Graph and download economic data for Consumer Price Index for All Urban Consumers: Housing in Seattle-Tacoma-Bellevue WA (CBSA) (CUURA423SAH) from Nov 1975 to Apr 2025 about Seattle, WA, urban, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

U.S. Census Bureau QuickFacts statistics for Seattle city, Washington. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Data from: 2010 Decennial Census

Data from: 2010 Decennial Census

Table from the American Community Survey (ACS) 5-year series on housing tenure and cost related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B25003 Tenure of Occupied Housing Units, B25070 Gross Rent as a Percentage of Household Income in the Past 12 Months, B25063 Gross Rent, B25091 Mortgage Status by Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months, B25087 Mortgage Stauts and Selected Monthly Owner Costs, B25064 Median Gross Rent, B25088 Median Selected Monthly Owner Costs by Mortgage Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B25003, B25070, B25063, B25091, B25087, B25064, B25088Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Analysis of ‘Census Block - 2010 Housing Statistics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/23c9060f-7640-4206-a9d0-99bc2b1a9b11 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

Data from: 2010 Decennial Census

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Census Tract - 2010 Household Statistics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/16e5c03b-655b-4bff-9685-8c84109acc16 on 11 February 2022.

--- Dataset description provided by original source is as follows ---

Data from: 2010 Decennial Census

--- Original source retains full ownership of the source dataset ---

Graph and download economic data for Consumer Price Index for All Urban Consumers: Food at Home in Seattle-Tacoma-Bellevue WA (CBSA) (CUURA423SAF11) from Jan 1953 to May 2025 about Seattle, WA, urban, food, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

In the first quarter of 2025, San Francisco, Chicago, New York, and Honolulu were some of the U.S. cities with the highest housing construction costs. Meanwhile, Phoenix had one of the lowest construction costs for high-end multifamily homes at *** U.S. dollars per square foot and Las Vegas for single-family homes between *** and *** U.S. dollars per square foot. Construction cost disparities As seen here, the construction cost for a high-end multi-family home in San Francisco in the first quarter of 2024 was over ***** more expensive than in Phoenix. Meanwhile, there were also great differences in the cost of building a single-family house in New York and in Portland or Seattle. Some factors that may cause these disparities are the construction materials, installation, and composite costs, differing land values, wages, etc. For example, although the price of construction materials in the U.S. was rising at a slower level than in 2022 and 2023, several materials that are essential in most construction projects had growth rates of over **** percent in 2024. Growing industry revenue Despite the economic uncertainty and other challenges, the size of the private construction market in the U.S. rose during the past years. It is important to consider that supply and demand for housing influences the revenue of this segment of the construction market. On the supply side, single-family home construction fell in 2023, but it is expected to rise in 2024 and 2025. On the demand side, some of the U.S. metropolitan areas with the highest sale prices of single-family homes were located in California, with San Jose-Sunnyvale-Santa Clara at the top of the ranking.

The U.S. housing market has slowed, after ** consecutive years of rising home prices. In 2021, house prices surged by an unprecedented ** percent, marking the highest increase on record. However, the market has since cooled, with the Freddie Mac House Price Index showing more modest growth between 2022 and 2024. In 2024, home prices increased by *** percent. That was lower than the long-term average of *** percent since 1990. Impact of mortgage rates on homebuying The recent cooling in the housing market can be partly attributed to rising mortgage rates. After reaching a record low of **** percent in 2021, the average annual rate on a 30-year fixed-rate mortgage more than doubled in 2023. This significant increase has made homeownership less affordable for many potential buyers, contributing to a substantial decline in home sales. Despite these challenges, forecasts suggest a potential recovery in the coming years. How much does it cost to buy a house in the U.S.? In 2023, the median sales price of an existing single-family home reached a record high of over ******* U.S. dollars. Newly built homes were even pricier, despite a slight decline in the median sales price in 2023. Naturally, home prices continue to vary significantly across the country, with West Virginia being the most affordable state for homebuyers.

In November 2024, a single-family house in Oak Bay cost 1.9 million Canadian dollars. Oak Bay was the most expensive suburb in Victoria, British Columbia, followed by Highlands and North Saanich. Victoria: an overview Victoria is the capital city of the province of British Columbia. The city is located south of Vancouver, and across the U.S. border from Seattle. In 2020, the average home price in Victoria was 961,000 Canadian dollars, which placed the city as the sixth most expensive Canadian city for residential real estate. Home affordability in Canada Housing affordability is, undoubtedly, one of the biggest barriers to homeownership in Canada. In 2023, the ratio of homeownership costs to income was 62.5 percent. Nevertheless, more expensive locations in the country had a higher ratio, with Vancouver exceeding 100 percent, suggesting that on average, mortgage payments exceeded the monthly income. Amid lower affordability and worsening homebuyer sentiment, house prices in some of Canada's markets are forecast to decline slightly in 2024.