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11 states where you don't have to spend more than 30% of your income on housing

Chimera readability score 61 out of 100, Academic reading level.

Most of us have heard the golden rule of housing: Don't spend more than 30% of your income on housing. Known as the 30% rule, it's a benchmark financial experts often cite to help households avoid becoming "house poor" — meaning you have little savings left after paying monthly housing costs.
Unfortunately, for many Americans, that standard works better in theory than in practice. Realtor.com data shows that in most states, households earning the median income cannot comfortably afford a median-priced home without stretching their budgets too thin.
It's a reality shaped by the same persistent strains on housing affordability: high mortgage rates, high home prices, and economic headwinds such as inflation, which continue to drive up the cost of everyday necessities like food and gas.
The good news is that Realtor.com has identified 11 states where homebuyers can still afford homes without overburdening themselves financially. The majority are located in the Midwest, and surprisingly, not a single state in the South — a region often associated with lower living costs — made the cut.
"Midwestern states tend to have stronger labor markets, which keep incomes high relative to home values," said Joel Berner, a senior economist at Realtor.com. They also "have less of a lower tail of household incomes than the Southern states, so more Midwesterners end up able to afford homes."
Here are the 11 states where a household earning the median income can afford a typical home without spending more than 30% of its income, according to Realtor.com.
11. Minnesota
- Share of median income needed to afford a median-priced home: 29.9%
- Median household income: $88,572
- Median home-list price: $388,212
10. Maryland
- Share of median income needed to afford a median-priced home: 29.8%
- Median household income: $99,340
- Median home-list price: $434,302
9. Missouri
- Share of median income needed to afford a median-priced home: 29.5%
- Median household income: $69,725
- Median home-list price: $301,158
8. West Virginia
- Share of median income needed to afford a median-priced home: 29.4%
- Median household income: $60,185
- Median home-list price: $259,523
7. Pennsylvania
- Share of median income needed to afford a median-priced home: 28.5%
- Median household income: $74,855
- Median home-list price: $312,487
6. Michigan
- Share of median income needed to afford a median-priced home: 28.3%
- Median household income: $70,131
- Median home-list price: $290,329
5. Indiana
- Share of median income needed to afford a median-priced home: 28.3%
- Median household income: $71,469
- Median home-list price: $295,810
4. Kansas
- Share of median income needed to afford a median-priced home: 27%
- Median household income: $74,030
- Median home-list price: $292,632
3. Ohio
- Share of median income needed to afford a median-priced home: 27%
- Median household income: $70,196
- Median home-list price: $277,348
2. Illinois
- Share of median income needed to afford a median-priced home: 26%
- Median household income: $80,648
- Median home-list price: $307,674
1. Iowa
- Share of median income needed to afford a median-priced home: 25.4%
- Median household income: $75,991
- Median home-list price: $282,886

Sentinel — Human

Confidence

This text is a well-structured, fact-based report that successfully synthesizes specific data with broader socioeconomic implications regarding housing affordability across US regions.

Signals Detected
low severity: Sentence length and flow are varied, interspersed with specific data presentation rather than uniform rhythm.
low severity: The text successfully connects an abstract rule (30% rule) to concrete, verifiable data points, demonstrating logical flow appropriate for journalistic analysis.
low severity: The structure is highly coordinated; the expert quote flows logically into the empirical results. No verbatim talking points are present.
low severity: All presented data points (state names, income figures, price list prices) require cross-referencing with Realtor.com data, indicating a reliance on external, verifiable sources rather than internal fabrication.
Human Indicators
Use of nuanced contextual framing (e.g., discussing systemic bias and underlying assumptions) that goes beyond simple data recitation.
The integration of a specialized expert quote tied directly to the geographical analysis provides an analytical layer not typical of pure LLM generation.
The ability to pivot from a widely accepted financial rule into a deep discussion of regional economic disparities demonstrates interpretive capacity.