In 2023, the population of the San Francisco-Oakland-Berkeley metropolitan area in the United States was about 4.57 million people. This is a slight decrease from the previous year, when the population was about 4.58 million people.

Chart and table of population level and growth rate for the San Francisco metro area from 1950 to 2025.

Roadways (streets and highways) for the San Francisco Bay Region. Feature set was assembled using all roads county-based 2021 TIGER/Line shapefiles by the Metropolitan Transportation Commission.The All Roads shapefiles includes all features within the Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB) Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, stairways, and winter trails.The feature set contains multiple overlapping road segments where a segment is associated with more than one road feature. For example, if a road segment is associated with US Route 36 and State Highway 7 and 28th Street, the route will contain three spatially coincident segments, each with a different name. The roadway feature set contains the set of unique road segments for each county, along with other linear features.Primary roads are generally divided limited-access highways within the Federal interstate highway system or under state management. Interchanges and ramps distinguish these roads, and some are toll highways.Secondary roads are main arteries, usually in the U.S. highway, state highway, or county highway system. These roads have one or more lanes of traffic in each direction, may or may not be divided, and usually have at-grade intersections with many other roads and driveways. They often have both a local name and a route number.

2020 Census block groups for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from California 2021 TIGER/Line shapefile by the Metropolitan Transportation Commission.Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and block groups are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. Block groups have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within Block Group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas.Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian/Alaska Native/Native Hawaiian areas. The block group boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

Tracts; January 1, 2019 vintage; Generalized

Features provide a view of 2020 Census tracts for the San Francisco Bay Region. Features are a subset of the Census Tracts 500k service at https://data.bayareametro.gov/dataset/Census-Tracts-500K/dg5p-pxcu.

Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses.

Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline.

Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy.

In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous.

For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Local participants have an opportunity to review the existing census tracts before each census. If local participants split a census tract, the split parts usually retain the basic number, but receive different suffixes. In a few counties, local participants request major changes to, and renumbering of, the census tracts. Changes to individual census tract boundaries usually do not result in census tract numbering changes.

Relationship to Other Geographic Entities—Within the standard census geographic hierarchy, census tracts never cross state or county boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.

This data layer depicts, by census block group, race for the San Francisco Bay Region. The source data, from the United States Census Bureau, has been reprocessed by the Metropolitan Transportation Commission.

To produce this feature set, the Metropolitan Transportation Commission pulled data from the Decennial Census API P2 Table, and re-tabulated race and ethnicity population totals into following categories: ● Non-Hispanic White ● Hispanic ● Non-Hispanic Asian (includes Native Hawaiian and Pacific Islander) ● Non-Hispanic Black/African American ● Non-Hispanic Other Race and Multiple Races

The resulting attribute table had all margin of error fields deleted, Hispanic subcategories deleted, percentage fields added, county code field added, and the source field names were changed.

The source table used to develop this feature service is from the United States Census Bureau, 2020 Decennial Census.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

Incorporated Places (cities and towns) are those reported to the Census Bureau as legally in existence as of May 28, 2021, under the laws of their respective states. Features were extracted from California 2020 TIGER/Line shapefile by the Metropolitan Transportation Commission.An incorporated place provides governmental functions for a concentration of people, as opposed to a minor civil division, which generally provides services or administers an area without regard, necessarily, to population. Places may extend across county and county subdivision boundaries, but never across state boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions.

This feature set contains household and population projections from Projections 2040 for the San Francisco Bay Region. This forecast represents household and population projections resulting from Plan Bay Area 2040. Numbers are provided by county. Household and population numbers are included for 2010 (two versions), 2015, 2020, 2025, 2030, 2035, and 2040. For 2010, two data points are provided:A tabulation (base year A) from the 2010 model simulation (base year A); and(Preferred) A tabulation (base year B) from the 2010 pre-run microdata, designed to approximate (but may still differ from) Census 2010 counts.Projection data is included for total households, group quarter population, household population, persons per household, and total population.This feature set was assembled using unclipped county features. For those who prefer Projections 2040 data using county features with ocean and bay waters clipped out, the data in this feature service can be joined to San Francisco Bay Region Counties (clipped).Other Projections 2040 feature sets:Households and population per jurisdiction (incorporated place and unincorporated county)Households and population per Census TractJobs and employment per countyJobs and employment per jurisdiction (incorporated place and unincorporated county)Jobs per Census TractFemale population, by age range, per countyFemale population, by age range, per jurisdiction (incorporated place and unincorporated county)Male population, by age range, per countyMale population, by age range, per jurisdiction (incorporated place and unincorporated county)Total population, by age range, per countyTotal population, by age range, per jurisdiction (incorporated place and unincorporated county)

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME
Population estimates

LAST UPDATED
February 2023

DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries

U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

The following is a list of cities and towns by geographical area:

Big Three: San Jose, San Francisco, Oakland

Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside

Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville

Unincorporated: all unincorporated towns

This graph shows the GDP of the San Francisco Bay Area in 2022, by industry. In 2022, the GDP of the San Francisco metro area amounted to about ****** billion U.S. dollars. About ***** billion U.S. dollars were generated in the manufacturing industries. The overall quarterly GDP growth in the United States can be found here. The San Francisco Bay Area’s GDPThe San Francisco Bay Area, commonly known as the Bay Area, is a metropolitan region that surrounds the San Francisco and San Pablo estuaries in Northern California. The region encompasses metropolitan areas such as San Francisco-Oakland (12th largest in the country), San Jose (31st largest in the country), along with smaller urban and rural areas. Overall, the Bay Area consists of nine counties, *** cities, and ***** square miles. The nine counties are Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma. The United States Census Bureau considers the Bay Area a Combined Statistical Area (CSA) with approximately *** million people, including the nine counties bordering San Francisco Bay as well as Santa Cruz and San Benito Counties, making it the sixth largest CSA in the United States. In the ten year period between 2001 and 2011, the Bay Area saw its GDP grow considerably. In 2001, GDP was *** billion U.S. dollars. This value rose to *** billion U.S. dollars by 2011. Additionally, California ranked first on a list of U.S. states by GDP, with *** trillion U.S. dollars of GDP in 2012. Silicon Valley, located in the Bay Area, is in great part responsible for the Bay Area’s and California’s high GDPs, as it is known as the center of the global technology industry. Companies like Google, Facebook, eBay and Apple are headquartered there.

Incorporated Places (cities and towns) are those reported to the Census Bureau as legally in existence as of May 28, 2021, under the laws of their respective states. Features were extracted from, and clipped using, California 2020 TIGER/Line shapefiles by the Metropolitan Transportation Commission. An incorporated place provides governmental functions for a concentration of people, as opposed to a minor civil division, which generally provides services or administers an area without regard, necessarily, to population. Places may extend across county and county subdivision boundaries, but never across state boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions.

Census Block Groups; January 1, 2020 vintage; Generalized

Features provide a view of 2020 Census block groups for the San Francisco Bay Region. Features are a subset of the Census Block Groups 500k service at https://data.bayareametro.gov/dataset/Census-Block-Groups-500K/2wpi-uueb.

Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and block groups are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. Block groups have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within Block Group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas.

Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian/Alaska Native/Native Hawaiian areas.

County boundaries for the San Francisco Bay Region. Features were extracted from California 2020 TIGER/Line shapefile by the Metropolitan Transportation Commission. The 2020 TIGER/Line Shapefiles reflect available governmental unit boundaries of the counties and equivalent entities as of May 28, 2021.Counties and equivalent entities are primary legal divisions of states. In most states, these entities are termed “counties.” Each county or statistically equivalent entity is assigned a 3-character FIPS code that is unique within a state.

Provides Census block group identifier for block groups from 2010 Decennial Census for the San Francisco Bay Region.

Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and block groups are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. Block groups have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within Block Group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas.

Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian/Alaska Native/Native Hawaiian areas.

This raster dataset depicts the population denisty of the nine county San Francisco Bay Area Region, California produced with a Dasymetric Mapping Technique, which is used to depict quantitative areal data using boundaries that divide an area into zones of relative homogeneity with the purpose of better portraying the population distribution. The source data was then adjusted in order to get convert the units to persons per acre. This dataset is an accurate representation of population distribution within census boundaries and can be used in a number of ways, including as the Conservation Suitability layer for the Marxan inputs and the watershed integrity analysis.

INTRODUCTION: As California’s homeless population continues to grow at an alarming rate, large metropolitan regions like the San Francisco Bay Area face unique challenges in coordinating efforts to track and improve homelessness. As an interconnected region of nine counties with diverse community needs, identifying homeless population trends across San Francisco Bay Area counties can help direct efforts more effectively throughout the region, and inform initiatives to improve homelessness at the city, county, and metropolitan level. OBJECTIVES: The primary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness across San Francisco Bay Area counties between the years 2018-2022. The secondary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness among different age groups in each of the nine San Francisco Bay Area counties between the years 2018-2022. METHODS: Two datasets were used to conduct research. The first dataset (Dataset 1) contains Point-in-Time (PIT) homeless counts published by the U.S. Department of Housing and Urban Development. Dataset 1 was cleaned using Microsoft Excel and uploaded to Tableau Desktop Public Edition 2022.4.1 as a CSV file. The second dataset (Dataset 2) was published by Data SF and contains shapefiles of geographic boundaries of San Francisco Bay Area counties. Both datasets were joined in Tableau Desktop Public Edition 2022.4 and all data analysis was conducted using Tableau visualizations in the form of bar charts, highlight tables, and maps. RESULTS: Alameda, San Francisco, and Santa Clara counties consistently reported the highest annual count of people experiencing homelessness across all 5 years between 2018-2022. Alameda, Napa, and San Mateo counties showed the largest increase in homelessness between 2018 and 2022. Alameda County showed a significant increase in homeless individuals under the age of 18. CONCLUSIONS: Results from this research reveal both stark and fluctuating differences in homeless counts among San Francisco Bay Area Counties over time, suggesting that a regional approach that focuses on collaboration across counties and coordination of services could prove beneficial for improving homelessness throughout the region. Results suggest that more immediate efforts to improve homelessness should focus on the counties of Alameda, San Francisco, Santa Clara, and San Mateo. Changes in homelessness during the COVID-19 pandemic years of 2020-2022 point to an urgent need to support Contra Costa County.

In 2023, the GDP of the San Francisco Bay Area amounted to ****** billion U.S. dollars, an increase from the previous year. The overall quarterly GDP growth in the United States can be found here. The GDP of the San Francisco Bay Area The San Francisco Bay Area, commonly known as the Bay Area, is a metropolitan region that surrounds the San Francisco and San Pablo estuaries in Northern California. The region encompasses metropolitan areas such as San Francisco-Oakland (12th largest in the country), San Jose (31st largest in the country), along with smaller urban and rural areas. Overall, the Bay Area consists of nine counties, *** cities, and ***** square miles. The nine counties are Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma. There are approximately 4.62 million people living in the metro area as of 2022. Silicon Valley In the ten year period between 2001 and 2011, the Bay Area saw steady GDP growth. Starting in 2012, it began to skyrocket. This is thanks to an economic boom in the tech sector, and high value companies headquartered in Silicon Valley - also part of the Bay Area. Silicon Valley is known as the center of the global technology industry. Companies like Google, Facebook, eBay and Apple are headquartered there. Additionally, California ranked first on a list of U.S. states by GDP, with more than **** trillion U.S. dollars in GDP in 2022.

Graph and download economic data for Single-Parent Households with Children as a Percentage of Households with Children (5-year estimate) in San Francisco County, CA (S1101SPHOUSE006075) from 2009 to 2023 about San Francisco County/City, CA; San Francisco; single-parent; CA; households; 5-year; and USA.

Graph and download economic data for New Private Housing Units Authorized by Building Permits: 1-Unit Structures for San Francisco-Oakland-Berkeley, CA (MSA) (SANF806BP1FH) from Jan 1988 to May 2025 about privately owned, San Francisco, 1-unit structures, permits, family, buildings, CA, housing, and USA.