How affordable is this community?
This chart tracks whether housing prices are keeping pace with local incomes. The gap between what homes cost and what households can afford reveals affordability trends over time.
| $339,218 | Typical home price (Zillow, Dec 2025) |
| 6.20% | 30-year fixed mortgage rate (Freddie Mac, Dec 2025) |
| 3.08% | Effective property tax rate |
| N/A | Average annual homeowner's insurance |
| $119,400 | Area median income (HUD, 2025) |
| 30% | Assumed max housing cost share of income |
Housing affordability data combines Zillow home value estimates with American Community Survey income data. Monthly costs include mortgage payments (at current rates), property taxes, insurance, and HOA fees where applicable.
How is the population changing?
Population growth patterns reveal how communities are evolving. This chart shows historical population changes by age group and projects future trends based on demographic patterns.
Population data comes from the American Community Survey (ACS) annual estimates. Age cohort breakdowns use Census Bureau age groupings to show generational patterns in community growth.
How are households changing by income?
Understanding how households at different income levels are growing or declining helps identify which groups face the greatest housing pressure and where new housing is most needed.
| AMI Group | Income Range | Households |
|---|---|---|
| <30% | <$36K | 43,965 |
| 30-60% | $36K - $72K | 27,545 |
| 60-80% | $72K - $96K | 36,918 |
| 80-100% | $96K - $119K | 22,010 |
| 100-120% | $119K - $143K | 17,390 |
| >120% | >$143K | 58,073 |
Household income distribution data comes from the American Community Survey Public Use Microdata Sample (PUMS). Income groups are defined based on Area Median Income (AMI) thresholds from HUD.
Who lives here today?
Households may have different structure type preferences depending on characteristics such as household size, income, employment, presence of children, age of individuals, and lifestyle choices. Understanding the housing stock in corresponding terms helps assess how well existing units align with existing households' ideals.
This chart shows how household composition has changed over time, comparing the distribution of household types between 2015 and 2023. Changes in household types can indicate shifting demographics and evolving housing needs in a community.
Cost burden measures the share of household income spent on housing. Households paying more than 30% are considered cost burdened, while those paying more than 50% are severely cost burdened. Lower-income households typically face the highest rates of cost burden.
This analysis cross-tabulates household demographic characteristics with income levels using Public Use Microdata Sample (PUMS) data from the American Community Survey. Income groups are defined based on Area Median Income (AMI) thresholds obtained from HUD, creating six bins of AMI. These AMI-based thresholds are converted to dollar amounts for each year and adjusted for inflation to ensure temporal consistency. For each characteristic, the analysis counts weighted households falling within each income bin, using PUMS household weights where relevant.
What does the housing stock look like?
The mix of housing types and ownership patterns shapes a community's character. This chart breaks down housing units by structure type and whether they're owner-occupied or rented.
Housing stock data comes from the American Community Survey (ACS) 5-year estimates. Structure types include single-family detached, townhomes, small multifamily (2-4 units), and larger apartment buildings.
How much new housing supply is needed?
To keep up with growth and fill current housing shortages, Camden County, NJ needs 19,358 new units over the next 6 years.
| 11,304 |
Units needed to keep up with expected growth
Projected total household growth from 2026 to 2032.
|
| 5.5% |
Projected household growth rate
Expected increase in total households from 205,901 in 2026 to 217,205 in 2032
|
| 8,054 |
Units to address shortages in existing housing stock
Production needs to address vacancy rates and other factors.
|
| 128 |
Replacement housing
Annual replacement rate for overall housing stock is 0.01%
|
| 1,113 |
Ownership vacancy adjustment
Owner-occupied vacancy is 1.0%, below the minimum stable target of 1.5%
|
| 6,813 |
Rental vacancy adjustment
Rental vacancy is 4.2%, below the minimum stable target of 7.4%
|
| 19,358 |
Total 6-year housing production need (2026-2032)
|
| 3,226 |
Annual production pace
Average units needed per year to meet 6-year need
|
| 9.1% |
Total housing unit growth
Percent increase in housing stock over 6 years
|
| 1.5% |
Annual housing unit growth
Average percent increase in housing stock per year
|
6-Year Housing Production Need Methodology
The housing production need represents the total number of new housing units needed over a 6-year period to accommodate projected growth while addressing existing market imbalances. This comprehensive approach accounts for six distinct components of housing need.
Net Household Growth forms the baseline demand, calculated by projecting net positive household growth as described earlier. The household formation rate captures demographic shifts and changing living arrangements over the forecast period.
Replacement Housing accounts for units lost to demolition, disaster, or conversion to non-residential use. The annual replacement rate is calculated from historical patterns in the American Community Survey's year-built data (B25034), identifying the typical rate at which older housing stock exits the market.
Vacancy Adjustments ensure healthy market functioning by comparing current vacancy rates to minimum stability targets. For owner-occupied units, a 1.5% vacancy rate enables normal market turnover for home sales. For rentals, a 7.4% vacancy rate (derived from historical market equilibrium analysis) allows reasonable choice and mobility. When current rates fall below these thresholds, additional units are needed to restore market fluidity. The adjustment equals the existing housing stock multiplied by the gap between target and actual vacancy rates. Source: Belsky, E. S., Drew, R. B., & McCue, D. (2007). Projecting the Underlying Demand for New Housing Units: Inferences from the Past, Assumptions about the Future (W07-7). Joint Center for Housing Studies, Harvard University.
Overcrowding and Substandard Housing Adjustments address existing deficiencies in housing quality. Overcrowding (more than one person per room) and substandard conditions (lacking complete plumbing or kitchen facilities) are compared to national averages from ACS data. If local rates exceed national benchmarks, additional units are prescribed to provide adequate housing options. These adjustments equal zero when local conditions are less than the national norms.
The total production need sums all components to address market health and housing adequacy.