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Demographics by ZIP Code

Housing Data by ZIP Code: Owners, Renters, and Values

ZIP-level housing data reveals owner-renter ratios, median home values, and vacancy rates that shape neighborhood character.

## Housing at the ZIP Level

The Census Bureau's American Community Survey tracks detailed housing data at the ZCTA level, providing a window into neighborhood stability, affordability, and character.

## Key Housing Metrics

| Metric | National Avg | Range |
|--------|-------------|-------|
| Owner-occupied rate | 65.4% | 5% - 98% |
| Median home value | $281,900 | $25,000 - $3,000,000+ |
| Median rent | $1,163/mo | $400 - $3,500+ |
| Vacancy rate | 10.3% | 0% - 85% |
| Housing units per ZCTA | ~3,000 | 10 - 40,000+ |

*Source: ACS 5-Year Estimates, 2018-2022*

## Owner vs. Renter Geography

The owner-renter split varies dramatically by ZIP:

- **Highest ownership** — Rural and suburban ZIPs often exceed 85% owner-occupied
- **Lowest ownership** — Manhattan ZIPs are 75-80% renter-occupied
- **College towns** — High renter rates due to student populations
- **Military bases** — High renter rates due to transient population
- **Retirement communities** — Often high ownership despite older demographics

## Home Value Extremes

Median home values span three orders of magnitude:

| ZIP | Location | Median Home Value |
|-----|----------|-------------------|
| 94027 | Atherton, CA | $7,100,000 |
| 90210 | Beverly Hills, CA | $3,800,000 |
| 10007 | New York, NY (FiDi) | $2,900,000 |
| 48209 | Detroit, MI | $45,000 |
| 38702 | Greenville, MS | $38,000 |

## Vacancy Patterns

High vacancy rates tell different stories:

- **Seasonal** — Beach towns and ski resorts (30-60% vacant seasonally)
- **Declining** — Rust Belt cities with population loss
- **Transitional** — Neighborhoods undergoing rapid change
- **New construction** — Recently built developments not yet occupied

## Using Housing Data

Housing data by ZIP code serves multiple purposes:

- **Real estate investment** — Identifying undervalued or growing markets
- **Lending** — Banks use ZIP-level data for CRA compliance
- **Urban planning** — Targeting affordable housing investments
- **Insurance** — Homeowner insurance rates correlate with home values

Key Terms

Housing Units Median Home Value Owner-Occupied Housing Renter-Occupied Housing ZIP Code Tabulation Area

Related Tools

Population Lookup

Look up population data for any ZIP code, city, or county. Census-derived population estimates.

 Income Comparison

Compare median household income between ZIP codes. See how neighborhoods stack up economically.

 Cost of Living Comparison

Compare cost of living between ZIP codes using housing, income, and demographic data.

相关故事

Census Data and ZIP Codes: What You Can Learn

What Census data is available by ZIP code? Learn about ACS demographics, ZCTAs, data sources, and common pitfalls.

Income Inequality by ZIP Code

Income inequality by ZIP code: the richest vs poorest ZIPs, geographic patterns, and what the data reveals about opportunity.

Population Density: Urban, Suburban, and Rural ZIPs

Population density by ZIP code: urban vs rural extremes, Census classifications, and why density drives business decisions.

Education Levels by ZIP Code

Education levels by ZIP code: college degree rates, geographic patterns, the education-income link, and practical uses.

常见问题

在哪里可以了解更多关于邮政编码系统的信息？
ZipFYI的故事专栏刊载有关全球邮政编码系统的深度文章，包括其历史、工作原理和重要性。主题涵盖从ZIP code的起源到现代邮政系统如何每天处理数百万个包裹。
邮政编码系统如何随时间演变？
邮政编码系统会发展演变以适应人口增长、城市化和邮件量变化。当地区发展时会创建新代码，当投递路线变化时代码可能被重新分配，整个系统可以进行改革（如爱尔兰2015年推出Eircode）。
为什么邮政编码对企业很重要？
企业使用邮政编码进行运输和物流、销售税计算、市场分析、客户人口统计、配送区域确定、保险承保和法规合规。准确的邮政编码可以减少投递失败并改善客户体验。
邮政编码与人口统计数据有什么关系？
在美国，人口普查局将人口统计数据与ZIP Code Tabulation Areas（ZCTA）关联。这使得在邮政编码级别分析人口、收入、教育、住房和通勤模式成为可能。营销人员、研究人员和政策制定者广泛依赖这些数据。
什么是地理编码，它与邮政编码有什么关系？
地理编码将地址和邮政编码转换为地理坐标（纬度/经度）。它实现了地图绘制、距离计算、配送路线规划和空间分析。邮政编码是地理编码服务的常见输入，因为它们提供大致的位置数据。