How much income does a household need to buy the median-priced home?
This chart compares [place]’s specific median income estimate with the income needed to afford the median home price in [place]. A wider gap means a higher barrier to entry for homebuyers.
| $597,535 | Median home price (June 2025) |
| 6.65% | Mortgage rate (FRED, June 2025) |
| 2.68% | Property tax rate (estimate, 2025) |
| 0.04% | Homeowners insurance as percentage of home value (treasury.gov estimate, 2025) |
| 30% | Percent of household income spent on housing costs |
| 20% | Downpayment assumption |
How is the population growing by age group?
This chart illustrates trends in population by age cohort, both historic and projected. The projection is based on recent trends extended. Depending on economic, policy, and other conditions, the future age distribution may vary over time.
This population projection method divides people into age groups and tracks how each group changes over time. It analyzes past patterns to predict future population changes using annual change ratios and birth rates.
What is the household growth trajectory by income group?
Housing needs are influenced by a change in the number of households, and by those households’ incomes. These income groups are represented by the percentage of HUD’s published area median income. The growth trend is based on the slope of the previous 15 years.
| AMI group | Household income | Households | Max monthly housing costs | Max purchase price | Bedrooms demand avg. | Income earners avg. | Householder age avg. |
|---|---|---|---|---|---|---|---|
| <50% | <$50K | 1,924 | <$1,250 | $136K | 2.0 | 0.4 | 60 |
| 50-80% | $50K - $80K | 1,772 | <$2,000 | <$217K | 2.4 | 0.9 | 56 |
| 80-120% | $80K - $120K | 1,867 | <$3,000 | <$333K | 2.7 | 1.4 | 54 |
| 120-150% | $120K - $150K | 1,302 | <$3,750 | <$417K | 2.9 | 1.7 | 53 |
| 150-190% | $150K - $200K | 1,698 | <$5,000 | <$560K | 3.1 | 1.8 | 54 |
| >190% | >$200K | 5,826 | >$5,000 | >$560K | 3.2 | 1.8 | 52 |
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.
Cost burden measures the percentage of household income spent on housing costs. Households spending more than 30% of their income on housing are considered cost-burdened, while those spending more than 50% are severely cost-burdened. This analysis helps identify which income groups face the greatest housing affordability challenges.
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 housing is on the ground today?
Inventory of the current local housing stock by tenure, including structure type and bedroom count.
This analysis characterizes the local housing inventory across multiple dimensions using American Community Survey (ACS) data supplemented by Public Use Microdata Sample (PUMS) analysis. Housing tenure is derived from ACS table B25003, which categorizes all housing units as owner-occupied, renter-occupied, or vacant. Structure type classification uses ACS table B25024 to group housing units into five categories: single-family detached, single-family attached and 2-4 unit buildings, 5-49 unit buildings, 50+ unit buildings, and other structures (including mobile homes). Bedroom distribution is extracted from ACS table B25041, categorizing units as studio/1-bedroom, 2-bedroom, 3-bedroom, or 4+ bedroom homes. Cross-tabulations between tenure and both structure type (B25032) and bedroom count (B25042) reveal how different housing configurations serve owner versus renter households.
How much new housing supply is needed?
This 10-year housing production target accounts for projected household growth plus adjustments intended to relieve underlying market pressures, such as pent up demand and current shortages.
| 1,437 |
Total 10-year housing production target (2025-2035)
|
| 1,133 |
Net growth in households
Projected total household growth from 2025 to 2035 is 9.8%.
|
| 62 |
Replacement housing
Annual replacement rate for overall housing stock is 0.1%
|
| 166 |
Ownership vacancy adjustment
Owner-occupied vacancy is 0.4%, below the minimum stable target of 1.5%
|
| 76 |
Rental vacancy adjustment
Rental vacancy is 6.9%, below the minimum stable target of 7.4%
|
| 0 |
Overcrowding adjustment
Overcrowding rate is 0.4%, below the National avg. of 3.4%
|
| 0 |
Substandard housing adjustment
Substandard housing rate is 0.2%, below the National avg. of 0.4%
|
10-Year Housing Production Target Methodology
The housing production target represents the total number of new housing units needed over a 10-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 target sums all component to address market health and housing adequacy.
Map
How does [place] compare to similar communities?
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.
| Place | Households | Household growth 2010-2023 | 65+ households | Median household income | Vacant units |
|---|---|---|---|---|---|
| Carmel, IN | 38,160 | 36.17% | 25.98% | $138,640 | 5.72% |
| Brookline, MA | 27,210 | 11.17% | 26.48% | $144,850 | 5.18% |
| Oak Park, IL | 23,267 | 6.06% | 28.21% | $111,267 | 5.70% |
| Dublin, OH | 17,797 | 25.84% | 24.56% | $159,940 | 3.39% |
| Upper Arlington, OH | 14,389 | 8.29% | 33.73% | $155,523 | 4.85% |
| Manhattan, NY | 14,258 | 2.50% | 23.48% | $178,571 | 16.00% |
| Westfield, NJ | 10,989 | 3.61% | 20.29% | $198,042 | 5.50% |
| Needham, MA | 10,971 | 1.35% | 29.48% | $226,875 | 5.62% |
| Lexington, MA | 10,909 | -5.41% | 27.35% | $206,190 | 6.24% |
| Birmingham, MI | 8,815 | 1.35% | 29.45% | $130,648 | 4.01% |
| Great Neck village, NY | 3,916 | 3.46% | 27.48% | $157,500 | 4.46% |