Do movers push up home prices?
Mostly yes, with loud exceptions. Across the 50 states and DC, net migration per 1,000 residents over 2020 to 2023 and the change in typical home value from January 2020 to December 2023 correlate at 0.74: Idaho gained 53 people per 1,000 and its homes rose 54%, Montana 38 and 61%, Florida 35 and 59%, while the District of Columbia lost 61 per 1,000 and rose 6%. At county level the link is weaker (0.43) but holds: counties gaining 40 or more per 1,000 rose a median 50%, counties losing 10 or more a median 34%. The exceptions are where the story is: Miami-Dade lost 49 people per 1,000 and rose 61%, and Austin’s Travis County lost people every year from 2020 while prices rose 32% in 2021 and then fell 8% in 2023.
- 0.74correlation across the states between net migration per 1,000 (2020 to 2023) and home-value change (January 2020 to December 2023)
- +50%median home-value rise in counties that gained 40 or more people per 1,000, against +34% in counties that lost 10 or more
- −49Miami-Dade’s net migration per 1,000 residents over 2020 to 2023, while its typical home rose 61%
- 0.59the state correlation when prices are measured a year later (January 2021 to December 2024)
Based on IRS county-to-county migration for the 2020 to 2023 migration years and Zillow typical home values at January 2020 and December 2023, for the 50 states and DC, 962 metro and micro areas and 2,984 counties with both series. Explore the live data.
Did the states that gained people see the biggest price rises?
Broadly, yes: the correlation across the 50 states and DC is 0.74. Idaho gained 53 people per 1,000 residents over the 2020 to 2023 migration years and its typical home went from 298,900 dollars in January 2020 to 460,200 in December 2023, up 54%; Montana (38 per 1,000, up 61%), Maine (28, up 61%), Florida (35, up 59%), North Carolina (28, up 54%), Arizona (27, up 53%) and Tennessee (30, up 52%) all beat the median state’s 40%. The District of Columbia lost 61 per 1,000 and rose 6%, Louisiana lost 20 and rose 9%, Alaska and North Dakota lost 28 and 20 and rose 14%. The big outlier is Massachusetts, which lost 22 per 1,000 and still rose 40%.
| State | Net per 1,000 | Jan 2020 | Dec 2023 | Change |
|---|---|---|---|---|
| Idaho | +52.9 | $298,900 | $460,200 | +54% |
| South Carolina | +47.3 | $200,500 | $300,100 | +50% |
| Montana | +38.3 | $277,200 | $446,800 | +61% |
| Delaware | +37.3 | $277,200 | $387,200 | +40% |
| Florida | +35.2 | $252,600 | $401,400 | +59% |
| Tennessee | +30.0 | $214,600 | $326,100 | +52% |
| Maine | +28.2 | $246,000 | $397,200 | +61% |
| North Carolina | +27.8 | $215,100 | $331,400 | +54% |
| Massachusetts | −22.0 | $437,800 | $614,400 | +40% |
| Hawaii | −25.1 | $616,200 | $834,700 | +35% |
| Illinois | −27.4 | $200,400 | $262,400 | +31% |
| California | −28.1 | $551,200 | $757,600 | +37% |
| Alaska | −28.3 | $316,700 | $361,600 | +14% |
| New York | −44.9 | $352,600 | $456,500 | +29% |
| District of Columbia | −61.1 | $574,800 | $611,100 | +6% |
Correlation is not cause, and the arrow could point either way: cheap states attract movers as surely as movers bid up prices. The report draws this scatter with a fitted line for any range of years and any population floor, and switches the same view to metros and counties.
Does the link hold at county level?
It holds, but it is weaker: 0.43 across the 1,001 counties with 50,000 or more residents, and the same across all 2,984 counties with both series. Counties that gained 40 or more people per 1,000 residents over 2020 to 2023 saw their typical home rise a median 50%; those gaining 20 to 40 rose 43%, 10 to 20 rose 42%, 0 to 10 rose 39%, those losing up to 10 rose 38%, and those losing more than 10 per 1,000 rose 34%. Splitting the 1,001 counties at the median price rise of 41%, 395 gained people and beat it and 236 lost people and missed it, which leaves 370 counties, more than a third, in the two off-diagonal corners.
| Net migration per 1,000 | Counties | Median price change | Mean price change |
|---|---|---|---|
| Lost more than 10 | 226 | +34% | +32% |
| Lost 0 to 10 | 115 | +38% | +38% |
| Gained 0 to 10 | 149 | +39% | +39% |
| Gained 10 to 20 | 108 | +42% | +43% |
| Gained 20 to 40 | 174 | +43% | +43% |
| Gained more than 40 | 229 | +50% | +49% |
The fastest-growing large counties mostly did see big rises: Brunswick County, North Carolina gained 181 per 1,000 and rose 57%, St. Johns County, Florida 173 and 59%, Jackson County, Georgia 156 and 57%, Flagler County, Florida 158 and 50%. But Kaufman County, Texas, the fastest of all at 215 per 1,000, rose only 40%, and Liberty County, Texas, at 184, rose 27%.
Where did prices rise without arrivals?
Resort and second-home counties, and Miami. Eagle County, Colorado (Vail) lost 37 people per 1,000 residents over 2020 to 2023 and its typical home went from 690,800 to 1,195,800 dollars, up 73%; Monroe County, Florida (the Keys) lost 18 per 1,000 and rose 69%, from 593,600 to 1,005,500. Miami-Dade lost 49 per 1,000, the steepest loss of any large county in Florida, and rose 61%. Clayton County, Georgia lost 27 per 1,000 and rose 72%, Clarke County, Georgia (Athens) lost 39 and rose 60%, Cumberland County, North Carolina (Fayetteville) lost 27 and rose 60%. Among metros, Miami lost 23 per 1,000 and rose 60%, San Diego lost 27 and rose 50%, and El Paso, Rochester and Syracuse all lost people and rose about 50%.
| Place | Net per 1,000 | Jan 2020 | Dec 2023 | Change |
|---|---|---|---|---|
| Eagle County, CO | −36.7 | $690,800 | $1,195,800 | +73% |
| Clayton County, GA | −27.1 | $150,100 | $258,600 | +72% |
| Monroe County, FL | −18.3 | $593,600 | $1,005,500 | +69% |
| Miami-Dade County, FL | −48.8 | $321,800 | $517,100 | +61% |
| Clarke County, GA | −38.6 | $195,500 | $313,100 | +60% |
| Camden County, NJ | −2.2 | $195,900 | $313,700 | +60% |
| Cumberland County, NC | −26.6 | $139,300 | $222,700 | +60% |
| Miami-Fort Lauderdale metro | −23.4 | $306,700 | $489,600 | +60% |
| El Paso metro | −10.6 | $146,500 | $220,800 | +51% |
| San Diego metro | −27.1 | $606,600 | $910,600 | +50% |
| Rochester, NY metro | −14.4 | $166,900 | $249,400 | +49% |
Miami is the clearest case of the thing the headcount misses: it lost 40,000 people a year to the rest of the country while the households arriving, from Manhattan above all, earned two to four times what the leavers did. Second homes and investors do not file from the county at all, so they never appear in migration data.
Where did arrivals not move prices?
Texas and Louisiana, where there is room to build. Hardin County, Texas (outside Beaumont) gained 43 people per 1,000 over 2020 to 2023 and its typical home rose 12%, from 201,700 to 224,900 dollars; Laurens County, South Carolina gained 45 and rose 16%; Liberty County, Texas gained 184 per 1,000, the third-fastest of any large county, and rose 27%; Chambers County, Texas gained 128 and rose 24%; Atascosa County, Texas gained 60 and rose 22%. Tangipahoa, St. Tammany and Livingston parishes outside New Orleans gained 21 to 45 per 1,000 and rose 13% to 23%. Among metros, the rural remainder of Texas gained 43 per 1,000 and rose 26%, San Antonio gained 36 and rose 36%, and Houston gained 14 and rose 37%, all under the metro median of 40%.
| County | Net per 1,000 | Jan 2020 | Dec 2023 | Change |
|---|---|---|---|---|
| Hardin County, TX | +42.8 | $201,700 | $224,900 | +12% |
| Tangipahoa Parish, LA | +21.3 | $203,000 | $229,100 | +13% |
| Laurens County, SC | +44.9 | $215,800 | $249,700 | +16% |
| Harrison County, TX | +26.4 | $184,000 | $215,400 | +17% |
| Kenai Peninsula Borough, AK | +34.5 | $264,700 | $313,300 | +18% |
| Cherokee County, SC | +24.2 | $167,000 | $198,000 | +19% |
| St. Tammany Parish, LA | +34.3 | $237,300 | $283,800 | +20% |
| Atascosa County, TX | +60.1 | $204,400 | $249,100 | +22% |
| Livingston Parish, LA | +44.5 | $196,100 | $241,000 | +23% |
| Chambers County, TX | +128.0 | $272,200 | $336,900 | +24% |
| Liberty County, TX | +184.0 | $195,000 | $247,900 | +27% |
Every county in this table started under 275,000 dollars, and most are flat land with few building constraints. Where new houses can be built as fast as people arrive, the arrivals show up in rooftops rather than prices.
What happened in Austin?
The price boom ran on something other than headcount. Travis County, the core of Austin, gained people from migration in 2012 to 2014 and has lost them in every year since 2015 except 2019, including 8,078 in 2021 (6.2 per 1,000) and 8,895 in 2023 (6.6 per 1,000); the growth went to the suburbs. Yet its typical home rose 13% in 2020 and 32% in 2021, from 424,420 dollars in December 2020 to 561,383 a year later, and the median household’s income went from 48,926 to 64,813 dollars between 2020 and 2023. Then it stalled: up 4% in 2022 and down 8% in 2023, to 536,905, and by August 2026 it had fallen to 466,100, 15% below August 2021.
| Year | Net people | Per 1,000 | Value in December | Change in year | Median income |
|---|---|---|---|---|---|
| 2019 | +5,063 | +4.0 | $375,078 | +4.5% | $48,254 |
| 2020 | −2,825 | −2.2 | $424,420 | +13.2% | $48,926 |
| 2021 | −8,078 | −6.2 | $561,383 | +32.3% | $55,897 |
| 2022 | −9,351 | −7.0 | $586,302 | +4.4% | $61,413 |
| 2023 | −8,895 | −6.6 | $536,905 | −8.4% | $64,813 |
The county’s 2012 to 2014 gains of 17,529, 41,210 and 121,251 people are in the IRS data as published and are the only years it gained; the report shows the whole series. Williamson and Hays counties next door, which took the arrivals, have also fallen 12% and 11% since 2021.
Does a one-year lag change the answer?
It weakens it. If movers bid up prices, the effect should show up after they arrive, so the report can shift the price window a year later: January 2021 to December 2024 against the same 2020 to 2023 migration. The state correlation falls from 0.74 to 0.59 and the median rise from 40% to 31%, because the lagged window drops the 2020 surge and adds 2024, when prices in the fastest-growing states had stopped rising. Idaho’s lagged rise is 29% against 54% unlagged, Florida’s 44% against 59%, Montana’s 46% against 61%, while New York is 29% either way and the District of Columbia goes from +6% to −3%.
| State | Net per 1,000 | Same years | One year later |
|---|---|---|---|
| Idaho | +52.9 | +54% | +29% |
| South Carolina | +47.3 | +50% | +38% |
| Montana | +38.3 | +61% | +46% |
| Delaware | +37.3 | +40% | +30% |
| Florida | +35.2 | +59% | +44% |
| Tennessee | +30.0 | +52% | +40% |
| Maine | +28.2 | +61% | +43% |
| North Carolina | +27.8 | +54% | +40% |
| New York | −44.9 | +29% | +29% |
| District of Columbia | −61.1 | +6% | −3% |
The lag is a toggle in the report, beside the year range and the population floor, and the correlation in the scatter’s corner updates with it.
Has the link always been this strong?
No. Across the states the correlation between net migration per 1,000 and home-value change was 0.49 over the 2012 to 2015 migration years, 0.70 over 2016 to 2019 and 0.74 over 2020 to 2023; over the whole of 2012 to 2023 it is 0.64, with the median state’s typical home up 102%. Year by year it peaked in 2016 and 2021 at 0.72, when the median state rose 14% in a single year, and collapsed to −0.06 in 2023, when the median state rose 3% and where people went no longer told you where prices rose.
| Migration years | Correlation | Median price change |
|---|---|---|
| 2012 to 2015 | 0.49 | +16% |
| 2016 to 2019 | 0.70 | +23% |
| 2020 to 2023 | 0.74 | +40% |
| 2012 to 2023 | 0.64 | +102% |
| 2021 alone | 0.72 | +14% |
| 2023 alone | −0.06 | +3% |
The number of people changing states roughly doubled from 2012 to 2021, so the later periods have more movement to correlate. Set the report’s year range to 2012 to 2019 to see the pre-pandemic pattern on the map and the scatter.
How was this measured?
Migration is the IRS county-to-county migration data, 2012 to 2023: people are the exemptions on tax returns that moved county between one year’s filing and the next, netted and divided by the Census Bureau’s average population over the window. Home values are Zillow’s typical home value, compared between January of the first migration year and December of the last, or shifted a year later when the lag is on. Income is the median adjusted gross income of households filing from the county, from IRS brackets, 2013 to 2023.
Correlations are Pearson’s r across the areas named in each caption, computed from the report’s own rows; county and metro figures use the population floors stated. A migration year is a pair of tax years and a price window is calendar months, so the two are aligned to the year, not the day. None of this is cause: a cheap place attracts movers as surely as movers bid up prices, and people who buy a second home or invest do not file from the county and are invisible here.
The data lives in a Power BI semantic model on Microsoft Fabric. Every number on this page was produced by an AI assistant running the report’s own queries against that model, and the same model powers the live public report.
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