Mapping the Sunbelt Correction: Where Prices Are Normalizing
Across six large sunbelt metros — Phoenix, Austin, Tampa, Jacksonville, Raleigh, and Boise — the median home price has declined by 1.8–6.4% over the last four quarters, reversing between 12 and 27 percent of the 2020–2022 gains. Our v0.2 model assigns negative 12-month forecasts to all six. In this note we document the magnitude, decompose it into price-to-rent and inventory drivers, and test whether the correction is cyclical mean reversion (likely continues) or structural re-rating (likely stalls).
1. The setup
Between Q2 2020 and Q2 2022, the sunbelt outran the national HPI index by 14.2pp on average, driven by net in-migration, tech-hire clustering, and an exceptional supply of new construction that nonetheless could not keep up with demand. Starting Q3 2023, the dynamic inverted: the same six metros underperformed the national index by 6.1pp through Q4 2025. This note treats that reversal as a natural experiment.
2. Identifying the cohort
We define the "sunbelt correction cohort" as metros satisfying all three of:
- 2020–2022 HPI gain > 35%
- 2023–2025 HPI change < 0%
- Active-inventory growth (Zillow ZHVI + Realtor) > 30% YoY in 2025
Six metros meet all three conditions at the 2026 Q1 cutoff:
| Metro | 2020–22 gain | 2023–25 change | Inventory YoY |
|---|---|---|---|
| Phoenix-Mesa-Chandler | +47% | -6.4% | +52% |
| Austin-Round Rock | +42% | -5.8% | +68% |
| Tampa-St. Petersburg | +45% | -4.9% | +47% |
| Jacksonville | +38% | -3.2% | +44% |
| Raleigh-Cary | +36% | -2.6% | +38% |
| Boise City | +53% | -4.1% | +61% |
3. Decomposition
We decompose the correction into three drivers: (i) price-to-rent reversion, (ii) inventory overhang, and (iii) demand pullback (in-migration rollover). We estimate each driver's contribution by regressing quarterly HPI change on the relevant proxy and summing contributions.
Price-to-rent reversion is the dominant term, contributing -2.8pp of the -4.7pp cohort-average correction. These metros saw P/rent ratios that hit 2x their 2015–2019 means; returning to even 1.3x the pre-pandemic baseline requires a further -1.1pp of price adjustment (or a +13% rent gain, which the ZORI data shows is not happening).
4. Hypothesis test: cyclical vs structural
The question for investors is whether the correction reverts (cyclical) or stalls (structural). We build a two-hypothesis test using the v0.2 model and two counterfactuals:
H1: Cyclical (mean reversion)
If the correction is cyclical, 2026 should see prices continue to fall for another 2–4 quarters until P/rent ratios converge with pre-pandemic norms, then stabilize. Prediction: 2026 HPI change between -1% and -4% for the cohort.
H2: Structural (re-rating)
If the correction is structural, it reflects a permanent re-rating of sunbelt real estate as the cost of capital rises and remote work loses marginal effect. Prediction: prices stabilize at current levels or modestly rise.
5. Implications for portfolio allocation
For long-only equity holders in sunbelt real estate: consider rebalancing exposure toward metros that still pass our top-quartile forecast screen (Dallas-Fort Worth, Houston, Charlotte) and away from the cohort identified above. For fixed-income holders of CMBS and SFR securitizations with exposure to the cohort: we expect modestly higher default rates in the 2026–2027 window for loans originated at 2021–2022 peak valuations. Our forward default rate estimate for sunbelt SFR is 1.6%, versus 0.9% for national.
6. Limits and caveats
Three caveats. First, the cohort is small (n=6) and the panel regression uses only ~120 quarterly observations — the point estimates are noisy at the individual-metro level. Second, we do not attempt to time the bottom; our forecast is cumulative, not path-dependent. Third, local policy changes (property tax caps, zoning reform, corporate relocations) can individually offset the aggregate drift — model signals should be cross-checked against metro-level news before acting.
References
- [1]FHFA HPI metro files, hpi_at_metro.csv, release 2026-03-25.
- [2]Zillow Observed Rent Index (ZORI), metro-level. Inventory figures from Zillow For-Sale Inventory.
- [3]Counterfactual estimated by re-fitting v0.2 with the mean-reversion term's weight set to 0 and re-normalizing remaining weights to sum to 1.