Fact id |
| --- | --- | --- | ---: | --- | ---: | --- | --- | --- |
| share of votes cast in precincts in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election | 65.0% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | share_land_precinct |
| definition | definition used in this chapter | 2024 presidential general election | 20 |   |   | none (definition) | Precinct presidential returns | cut_land |
| share of votes cast in counties in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election | 57.2% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | share_land_county |
| sum of Democratic and Republican votes | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election | 149.0 million |   |   | none (full counts) | Precinct presidential returns | votes_sample |
| share of votes cast in precincts in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election | 18.5% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | share_comp_precinct |
| definition | definition used in this chapter | 2024 presidential general election | 10 |   |   | none (definition) | Precinct presidential returns | cut_comp |
| share of votes cast in counties in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election | 23.1% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | share_comp_county |
| mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 23.3 | 95% CI 22.5 to 24.1 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | sd_vw_mean |
| definition | definition used in this chapter | 2024 presidential general election | 5 |   |   | none (definition) | Precinct presidential returns | cut_near |
| definition | definition used in this chapter | 2024 presidential general election | 20 |   |   | none (definition) | Precinct presidential returns | cut_near_units |
| definition | definition used in this chapter | 2024 presidential general election | 60% |   |   | none (definition) | Precinct presidential returns | land_equiv |
| definition | definition used in this chapter | 2024 presidential general election | 55% |   |   | none (definition) | Precinct presidential returns | comp_equiv |
| definition | definition used in this chapter | 2024 presidential general election | 30 |   |   | none (definition) | Precinct presidential returns | cut_sd |
| definition | definition used in this chapter | 2024 presidential general election | 15 |   |   | none (definition) | Precinct presidential returns | sd_equiv |
| two-party margin, Democratic positive | Bucks County, PA | 2024 presidential general election | −0.1 |   |   | none (full counts) | Precinct presidential returns | bucks_margin |
| count | Bucks County, PA | 2024 presidential general election | 304 |   |   | none (full counts) | Precinct presidential returns | bucks_units |
| vote-weighted standard deviation of precinct margins | Bucks County, PA | 2024 presidential general election | 14.8 |   | 304 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | bucks_sd |
| share of votes cast in precincts decided by under 10 points | Bucks County, PA | 2024 presidential general election | 50.0% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | bucks_comp |
| margin of the most Democratic precinct | Bucks County, PA | 2024 presidential general election | 42.0 |   |   | none (full counts) | Precinct presidential returns | bucks_max_d |
| margin of the most Republican precinct, as a Republican lead | Bucks County, PA | 2024 presidential general election | 33.7 |   |   | none (full counts) | Precinct presidential returns | bucks_max_r |
| two-party margin, Democratic positive | Centre County, PA | 2024 presidential general election | +2.9 |   |   | none (full counts) | Precinct presidential returns | centre_margin |
| count | Centre County, PA | 2024 presidential general election | 87 |   |   | none (full counts) | Precinct presidential returns | centre_units |
| vote-weighted standard deviation of precinct margins | Centre County, PA | 2024 presidential general election | 36.3 |   | 87 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | centre_sd |
| share of votes cast in precincts decided by under 10 points | Centre County, PA | 2024 presidential general election | 5.5% |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns | centre_comp |
| margin of the most Democratic precinct | Centre County, PA | 2024 presidential general election | 65.0 |   |   | none (full counts) | Precinct presidential returns | centre_max_d |
| margin of the most Republican precinct, as a Republican lead | Centre County, PA | 2024 presidential general election | 75.2 |   |   | none (full counts) | Precinct presidential returns | centre_max_r |
| count | reporting units (precincts) in the analysis sample | 2024 presidential general election | 175,345 |   |   | none (full counts) | Precinct presidential returns | n_units |
| count | counties in the analysis sample | 2024 presidential general election | 3,043 |   |   | none (full counts) | Precinct presidential returns | n_counties |
| count | states in the analysis sample, not counting the District of Columbia | 2024 presidential general election | 48 |   |   | none (full counts) | Precinct presidential returns | n_states |
| count | Louisiana parishes | 2024 presidential general election | 64 |   |   | none (full counts) | Precinct presidential returns | n_out_la |
| ratio of precinct votes to certified votes | Louisiana parishes | 2024 presidential general election | 51.5% |   |   | none (full counts) | Precinct presidential returns | la_share |
| count | counties outside Louisiana whose precinct rows do not add to the certified total | 2024 presidential general election | 6 |   |   | none (full counts) | Precinct presidential returns | n_out_other |
| count | counties whose precinct rows do not add to the certified total (Louisiana and others) | 2024 presidential general election | 70 |   |   | none (full counts) | Precinct presidential returns | n_out_total |
| share | all counties with returns | 2024 presidential general election | 2.0% |   |   | none (full counts) | County election returns | out_share_cert |
| share of certified two-party votes cast in Alaska | all counties with returns | 2024 presidential general election | 0.2% |   |   | none (full counts) | County election returns | alaska_share_cert |
| count | counties in the analysis sample | 2024 presidential general election | 190 |   |   | none (full counts) | Precinct presidential returns | n_below_floor |
| definition | definition used in this chapter | 2024 presidential general election | 5 |   |   | none (definition) | Precinct presidential returns | cut_floor_units |
| count | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 2,853 |   |   | none (full counts) | Precinct presidential returns | n_counties_disp |
| definition | definition used in this chapter | 2024 presidential general election | 2,000 |   |   | none (definition) | Precinct presidential returns | n_boot |

## Findings

In 2024, 65.0% of the 149.0 million two-party presidential votes in this chapter's sample were cast in precincts decided by 20 points or more, against 57.2% cast in counties decided by that margin. At the other end, 18.5% of votes were cast in precincts decided by under 10 points, against 23.1% in counties. A precinct here is a reporting unit, the area for which an election office reports its votes, and not a neighborhood.

A county's margin is the average of its precinct margins weighted by their votes. This chapter measures how far the precinct margins vary around that average, and which counties vary most. The standard deviation of precinct margins inside a county, called its spread here, has a mean across counties of 23.3 (95% CI 22.5 to 24.1) points when each county counts in proportion to its votes. Spread is higher in metro counties and in counties that lean Democratic, and it varies widely among counties that finished near a tie, with a margin under 5 points and at least 20 precincts.

A two-party margin is the Democratic vote minus the Republican vote over their sum, in points, and a positive margin is a Democratic lead. A margin of 20 points gives the winner 60% of the two-party vote, and a margin of 10 points gives the winner 55%. The spread is weighted by each precinct's two-party votes and stated in the same points. A county that cast equal numbers of votes in precincts at Democratic +30 and at Republican +30 would have a margin of zero and a spread of 30, which is 15 points of Democratic vote share. Third-party votes are left out.

Two Pennsylvania counties that finished nearly even show what spread measures. Table 1 gives the share of each county's votes by the margin of the precinct where they were cast. Bucks County finished at a margin of −0.1 points, with 304 precincts and a spread of 14.8, and 50.0% of its votes were cast in precincts decided by under 10 points. Its most Democratic precinct had a margin of 42.0 points and its most Republican a Trump lead of 33.7. Centre County finished at +2.9 with 87 precincts and a spread of 36.3, and only 5.5% of its votes were cast in precincts that close. The most Democratic precinct in Centre County had a margin of 65.0 points and the most Republican a Trump lead of 75.2. The [Neighborhoods explorer](https://vishalsingh.org/politics/explore/neighborhoods) will map these counties and others below the precinct level.

Table 1. Bucks County precincts cluster near an even split, while Centre County precincts form two groups, one on each side

How the gap between precincts and counties changes across scales, from states to blocks, is the subject of Planned, Sorting by geographic scale, 2016 to 2024 (https://vishalsingh.org/politics/sorting-by-geographic-scale; planned), a planned chapter. This chapter asks what the precinct distribution looks like inside each county, which is the information that a county color leaves out. County-level maps supported the argument that Americans sort into like-minded places [1], a claim that others contested [2], and address-level data show that many voters live with almost no exposure to voters of the other party [3]. Precinct returns sit between the two scales.

The sample covers 175,345 reporting units in 3,043 counties in 48 states and the District of Columbia; Alaska and Louisiana are absent. (Note: The precinct file from the MIT Election Data and Science Lab reports votes by whatever unit each state or county election office uses, so a precinct here is a reporting unit and differs in size and kind by state. Alaska is left out because its 2024 county codes are election districts. So are the 64 Louisiana parishes, where the precinct rows hold 51.5% of the certified vote, and 6 other counties whose precinct rows do not add to the certified county total. The 70 excluded counties hold 2.0% of certified votes, and Alaska holds a further 0.2%. 190 counties in the sample have too few reporting units for a spread.) A county needs at least 5 reporting units to have a spread, which leaves 2,853 counties. The returns are full counts, so shares and spreads carry no sampling error; a statistic across counties, such as a mean or a correlation, carries a 95% interval from resampling counties 2,000 times.

### Precincts are more lopsided than the counties that contain them

Table 2 counts the same votes by the margin of the precinct they were cast in, by the margin of the county, and by the margin of a simulated precinct. Precincts hold more of the votes in landslides and fewer in close contests. Precincts decided by 40 points or more held 36.4% of votes, against 25.4% for counties decided by that margin.

Table 2. Precincts are more often lopsided, and less often close, than counties or than random assignment of voters would make them

Because each county margin is the average of its precinct margins weighted by their votes, precinct margins are at least as spread out as county margins, counting each vote once. That alone does not put more votes in landslide precincts, since a county decided by a landslide can split into precincts of which some are not. The simulation is a benchmark for how much of the gap chance alone would produce. In each of 200 runs, every precinct keeps its number of votes and its county's Democratic share, and its Democratic votes are drawn at random. The simulated precincts hold 56.6% of votes in landslide precincts, 23.3% in close ones and 25.0% in very lopsided ones, within about 0.7 points of the county shares. Each share moves by at most 0.4 points from run to run. Small units alone therefore do not produce the gap between precincts and counties. Precinct margins inside a county vary more than random assignment of voters would make them.

Random assignment still leaves some spread. If the voters of a county were assigned to its precincts at random, the spread would be 3.1 points on average across counties, weighted by votes, and 3.4 points in the median near-tied county.

### Spread is widest in Mississippi and Alabama

Across the 2,853 counties with at least 5 reporting units, the median county, counted once, has a spread of 15.6 (95% CI 15.0 to 16.0) points. That is lower than the vote-weighted mean because counties with more votes tend to have wider spreads, as the next sections show. A spread of 30 points or more occurs in 368 counties, which hold 18.7% of the votes cast in the 2,853 counties. Table 3 maps the spread, and its second view maps the county margin.

Table 3. Spread inside counties is widest in Mississippi and Alabama and scattered across the Southwest and Plains

The vote-weighted mean spread is 38.2 (95% CI 34.9 to 41.5) points in Mississippi and 32.2 (95% CI 25.2 to 38.3) in Alabama, the two highest of the 48 states and the District of Columbia. The units that election offices report differ in size by state. The median precinct holds 227 two-party votes in Kansas and 2,083 in Connecticut, and California reports 578 precincts per county on average while North Dakota reports 7. Smaller units can show more spread, so a comparison of spread across states mixes the electorate with the way votes are counted. Counties with few reporting units also have spreads that one unit can move a long way. Of the 33 counties with a spread of 50 points or more, 4 have fewer than 10 reporting units. The state controls in Table 6 address part of that mix.

Among the 318 counties with at least 100,000 two-party votes, the widest spreads are in Kings County, New York (54.9 points), Jefferson County, Alabama (53.5) and Mobile County, Alabama (50.2). The narrowest are in Arlington County, Virginia (6.5) and the District of Columbia (5.9), whose margins are +59.9 and +86.6 points.

#### Spread falls from metro to less urban counties

Table 4 groups counties by Rural-Urban Continuum Code. The vote-weighted mean spread falls from 24.8 (95% CI 23.5 to 26.1) points in the largest metro counties to 22.7 in smaller metro counties, 19.4 in the larger nonmetro counties and 15.5 (95% CI 14.6 to 16.5) in the least urban ones. The two ends of the scale also differ in lean. The vote-weighted mean margin is +11.7 (95% CI 7.3 to 15.7) points in the largest metro counties and −45.2 (95% CI −47.6 to −42.7) in the least urban, so the next section separates lean from size. The demographics panel has no code for 10 counties, which are left out of the bars: the Connecticut counties, Kansas City, Missouri, and Oglala Lakota County, South Dakota.

Table 4. Spread of precinct margins falls from the largest metro counties to the least urban ones

### Spread rises with Democratic lean, partly through county size

Table 5 plots each county's spread against its margin. Weighted by votes, the correlation is +0.41 (95% CI 0.33 to 0.49) across 2,853 counties. The binned means rise from 6.7 (95% CI 5.2 to 8.0) points in counties near Trump +82 to 25.4 (95% CI 23.4 to 27.5) in counties near Trump +14. The 6 bins from there to Harris +34 have means between 24.1 and 28.4. The highest bin, 31.1 (95% CI 24.7 to 36.8) near Harris +43, has an interval that overlaps each of them. The interval for its difference from each of them includes zero, except for the lowest, near Trump +4, where the difference is 6.9 (95% CI 0.7 to 12.9) points. The data show a rise and then a plateau, with the highest bin distinguishable from only the lowest of the bins before it. The 12 counties near Harris +66 average 19.3 (95% CI 15.3 to 23.9), which is 11.8 (95% CI 3.9 to 18.9) points below the highest bin, and few counties are that blue.

Table 5. Spread rises from the reddest counties to about Trump +14, then levels off

Bluer counties are also larger. The correlation of county margin with the log of two-party votes (the natural logarithm, so that each doubling of a county's votes adds the same amount) is +0.64 (95% CI 0.59 to 0.69), in line with the concentration of Democratic voters in dense places [4]. The correlation of spread with the log of votes is +0.40 (95% CI 0.33 to 0.46). Larger counties have more precincts, and with more precincts there is more room for very different ones. Table 6 holds fixed the log of a county's votes and the log of its number of precincts, and the correlation of lean with spread falls from +0.41 to +0.21 (95% CI 0.12 to 0.30). It then adds state fixed effects, which compare counties within the same state and so absorb each state's own precinct conventions, and the correlation is +0.28 (95% CI 0.19 to 0.37). With both controls, a county 10 points more Democratic has a spread 0.9 (95% CI 0.6 to 1.3) points wider, against 1.1 (95% CI 0.8 to 1.4) points without them. The correlation is also positive when each county counts once, so its sign does not depend on the vote weights.

Table 6. Spread rises with Democratic lean, with or without controls for county size and state

Two county characteristics measured outside the vote show a similar pattern. Across 2,843 counties with demographic data, which leaves out the Connecticut counties, spread correlates +0.43 (95% CI 0.36 to 0.50) with the nonwhite share of residents (the share who are not non-Hispanic white, American Community Survey, 2024). It correlates −0.36 (95% CI −0.41 to −0.30) with the rural share (the share living outside urban areas as the 2020 Census defines them). With size and state held fixed the two are +0.31 (95% CI 0.22 to 0.40) and −0.13 (95% CI −0.19 to −0.08), so the tie to the nonwhite share weakens less than the tie to the rural share does.

### Spread falls with distance from an even split

Distance from an even split is the size of a county's margin, whichever party leads. One might expect the counties closest to a tie to be the most divided, because a near-tied county needs votes from precincts on both sides. Across all counties, the correlation of spread with distance from an even split is −0.29 (95% CI −0.39 to −0.20) when weighted by votes, and it stays negative with size and state held fixed, at −0.19 and −0.25. Counting each county once, it is −0.55 (95% CI −0.57 to −0.52). Spread is lower in counties that are farther from an even split.

Among the 1,725 counties with a margin of 50 points or less, the vote-weighted correlation is −0.04 (95% CI −0.18 to 0.08), an interval that includes zero, against −0.26 (95% CI −0.30 to −0.22) when each county counts once. The vote-weighted result depends on the cutoff, as Table 7 shows. Its interval excludes zero only from 60 points up, where the correlation is −0.15. The absence of a link is specific to the vote-weighted comparison of counties within 50 points or less, and it is not a finding about counties in general.

Table 7. Spread falls with distance from an even split, except in vote-weighted comparisons of counties within 50 points

The negative correlation grows as the tails are added. Precinct margins cannot pass 100 points in either direction, so a county with a margin near the limit has little room for spread. Among the 260 counties with a margin beyond 70 points, however, the widest spread is 34.7 points, against a limit of 71.4 at a margin of 70 points. The highest ratio of a county's spread to the limit at its own margin is 49%. (Note: The largest spread a county can have is the square root of 100 squared minus its margin squared, so it falls to zero as the margin approaches 100. Among the 260 counties beyond 70 points, the mean ratio of a county's spread to the limit at its own margin is 12%.) The limit therefore does not account for the low spread in lopsided counties, and the data cannot say what does. One candidate is that the losing party has few precincts in those counties, and another is that margins are compressed near one side of the scale well short of the mathematical limit. This chapter reports the pattern and does not read the negative correlation as a finding about competitiveness. The link of spread to Democratic lean does not come from the tails. Within 50 points the correlation of spread with lean is +0.41 (95% CI 0.32 to 0.49), against +0.41 (95% CI 0.33 to 0.49) across all counties.

### Near-tied counties differ widely in spread

A near-tied county has a margin under 5 points and at least 20 precincts. The group has 111 counties with 18.9 million two-party votes. Table 8 shows their spreads. The median is 23.9 (95% CI 22.8 to 24.9) points, against 3.4 for the median county if voters were assigned to precincts at random, and the range runs from 10.1 to 58.1. A spread of 30 points or more occurs in 29 counties, 26.1% of the group.

Table 8. Near-tied counties differ widely in how much their precinct margins vary

The median near-tied spread is above the 15.6 of all counties. Near-tied counties are larger, though, with a median of 78,269 two-party votes against 13,707 for the median county with a spread, and larger counties have wider spreads. The comparison of the two medians therefore mixes closeness with size.

Their votes are spread across the range of precinct margins. Near-tied counties cast 35.6% of their votes in precincts decided by under 10 points, against 18.5% in all precincts, and 38.2% in precincts decided by 20 points or more, against 65.0%. The landslide share divides into 17.5% in Democratic precincts and 20.7% in Republican ones, and precincts decided by 40 points or more held 10.5%. A county built from two landslides would have at least 20% of its votes in Democratic landslide precincts and at least 20% in Republican ones. Of the 111 counties, 39 (35.1%) meet that test. The near-tied counties as a group hold more of their votes in close precincts than the country does and fewer in landslide precincts, and they differ from one another in how the votes divide.

The counties in Table 1 fall at different points of this range. Bucks County, with a spread of 14.8, is in the lowest bin of Table 8, and Centre County, at 36.3, is past the 30-point line.

### What these data cannot show

The chapter describes one election. It says nothing about whether precinct margins are spreading or narrowing, and it makes no comparison with earlier years. Planned, Sorting by geographic scale, 2016 to 2024 (https://vishalsingh.org/politics/sorting-by-geographic-scale; planned), a planned chapter, will compare precincts across elections, and Chapter 6.1, Nationalization of the county vote (https://vishalsingh.org/politics/nationalization-of-the-county-vote) measures how closely county results move together from one election to the next.

A precinct is a reporting unit and not a neighborhood. The file has no boundaries, so the data cannot say which precincts are adjacent, and a county with a wide spread need not have opposed precincts next to each other. Units also differ in kind. Units labelled absentee, provisional, early voting, mail, failsafe, military or overseas, and units labelled as statistical adjustments, hold 1.5% of votes across 870 units, and they are buckets of ballots and not places. Table 9 repeats the main statistics without them and without the counties where they hold 20% of votes or more. That leaves 2,721 counties with a spread and 106 near-tied counties, against 111 in the full sample.

Table 9. Dropping ballot-bucket units moves each correlation by at most 0.02 and each vote share by at most 0.3 points

A precinct margin describes a place and not the voters in it. A precinct that gave one party 60% or more still holds voters of the other. Ecological inference, which moves from places to individuals, can fail, because a pattern across places can differ from the pattern among individuals [5]. The results also depend on the units. Shares and spreads change with the size and shape of the areas, a problem known as the modifiable areal unit problem [6], and this chapter uses the units that election offices happened to report. The 64 Louisiana parishes, the 6 other counties and Alaska that are left out are not a random set. The cutoffs for near-tied counties and for a wide spread are choices, and so are the vote weights and the 50-point cutoff behind the correlation of spread with distance from an even split. That correlation is near zero only in the vote-weighted comparisons within 50 points or less. A single spread cannot tell a county with two humps from a county with a long tail. The random-assignment benchmark holds each unit's size and its county's margin fixed and does not model why voters differ across precincts. Nothing here identifies why spread is wider in some counties. It goes with lean, size, nonwhite share and place type, and the controls are few and linear.

## Tables

### Table 1. Bucks County precincts cluster near an even split, while Centre County precincts form two groups, one on each side

Share of each county's 2024 two-party votes cast in precincts in each 10-point band of margin

| county | n | share | x0 | x1 |
| --- | ---: | ---: | ---: | ---: |
| Bucks County, PA | 0 | 0 | −100 | −90 |
| Bucks County, PA | 0 | 0 | −90 | −80 |
| Bucks County, PA | 0 | 0 | −80 | −70 |
| Bucks County, PA | 0 | 0 | −70 | −60 |
| Bucks County, PA | 0 | 0 | −60 | −50 |
| Bucks County, PA | 0 | 0 | −50 | −40 |
| Bucks County, PA | 4 | 1.05 | −40 | −30 |
| Bucks County, PA | 25 | 8.35 | −30 | −20 |
| Bucks County, PA | 54 | 17.71 | −20 | −10 |
| Bucks County, PA | 83 | 27.62 | −10 | 0 |
| Bucks County, PA | 68 | 22.48 | 0 | 10 |
| Bucks County, PA | 40 | 13.77 | 10 | 20 |
| Bucks County, PA | 15 | 5.06 | 20 | 30 |
| Bucks County, PA | 13 | 3.63 | 30 | 40 |
| Bucks County, PA | 2 | 0.315 | 40 | 50 |
| Bucks County, PA | 0 | 0 | 50 | 60 |
| Bucks County, PA | 0 | 0 | 60 | 70 |
| Bucks County, PA | 0 | 0 | 70 | 80 |
| Bucks County, PA | 0 | 0 | 80 | 90 |
| Bucks County, PA | 0 | 0 | 90 | 100 |
| Centre County, PA | 0 | 0 | −100 | −90 |
| Centre County, PA | 0 | 0 | −90 | −80 |
| Centre County, PA | 1 | 0.333 | −80 | −70 |
| Centre County, PA | 5 | 4.17 | −70 | −60 |
| Centre County, PA | 8 | 6.12 | −60 | −50 |
| Centre County, PA | 12 | 6.15 | −50 | −40 |
| Centre County, PA | 7 | 7.06 | −40 | −30 |
| Centre County, PA | 8 | 10.56 | −30 | −20 |
| Centre County, PA | 5 | 5.43 | −20 | −10 |
| Centre County, PA | 3 | 4.12 | −10 | 0 |
| Centre County, PA | 2 | 1.34 | 0 | 10 |
| Centre County, PA | 7 | 11.96 | 10 | 20 |
| Centre County, PA | 8 | 14.10 | 20 | 30 |
| Centre County, PA | 7 | 12.99 | 30 | 40 |
| Centre County, PA | 7 | 9.71 | 40 | 50 |
| Centre County, PA | 3 | 2.83 | 50 | 60 |
| Centre County, PA | 4 | 3.13 | 60 | 70 |
| Centre County, PA | 0 | 0 | 70 | 80 |
| Centre County, PA | 0 | 0 | 80 | 90 |
| Centre County, PA | 0 | 0 | 90 | 100 |

Note: The number in the tooltip is the number of precincts in the band. The two counties were chosen for the contrast between them, not at random.

Note: Full counts of votes: there is no sampling, so the shares carry no confidence interval.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/example_counties.json

### Table 2. Precincts are more often lopsided, and less often close, than counties or than random assignment of voters would make them

Share of 2024 two-party presidential votes cast in units decided by each margin, in percent of votes

| band | share | unit |
| --- | ---: | --- |
| Under 10 points | 18.52 | Precincts |
| Under 10 points | 23.13 | Counties |
| Under 10 points | 23.32 | Simulated precincts |
| 20 points or more | 64.97 | Precincts |
| 20 points or more | 57.25 | Counties |
| 20 points or more | 56.58 | Simulated precincts |
| 40 points or more | 36.37 | Precincts |
| 40 points or more | 25.38 | Counties |
| 40 points or more | 24.96 | Simulated precincts |

Note: Full counts of votes: there is no sampling, so the shares carry no confidence interval.

Note: The simulated bars are means over 200 runs and move by at most 0.4 points across runs.

Note: The sample is 175,345 reporting units in 3,043 counties: Alaska, the 64 Louisiana parishes and 6 other counties whose precinct rows do not match the certified total are left out.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/landslide_shares.json

### Table 3. Spread inside counties is widest in Mississippi and Alabama and scattered across the Southwest and Plains

Vote-weighted standard deviation of precinct margins inside each county, 2024, in points of two-party margin; counties with at least 5 reporting units

No inline rows: the values of Table 3 are in https://vishalsingh.org/politics/data/precincts-within-counties/county_sd_map.json.

Views: Spread inside the county; County margin.

Note: Counties with fewer than 5 reporting units (190 of the 3,043 in the sample), the 64 Louisiana parishes, 6 other counties whose precinct rows do not match the certified total, Alaska and Kansas City, Missouri are drawn as no data.

Note: A county near the floor of 5 reporting units has a spread that one unit can move a long way.

Note: Full counts of votes: there is no sampling, so county margins and spreads carry no sampling error.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/county_sd_map.json

### Table 4. Spread of precinct margins falls from the largest metro counties to the least urban ones

Vote-weighted mean of county spreads by Rural-Urban Continuum Code group, 2024, in points of two-party margin

| Place type | Description | Rural-Urban Continuum Code | Mean spread (points) | Interval, low | Interval, high | Counties |
| --- | --- | --- | ---: | ---: | ---: | ---: |
| Largest metro | Metro area of 1 million or more | 1 | 24.8 | 23.5 | 26.1 | 419 |
| Smaller metro | Smaller metro area | 2 to 3 | 22.7 | 21.9 | 23.5 | 690 |
| Larger nonmetro | Nonmetro, larger towns | 4 to 7 | 19.4 | 18.7 | 20.1 | 861 |
| Least urban | Nonmetro, smaller towns and open country | 8 to 9 | 15.5 | 14.6 | 16.5 | 873 |

Note: The number in the tooltip is the number of counties in the group. 2,853 counties have at least 5 reporting units; 10 of them have no code in the demographics panel (the Connecticut counties, Kansas City, Missouri, and Oglala Lakota County, South Dakota) and are left out of the bars.

Note: The returns are full counts with no sampling error. The whiskers show how much a mean would move with a different set of counties, from a county bootstrap.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated; county demographics panel (ACS 2024, Rural-Urban Continuum Code 2023)

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/sd_by_place_type.json

### Table 5. Spread rises from the reddest counties to about Trump +14, then levels off

Vote-weighted standard deviation of precinct margins inside each county against the county two-party margin, 2024; one dot per county, sized by two-party votes

| County | Margin (points) | Spread (points) | Two-party votes | Precincts |
| --- | ---: | ---: | ---: | ---: |
| Autauga, AL | −46.7 | 17.4 | 27,923 | 21 |
| Baldwin, AL | −58.7 | 16.3 | 120,732 | 61 |
| Barbour, AL | −14.8 | 32.1 | 9,764 | 18 |
| Bibb, AL | −64.8 | 24.6 | 9,191 | 10 |
| Blount, AL | −81.6 | 6.7 | 27,930 | 26 |
| Bullock, AL | +46.1 | 42.8 | 4,084 | 10 |
| Butler, AL | −22.8 | 41.2 | 8,423 | 23 |
| Calhoun, AL | −45.1 | 37.0 | 48,106 | 44 |
| Chambers, AL | −23.4 | 30.5 | 14,116 | 18 |
| Cherokee, AL | −75.9 | 9.7 | 12,911 | 25 |
| Chilton, AL | −72.5 | 15.5 | 19,618 | 20 |
| Choctaw, AL | −24.0 | 55.1 | 6,618 | 34 |
| Clarke, AL | −17.1 | 41.6 | 11,892 | 31 |
| Clay, AL | −70.5 | 19.7 | 6,727 | 17 |
| Cleburne, AL | −84.1 | 8.2 | 7,593 | 16 |
| Coffee, AL | −58.4 | 26.2 | 22,096 | 29 |
| Colbert, AL | −46.8 | 26.4 | 26,851 | 36 |
| Conecuh, AL | −14.0 | 52.0 | 6,003 | 28 |
| Coosa, AL | −43.5 | 48.4 | 5,236 | 14 |
| Covington, AL | −72.8 | 15.1 | 16,991 | 27 |
| Crenshaw, AL | −54.9 | 31.7 | 6,457 | 17 |
| Cullman, AL | −81.1 | 9.6 | 42,743 | 51 |
| Dale, AL | −52.7 | 20.9 | 18,960 | 20 |
| Dallas, AL | +32.7 | 47.3 | 15,426 | 31 |
| Dekalb, AL | −74.4 | 10.2 | 29,391 | 46 |
| Elmore, AL | −52.5 | 22.7 | 41,148 | 31 |
| Escambia, AL | −46.6 | 39.9 | 14,848 | 31 |
| Etowah, AL | −56.1 | 37.1 | 45,680 | 33 |
| Fayette, AL | −72.5 | 21.8 | 8,300 | 26 |
| Franklin, AL | −73.8 | 17.8 | 11,985 | 26 |
| Geneva, AL | −77.4 | 10.6 | 12,320 | 23 |
| Greene, AL | +55.9 | 21.4 | 4,018 | 16 |
| Hale, AL | +6.9 | 37.0 | 7,237 | 16 |
| Henry, AL | −51.1 | 24.4 | 9,252 | 16 |
| Houston, AL | −48.2 | 31.8 | 43,821 | 30 |
| Jackson, AL | −71.9 | 8.8 | 23,349 | 32 |
| Jefferson, AL | +10.6 | 53.5 | 293,235 | 179 |
| Lamar, AL | −76.4 | 15.6 | 6,839 | 27 |
| Lauderdale, AL | −52.0 | 27.6 | 43,034 | 33 |
| Lawrence, AL | −62.7 | 37.2 | 16,007 | 31 |
| Lee, AL | −28.2 | 28.7 | 71,818 | 27 |
| Limestone, AL | −44.4 | 24.2 | 52,468 | 27 |
| Lowndes, AL | +37.5 | 44.6 | 5,625 | 14 |
| Macon, AL | +56.7 | 38.4 | 7,766 | 16 |
| Madison, AL | −9.1 | 31.9 | 193,254 | 81 |
| Marengo, AL | −3.8 | 38.7 | 9,626 | 20 |
| Marion, AL | −82.2 | 4.1 | 13,442 | 17 |
| Marshall, AL | −72.2 | 7.1 | 39,987 | 31 |
| Mobile, AL | −16.6 | 50.2 | 172,814 | 82 |
| Monroe, AL | −23.3 | 50.6 | 9,747 | 29 |
| Montgomery, AL | +31.1 | 40.0 | 88,423 | 53 |
| Morgan, AL | −53.1 | 31.9 | 52,841 | 41 |
| Perry, AL | +42.9 | 46.9 | 4,443 | 14 |
| Pickens, AL | −23.5 | 47.9 | 8,853 | 21 |
| Pike, AL | −25.3 | 41.8 | 13,123 | 36 |
| Randolph, AL | −65.2 | 23.0 | 11,022 | 22 |
| Russell, AL | +1.7 | 40.2 | 20,500 | 20 |
| St. Clair, AL | −64.6 | 14.0 | 43,141 | 32 |
| Shelby, AL | −41.3 | 16.8 | 112,753 | 40 |
| Sumter, AL | +41.4 | 23.8 | 5,267 | 15 |
| Talladega, AL | −33.9 | 30.2 | 32,998 | 28 |
| Tallapoosa, AL | −49.9 | 37.2 | 19,859 | 28 |
| Tuscaloosa, AL | −20.6 | 47.1 | 84,123 | 56 |
| Walker, AL | −72.3 | 16.2 | 29,566 | 47 |
| Washington, AL | −55.6 | 35.8 | 8,397 | 21 |
| Wilcox, AL | +31.6 | 48.9 | 5,242 | 21 |
| Winston, AL | −84.0 | 4.8 | 11,075 | 20 |
| Apache, AZ | +19.2 | 57.9 | 31,667 | 44 |
| Cochise, AZ | −23.4 | 26.6 | 58,232 | 54 |
| Coconino, AZ | +20.2 | 34.4 | 69,080 | 75 |
| Gila, AZ | −37.9 | 28.2 | 27,405 | 39 |
| Graham, AZ | −48.6 | 34.3 | 15,044 | 23 |
| Greenlee, AZ | −41.5 | 17.5 | 3,262 | 6 |
| La Paz, AZ | −44.5 | 22.5 | 7,571 | 11 |
| Maricopa, AZ | −3.5 | 24.2 | 2,031,547 | 907 |
| Mohave, AZ | −56.1 | 9.4 | 109,725 | 24 |
| Navajo, AZ | −17.4 | 52.7 | 50,234 | 17 |
| Pima, AZ | +15.3 | 24.6 | 507,119 | 265 |
| Pinal, AZ | −22.3 | 17.9 | 207,582 | 108 |
| Santa Cruz, AZ | +18.8 | 19.2 | 18,950 | 31 |
| Yavapai, AZ | −34.0 | 20.9 | 147,083 | 54 |
| Yuma, AZ | −20.6 | 24.2 | 67,568 | 44 |
| Arkansas, AR | −44.9 | 39.5 | 5,454 | 30 |
| Ashley, AR | −48.7 | 40.0 | 6,919 | 30 |
| Baxter, AR | −57.8 | 5.8 | 20,594 | 11 |
| Benton, AR | −27.7 | 20.6 | 124,948 | 426 |
| Boone, AR | −66.1 | 9.1 | 16,822 | 12 |
| Bradley, AR | −39.4 | 44.8 | 3,174 | 14 |
| Calhoun, AR | −63.1 | 18.1 | 2,053 | 8 |
| Carroll, AR | −32.4 | 33.2 | 11,282 | 11 |
| Chicot, AR | +4.0 | 49.0 | 3,454 | 7 |
| Clark, AR | −20.9 | 35.2 | 7,485 | 20 |
| Clay, AR | −62.8 | 9.1 | 4,875 | 17 |
| Cleburne, AR | −69.0 | 9.7 | 12,536 | 34 |
| Cleveland, AR | −68.5 | 22.5 | 3,328 | 17 |
| Columbia, AR | −37.0 | 35.1 | 7,833 | 14 |
| Conway, AR | −41.3 | 25.2 | 8,342 | 31 |
| Craighead, AR | −38.3 | 27.2 | 36,362 | 53 |
| Crawford, AR | −59.3 | 7.5 | 23,368 | 13 |
| Crittenden, AR | +2.3 | 41.8 | 14,390 | 17 |
| Cross, AR | −48.6 | 40.6 | 6,395 | 14 |
| Dallas, AR | −30.0 | 47.2 | 2,280 | 9 |
| Desha, AR | −4.9 | 45.7 | 3,443 | 21 |
| Drew, AR | −34.4 | 29.2 | 6,253 | 17 |
| Faulkner, AR | −33.1 | 29.8 | 53,109 | 51 |
| Franklin, AR | −63.8 | 9.4 | 6,814 | 39 |
| Fulton, AR | −63.4 | 9.0 | 4,946 | 10 |
| Garland, AR | −37.1 | 20.5 | 41,374 | 52 |
| Grant, AR | −70.0 | 9.4 | 7,947 | 18 |
| Greene, AR | −62.3 | 8.9 | 15,552 | 11 |
| Hempstead, AR | −40.5 | 41.1 | 5,969 | 24 |
| Hot Spring, AR | −53.2 | 29.0 | 12,044 | 32 |
| Howard, AR | −47.4 | 34.8 | 4,404 | 9 |
| Independence, AR | −60.8 | 17.1 | 13,712 | 34 |
| Izard, AR | −67.3 | 9.2 | 5,803 | 45 |
| Jackson, AR | −49.6 | 30.7 | 4,692 | 45 |
| Jefferson, AR | +20.4 | 59.6 | 21,270 | 169 |
| Johnson, AR | −52.5 | 12.6 | 8,873 | 11 |
| Lafayette, AR | −39.0 | 42.9 | 2,287 | 9 |
| Lawrence, AR | −65.4 | 9.2 | 5,573 | 28 |
| Lee, AR | +3.6 | 43.2 | 2,451 | 9 |
| Lincoln, AR | −51.0 | 51.2 | 3,315 | 26 |
| Little River, AR | −55.1 | 27.9 | 4,828 | 20 |
| Logan, AR | −63.5 | 9.4 | 8,031 | 36 |
| Lonoke, AR | −54.8 | 20.0 | 30,015 | 55 |
| Madison, AR | −59.6 | 6.2 | 7,376 | 10 |
| Marion, AR | −61.2 | 9.2 | 7,731 | 29 |
| Miller, AR | −51.7 | 35.1 | 15,611 | 19 |
| Mississippi, AR | −32.2 | 45.1 | 10,537 | 16 |
| Monroe, AR | −16.0 | 48.4 | 2,387 | 24 |
| Montgomery, AR | −64.5 | 9.0 | 3,632 | 16 |
| Nevada, AR | −40.4 | 43.2 | 2,851 | 20 |
| Newton, AR | −65.3 | 18.2 | 3,707 | 19 |
| Ouachita, AR | −19.4 | 38.3 | 8,468 | 18 |
| Perry, AR | −58.8 | 9.1 | 4,482 | 17 |
| Phillips, AR | +13.5 | 39.5 | 4,852 | 10 |
| Pike, AR | −74.0 | 14.3 | 4,306 | 11 |
| Poinsett, AR | −64.5 | 9.4 | 6,966 | 12 |
| Polk, AR | −71.8 | 7.5 | 8,132 | 17 |
| Pope, AR | −53.5 | 18.9 | 23,605 | 55 |
| Prairie, AR | −66.8 | 16.1 | 3,152 | 24 |
| Pulaski, AR | +22.7 | 35.3 | 150,015 | 132 |
| Randolph, AR | −65.0 | 10.6 | 6,505 | 29 |
| St Francis, AR | +0.8 | 53.8 | 5,862 | 15 |
| Saline, AR | −41.0 | 20.1 | 56,345 | 42 |
| Scott, AR | −74.5 | 10.5 | 3,338 | 26 |
| Searcy, AR | −73.2 | 8.1 | 3,816 | 15 |
| Sebastian, AR | −38.5 | 27.2 | 44,371 | 180 |
| Sevier, AR | −62.8 | 18.8 | 4,634 | 9 |
| Sharp, AR | −63.9 | 10.4 | 7,294 | 25 |
| Stone, AR | −63.1 | 7.6 | 5,897 | 18 |
| Union, AR | −34.0 | 41.0 | 15,215 | 28 |
| Van Buren, AR | −61.5 | 11.9 | 7,460 | 21 |
| Washington, AR | −6.9 | 33.1 | 94,022 | 224 |
| White, AR | −62.6 | 14.1 | 30,155 | 92 |
| Woodruff, AR | −33.1 | 45.0 | 2,273 | 20 |
| Yell, AR | −61.9 | 16.1 | 6,360 | 28 |
| Alameda, CA | +56.0 | 26.1 | 640,028 | 822 |
| Alpine, CA | +32.7 | 20.6 | 722 | 5 |
| Amador, CA | −28.5 | 20.3 | 21,742 | 79 |
| Butte, CA | −3.1 | 31.4 | 91,203 | 212 |
| Calaveras, CA | −28.8 | 25.8 | 25,806 | 50 |
| Colusa, CA | −29.0 | 20.6 | 6,845 | 19 |
| Contra Costa, CA | +39.3 | 24.3 | 510,211 | 1,202 |
| Del Norte, CA | −16.8 | 18.1 | 10,257 | 36 |
| El Dorado, CA | −12.3 | 25.0 | 108,695 | 260 |
| Fresno, CA | −4.5 | 27.6 | 316,996 | 684 |
| Glenn, CA | −35.7 | 27.4 | 9,928 | 113 |
| Humboldt, CA | +29.8 | 30.0 | 61,284 | 164 |
| Imperial, CA | −0.7 | 23.3 | 52,228 | 215 |
| Inyo, CA | −2.9 | 19.6 | 8,650 | 28 |
| Kern, CA | −21.6 | 26.4 | 275,461 | 1,082 |
| Kings, CA | −23.4 | 21.6 | 40,435 | 174 |
| Lake, CA | −1.4 | 14.4 | 25,945 | 73 |
| Lassen, CA | −55.2 | 16.0 | 10,972 | 65 |
| Los Angeles, CA | +34.0 | 29.4 | 3,605,749 | 4,808 |
| Madera, CA | −21.3 | 21.1 | 53,240 | 112 |
| Marin, CA | +65.7 | 14.9 | 140,102 | 217 |
| Mariposa, CA | −21.5 | 25.8 | 9,159 | 32 |
| Mendocino, CA | +28.1 | 25.1 | 37,197 | 240 |
| Merced, CA | −3.9 | 28.4 | 82,772 | 621 |
| Modoc, CA | −48.1 | 14.3 | 3,874 | 30 |
| Mono, CA | +21.1 | 31.4 | 5,808 | 22 |
| Monterey, CA | +30.8 | 20.8 | 142,286 | 403 |
| Napa, CA | +36.1 | 17.7 | 63,325 | 336 |
| Nevada, CA | +12.7 | 31.3 | 59,904 | 180 |
| Orange, CA | +2.8 | 25.4 | 1,346,071 | 2,899 |
| Placer, CA | −8.7 | 23.9 | 227,596 | 468 |
| Plumas, CA | −17.5 | 20.0 | 9,745 | 28 |
| Riverside, CA | −1.3 | 24.9 | 914,400 | 1,711 |
| Sacramento, CA | +20.4 | 27.2 | 633,476 | 1,249 |
| San Benito, CA | +12.9 | 22.8 | 26,881 | 80 |
| San Bernardino, CA | −2.1 | 24.1 | 738,081 | 2,738 |
| San Diego, CA | +17.3 | 26.6 | 1,433,911 | 3,315 |
| San Francisco, CA | +67.6 | 18.0 | 386,298 | 1,014 |
| San Joaquin, CA | −0.9 | 25.2 | 255,429 | 437 |
| San Luis Obispo, CA | +11.2 | 28.3 | 146,169 | 251 |
| San Mateo, CA | +52.1 | 15.9 | 319,349 | 523 |
| Santa Barbara, CA | +27.6 | 31.9 | 178,735 | 424 |
| Santa Clara, CA | +41.6 | 20.7 | 721,284 | 1,311 |
| Santa Cruz, CA | +56.6 | 17.8 | 128,801 | 282 |
| Shasta, CA | −37.4 | 16.0 | 86,661 | 128 |
| Sierra, CA | −24.9 | 22.6 | 1,707 | 19 |
| Siskiyou, CA | −19.9 | 29.1 | 20,790 | 105 |
| Solano, CA | +23.8 | 24.9 | 184,102 | 366 |
| Sonoma, CA | +47.8 | 14.5 | 242,395 | 755 |
| Stanislaus, CA | −11.2 | 22.6 | 192,155 | 469 |
| Sutter, CA | −32.2 | 14.8 | 38,388 | 48 |
| Tehama, CA | −42.7 | 16.5 | 25,869 | 68 |
| Trinity, CA | −9.8 | 13.5 | 5,428 | 14 |
| Tulare, CA | −21.2 | 24.3 | 135,075 | 584 |
| Tuolumne, CA | −22.4 | 17.8 | 28,098 | 78 |
| Ventura, CA | +15.6 | 24.4 | 374,949 | 1,715 |
| Yolo, CA | +37.6 | 31.3 | 89,249 | 95 |
| Yuba, CA | −26.6 | 20.2 | 29,216 | 63 |
| Adams, CO | +9.3 | 20.1 | 227,080 | 275 |
| Alamosa, CO | −11.1 | 20.4 | 7,301 | 8 |
| Arapahoe, CO | +20.7 | 16.7 | 316,036 | 394 |
| Archuleta, CO | −14.4 | 9.9 | 9,122 | 8 |
| Baca, CO | −72.0 | 7.4 | 1,961 | 9 |
| Bent, CO | −39.7 | 24.7 | 2,141 | 5 |
| Boulder, CO | +57.3 | 17.6 | 190,907 | 190 |
| Broomfield, CO | +29.4 | 10.9 | 45,497 | 58 |
| Chaffee, CO | +14.0 | 20.3 | 14,026 | 11 |
| Cheyenne, CO | −79.2 | 10.3 | 1,038 | 5 |
| Clear Creek, CO | +17.1 | 9.3 | 5,916 | 9 |
| Conejos, CO | −18.3 | 27.8 | 3,985 | 10 |
| Costilla, CO | +15.2 | 23.8 | 2,005 | 8 |
| Crowley, CO | −48.9 | 4.9 | 1,653 | 6 |
| Delta, CO | −36.5 | 23.3 | 18,978 | 20 |
| Denver, CO | +57.7 | 16.6 | 353,399 | 301 |
| Douglas, CO | −7.2 | 14.3 | 237,859 | 204 |
| Eagle, CO | +25.1 | 17.1 | 27,091 | 34 |
| Elbert, CO | −52.3 | 8.5 | 19,977 | 18 |
| El Paso, CO | −10.1 | 21.0 | 370,530 | 324 |
| Fremont, CO | −39.4 | 9.3 | 24,839 | 20 |
| Garfield, CO | +2.1 | 38.2 | 29,621 | 27 |
| Gilpin, CO | +13.2 | 16.6 | 3,983 | 6 |
| Grand, CO | −0.8 | 28.9 | 9,565 | 12 |
| Gunnison, CO | +30.2 | 31.2 | 10,576 | 15 |
| Huerfano, CO | −8.8 | 9.5 | 4,311 | 5 |
| Jefferson, CO | +20.0 | 14.1 | 351,380 | 296 |
| Kit Carson, CO | −69.4 | 7.6 | 3,639 | 13 |
| Lake, CO | +17.1 | 7.9 | 3,756 | 6 |
| La Plata, CO | +19.2 | 33.6 | 34,701 | 33 |
| Larimer, CO | +18.1 | 25.8 | 219,056 | 155 |
| Las Animas, CO | −13.8 | 21.7 | 7,604 | 7 |
| Lincoln, CO | −65.7 | 7.5 | 2,522 | 13 |
| Logan, CO | −57.8 | 15.9 | 9,953 | 16 |
| Mesa, CO | −24.9 | 19.2 | 89,412 | 67 |
| Moffat, CO | −64.2 | 9.5 | 6,525 | 13 |
| Montezuma, CO | −21.5 | 21.8 | 14,765 | 12 |
| Montrose, CO | −33.3 | 17.0 | 25,058 | 21 |
| Morgan, CO | −49.8 | 15.6 | 13,121 | 18 |
| Otero, CO | −27.1 | 24.2 | 8,684 | 17 |
| Ouray, CO | +21.6 | 23.8 | 4,015 | 5 |
| Park, CO | −17.0 | 17.1 | 11,669 | 13 |
| Phillips, CO | −64.2 | 8.7 | 2,300 | 8 |
| Pitkin, CO | +45.2 | 5.2 | 10,924 | 12 |
| Prowers, CO | −51.5 | 11.6 | 5,060 | 5 |
| Pueblo, CO | −5.3 | 24.3 | 83,016 | 144 |
| Rio Blanco, CO | −64.9 | 9.8 | 3,625 | 5 |
| Rio Grande, CO | −23.8 | 18.5 | 6,049 | 15 |
| Routt, CO | +28.5 | 26.9 | 15,884 | 19 |
| Saguache, CO | +3.9 | 34.0 | 3,281 | 7 |
| San Miguel, CO | +50.7 | 30.0 | 4,683 | 6 |
| Sedgwick, CO | −57.5 | 7.5 | 1,331 | 5 |
| Summit, CO | +38.3 | 8.9 | 17,006 | 20 |
| Teller, CO | −36.4 | 5.6 | 15,921 | 14 |
| Washington, CO | −76.2 | 4.3 | 2,765 | 6 |
| Weld, CO | −21.5 | 21.9 | 175,221 | 184 |
| Yuma, CO | −66.8 | 8.3 | 4,565 | 14 |
| Fairfield, CT | +19.9 | 17.6 | 445,282 | 190 |
| Hartford, CT | +22.9 | 23.7 | 421,938 | 167 |
| Litchfield, CT | −8.2 | 20.7 | 104,392 | 48 |
| Middlesex, CT | +13.1 | 13.5 | 95,827 | 33 |
| New Haven, CT | +12.2 | 27.5 | 390,416 | 204 |
| New London, CT | +12.8 | 17.2 | 135,048 | 54 |
| Tolland, CT | +8.2 | 18.5 | 80,084 | 28 |
| Windham, CT | −10.4 | 17.3 | 55,984 | 32 |
| Kent, DE | +2.0 | 30.3 | 86,680 | 98 |
| New Castle, DE | +33.1 | 23.3 | 271,568 | 312 |
| Sussex, DE | −11.1 | 23.7 | 145,861 | 119 |
| District of Columbia, DC | +86.6 | 5.9 | 315,261 | 144 |
| Alachua, FL | +21.3 | 29.3 | 134,517 | 63 |
| Baker, FL | −73.4 | 12.3 | 14,908 | 9 |
| Bay, FL | −47.9 | 17.0 | 96,698 | 29 |
| Bradford, FL | −57.5 | 28.2 | 13,866 | 13 |
| Brevard, FL | −21.0 | 13.4 | 357,766 | 150 |
| Broward, FL | +17.1 | 26.3 | 866,280 | 358 |
| Calhoun, FL | −68.0 | 22.5 | 6,388 | 10 |
| Charlotte, FL | −34.2 | 10.4 | 122,930 | 81 |
| Citrus, FL | −46.2 | 7.7 | 97,632 | 32 |
| Clay, FL | −39.6 | 24.6 | 125,637 | 48 |
| Collier, FL | −33.3 | 12.6 | 214,987 | 67 |
| Columbia, FL | −50.5 | 21.0 | 33,358 | 26 |
| Desoto, FL | −43.2 | 28.7 | 12,413 | 15 |
| Dixie, FL | −70.8 | 13.2 | 8,103 | 10 |
| Duval, FL | −1.5 | 31.3 | 465,650 | 160 |
| Escambia, FL | −19.8 | 28.8 | 161,008 | 80 |
| Flagler, FL | −28.4 | 9.5 | 79,445 | 21 |
| Franklin, FL | −44.2 | 28.6 | 6,701 | 8 |
| Gadsden, FL | +30.9 | 39.8 | 21,698 | 25 |
| Gilchrist, FL | −68.6 | 7.2 | 10,593 | 10 |
| Glades, FL | −53.5 | 24.5 | 5,256 | 13 |
| Gulf, FL | −54.5 | 24.1 | 8,654 | 10 |
| Hamilton, FL | −39.3 | 30.8 | 5,691 | 8 |
| Hardee, FL | −56.7 | 23.6 | 8,088 | 12 |
| Hendry, FL | −38.6 | 29.0 | 13,349 | 10 |
| Hernando, FL | −37.3 | 9.7 | 109,877 | 32 |
| Highlands, FL | −41.0 | 17.3 | 51,609 | 25 |
| Hillsborough, FL | −3.1 | 24.2 | 663,472 | 448 |
| Holmes, FL | −80.6 | 4.5 | 9,075 | 8 |
| Indian River, FL | −27.5 | 10.9 | 98,391 | 34 |
| Jackson, FL | −46.4 | 25.2 | 21,966 | 14 |
| Jefferson, FL | −18.7 | 20.3 | 8,440 | 16 |
| Lafayette, FL | −76.4 | 15.5 | 3,737 | 5 |
| Lake, FL | −24.9 | 17.6 | 225,046 | 92 |
| Lee, FL | −28.6 | 13.8 | 389,901 | 99 |
| Leon, FL | +22.0 | 29.8 | 154,917 | 132 |
| Levy, FL | −50.5 | 14.5 | 24,239 | 13 |
| Liberty, FL | −67.3 | 30.8 | 3,464 | 8 |
| Madison, FL | −29.0 | 34.1 | 9,105 | 11 |
| Manatee, FL | −23.7 | 15.2 | 227,160 | 71 |
| Marion, FL | −31.9 | 17.7 | 212,609 | 106 |
| Martin, FL | −31.3 | 10.8 | 97,660 | 28 |
| Miami-Dade, FL | −11.5 | 34.0 | 1,085,945 | 721 |
| Monroe, FL | −18.5 | 22.9 | 43,997 | 33 |
| Nassau, FL | −47.3 | 22.6 | 65,088 | 18 |
| Okaloosa, FL | −42.9 | 15.4 | 112,383 | 52 |
| Okeechobee, FL | −54.1 | 10.9 | 15,986 | 11 |
| Orange, FL | +13.8 | 21.1 | 599,086 | 257 |
| Osceola, FL | −1.5 | 20.2 | 170,918 | 127 |
| Palm Beach, FL | +0.8 | 23.9 | 739,348 | 781 |
| Pasco, FL | −25.5 | 12.8 | 315,229 | 120 |
| Pinellas, FL | −5.3 | 22.8 | 511,924 | 286 |
| Polk, FL | −20.9 | 23.0 | 345,923 | 172 |
| Putnam, FL | −48.1 | 27.6 | 36,054 | 37 |
| St. Johns, FL | −31.6 | 11.1 | 195,621 | 53 |
| St. Lucie, FL | −9.1 | 18.9 | 183,810 | 61 |
| Santa Rosa, FL | −51.4 | 11.7 | 111,349 | 41 |
| Sarasota, FL | −18.3 | 16.8 | 275,887 | 103 |
| Seminole, FL | −3.6 | 14.8 | 250,452 | 82 |
| Sumter, FL | −37.8 | 8.9 | 104,685 | 30 |
| Suwannee, FL | −61.3 | 18.6 | 21,778 | 14 |
| Taylor, FL | −60.0 | 35.5 | 9,945 | 14 |
| Union, FL | −68.7 | 7.0 | 6,195 | 8 |
| Volusia, FL | −21.9 | 19.0 | 307,823 | 143 |
| Wakulla, FL | −44.7 | 7.9 | 19,687 | 12 |
| Walton, FL | −58.2 | 9.9 | 49,257 | 21 |
| Washington, FL | −65.8 | 15.0 | 12,510 | 12 |
| Appling, GA | −62.5 | 36.4 | 8,321 | 9 |
| Baker, GA | −19.9 | 24.0 | 1,473 | 5 |
| Baldwin, GA | −2.2 | 35.8 | 18,733 | 14 |
| Banks, GA | −78.3 | 3.8 | 10,494 | 13 |
| Barrow, GA | −40.7 | 11.2 | 43,679 | 8 |
| Bartow, GA | −51.3 | 13.9 | 57,213 | 17 |
| Berrien, GA | −70.0 | 7.4 | 8,050 | 5 |
| Bibb, GA | +22.5 | 40.6 | 68,830 | 31 |
| Brooks, GA | −26.9 | 30.5 | 7,189 | 7 |
| Bryan, GA | −36.5 | 16.0 | 24,517 | 10 |
| Bulloch, GA | −29.1 | 28.5 | 32,499 | 16 |
| Burke, GA | −9.4 | 24.6 | 11,021 | 16 |
| Calhoun, GA | +12.3 | 32.5 | 2,053 | 5 |
| Camden, GA | −35.9 | 12.4 | 26,224 | 11 |
| Carroll, GA | −41.4 | 25.7 | 60,170 | 28 |
| Catoosa, GA | −55.8 | 6.7 | 34,854 | 11 |
| Charlton, GA | −56.4 | 25.1 | 4,614 | 6 |
| Chatham, GA | +18.1 | 38.5 | 140,094 | 87 |
| Chattooga, GA | −64.4 | 9.1 | 10,665 | 7 |
| Cherokee, GA | −39.3 | 15.3 | 160,980 | 42 |
| Clarke, GA | +38.7 | 16.1 | 52,346 | 24 |
| Clay, GA | +7.5 | 32.0 | 1,434 | 5 |
| Clayton, GA | +69.6 | 13.5 | 111,080 | 70 |
| Clinch, GA | −51.6 | 14.2 | 2,903 | 5 |
| Cobb, GA | +15.0 | 26.6 | 397,083 | 148 |
| Coffee, GA | −45.2 | 15.7 | 15,683 | 6 |
| Colquitt, GA | −50.3 | 35.0 | 16,565 | 19 |
| Columbia, GA | −25.8 | 21.5 | 85,281 | 46 |
| Cook, GA | −46.6 | 35.4 | 7,330 | 8 |
| Coweta, GA | −34.1 | 22.6 | 85,315 | 24 |
| Crawford, GA | −50.0 | 29.3 | 6,324 | 5 |
| Crisp, GA | −26.0 | 39.3 | 8,092 | 5 |
| Dade, GA | −67.0 | 9.1 | 8,147 | 7 |
| Decatur, GA | −24.0 | 27.9 | 11,512 | 10 |
| Dekalb, GA | +65.4 | 24.7 | 362,252 | 191 |
| Dodge, GA | −50.0 | 21.6 | 8,330 | 16 |
| Dooly, GA | −7.7 | 13.6 | 4,164 | 5 |
| Dougherty, GA | +41.3 | 36.0 | 33,735 | 25 |
| Douglas, GA | +31.7 | 32.1 | 70,236 | 25 |
| Early, GA | −11.5 | 37.5 | 4,876 | 5 |
| Effingham, GA | −49.3 | 12.0 | 36,087 | 20 |
| Elbert, GA | −43.5 | 23.5 | 9,560 | 11 |
| Emanuel, GA | −44.3 | 23.7 | 9,592 | 11 |
| Fannin, GA | −65.0 | 5.0 | 16,039 | 12 |
| Fayette, GA | −3.2 | 32.7 | 73,999 | 36 |
| Floyd, GA | −42.2 | 25.2 | 44,493 | 19 |
| Forsyth, GA | −33.5 | 16.9 | 136,790 | 29 |
| Franklin, GA | −72.8 | 8.4 | 12,106 | 7 |
| Fulton, GA | +45.4 | 38.7 | 529,389 | 450 |
| Gilmer, GA | −62.9 | 4.9 | 18,389 | 13 |
| Glynn, GA | −26.1 | 29.2 | 43,702 | 17 |
| Gordon, GA | −63.7 | 13.3 | 27,477 | 12 |
| Grady, GA | −38.4 | 40.4 | 10,675 | 13 |
| Greene, GA | −29.1 | 25.6 | 12,729 | 5 |
| Gwinnett, GA | +16.7 | 21.3 | 415,548 | 156 |
| Habersham, GA | −65.2 | 6.0 | 23,178 | 6 |
| Hall, GA | −44.1 | 22.0 | 101,338 | 31 |
| Hancock, GA | +35.5 | 33.4 | 4,228 | 10 |
| Haralson, GA | −74.7 | 6.9 | 16,304 | 12 |
| Harris, GA | −46.3 | 12.1 | 22,259 | 12 |
| Hart, GA | −55.0 | 12.1 | 14,274 | 7 |
| Heard, GA | −72.3 | 8.4 | 6,194 | 6 |
| Henry, GA | +29.8 | 31.3 | 128,235 | 37 |
| Houston, GA | −11.3 | 23.5 | 80,997 | 17 |
| Jeff Davis, GA | −68.5 | 25.6 | 5,859 | 9 |
| Jefferson, GA | −1.2 | 26.3 | 7,439 | 8 |
| Jenkins, GA | −30.6 | 37.0 | 3,396 | 5 |
| Jones, GA | −38.2 | 25.0 | 16,038 | 10 |
| Laurens, GA | −32.8 | 36.7 | 23,280 | 15 |
| Lee, GA | −43.7 | 11.7 | 17,612 | 10 |
| Liberty, GA | +17.5 | 25.7 | 22,900 | 12 |
| Lincoln, GA | −45.0 | 23.6 | 4,910 | 7 |
| Long, GA | −29.6 | 17.9 | 7,033 | 7 |
| Lowndes, GA | −18.1 | 35.3 | 47,568 | 18 |
| McDuffie, GA | −25.0 | 41.4 | 10,499 | 7 |
| McIntosh, GA | −28.7 | 25.4 | 7,375 | 5 |
| Macon, GA | +18.0 | 24.0 | 4,671 | 5 |
| Madison, GA | −55.1 | 18.5 | 16,704 | 12 |
| Marion, GA | −30.4 | 44.3 | 3,601 | 5 |
| Meriwether, GA | −25.6 | 25.4 | 11,748 | 14 |
| Mitchell, GA | −16.4 | 39.9 | 8,851 | 11 |
| Monroe, GA | −46.8 | 27.1 | 17,643 | 14 |
| Morgan, GA | −46.2 | 28.5 | 13,122 | 5 |
| Murray, GA | −71.8 | 5.0 | 17,424 | 7 |
| Muscogee, GA | +23.5 | 40.3 | 80,029 | 25 |
| Newton, GA | +15.2 | 39.9 | 58,732 | 19 |
| Oconee, GA | −36.3 | 11.8 | 27,044 | 8 |
| Paulding, GA | −24.3 | 21.1 | 94,571 | 21 |
| Peach, GA | −6.1 | 36.1 | 13,397 | 7 |
| Pickens, GA | −66.1 | 9.0 | 20,803 | 12 |
| Pierce, GA | −77.6 | 9.0 | 9,744 | 8 |
| Pike, GA | −73.7 | 7.9 | 12,512 | 8 |
| Polk, GA | −60.7 | 14.7 | 19,101 | 7 |
| Putnam, GA | −42.4 | 25.2 | 12,832 | 5 |
| Randolph, GA | +7.7 | 28.5 | 2,974 | 6 |
| Richmond, GA | +36.3 | 38.6 | 83,129 | 68 |
| Rockdale, GA | +47.8 | 20.9 | 44,876 | 16 |
| Screven, GA | −25.3 | 28.7 | 6,906 | 7 |
| Seminole, GA | −40.5 | 46.9 | 4,002 | 5 |
| Spalding, GA | −16.8 | 38.4 | 32,863 | 17 |
| Sumter, GA | +2.2 | 38.7 | 12,005 | 11 |
| Talbot, GA | +12.0 | 27.3 | 3,371 | 7 |
| Tattnall, GA | −53.6 | 13.7 | 8,482 | 8 |
| Telfair, GA | −39.4 | 24.1 | 4,204 | 6 |
| Terrell, GA | +4.1 | 42.3 | 4,328 | 6 |
| Thomas, GA | −24.2 | 39.7 | 22,017 | 20 |
| Tift, GA | −35.8 | 39.4 | 16,934 | 12 |
| Toombs, GA | −50.9 | 17.8 | 10,882 | 5 |
| Troup, GA | −24.5 | 36.5 | 31,149 | 13 |
| Twiggs, GA | −14.7 | 34.9 | 4,444 | 5 |
| Union, GA | −62.8 | 4.1 | 17,786 | 11 |
| Walker, GA | −59.6 | 10.7 | 31,898 | 11 |
| Walton, GA | −46.2 | 20.7 | 58,012 | 19 |
| Ware, GA | −43.3 | 46.6 | 14,347 | 13 |
| Washington, GA | −1.9 | 20.9 | 9,467 | 8 |
| Wayne, GA | −59.9 | 29.0 | 13,519 | 12 |
| White, GA | −68.8 | 8.9 | 16,745 | 10 |
| Whitfield, GA | −44.7 | 23.6 | 39,608 | 23 |
| Wilcox, GA | −49.3 | 34.2 | 3,340 | 6 |
| Wilkes, GA | −16.9 | 33.8 | 5,083 | 7 |
| Wilkinson, GA | −17.9 | 42.4 | 4,900 | 9 |
| Worth, GA | −50.5 | 36.8 | 9,291 | 12 |
| Hawaii, HI | +28.9 | 19.7 | 80,911 | 64 |
| Honolulu, HI | +22.0 | 23.7 | 334,790 | 302 |
| Kauai, HI | +19.9 | 21.2 | 29,478 | 31 |
| Maui, HI | +26.5 | 19.3 | 61,526 | 70 |
| Ada, ID | −10.6 | 34.1 | 259,875 | 197 |
| Adams, ID | −55.9 | 15.1 | 2,614 | 5 |
| Bannock, ID | −25.9 | 21.6 | 38,635 | 57 |
| Bear Lake, ID | −78.7 | 8.2 | 3,254 | 15 |
| Benewah, ID | −62.8 | 12.8 | 5,029 | 11 |
| Bingham, ID | −61.3 | 22.4 | 20,066 | 27 |
| Blaine, ID | +32.6 | 27.8 | 12,705 | 16 |
| Boise, ID | −55.6 | 12.5 | 4,792 | 7 |
| Bonner, ID | −47.2 | 25.2 | 29,002 | 30 |
| Bonneville, ID | −47.0 | 16.8 | 54,511 | 51 |
| Boundary, ID | −67.0 | 14.7 | 6,939 | 7 |
| Canyon, ID | −47.8 | 15.2 | 98,424 | 51 |
| Caribou, ID | −73.4 | 6.6 | 3,351 | 9 |
| Cassia, ID | −70.8 | 11.7 | 9,318 | 24 |
| Clearwater, ID | −64.2 | 7.7 | 4,324 | 14 |
| Custer, ID | −54.6 | 28.4 | 2,584 | 9 |
| Elmore, ID | −49.8 | 6.5 | 10,402 | 17 |
| Franklin, ID | −79.9 | 4.6 | 6,982 | 18 |
| Fremont, ID | −71.1 | 12.3 | 6,599 | 13 |
| Gem, ID | −67.3 | 8.8 | 10,406 | 14 |
| Gooding, ID | −61.9 | 8.7 | 5,776 | 6 |
| Idaho, ID | −69.6 | 10.9 | 9,608 | 28 |
| Jefferson, ID | −75.4 | 5.2 | 15,372 | 21 |

The first 500 of 2853 rows; every row is in https://vishalsingh.org/politics/report/precincts-within-counties/figures/sd_by_margin.json.

Note: The number in the tooltip is the county's number of reporting units. Kings County, New York, and the two Pennsylvania counties named in the text are labeled.

Note: The returns are full counts with no sampling error. The whiskers show how much a mean would move with a different set of counties, from a county bootstrap.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/sd_by_margin.json

### Table 6. Spread rises with Democratic lean, with or without controls for county size and state

Correlation between the spread of precinct margins and the county two-party margin, Democratic positive, across 2,853 counties, 2024, with 95% intervals

| Weighting | Controls | Correlation | Interval, low | Interval, high | Counties |
| --- | --- | ---: | ---: | ---: | ---: |
| Vote-weighted | No controls | +0.41 | +0.33 | +0.49 | 2,853 |
| Vote-weighted | Size fixed | +0.21 | +0.12 | +0.30 | 2,853 |
| Vote-weighted | Size and state fixed | +0.28 | +0.19 | +0.37 | 2,853 |
| Unweighted | No controls | +0.54 | +0.51 | +0.56 | 2,853 |
| Unweighted | Size fixed | +0.46 | +0.43 | +0.50 | 2,853 |
| Unweighted | Size and state fixed | +0.47 | +0.43 | +0.51 | 2,853 |

Note: Each interval resamples counties 2,000 times; a full count has no sampling error, so the interval says how much the correlation would move with a different set of counties.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/dispersion_partials.json

### Table 7. Spread falls with distance from an even split, except in vote-weighted comparisons of counties within 50 points

Correlation between the spread of precinct margins and the size of the county margin, among counties with a margin at or below each cutoff, 2024, with 95% intervals

| Cutoff (points of margin) | Weighting | Counties | No controls | Size fixed | Size and state fixed |
| ---: | --- | ---: | --- | --- | --- |
| 30 | Vote-weighted | 954 | −0.02 [−0.13, +0.08] | +0.01 [−0.09, +0.10] | −0.07 [−0.18, +0.02] |
| 30 | Unweighted | 954 | −0.12 [−0.18, −0.06] | −0.13 [−0.19, −0.07] | −0.17 [−0.23, −0.11] |
| 40 | Vote-weighted | 1,321 | −0.07 [−0.18, +0.04] | −0.03 [−0.13, +0.05] | −0.08 [−0.20, 0.00] |
| 40 | Unweighted | 1,321 | −0.20 [−0.25, −0.14] | −0.21 [−0.26, −0.15] | −0.25 [−0.30, −0.20] |
| 50 | Vote-weighted | 1,725 | −0.04 [−0.18, +0.08] | +0.01 [−0.12, +0.12] | −0.04 [−0.19, +0.06] |
| 50 | Unweighted | 1,725 | −0.26 [−0.30, −0.22] | −0.26 [−0.30, −0.21] | −0.31 [−0.36, −0.27] |
| 60 | Vote-weighted | 2,156 | −0.15 [−0.26, −0.04] | −0.08 [−0.18, +0.03] | −0.11 [−0.24, −0.02] |
| 60 | Unweighted | 2,156 | −0.38 [−0.41, −0.34] | −0.36 [−0.39, −0.32] | −0.39 [−0.44, −0.35] |
| 70 | Vote-weighted | 2,593 | −0.24 [−0.34, −0.13] | −0.15 [−0.25, −0.04] | −0.20 [−0.33, −0.10] |
| 70 | Unweighted | 2,593 | −0.48 [−0.51, −0.45] | −0.44 [−0.47, −0.40] | −0.48 [−0.52, −0.45] |
| 100 | Vote-weighted | 2,853 | −0.29 [−0.39, −0.20] | −0.19 [−0.30, −0.09] | −0.25 [−0.37, −0.16] |
| 100 | Unweighted | 2,853 | −0.55 [−0.57, −0.52] | −0.49 [−0.52, −0.46] | −0.55 [−0.58, −0.52] |

Note: The last cutoff, 100 points, includes every county, because no margin can be larger. The number in the tooltip is the number of counties in the row. Each interval resamples the counties of the row 2,000 times; a full count has no sampling error, so the interval says how much the correlation would move with a different set of counties.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/ext_by_cutoff.json

### Table 8. Near-tied counties differ widely in how much their precinct margins vary

Share of the near-tied counties in each 5-point bin of spread of precinct margins, 2024; margin under 5 points and at least 20 precincts

| n | share | x0 | x1 |
| ---: | ---: | ---: | ---: |
| 11 | 9.91 | 10 | 15 |
| 21 | 18.92 | 15 | 20 |
| 34 | 30.63 | 20 | 25 |
| 16 | 14.41 | 25 | 30 |
| 11 | 9.91 | 30 | 35 |
| 11 | 9.91 | 35 | 40 |
| 5 | 4.50 | 40 | 45 |
| 1 | 0.901 | 45 | 50 |
| 0 | 0 | 50 | 55 |
| 1 | 0.901 | 55 | 60 |

Note: The number in the tooltip is the number of counties in the bin.

Note: Full counts of votes: there is no sampling, so the shares carry no confidence interval.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/near_tied_sd.json

### Table 9. Dropping ballot-bucket units moves each correlation by at most 0.02 and each vote share by at most 0.3 points

Main statistics in the full sample and in a side check that drops ballot-bucket units, 2024 two-party presidential returns

| Statistic | Full sample | Without ballot-bucket units |
| --- | --- | --- |
| Counties with a spread | 2,853 | 2,721 |
| Near-tied counties | 111 | 106 |
| Median spread of near-tied counties (points) | 23.9 | 24.0 |
| Correlation of spread with Democratic lean | +0.41 | +0.40 |
| Same, with county size and state fixed | +0.28 | +0.27 |
| Correlation of spread with distance from an even split, counties within 50 points | −0.04 | −0.04 |
| Votes in precincts decided by 20 points or more | 65.0% | 64.8% |
| Votes in precincts decided by under 10 points | 18.5% | 18.6% |

Note: The changes in the title are the largest differences before rounding, rounded up to the decimals printed.

Source: MIT Election Data and Science Lab, 2024 precinct-level presidential returns; county totals summed from the precincts; full counts of votes, not survey estimates, so nothing is weighted except by two-party votes where stated

Data: https://vishalsingh.org/politics/report/precincts-within-counties/figures/side_check.json

## All estimates

Every fact in facts.json (160), sorted by id.

| Fact id | Value | Unit | Estimand | Population | Period | Interval | n | Weights | Source | Note |
| --- | ---: | --- | --- | --- | --- | --- | ---: | --- | --- | --- |
| alaska_share_cert | 0.2% | percent of the certified two-party votes | share of certified two-party votes cast in Alaska | all counties with returns | 2024 presidential general election |   |   | none (full counts) | County election returns |   |
| all_median_votes | 13,707 | two-party votes | median county size | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   | 2,853 | none (full counts); each county counted once | Precinct presidential returns |   |
| beyond_max_sd | 34.7 | points of two-party margin | largest county spread | counties with a margin larger than 70 points | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| beyond_n | 260 | counties | count of counties with a margin larger than 70 points | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| beyond_ratio_max | 49% | percent of the limit | largest ratio of a county's spread to the largest spread its margin allows | counties with a margin larger than 70 points | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| beyond_ratio_mean | 12% | percent of the limit | mean ratio of a county's spread to the largest spread its margin allows | counties with a margin larger than 70 points | 2024 presidential general election |   | 260 | none (full counts); each county counted once | Precinct presidential returns |   |
| bin_blue_end | 19.3 | points of two-party margin | mean county spread weighted by votes | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election | 95% CI 15.3 to 23.9 | 12 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| bin_blue_end_n | 12 | counties | count | counties in that bin | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| bin_blue_end_x | 66 | points of two-party margin | vote-weighted mean county margin | counties in the analysis sample in that bin | 2024 presidential general election |   | 12 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_diff_gap | 6.9 | points of two-party margin | difference between the vote-weighted mean spreads of the highest bin and that bin | counties in the highest bin and in that bin | 2024 presidential general election | 95% CI 0.7 to 12.9 | 203 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from resampling the counties of each bin separately (2,000 replicates, seed 12345). |
| bin_diff_x | 4 | points of two-party margin | vote-weighted mean county margin (Republican lead) | counties in that bin | 2024 presidential general election |   | 169 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | The one bin of the run, other than the highest bin, whose difference from the highest bin has a 95% interval that excludes zero. |
| bin_gap_blue | 11.8 | points of two-party margin | difference between the vote-weighted mean spreads of the two bins | counties in the highest bin and in the bluest bin | 2024 presidential general election | 95% CI 3.9 to 18.9 | 46 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from resampling the counties of each bin separately (2,000 replicates, seed 12345). |
| bin_peak | 31.1 | points of two-party margin | mean county spread weighted by votes | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election | 95% CI 24.7 to 36.8 | 34 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| bin_peak_x | 43 | points of two-party margin | vote-weighted mean county margin | counties in the analysis sample in that bin | 2024 presidential general election |   | 34 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_plat_end_x | 34 | points of two-party margin | vote-weighted mean county margin (Democratic lead) | counties in that bin | 2024 presidential general election |   | 50 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_plat_max | 28.4 | points of two-party margin | largest binned mean among those bins | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election |   |   | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_plat_min | 24.1 | points of two-party margin | smallest binned mean among those bins | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election |   |   | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_plat_n | 6 | bins | count | bins whose intervals overlap the interval of the highest bin, counted back from it, other than the highest bin | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| bin_plat_start | 25.4 | points of two-party margin | mean county spread weighted by votes | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election | 95% CI 23.4 to 27.5 | 201 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| bin_plat_start_x | 14 | points of two-party margin | vote-weighted mean county margin (Republican lead) | counties in that bin | 2024 presidential general election |   | 201 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_red_end | 6.7 | points of two-party margin | mean county spread weighted by votes | counties in the analysis sample in a 10-point bin of county margin (at least 10 counties) | 2024 presidential general election | 95% CI 5.2 to 8.0 | 40 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| bin_red_end_x | 82 | points of two-party margin | vote-weighted mean county margin | counties in the analysis sample in that bin | 2024 presidential general election |   | 40 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| bin_width | 10 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Width of the margin bins used for the binned means and the precinct histograms. |
| bound_at_cut | 71.4 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Precinct margins lie between -100 and 100, so a county with margin M cannot have a spread above the square root of 100 squared minus M squared; this is the limit for a margin of 70 points. |
| bucks_comp | 50.0% | percent of the county's two-party votes | share of votes cast in precincts decided by under 10 points | Bucks County, PA | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| bucks_margin | −0.1 | points of two-party margin | two-party margin, Democratic positive | Bucks County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| bucks_max_d | 42.0 | points of two-party margin | margin of the most Democratic precinct | Bucks County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| bucks_max_r | 33.7 | points of two-party margin | margin of the most Republican precinct, as a Republican lead | Bucks County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| bucks_sd | 14.8 | points of two-party margin | vote-weighted standard deviation of precinct margins | Bucks County, PA | 2024 presidential general election |   | 304 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| bucks_units | 304 | precincts | count | Bucks County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| centre_comp | 5.5% | percent of the county's two-party votes | share of votes cast in precincts decided by under 10 points | Centre County, PA | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| centre_margin | +2.9 | points of two-party margin | two-party margin, Democratic positive | Centre County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| centre_max_d | 65.0 | points of two-party margin | margin of the most Democratic precinct | Centre County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| centre_max_r | 75.2 | points of two-party margin | margin of the most Republican precinct, as a Republican lead | Centre County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| centre_sd | 36.3 | points of two-party margin | vote-weighted standard deviation of precinct margins | Centre County, PA | 2024 presidential general election |   | 87 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| centre_units | 87 | precincts | count | Centre County, PA | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| comp_equiv | 55% | percent of the two-party vote | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A margin of 10 points is a 55 to 45 split of the two-party vote. |
| cut_beyond | 70 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Counties with a margin larger than this are the tails of the distribution. |
| cut_big_votes | 100,000 | two-party votes | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Counties with at least this many two-party votes are called large. |
| cut_comp | 10 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A place is called close when its two-party margin is smaller than this. |
| cut_deep | 40 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A place is called very lopsided when its two-party margin is this large or larger. |
| cut_floor_units | 5 | reporting units | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A county needs at least this many reporting units for a spread estimate. |
| cut_land | 20 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A place is called a landslide when its two-party margin is this large or larger. |
| cut_mid_lo | 15 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Lower end of the middle range of near-tied spreads: a spread of this many points or more and under the wide-spread cutoff. |
| cut_near | 5 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A county is near-tied when its two-party margin is smaller than this. |
| cut_near_units | 20 | precincts | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A near-tied county needs at least this many precincts. |
| cut_nongeo_share | 20% | percent of the county's votes | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Counties in which ballot-bucket units (absentee, provisional, early voting and the like) hold this share of votes or more are left out of the side check. |
| cut_sd | 30 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A county spread of 30 points is called wide. |
| cut_sd_top | 50 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A county is called one of the widest-spread counties when its spread is this many points or more. |
| cut_small_units | 10 | reporting units | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A county with fewer reporting units than this is called small in the note on the map. |
| cut_two_share | 20% | percent of the county's votes | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Share of a county's votes in landslide precincts of one party for the two-landslide test. |
| cut_within | 50 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Counties with a margin of this many points or less (a margin of exactly this size included) are used for the check that leaves out the tails. |
| cutoff_30 | 30 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A cutoff of the county margin in the check of how the distance correlation depends on the cutoff (counties with a margin of this many points or less). |
| cutoff_40 | 40 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A cutoff of the county margin in the check of how the distance correlation depends on the cutoff (counties with a margin of this many points or less). |
| cutoff_60 | 60 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A cutoff of the county margin in the check of how the distance correlation depends on the cutoff (counties with a margin of this many points or less). |
| floor_vw_mean | 3.1 | points of two-party margin | mean of the spread expected if voters were assigned to precincts at random, weighted by votes | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| la_share | 51.5% | percent of the certified two-party votes | ratio of precinct votes to certified votes | Louisiana parishes | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| land_equiv | 60% | percent of the two-party vote | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A margin of 20 points is a 60 to 40 split of the two-party vote. |
| margin_arlington | +59.9 | points of two-party margin | two-party margin, Democratic positive | Arlington (a county with at least 100,000 two-party votes) | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| margin_dc | +86.6 | points of two-party margin | two-party margin, Democratic positive | District of Columbia (a county with at least 100,000 two-party votes) | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| margin_max | 100 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | The largest possible two-party margin, in points. |
| margin_metro1 | +11.7 | points of two-party margin | vote-weighted mean county margin | metro counties of 1 million or more in the analysis sample | 2024 presidential general election | 95% CI 7.3 to 15.7 | 419 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| margin_open | −45.2 | points of two-party margin | vote-weighted mean county margin | the least urban nonmetro counties in the analysis sample | 2024 presidential general election | 95% CI −47.6 to −42.7 | 873 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| min_bin_counties | 10 | counties | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A bin of county margin is shown only when it holds at least this many counties. |
| n_acs | 2,843 | counties | count | counties in the analysis sample with at least 5 reporting units and ACS measures | 2024 presidential general election |   |   | none (full counts) | County demographics panel |   |
| n_below_floor | 190 | counties | count | counties in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns | Counties with fewer than 5 reporting units have no spread estimate. |
| n_big | 318 | counties | count | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_boot | 2,000 | resamples | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Number of county resamples behind each interval. |
| n_counties | 3,043 | counties | count | counties in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_counties_disp | 2,853 | counties | count | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_no_rucc | 10 | counties | count of counties with no Rural-Urban Continuum Code in the panel | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | County demographics panel | The Connecticut counties (the panel uses the 2022 planning regions), Kansas City, Missouri, and Oglala Lakota County, South Dakota. |
| n_out_la | 64 | parishes | count | Louisiana parishes | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_out_other | 6 | counties | count | counties outside Louisiana whose precinct rows do not add to the certified total | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_out_total | 70 | counties | count | counties whose precinct rows do not add to the certified total (Louisiana and others) | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_sd30 | 368 | counties | count | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_sd_top | 33 | counties | count of counties with a spread of 50 points or more | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_sd_top_msal | 20 | counties | count of those counties in Mississippi or Alabama | counties in the analysis sample with a spread of 50 points or more | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_sd_top_small | 4 | counties | count of those counties with fewer than 10 reporting units | counties in the analysis sample with a spread of 50 points or more | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_sim | 200 | simulated assignments | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Number of simulated assignments of voters to precincts behind the random-assignment bars. |
| n_states | 48 | states | count | states in the analysis sample, not counting the District of Columbia | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_units | 175,345 | reporting units | count | reporting units (precincts) in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| n_within50 | 1,725 | counties | count | counties in the analysis sample with at least 5 reporting units and a margin of 50 points or less | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_floor | 3.4 | points of two-party margin | median of the spread expected if voters were assigned to precincts at random | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   | 111 | none (full counts); each county counted once | Precinct presidential returns |   |
| near_max_sd | 58.1 | points of two-party margin | largest county spread | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_median_sd | 23.9 | points of two-party margin | median of county spreads | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election | 95% CI 22.8 to 24.9 | 111 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| near_median_votes | 78,269 | two-party votes | median county size | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   | 111 | none (full counts); each county counted once | Precinct presidential returns |   |
| near_min_sd | 10.1 | points of two-party margin | smallest county spread | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_n | 111 | counties | count | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_n_sd30 | 29 | counties | count with a spread of 30 or more | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_n_two | 39 | counties | count with one fifth or more of the votes in Democratic landslide precincts and one fifth or more in Republican landslide precincts | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| near_share_comp | 35.6% | percent of the two-party votes of these counties | share of votes cast in precincts in the band | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| near_share_deep | 10.5% | percent of the two-party votes of these counties | share of votes cast in precincts in the band | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| near_share_land | 38.2% | percent of the two-party votes of these counties | share of votes cast in precincts in the band | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| near_share_land_d | 17.5% | percent of the two-party votes of these counties | share of votes cast in precincts in the band | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| near_share_land_r | 20.7% | percent of the two-party votes of these counties | share of votes cast in precincts in the band | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| near_share_mid | 64.0% | percent of counties | share with a spread of 15 points or more and under 30 | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); each county counted once | Precinct presidential returns |   |
| near_share_sd30 | 26.1% | percent of counties | share with a spread of 30 or more | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); each county counted once | Precinct presidential returns |   |
| near_share_two | 35.1% | percent of counties | share of counties in the previous count | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts); each county counted once | Precinct presidential returns |   |
| near_votes | 18.9 million | two-party votes | sum | near-tied counties in the analysis sample: two-party margin within 5 points and at least 20 precincts | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| nongeo_share | 1.5% | percent of two-party votes | share of votes in units labelled as ballot buckets: absentee, provisional, early voting, mail, failsafe, military, overseas and statistical-adjustment | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| nongeo_units | 870 | reporting units | count | reporting units (precincts) in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| out_share_cert | 2.0% | percent of the certified two-party votes | share | all counties with returns | 2024 presidential general election |   |   | none (full counts) | County election returns | The 70 counties left out by the reconciliation rule; Alaska is a further share. |
| r_cut60 | −0.15 | correlation coefficient | correlation of distance from an even split with county spread | counties in the analysis sample with at least 5 reporting units and a margin of 60 points or less | 2024 presidential general election | 95% CI −0.26 to −0.04 | 2,156 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_cutallu | −0.55 | correlation coefficient | correlation of distance from an even split with county spread, each county counted once | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI −0.57 to −0.52 | 2,853 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_ext50_raw | −0.04 | correlation coefficient | correlation of distance from an even split with county spread | counties in the analysis sample with at least 5 reporting units and a margin of 50 points or less | 2024 presidential general election | 95% CI −0.18 to 0.08 | 1,725 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_ext50u_raw | −0.26 | correlation coefficient | correlation of distance from an even split with county spread, each county counted once | counties in the analysis sample with at least 5 reporting units and a margin of 50 points or less | 2024 presidential general election | 95% CI −0.30 to −0.22 | 1,725 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_ext_fe | −0.25 | correlation coefficient | correlation of distance from an even split with county spread after size and state controls | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI −0.37 to −0.16 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_ext_raw | −0.29 | correlation coefficient | correlation of the county margin's distance from zero with county spread | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI −0.39 to −0.20 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_ext_size | −0.19 | correlation coefficient | correlation of distance from an even split with county spread after removing size | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI −0.30 to −0.09 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean50_raw | +0.41 | correlation coefficient | correlation of county margin with county spread | counties in the analysis sample with at least 5 reporting units and a margin of 50 points or less | 2024 presidential general election | 95% CI 0.32 to 0.49 | 1,725 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_fe | +0.28 | correlation coefficient | correlation of county margin with county spread after removing the linear effects of log votes and log precincts and state means | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.19 to 0.37 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_logvotes | +0.64 | correlation coefficient | correlation of county margin with the log of two-party votes | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.59 to 0.69 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_raw | +0.41 | correlation coefficient | correlation of county margin with county spread | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.33 to 0.49 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_size | +0.21 | correlation coefficient | correlation of county margin with county spread after removing linear effects of log votes and log precincts | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.12 to 0.30 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_unw | +0.54 | correlation coefficient | correlation of county margin with county spread, each county counted once | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.51 to 0.56 | 2,853 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_lean_unw_fe | +0.47 | correlation coefficient | correlation of county margin with county spread after size and state controls, each county counted once | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.43 to 0.51 | 2,853 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_nonwhite_fe | +0.31 | correlation coefficient | correlation of the nonwhite share with county spread after size and state controls | counties in the analysis sample with at least 5 reporting units and ACS measures | 2024 presidential general election | 95% CI 0.22 to 0.40 | 2,843 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_nonwhite_raw | +0.43 | correlation coefficient | correlation of the nonwhite share (ACS 2024) with county spread | counties in the analysis sample with at least 5 reporting units and ACS measures | 2024 presidential general election | 95% CI 0.36 to 0.50 | 2,843 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_rural_fe | −0.13 | correlation coefficient | correlation of the rural share with county spread after size and state controls | counties in the analysis sample with at least 5 reporting units and ACS measures | 2024 presidential general election | 95% CI −0.19 to −0.08 | 2,843 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_rural_raw | −0.36 | correlation coefficient | correlation of the rural share (2020 census urban area definition, county panel) with county spread | counties in the analysis sample with at least 5 reporting units and ACS measures | 2024 presidential general election | 95% CI −0.41 to −0.30 | 2,843 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| r_sd_logvotes | +0.40 | correlation coefficient | correlation of county spread with the log of two-party votes | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.33 to 0.46 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| rb_dcorr_max | 0.02 | correlation coefficient | largest absolute change, rounded up to two decimals, across the correlations of spread with lean (raw and with size and state fixed) and with distance from an even split within 50 points | counties in the side check and in the full sample | 2024 presidential general election |   |   | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |
| rb_dshare_max | 0.3 | percentage points of votes | largest absolute change, rounded up to one decimal, across the shares of votes in precincts decided by 20 points or more and by under 10 points | units in the side check and in the full sample | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| rb_n_counties | 2,721 | counties | count | counties in the side check | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| rb_near_n | 106 | counties | count | near-tied counties in the side check | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| sd_al | 32.2 | points of two-party margin | mean of county spreads weighted by votes | Alabama counties with at least 5 reporting units | 2024 presidential general election | 95% CI 25.2 to 38.3 | 67 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345), resampling the counties of the state. |
| sd_arlington | 6.5 | points of two-party margin | vote-weighted standard deviation of precinct margins | Arlington (a county with at least 100,000 two-party votes) | 2024 presidential general election |   | 55 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sd_bin_width | 5 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Width of the spread bins in the histogram of near-tied counties. |
| sd_dc | 5.9 | points of two-party margin | vote-weighted standard deviation of precinct margins | District of Columbia (a county with at least 100,000 two-party votes) | 2024 presidential general election |   | 144 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sd_equiv | 15 | points of Democratic vote share | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | A spread of 30 margin points is a spread of 15 points of the Democratic share of the two-party vote. |
| sd_jeffal | 53.5 | points of two-party margin | vote-weighted standard deviation of precinct margins | Jefferson County, AL, 2024 (a county with at least 100,000 two-party votes) | 2024 presidential general election |   | 179 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sd_kings | 54.9 | points of two-party margin | vote-weighted standard deviation of precinct margins | Kings County, NY, 2024 (a county with at least 100,000 two-party votes) | 2024 presidential general election |   | 1,341 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sd_median | 15.6 | points of two-party margin | median of county spreads | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 15.0 to 16.0 | 2,853 | none (full counts); each county counted once | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| sd_metro1 | 24.8 | points of two-party margin | mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units, metro area of 1 million or more (Rural-Urban Continuum Code 1, 2023) | 2024 presidential general election | 95% CI 23.5 to 26.1 | 419 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| sd_metro2 | 22.7 | points of two-party margin | mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units, smaller metro area (Rural-Urban Continuum Code 2 to 3, 2023) | 2024 presidential general election | 95% CI 21.9 to 23.5 | 690 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| sd_mobile | 50.2 | points of two-party margin | vote-weighted standard deviation of precinct margins | Mobile County, AL, 2024 (a county with at least 100,000 two-party votes) | 2024 presidential general election |   | 82 | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sd_ms | 38.2 | points of two-party margin | mean of county spreads weighted by votes | Mississippi counties with at least 5 reporting units | 2024 presidential general election | 95% CI 34.9 to 41.5 | 82 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345), resampling the counties of the state. |
| sd_open | 15.5 | points of two-party margin | mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units, nonmetro, smaller towns and open country (Rural-Urban Continuum Code 8 to 9, 2023) | 2024 presidential general election | 95% CI 14.6 to 16.5 | 873 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| sd_town | 19.4 | points of two-party margin | mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units, nonmetro, larger towns (Rural-Urban Continuum Code 4 to 7, 2023) | 2024 presidential general election | 95% CI 18.7 to 20.1 | 861 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| sd_vw_mean | 23.3 | points of two-party margin | mean of county spreads weighted by two-party votes | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 22.5 to 24.1 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| share_comp_county | 23.1% | percent of two-party votes | share of votes cast in counties in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_comp_precinct | 18.5% | percent of two-party votes | share of votes cast in precincts in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_comp_random | 23.3% | percent of two-party votes | mean over 200 simulated assignments of the share of votes in precincts in the band, when each precinct's Democratic votes are a binomial draw of its votes at its county's Democratic share | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   | 200 | none; simulation with unit sizes and county margins held fixed (seed 12345) | Precinct presidential returns |   |
| share_deep_county | 25.4% | percent of two-party votes | share of votes cast in counties in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_deep_precinct | 36.4% | percent of two-party votes | share of votes cast in precincts in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_deep_random | 25.0% | percent of two-party votes | mean over 200 simulated assignments of the share of votes in precincts in the band, when each precinct's Democratic votes are a binomial draw of its votes at its county's Democratic share | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   | 200 | none; simulation with unit sizes and county margins held fixed (seed 12345) | Precinct presidential returns |   |
| share_land_county | 57.2% | percent of two-party votes | share of votes cast in counties in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_land_precinct | 65.0% | percent of two-party votes | share of votes cast in precincts in the band | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| share_land_random | 56.6% | percent of two-party votes | mean over 200 simulated assignments of the share of votes in precincts in the band, when each precinct's Democratic votes are a binomial draw of its votes at its county's Democratic share | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   | 200 | none; simulation with unit sizes and county margins held fixed (seed 12345) | Precinct presidential returns |   |
| sim_county_gap | 0.7 | percentage points of votes | largest absolute difference across the three bands between the random-assignment share and the county share | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts); precinct results weighted by their two-party votes | Precinct presidential returns |   |
| sim_range | 0.4 | percentage points of votes | largest difference between the highest and lowest of the simulated shares, across the three bands | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   | 200 | none; simulation (seed 12345) | Precinct presidential returns |   |
| slope_fe | 0.9 | points of spread per 10 points of margin | weighted least squares slope of county spread on county margin, times 10, with log votes, log precincts and state means | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.6 to 1.3 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| slope_raw | 1.1 | points of spread per 10 points of margin | weighted least squares slope of county spread on county margin, times 10 | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election | 95% CI 0.8 to 1.4 | 2,853 | none (full counts); counties weighted by their two-party votes | Precinct presidential returns | 95% interval from a county bootstrap (2,000 replicates, seed 12345). |
| slope_step | 10 | points of two-party margin | definition | definition used in this chapter | 2024 presidential general election |   |   | none (definition) | Precinct presidential returns | Step in county margin for the slope of spread on margin. |
| unit_ca_per_county | 578 | precincts per county | mean count of reporting units per county | California counties in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| unit_med_max | 2,083 | two-party votes per precinct | median precinct size | Connecticut precincts in the analysis sample | 2024 presidential general election |   | 756 | none (full counts) | Precinct presidential returns |   |
| unit_med_min | 227 | two-party votes per precinct | median precinct size | Kansas precincts in the analysis sample | 2024 presidential general election |   | 3,737 | none (full counts) | Precinct presidential returns |   |
| unit_nd_per_county | 7 | precincts per county | mean count of reporting units per county | North Dakota counties in the analysis sample | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| votes_sample | 149.0 million | two-party votes | sum of Democratic and Republican votes | two-party presidential votes in the analysis sample (counties whose precinct rows match the certified total; Alaska left out) | 2024 presidential general election |   |   | none (full counts) | Precinct presidential returns |   |
| votes_sd30 | 18.7% | percent of two-party votes | share of the votes of these counties cast in counties with a spread of 30 or more | counties in the analysis sample with at least 5 reporting units | 2024 presidential general election |   |   | none (full counts); counties weighted by their two-party votes | Precinct presidential returns |   |

## Definitions

- Precinct: The smallest area for which election officials report votes, usually the voters assigned to one polling place. Precinct boundaries change between elections, so the same precinct cannot be followed over time.
- Standard deviation: A measure of how far values typically fall from their average. A larger standard deviation means the values are more spread out.
- County two-party margin: The Democratic vote minus the Republican vote, divided by the sum of the two, so a positive value is a Democratic lead. Votes for other candidates are left out.
- Percentage point: The unit for the difference between two percentages. A change from one share to another is stated in points, not in percent, so that absolute and relative change are not confused.
- Rural-Urban Continuum Code: A USDA scheme that sorts counties into nine classes, from large metropolitan areas to remote rural ones, by population size and nearness to a metropolitan area. The 2013 and 2023 editions classify some counties differently.
- Correlation: A number from minus 1 to plus 1 for how closely two measures move together in a straight-line pattern. Zero means no straight-line pattern; a correlation does not say that one measure causes the other.
- Fixed effects: Regression terms that give each group, such as each country or each year, its own baseline. The other coefficients then compare respondents within the same group.
- Ecological inference: Drawing a conclusion about individuals from data on groups or places, such as counties. A pattern across counties can differ from the pattern among the people who live in them.

## Methods

Sample: the 2024 presidential returns in the MIT Election Data and Science Lab precinct file, two-party votes per reporting unit (Democratic: Harris; Republican: Trump; write-ins and other candidates left out) from b3.load.precinct_two_party, which takes a precinct's TOTAL row where the state reports one and otherwise adds the rows for each voting mode. A 'precinct' is the unit the state or county election office reports, so it varies in size and kind by state. Rules applied in order: units with no two-party vote or a negative count are dropped (15,602 units, three of them Michigan statistical adjustments); Alaska is dropped (523 units; its 2024 county codes are election districts); 4 units with no county code are dropped; 123 Kansas City units are moved from code 36000 to 2938000, the code of the county file; a county is kept only when its precinct rows add to between 95% and 105% of its certified two-party vote in the repaired county file, which removes 70 counties (64 Louisiana parishes, where the precinct rows hold about 52% of the certified vote, and 6 others, four of them with rows that appear twice, in Bergen and Gloucester, NJ, and Hendricks and St. Joseph, IN). The analysis sample is 175,345 units, 148,953,406 two-party votes and 3,043 counties in 48 states and the District of Columbia; the 70 excluded counties hold 2.0% of the certified votes and Alaska a further 0.2%. Estimands: a precinct or county margin is 100 times the Democratic minus the Republican votes over their sum; the spread of a county is the standard deviation of its precinct margins about the county margin, weighted by each precinct's two-party votes (population divisor), and needs at least 5 reporting units; the spread expected from chance is 200 times the square root of p(1 - p) times the number of units over the votes, with p the Democratic two-party share, which is the spread if each voter were assigned to a unit at random. Near-tied counties have a margin below 5 points in absolute value and at least 20 precincts. Shares of votes in bands use exact tests on vote counts (a margin of 20 points or more is 5 |D - R| >= D + R). Random-assignment benchmark for the shares in bands: 200 simulated assignments (seed 12345) in which each precinct keeps its two-party votes and its county's Democratic share and its Democratic votes are a binomial draw; the figure shows the mean of the runs, and the largest range of a share across runs is 0.4 points. County correlations are weighted by two-party votes unless the text says each county is counted once; holding county size fixed removes the linear effect of the log of two-party votes and the log of the number of units, and holding state fixed removes each state's weighted mean from every variable (equal to a regression with state dummies). The slope of spread on margin is the coefficient of a weighted regression with the same controls, per 10 points of margin. Counties within 50 points have a margin of 50 points or less in absolute value; the correlation of spread with distance from an even split is also computed at cutoffs of 30, 40, 60 and 70 points and across all counties, weighted and counting each county once, each with no controls, with county size fixed and with size and state fixed; the correlation of spread with lean is computed weighted and counting each county once, with the same three sets of controls. Binned means use 10-point bins of county margin and need 10 counties. Place types use the USDA Rural-Urban Continuum Code, 2023 edition (1; 2 and 3; 4 to 7; 8 and 9); nonwhite share is 100 minus the non-Hispanic white share (ACS 2024) and rural share is the share of residents outside 2020 census urban areas, both from the county demographics panel, which has no values for the Connecticut counties, Kansas City, Missouri, and Oglala Lakota County, South Dakota. Weights: none from a survey, because the returns are full counts; statistics are weighted by two-party votes as stated. Intervals: the returns have no sampling error, so shares, counts and county spreads carry no interval; a correlation, a slope, a mean or a median across a set of counties has a 95% percentile interval from a county bootstrap (2,000 replicates, seed 12345); the interval for the difference between two bins of county margin resamples the counties of each bin separately, and a state mean resamples the counties of the state. Side check: dropping the units labelled as absentee, provisional, early voting, mail, failsafe, military, overseas and statistical-adjustment units (870 units, found by these words in the label: absen(tee), abs, provisional, prov, early voting, early vote, earlyvote, early on its own, EV, mail, statistical adjustments, military, overseas, failsafe) and the counties where they hold 20% of the votes or more leaves 2,721 counties with a spread; the results are printed beside the full-sample values in the section on what the data cannot show. Suppression: no county with fewer than 5 reporting units enters a spread statistic; no other cell is suppressed. Everything is a 2024 cross-section.

## What these data cannot show

- The chapter describes one election.
- It says nothing about whether precinct margins are spreading or narrowing, and it makes no comparison with earlier years.
- Planned, Sorting by geographic scale, 2016 to 2024 (https://vishalsingh.org/politics/sorting-by-geographic-scale; planned), a planned chapter, will compare precincts across elections, and Chapter 6.1, Nationalization of the county vote (https://vishalsingh.org/politics/nationalization-of-the-county-vote) measures how closely county results move together from one election to the next.
- A precinct is a reporting unit and not a neighborhood.
- The file has no boundaries, so the data cannot say which precincts are adjacent, and a county with a wide spread need not have opposed precincts next to each other.
- Units also differ in kind.
- Units labelled absentee, provisional, early voting, mail, failsafe, military or overseas, and units labelled as statistical adjustments, hold 1.5% of votes across 870 units, and they are buckets of ballots and not places.
- Table 9 repeats the main statistics without them and without the counties where they hold 20% of votes or more.
- That leaves 2,721 counties with a spread and 106 near-tied counties, against 111 in the full sample.
- Table 9.
- Dropping ballot-bucket units moves each correlation by at most 0.02 and each vote share by at most 0.3 points
- A precinct margin describes a place and not the voters in it.
- A precinct that gave one party 60% or more still holds voters of the other.
- Ecological inference, which moves from places to individuals, can fail, because a pattern across places can differ from the pattern among individuals [5].
- The results also depend on the units.
- Shares and spreads change with the size and shape of the areas, a problem known as the modifiable areal unit problem [6], and this chapter uses the units that election offices happened to report.
- The 64 Louisiana parishes, the 6 other counties and Alaska that are left out are not a random set.
- The cutoffs for near-tied counties and for a wide spread are choices, and so are the vote weights and the 50-point cutoff behind the correlation of spread with distance from an even split.
- That correlation is near zero only in the vote-weighted comparisons within 50 points or less.
- A single spread cannot tell a county with two humps from a county with a long tail.
- The random-assignment benchmark holds each unit's size and its county's margin fixed and does not model why voters differ across precincts.
- Nothing here identifies why spread is wider in some counties.
- It goes with lean, size, nonwhite share and place type, and the controls are few and linear.

## References

1. Bishop, Bill; Cushing, Robert G. (2008). The Big Sort: Why the Clustering of Like-Minded America Is Tearing Us Apart. Houghton Mifflin.
2. Abrams, Samuel J.; Fiorina, Morris P. (2012). "The Big Sort" That Wasn't: A Skeptical Reexamination. PS: Political Science and Politics 45(2): 203-210. https://doi.org/10.1017/S1049096512000017
3. Brown, Jacob R.; Enos, Ryan D. (2021). The Measurement of Partisan Sorting for 180 Million Voters. Nature Human Behaviour 5: 998-1008. https://doi.org/10.1038/s41562-021-01066-z
4. Rodden, Jonathan A. (2019). Why Cities Lose: The Deep Roots of the Urban-Rural Political Divide. Basic Books.
5. Robinson, W. S. (1950). Ecological Correlations and the Behavior of Individuals. American Sociological Review 15(3): 351-357.
6. Openshaw, Stan (1984). The Modifiable Areal Unit Problem. Concepts and Techniques in Modern Geography 38, Norwich: Geo Books.

## Provenance

- Pipeline version: 1.0.0
- Build script: book3/chapters/precincts-within-counties/build.py (sha256 6ee74aa11054b92466524b4220c8cb6f1c7b699f116c5ba88fdf1807d0399232)
- Built on: 2026-09-30
- Site commit: 16414b2c7257546a7042d0b1734657f208999f60

Inputs:

| File | Size (bytes) | SHA-256, first 1 MB | SHA-256, last 1 MB |
| --- | ---: | --- | --- |
| data/county/pres_county_1868_2024.parquet | 6,295,675 | bec11c7a0cb5d4180bbd6809d048bc892dd00dfcdde527fa4da871b1dd3f835f | b2a4f000f2eea72d09af8939555289e924875cca40cd95ec8869104cd575bed7 |
| data/county/pres_county_2000_2024.parquet | 5,622,625 | 89e55d8bb32746282a8a0880a7d0e82892acf449eaea71ac1aa7466cc9b0cc23 | d6c6a14fdff6f54e9ee88e46c71dce64ee40b940e050f92d18540e4889f4a0f3 |
| data/precinct/pres_precinct_2016_2020_2024.parquet | 12,200,115 | 53917fd567a1a7267fb02b7f7c0f229d3b251f32be472968a3fd4577653b4956 | 7868d4ba4664ffc59db2f5966b3f8812b455b6ab9d8bd52781768a925552efd3 |

Outputs:

| File | SHA-256 |
| --- | --- |
| facts.json | b70068b8a5df4f5b567913a6a808faccbb78c09e76ae98eaa0eed42710d9917c |
| figures/county_sd_map.json | 580882435f9a85273f55857706f49cf5508aae9e94b6e74cee02c2e019b63f26 |
| figures/dispersion_partials.json | c5284a237834227b33ae4e818434b3d324f472cd0d0016b6884cd8a101a4260a |
| figures/example_counties.json | 32e2dc507cf27a8d8ef8e47f8aa8352b11ff9a886f1872af7d6c9f5eb07a8232 |
| figures/ext_by_cutoff.json | cb056155db52387ece816472721c76e8257657306cfee99fea7feb8c50269768 |
| figures/landslide_shares.json | 4140795df5735dc90b90f59f9edb9f3430b121cad17b9da46a23dd3f21474b4a |
| figures/near_tied_sd.json | 5e3c59449bdd3e963161dde8b8b0d3a10bb423c20f4474e0d72bfd7606dff632 |
| figures/sd_by_margin.json | d99808d3ebcbffbda1bc79e7c17d8ac7e8904b4fc3cf0ec8a8cbf85473d4ccb7 |
| figures/sd_by_place_type.json | 7703748d9a9d0d0201bf1339f7572ff87568f0601f0640f02904922db6535f94 |
| figures/side_check.json | 1341b4adf2a5a5ba4213bcec84f760b77c5a1c3cc3c38126e6ecb80d5056d13a |
| meta.json | e260af1fb522731536555d015f996b818ab3c4e075fb043f1f9c2ef3c42535c0 |
| public/data/precincts-within-counties/county_sd_map.json | eb9534e8c372ae01eb2b210f6b3fcff02124f3cfd187128d4fe4d31e4075f66c |
| refs.json | 599f99d0ff52632f0953ee9d7ed096112f2155d3d572417ab8ae566107896f1a |

## Machine formats

- Report (HTML): https://vishalsingh.org/politics/precincts-within-counties/report
- Report (Markdown): https://vishalsingh.org/politics/precincts-within-counties/report.md
- Every estimate (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/facts.json
- Table 1, figure "example_counties" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/example_counties.json
- Table 2, figure "landslide_shares" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/landslide_shares.json
- Table 3, figure "county_sd_map" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/county_sd_map.json
- Table 4, figure "sd_by_place_type" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/sd_by_place_type.json
- Table 5, figure "sd_by_margin" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/sd_by_margin.json
- Table 6, figure "dispersion_partials" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/dispersion_partials.json
- Table 7, figure "ext_by_cutoff" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/ext_by_cutoff.json
- Table 8, figure "near_tied_sd" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/near_tied_sd.json
- Table 9, figure "side_check" (JSON): https://vishalsingh.org/politics/report/precincts-within-counties/figures/side_check.json
- Payload of "county_sd_map" (JSON): https://vishalsingh.org/politics/data/precincts-within-counties/county_sd_map.json
- Index of every report: https://vishalsingh.org/politics/llms.txt; all reports in one file: https://vishalsingh.org/politics/llms-full.txt