House price index (2000 = 100) and Friending clustering
Where House price index (2000 = 100) is higher, Friending clustering tends to be lower. The link is weak: -0.36 across 2,373 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 38 states, the middle value of the link is -0.20.
Holds after adjusting
Every place, plotted
One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.
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What each measure is
House price index (2000 = 100)
House prices compared with the same place in 2000, which is set to 100. A value of 250 means prices are 2.5 times what they were in 2000. It is not a price in dollars, so it shows growth, not which place costs more.
FHFA House Price Index · FHFA HPI all-transactions annual (developmental county/state), HPI with 2000 base
Friending clustering
How often a person's friends are also friends with each other. It shows how tight-knit the local network is, which is separate from how far it reaches across income groups.
Social Capital Atlas · Opportunity Insights clustering_county
Highest and lowest
Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.
Counties
By house price index (2000 = 100)
| House price index (2000 = 100) | Friending clustering | |
|---|---|---|
| Highest | ||
| Adams County, ID | 468 | 0.104 |
| Williams County, ND | 466 | 0.103 |
| Shoshone County, ID | 465 | 0.126 |
| Hamlin County, SD | 458 | 0.115 |
| Richland County, MT | 452 | 0.123 |
| Lowest | ||
| Luce County, MI | 136 | 0.152 |
| Coahoma County, MS | 140 | 0.163 |
| Stephenson County, IL | 142 | 0.12 |
| Massac County, IL | 142 | 0.126 |
| McDonough County, IL | 143 | 0.113 |
By friending clustering
| House price index (2000 = 100) | Friending clustering | |
|---|---|---|
| Highest | ||
| Wilcox County, AL | 164 | 0.191 |
| Sac County, IA | 232 | 0.19 |
| Yazoo County, MS | 184 | 0.183 |
| Graham County, NC | 260 | 0.18 |
| Glacier County, MT | 299 | 0.178 |
| Lowest | ||
| Bronx County, NY | 294 | 0.0716 |
| Osceola County, FL | 325 | 0.0734 |
| Utah County, UT | 290 | 0.0758 |
| Kings County, NY | 342 | 0.0759 |
| Bernalillo County, NM | 240 | 0.0761 |
States — Friending clustering is not published for states
By house price index (2000 = 100)
| House price index (2000 = 100) | Friending clustering | |
|---|---|---|
| Highest | ||
| District of Columbia | 395 | — |
| Florida | 354 | — |
| Hawaii | 353 | — |
| Idaho | 344 | — |
| Montana | 329 | — |
| Lowest | ||
| Illinois | 173 | — |
| Michigan | 176 | — |
| West Virginia | 183 | — |
| Ohio | 184 | — |
| Mississippi | 190 | — |
Metro areas — House price index (2000 = 100) is not published for metro areas
By friending clustering
| House price index (2000 = 100) | Friending clustering | |
|---|---|---|
| Highest | ||
| Zapata, TX | — | 0.182 |
| Natchez, MS-LA | — | 0.176 |
| Greenwood, MS | — | 0.166 |
| Cleveland, MS | — | 0.165 |
| Clarksdale, MS | — | 0.163 |
| Lowest | ||
| Las Vegas-Henderson-North Las Vegas, NV | — | 0.0763 |
| Provo-Orem-Lehi, UT | — | 0.077 |
| El Paso, TX | — | 0.0772 |
| Colorado Springs, CO | — | 0.0784 |
| Orlando-Kissimmee-Sanford, FL | — | 0.0786 |
Counties furthest from the pattern
Compared with the straight line that best fits all 2,374 counties: the five with far more friending clustering than their house price index (2000 = 100) would suggest, and the five with far less.
| House price index (2000 = 100) | Friending clustering | |
|---|---|---|
| Above the line | ||
| Sac County, IA | 232 | 0.19 |
| Glacier County, MT | 299 | 0.178 |
| Graham County, NC | 260 | 0.18 |
| Wilcox County, AL | 164 | 0.191 |
| Yazoo County, MS | 184 | 0.183 |
| Below the line | ||
| Wayne County, MI | 153 | 0.0835 |
| McKinley County, NM | 182 | 0.0823 |
| Cook County, IL | 176 | 0.0843 |
| Bernalillo County, NM | 240 | 0.0761 |
| Cuyahoga County, OH | 165 | 0.0867 |
Two series, one county
Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.
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Every version of the link
Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.
| Before adjusting for anything | -0.378 | 2,373 counties reporting both |
| After adjusting for density, income and education | -0.363 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | -0.298 | size taken out as well as density |
| Also comparing only within each state | -0.116 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | -0.505 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 276 equally weighted counties |
| Middle value inside single states | -0.198 | the link worked out inside each of 38 states with at least 20 counties reporting |
| Using ranks, after adjusting | -0.380 | uses each county’s rank, not its value, so a few extreme counties cannot create the link |
How much to believe it
Could it be chance?
The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 9.1e-75. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 5.6e-13. The site tested 24,090 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 6.6e-74.
Do nearby places look alike?
Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.37 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.
Did they change together?
Not measurable: at least one of these is published for too few of the years a change needs (2014–2019 or 2019–2023), or for too few counties in both.
Related pairs
- Median home value and House price index (2000 = 100) — +0.49
- House price index (2000 = 100) and Local income tax collected — +0.49
- Friending clustering and Homicide rate, annual — +0.48
- Median gross rent and House price index (2000 = 100) — +0.47
- Taking blood pressure medication and House price index (2000 = 100) — -0.46
- Routine checkup in the past year and House price index (2000 = 100) — -0.46
- Share Black, not Hispanic and Friending clustering — +0.43
- Routine checkup in the past year and Friending clustering — +0.42
Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore House price index (2000 = 100) and Friending clustering