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.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2000 Decennial Census data at the block geography.Attributes:FIPSSTCO = The Federal Information Processing Series (FIPS) state and county codes. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.TRACT2000 = Census Tract Codes and Numbers. Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLOCK2000= Census Block Numbers are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.STFID = A concatenation of FIPSSTCO, TRACT2000, and BLOCK2000, which creates the entire FIPS code for this geography.WFD = Workforce Development Area (WFD) is a seven-county area created by agreement of county chief-elected officials, administered by the Atlanta Regional Commission and funded for training and employment activities under the federal Workforce Investment Act (WIA). For more information on ARC’s Workforce Development programs and services please consult www.atlantaregional.com/workforce/workforce.html.RDC_AAA = ARC Area Agency on Aging is a 10-county area funded by the Department of Human Resources and designated by the Older Americans Act to plan for the needs of the rapidly expanding group of older citizens in the Atlanta region. It is part of a statewide network of 12 AAAs and a national network of more than 670 AAAs. For more information on aging services please consult www.agewiseconnection.com.MNGWPD = The Metro North Georgia Water Planning District provides water resource plans, policies and coordination for metropolitan Atlanta. The District has developed regional plans for stormwater management, wastewater treatment and water supply and water conservation. The 15-county Water Planning District includes the ten counties in the ARC plus five additional counties (Bartow, Coweta, Forsyth, Hall, & Paulding). For more information please consult www.northgeorgiawater.org. MPO = The Metropolitan Planning Organization (MPO) is a 19-county area federally-designated for regional transportation planning to meet air quality standards and for programming projects to implement the adopted Regional Transportation Plan (RTP). The MPO planning area boundary includes the 10-county state-designated Regional Commission and nine additional counties (all of Coweta, Forsyth, & Paulding and parts of Barrow, Dawson, Newton, Pike, Spalding and Walton). This boundary takes into consideration both the current urbanized area as well as areas forecast to become urbanized in the next 20 years.MSA = the 29-County “Atlanta-Sandy Springs-Roswell, GA” Metropolitan Statistical Area (MSA) and the 39-county “Atlanta--Athens-Clarke County--Sandy Springs, GA” Combined Statistical Area (CSA), which includes the 29 counties of the Atlanta MSA along with the Athens-Clarke County and Gainesville MSAs and the micropolitan statistical areas of Calhoun, Cedartown, Jefferson, LaGrange and Thomaston, GA. The U.S. Office of Management and Budget (OMB) defines CSAs, MSAs and the smaller micropolitan statistical areas nationwide according to published standards applied to U.S. Census Bureau data. These various statistical areas describe substantial core areas of population together with adjacent communities having a high degree of economic and social integration, often illustrated in high rates of commuting from the adjacent areas to job locations in the core. For more information, please consult http://www.census.gov/population/metro/data/metrodef.htmlF1HR_NA = The Federal 1-Hour Air Quality Non-Attainment Area is a fine particulate matter standard (PM2.5). The non-attainment area under this standard includes the 15-county eight-hour ozone nonattainment area plus Barrow, Carroll, Hall, Spalding, Walton, and small parts of Heard and Putnam counties.F8HR_NA: The Federal 8-Hour Air Quality Non-Attainment Area for the 2008 eight-hour ozone standard is 15 counties.ACRES = The number of acres contained within the Block.SQ_MILES = The number of square miles contained within the Block.Source: United States Census Bureau, Atlanta Regional CommissionDate: 2000For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

During the American Civil War, not only was the Confederacy made up of fewer states than the Union, but these states were also much less populous than many in the North. For example, in the final census before the war in 1860, the five largest states in the South had around one million inhabitants each, while the largest states in the North had three to four million. In addition to the Union's larger population, the fact that European immigration into urban and industrial centers in the North was much higher also gave the Union a steady supply of recruits that were drafted as the war progressed, which was vital to the Union's victory in 1865.

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Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

Universe

All housing units and households; all individuals who passed the night of the census date in the dwelling

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Statistical Agency

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the country. NOTE: The sample includes data from both the short and the long questionnaire. Only one-fifth of household received the long questionnaire, thus only 20% of the population have responses for most variables.

SAMPLE UNIT: household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 7,434,086

Mode of data collection

Face-to-face [f2f]

Research instrument

Two census questionnaires, a short form and a long form, collected information in five sections: 1) Area identification, 2) Type of residence and housing identification, 3) Details of persons in the household, 4) Deaths in the household during the last 12 month, and 5) Information on housing unit. The long questionnaire was administerd to 1 in 5 households in each enumeration area. The short questionnaire with a subset of the long questionnaire items corresponding to basic demographic and social characteristics (population size, sex, age, religion, mother tongue, ethnic group, disability and orphanage) was administered to the remaining (non-sample) households.

This article describes a Climate-Smart Agriculture (CSA) database collected from 34 countries, 16 in Africa, 7 in Asia and 11 in Latin America and the Caribbean (LAC) by the International Center for Tropical Agriculture (CIAT) in collaboration with various stakeholders in respective countries. The dataset is a combination of both quantitative and qualitative data collected via a participatory approach that involved several players from different levels; farmers, input suppliers, processors, traders, policymakers, and donors. Primary data was collected from country experts in interviews, focus group discussions and workshops; a semi-structured survey questionnaire was used to conduct interviews and guide focus group discussions. A structured questionnaire was used to collect data in workshops. Secondary data on various agricultural indicators required for country CSA profiling were accessed via national and global public repositories. The data comprise of CSA practices, CSA scores across the three CSA pillars for selected production systems or value chains, existing climate-related policies at country level, and institutions implementing, overseeing or developing climate policies and interventions. The data shows CSA adoption levels, barriers to adoption and type of farmers using each of the practices the most. Over 1500 experts were interviewed in data collection