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.

VITAL SIGNS INDICATOR

Economic Output (EC13)

FULL MEASURE NAME

Gross regional product

LAST UPDATED

August 2022

DESCRIPTION

Economic output is measured by the total and per-capita gross regional product (GRP) and refers to the value of goods and services generated by workers and companies in a region.

DATA SOURCE

Bureau of Economic Analysis: Regional Economic Accounts - http://www.bea.gov/regional/

2001-2020

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

1970-2021

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

2001-2020

Bureau of Labor Statistics: Consumer Price Index - https://download.bls.gov/pub/time.series/cu

2012, 2020

CONTACT INFORMATION

vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)

Data is inflation-adjusted by using both nominal and real data developed by Bureau of Economic Analysis (BEA) and appropriately escalating real GRP data in 2012 chained dollars to 2020 dollars using metropolitan statistical area (MSA)-specific Consumer Price Index data from Bureau of Labor Statistics. Economic output per capita is calculated using CA Department of Finance historical population estimates and Census historical population estimates for Metro areas.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This graph shows the GDP of the San Francisco Bay Area in 2023, by industry. In 2023, 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.

On May 1, the California Department of Finance released population estimates updated through the end of year 2016, which include detailed data on housing production for the San Francisco Bay Region. While a single year is just one data point and may not necessarily be indicative of long-term trends, this data set is still useful to understand how the robust regional economy is affecting housing production trends in recent months.The June 2017 map of the month highlights how 2016 housing production compares to the annualized housing forecast from the Draft Plan Bay Area 2040 by identifying how many years it will take cities, at the current rate, to reach the year 2040 forecast. While some cities are on pace or even ahead of schedule to meet the forecast, numerous jurisdictions are way behind – many by centuries.

This feature set contains point features representing transportation investments nested within each relevant Plan Bay Area 2050 strategy. Only projects with a known location specified by the project sponsor are reflected; this data should be used solely for illustrative purposes. Project details, including the exact location of infrastructure, will be determined at a later date through project-level planning and environmental analyses. Plan Bay Area 2050 is the long-range regional plan for housing, transportation, the environment, and the economy in the San Francisco Bay Area. It was adopted by the Metropolitan Transportation Commission (MTC) and the Association of Bay Area Governments (ABAG) in October 2021.For more data representing Plan Bay Area 2050’s transportation investments, see:Plan Bay Area 2050 Transportation Projects (Line)Plan Bay Area 2050 Transportation Projects (Polygon) More information on the transportation project list may be found on the Plan Bay Area 2050 website.

The Bay Area Greenprint is a tool that reveals the multiple benefits of natural and agricultural lands, empowering users to inform land use decisions with better data. The Bay Area Greenprint identifies, maps, and measures the values that natural resources contribute to the ecosystem, the economy, and the local and regional community.

Source: https://www.bayareagreenprint.org/about/

Data is projected as EPSG:3310

In 2024, the total gross domestic product (GDP) of the Guangdong - Hong Kong - Macao Greater Bay Area amounted to more than *** trillion U.S. dollars. That year, the GDP of the city of Shenzhen alone amounted to around *** billion U.S. dollars, ranking first among cities in the Greater Bay Area. The Greater Bay Area in China The Guangdong - Hong Kong - Macao Greater Bay Area is an economic zone comprised of the two special administrative regions Hong Kong and Macao and nine cities of Guangdong province in mainland China, namely Shenzhen, Guangzhou, Zhuhai, Foshan, Zhongshan, Dongguan, Huizhou, Jiangmen, and Zhaoqing. The concept of the Greater Bay Area has been formulated by the Chinese government to further integrate Macao and Hong Kong into the Chinese mainland and to boost the economy of the cities in the Pearl River Delta. In the 1980s and 1990s, the Pearl River Delta had been one of the prime regions for economic development, but in recent years it has lost ground to the Yangtze River Delta in East China, the largest of the economic macro-regions in China. A development plan for the Greater Bay Area, which was initiated in 2017 and further elaborated thereafter, aims at developing the region into the world's largest and economically most successful Bay Area. GDP development in the Greater Bay Area In 2022, the GDP of the Greater Bay Area cities was still affected by the coronavirus pandemic and decreased slightly in U.S. dollar terms compared to the previous year. However, the development was uneven, with some of the cities on the mainland experiencing strong economic growth, while GDP growth in Hong Kong and Macau still suffered significantly from the pandemic. In 2024, per capita GDP in the Greater Bay Area ranged at about ****** U.S. dollars, which was one of the highest values in China. However, per capita GDP in Hong Kong and Macao is still considerably higher then in the neighboring cities on the mainland.

In 2024, the average per capita gross domestic product (GDP) in the Guangdong - Hong Kong - Macao Greater Bay Area ranged at ****** U.S. dollars. Per capita gross domestic product in Macao amounted to around ****** U.S. dollars in that year, ranking first among cities in the Greater Bay Area. The Greater Bay Area in China The political concept of the Guangdong - Hong Kong - Macao Greater Bay Area was introduced to the public in 2017 and further implemented by jointly signed agreements in the following years. It aims at integrating the special administrative regions of Macao and Hong Kong into the Chinese mainland and boosting the economy of all participating cities in the Pearl River Delta. The development plan for the Greater Bay Area is part of a national Chinese initiative to promote several economic city clusters in China. On the Chinese mainland, nine cities are part of the Greater Bay Area region, all of them located in Guangdong province: Shenzhen, Guangzhou, Zhuhai, Foshan, Zhongshan, Dongguan, Huizhou, Jiangmen, and Zhaoqing. In the long run, the joint plan intends to develop the region into the world's largest and economically most successful Bay Area. Per capita GDP in the Greater Bay Area In terms of per capita GDP, the more mature economies of Macao and Hong Kong are still ahead of mainland Chinese cities in the Greater Bay Area, although Shenzhen and Guangzhou belong to the most developed cities in the whole of mainland China. However, growth rates on the mainland are considerably higher than in Hong Kong and Macao. This is especially true for Shenzhen, which is famous for its past economic boom and has developed into a bustling high-tech location, home to the well-known computer and internet giants Huawei and Tencent.

Centrality of the business credit linkage network in the Hangzhou Bay Greater Bay Area.

In regions where the development of formal finance is relatively lagging behind, commercial credit has partially replaced the role of formal finance and facilitated the development of the private economy and even the country, thus making commercial credit an important entry point for understanding and promoting sustainable economic development. Taking the Hangzhou Bay Greater Bay Area as a case study, based on the City Business Credit Environment Index (CEI) from 2015 to 2019, we examine the characteristics of business credit networks using social network analysis and discuss the impact of business credit on urban green economy efficiency heterogeneity by drawing on spatial econometrics. The study confirms that the structure of business credit networks in the Hangzhou Bay Greater Bay Area tends to be dense, the network density and number of connections show growth, the spatial network structure is taking shape, and the strength of spatial connections among cities has increased. Hangzhou, Shaoxing, Jiaxing and Shanghai are at the centre of the network and play a radiation-driven role. The business credit network in the Hangzhou Bay Greater Bay Area is characterised by self-stability and has evolved from a multi-centre to a single centre. Business credit is negatively correlated with the efficiency of the green economy in the Hangzhou Bay Area, which is a departure from the Chinese "financial development paradox". In terms of heterogeneity, the relationship remains consistent for port cities and open coastal cities in general, while the effect is less pronounced for cities above sub-provincial level. The study concludes that, with the high-quality economic development of the Hangzhou Bay Greater Bay Area, the Chinese "financial development paradox" does not exist in the region at this stage, which also highlights the need to accelerate the construction of a Chinese-style modernisation theory and practice system.

Graph and download economic data for Total Real Gross Domestic Product for San Francisco-Oakland-Hayward, CA (MSA) (RGMP41860) from 2001 to 2023 about San Francisco, CA, real, industry, GDP, and USA.

• Provides information on the status of companies in each industrial complex managed by the Gwangyang Bay Free Economic Zone Authority (industrial complex name, company name, factory location, site area, etc.). - The Gwangyang Bay Free Economic Zone Authority (GFEZ) manages and operates the free economic zone that spans the Gwangyang Bay area of Jeollanam-do, including Gwangyang-si, Yeosu-si, Suncheon-si, Goheung-gun, Gurye-gun, Boseong-gun, and Hwasun-gun. This region is developing into a convergence industrial center in various fields such as industry, logistics, tourism, bio, and energy. - Main functions and roles - Investment attraction and corporate support: Promotes local economic activation through various support policies for companies located in the complex. - Industrial complex development and management: Creates an efficient industrial environment through the development, operation, and management of industrial complexes. - Provision of administrative services: Provides necessary administrative services to companies located in the complex and residents. - Promotion and international exchange: Enhances the image of the Gwangyang Bay Free Economic Zone through activities such as operating an e-promotion center and attracting overseas investment.

VITAL SIGNS INDICATOR
Airport Activity (EC17)

FULL MEASURE NAME
Enplanements or tonnage at airports

LAST UPDATED
August 2022

DESCRIPTION
Airport activity refers to the number of passenger boardings at Bay Area commercial airports and to the quantity of goods – measured in tons – that arrive in the region as air cargo.

DATA SOURCE
United States Department of Transportation, Bureau of Transportation Statistics, Air Carriers : T-100 Segment - https://www.transtats.bts.gov/DL_SelectFields.aspx?gnoyr_VQ=FMG&QO_fu146_anzr=Nv4%20Pn44vr45
1990-2021 (October)

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Freight data is reported in metric tons. Regional Bay Area airports include Oakland (OAK), San Francisco (SFO), San Jose (SJC), and Santa Rosa (STS).

driving_factor:Store the driver factor needed for the experiment development_probability:A file containing the development probabilities of the different elements generated by the model original_data:Storage of original element files (2010, 2020) simulated_data:File of elements for storing simulations (2020) predicted_data:Storage of forecast elements document (2030)

Density of business credit linkage networks in the Hangzhou Bay Greater Bay Area, 2015 to 2019.

This map shows the potential of widespread slope failures, in terms of Newmark displacement (measured in centimeters), triggered by a M7.0 scenario earthquake on the Hayward Fault in the 10-county area surrounding the San Francisco Bay region, California. The cumulative downslope displacement of hillslopes is calculated using a simplified Newmark rigid sliding block slope stability model utilizing four primary datasets: a regional-scale geologic map of the study area, geologic strength parameters compiled as part of the California Geological Survey Seismic Hazard Mapping Program, earthquake shaking data from the USGS ShakeMap developed for this scenario, and 10-meter digital elevation data from the USGS 2009 National Elevation Dataset.The seismic-landslide hazard potential map covers the counties of Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Santa Cruz, Solano, and Sonoma. The slope failures are triggered by a hypothetical earthquake with a moment magnitude of 7.0 occurring on April 18, 2018, at 4:18 p.m. on the Hayward Fault in the east bay part of California’s San Francisco Bay region.

This map shows the potential of widespread slope failures, in terms of landslide probability, triggered by a M7.0 scenario earthquake on the Hayward Fault in the 10-county area surrounding the San Francisco Bay region, California. The likelihood of landsliding was evaluated using an equation developed by Jibson and others (2000) that estimates landslide probability as a function of predicted Newmark displacement. Based on this equation, four landslide probability categories are established with their corresponding percent likelihood and displacement ranges: Low (0-2%; 0-1 cm), Moderate (2-15%; 1-5 cm), High (15-32%; 5-15 cm), and Very High (>32%; >15 cm).The seismic-landslide probability map covers the counties of Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Santa Cruz, Solano, and Sonoma. The slope failures are triggered by a hypothetical earthquake with a moment magnitude of 7.0 occurring on April 18, 2018, at 4:18 p.m. on the Hayward Fault in the east bay part of California’s San Francisco Bay region.

Results of QAP regression analysis of the factors influencing the information linkage network of Guangdong, Hong Kong and Macao Greater Bay Area.

In 2014, the Chinese government unveiled the New Urbanization Plan and Document No. 46, which profoundly influenced the development trajectory of the regional economy and sports industry. Using the coupling coordination model, this study aimed to assess the development progress of the sports industry and urban clusters economy. This study sampled Greater Bay Area urban clusters (GBAUC) and Yangtze River Delta urban clusters (YRDUC). The statistics covered one year after the release of the policies to date. We developed a total of 15 macro indicators to evaluate the sports industry and urban cluster economy as two distinct, yet interdependent, economic systems. Using the entropy weight method, we determined the standardized values and weights for the two systems before calculating the coupling coordination degree (D). Between 2015 and 2021, the sampled sports industry and urban clusters economy exhibited coordinated high growth across all economic metrics, with multiple sports industry metrics exhibiting double-digit growth. In 2015, both showed extreme imbalance: D of GBAUC = 0.092, D of YRDUC = 0.091. In 2017, both improved to bare coordination: D of GBAUC = 0.600, D of YRDUC = 0.566. In 2019, both reached well coordination: D of GBAUC = 0.851, D of YRDUC = 0.814. By 2021, both achieved quality coordination: D of GBAUC = 0.990, D of YRDUC = 1. This study provides the first evidence from the sports industry that China’s new urbanization model and Document No. 46 are highly effective for synergistic regional economic growth.

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001