Graph and download economic data for All-Transactions House Price Index for San Francisco-San Mateo-Redwood City, CA (MSAD) (ATNHPIUS41884Q) from Q3 1975 to Q3 2025 about San Francisco, appraisers, CA, HPI, housing, price index, indexes, price, and USA.

Graph and download economic data for S&P CoreLogic Case-Shiller CA-San Francisco Home Price Index (SFXRNSA) from Jan 1987 to Sep 2025 about San Francisco, CA, HPI, housing, price index, indexes, price, and USA.

The S&P Case Shiller San Francisco Home Price Index measures changes in the prices of existing single-family homes in San Francisco. The index value was equal to 100 as of January 2000, so if the index value is equal to 130 in a given month, for example, it means that the house prices have increased by 30 percent since 2000. The value of the S&P Case Shiller San Francisco Home Price Index amounted to nearly ****** in August 2025. That was significantly higher than the national average.

View monthly updates and historical trends for Case-Shiller Home Price Index: San Francisco, CA. Source: Standard and Poor's. Track economic data with YCh…

VITAL SIGNS INDICATOR
Home Prices (EC7)

FULL MEASURE NAME
Home Prices

LAST UPDATED
December 2022

DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021

Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021

US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.

Graph and download economic data for All-Transactions House Price Index for San Jose-Sunnyvale-Santa Clara, CA (MSA) (ATNHPIUS41940Q) from Q3 1975 to Q3 2025 about San Jose, appraisers, CA, HPI, housing, price index, indexes, price, and USA.

Graph and download economic data for Home Price Index (High Tier) for San Francisco, California (SFXRHTNSA) from Jan 1987 to Sep 2025 about high tier, San Francisco, HPI, housing, price index, indexes, price, and USA.

Graph and download economic data for Housing Inventory: Median Listing Price in San Francisco-Oakland-Hayward, CA (CBSA) (MEDLISPRI41860) from Jul 2016 to Oct 2025 about San Francisco, CA, listing, median, price, and USA.

VITAL SIGNS INDICATOR List Rents (EC9)

FULL MEASURE NAME List Rents

LAST UPDATED October 2016

DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

DATA SOURCE real Answers (1994 – 2015) no link

Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

Inflation-adjusted data are presented to illustrate how rents have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

A recent New York Times article examines one of the biggest drivers in a families' decision to leave cities: school. Using data from a number of sources, the New York Times developed charts that look at school performance and median home sale price per square foot for five metro areas including New York/New Jersey, San Francisco, Boston, Chicago, and Minneapolis.For most of the cities studied, home prices rise with the quality of the school district but a number of districts break this pattern. The map shown highlights five Bay Area schools that perform above average, and have below average housing costs.The New York Times used median price per square foot to measure housing costs and the median number of grades ahead (or behind) for school district quality. In the San Francisco Bay Region, the price per square foot was around $500 while students were .28 grades ahead of their grade placement. The five Bay Area schools that were selected had the lowest home prices and the best performing schools in the region.Source: New York Times

United States Median Existing Home Price: MA: Green Bay data was reported at 169.800 USD th in Mar 2018. This records an increase from the previous number of 165.100 USD th for Dec 2017. United States Median Existing Home Price: MA: Green Bay data is updated quarterly, averaging 131.100 USD th from Mar 1989 (Median) to Mar 2018, with 114 observations. The data reached an all-time high of 170.600 USD th in Sep 2017 and a record low of 57.200 USD th in Dec 1989. United States Median Existing Home Price: MA: Green Bay data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s USA – Table US.EB007: Median Existing Home Price: by Metropolitan Area.

In 2008, the Department of Housing and Urban Development (HUD) created a Neighborhood Stabilization Program to provide emergency assistance to state and local governments to acquire and redevelop foreclosed properties that might otherwise become sources of abandonment and blight within their communities. This program provides grants to every state, certain local communities, and other organizations to purchase foreclosed or abandoned homes and to rehabilitate, resell, or redevelop these homes in order to stabilize neighborhoods and stem the decline of house values of neighboring homes. This map scores neighborhoods in the bay area on a scale of 1 to 20 where 20 indicates areas in the highest 20% of risk nationwide for home foreclosures and abandonment. 1 indicates areas with lowest risk.This ranking is based upon the following factors developed by HUD:whether or not loans are high cost or highly leveraged in the neighborhoodchange in home values for the metropolitan, or non-metropolitan portion of the stateunemployment rate for the county in 2008, andthe change in unemployment in the county between 2007 and 2008.HUD is providing its data on estimated foreclosures (based on risk) and vacancy data to assist state and local governments in their efforts to target the communities and neighborhoods with the greatest needs. HUD recommends that if states and local governments have local data, such as county data on foreclosure filings, that those data also be given serious consideration in identifying areas of greatest needs.Map Source: https://www.huduser.org/portal/datasets/nsp.html

This project looked into transportation, population density, and proximity to major companies as potential predictor of housing market, and combined all features onto one map using ArcGIS. Finally, it built a linear regression and random forest model on choosing the best housing location near major companies in Bay Area. The features in the final model included the commute duration to the nearest bart station and nearest big employing company without traffic, the population density, and the Covid house appreciation factor for an area. Additional information in the Project PDFNotable Modules Used: Python: pandas, numpy, matplotlib, sklearn ArcGIS: overlay_layers, find_nearest

United States Median Home Sale Price: sa: All Residential: Coos Bay, OR data was reported at 260.000 USD th in Jul 2020. This records an increase from the previous number of 249.000 USD th for Jun 2020. United States Median Home Sale Price: sa: All Residential: Coos Bay, OR data is updated monthly, averaging 181.500 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 260.000 USD th in Jul 2020 and a record low of 106.000 USD th in May 2012. United States Median Home Sale Price: sa: All Residential: Coos Bay, OR data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB057: Median Home Sale Price: by Metropolitan Areas: Seasonally Adjusted.

Ebitda Time Series for Alexandria Real Estate Equities Inc. Alexandria Real Estate Equities, Inc. (NYSE: ARE), an S&P 500 company, is a best-in-class, mission-driven life science REIT making a positive and lasting impact on the world. With our founding in 1994, Alexandria pioneered the life science real estate niche. Alexandria is the preeminent and longest-tenured owner, operator, and developer of collaborative Megacampus ecosystems in AAA life science innovation cluster locations, including Greater Boston, the San Francisco Bay Area, San Diego, Seattle, Maryland, Research Triangle, and New York City. As of September 30, 2025, Alexandria has a total market capitalization of $27.8 billion and an asset base in North America that includes 39.1 million RSF of operating properties and 4.2 million RSF of Class A/A+ properties undergoing construction and one 100% pre-leased committed near-term project expected to commence construction in the next year. Alexandria has a long-standing and proven track record of developing Class A/A+ properties clustered in highly dynamic and collaborative Megacampus environments that enhance our tenants' ability to successfully recruit and retain world-class talent and inspire productivity, efficiency, creativity, and success. Alexandria also provides strategic capital to transformative life science companies through our venture capital platform. We believe our unique business model and diligent underwriting ensure a high-quality and diverse tenant base that results in higher occupancy levels, longer lease terms, higher rental income, higher returns, and greater long-term asset value.

Total-Current-Assets Time Series for Alexandria Real Estate Equities Inc. Alexandria Real Estate Equities, Inc. (NYSE: ARE), an S&P 500 company, is a best-in-class, mission-driven life science REIT making a positive and lasting impact on the world. With our founding in 1994, Alexandria pioneered the life science real estate niche. Alexandria is the preeminent and longest-tenured owner, operator, and developer of collaborative Megacampus ecosystems in AAA life science innovation cluster locations, including Greater Boston, the San Francisco Bay Area, San Diego, Seattle, Maryland, Research Triangle, and New York City. As of September 30, 2025, Alexandria has a total market capitalization of $27.8 billion and an asset base in North America that includes 39.1 million RSF of operating properties and 4.2 million RSF of Class A/A+ properties undergoing construction and one 100% pre-leased committed near-term project expected to commence construction in the next year. Alexandria has a long-standing and proven track record of developing Class A/A+ properties clustered in highly dynamic and collaborative Megacampus environments that enhance our tenants' ability to successfully recruit and retain world-class talent and inspire productivity, efficiency, creativity, and success. Alexandria also provides strategic capital to transformative life science companies through our venture capital platform. We believe our unique business model and diligent underwriting ensure a high-quality and diverse tenant base that results in higher occupancy levels, longer lease terms, higher rental income, higher returns, and greater long-term asset value.

Short-Term-Debt Time Series for Alexandria Real Estate Equities Inc. Alexandria Real Estate Equities, Inc. (NYSE: ARE), an S&P 500 company, is a best-in-class, mission-driven life science REIT making a positive and lasting impact on the world. With our founding in 1994, Alexandria pioneered the life science real estate niche. Alexandria is the preeminent and longest-tenured owner, operator, and developer of collaborative Megacampus ecosystems in AAA life science innovation cluster locations, including Greater Boston, the San Francisco Bay Area, San Diego, Seattle, Maryland, Research Triangle, and New York City. As of September 30, 2025, Alexandria has a total market capitalization of $27.8 billion and an asset base in North America that includes 39.1 million RSF of operating properties and 4.2 million RSF of Class A/A+ properties undergoing construction and one 100% pre-leased committed near-term project expected to commence construction in the next year. Alexandria has a long-standing and proven track record of developing Class A/A+ properties clustered in highly dynamic and collaborative Megacampus environments that enhance our tenants' ability to successfully recruit and retain world-class talent and inspire productivity, efficiency, creativity, and success. Alexandria also provides strategic capital to transformative life science companies through our venture capital platform. We believe our unique business model and diligent underwriting ensure a high-quality and diverse tenant base that results in higher occupancy levels, longer lease terms, higher rental income, higher returns, and greater long-term asset value.

Graph and download economic data for Condo Price Index for San Francisco, California (SFXRCNSA) from Jan 1995 to Aug 2025 about San Francisco, HPI, housing, price index, indexes, price, and USA.

Graph and download economic data for All-Transactions House Price Index for Oakland-Berkeley-Livermore, CA (MSAD) (ATNHPIUS36084Q) from Q2 1975 to Q3 2025 about Oakland, appraisers, CA, HPI, housing, price index, indexes, price, and USA.

Return-On-Equity Time Series for Alexandria Real Estate Equities Inc. Alexandria Real Estate Equities, Inc. (NYSE: ARE), an S&P 500 company, is a best-in-class, mission-driven life science REIT making a positive and lasting impact on the world. With our founding in 1994, Alexandria pioneered the life science real estate niche. Alexandria is the preeminent and longest-tenured owner, operator, and developer of collaborative Megacampus ecosystems in AAA life science innovation cluster locations, including Greater Boston, the San Francisco Bay Area, San Diego, Seattle, Maryland, Research Triangle, and New York City. As of September 30, 2025, Alexandria has a total market capitalization of $27.8 billion and an asset base in North America that includes 39.1 million RSF of operating properties and 4.2 million RSF of Class A/A+ properties undergoing construction and one 100% pre-leased committed near-term project expected to commence construction in the next year. Alexandria has a long-standing and proven track record of developing Class A/A+ properties clustered in highly dynamic and collaborative Megacampus environments that enhance our tenants' ability to successfully recruit and retain world-class talent and inspire productivity, efficiency, creativity, and success. Alexandria also provides strategic capital to transformative life science companies through our venture capital platform. We believe our unique business model and diligent underwriting ensure a high-quality and diverse tenant base that results in higher occupancy levels, longer lease terms, higher rental income, higher returns, and greater long-term asset value.