Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

VITAL SIGNS INDICATOR
Rent Payments (EC8)

FULL MEASURE NAME
Median rent payment

LAST UPDATED
January 2023

DESCRIPTION
Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time.

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Count 2 (1970)
Form STF1 (1980-1990)
Form SF3a (2000)

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B25058 (2005-2021; median contract rent)

Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Rent data reflects median rent payments rather than list rents (refer to measure definition above). American Community Survey 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

1970 Census data for median rent payments has been imputed from quintiles using methodology from California Department of Finance as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Inflation-adjusted data are presented to illustrate how rent payments 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 CPI itself.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

People in work on zero hours contracts in their main job, including by age, sex and region, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

In 2022, the marriage rate in the United States stood at 6.2 per 1,000 people of the population. This is a decrease from 1990 levels, when the marriage rate was 9.8 marriages per 1,000 people. Marriage Marriage is a union that can legally, culturally, and financially bind two people. Marriage occurs between all genders, races, and cultures. Marriage is drastically different all around the world, due to the diversity of cultures and religions. Marriage can be recognized by a state, religious authority, or an organization. Typically viewed as contract, it brings people together through a multitude of avenues. A part of marriage is the wedding, for which couples can decide to partake in or not. Weddings are also incredibly diverse and vary in time, money, and customs. Marriage in the United States Marriage in the United States is viewed differently across all 50 states. The number of married couples in the United States has been steadily increasing since 1960. On the other hand, the divorce rate in the United States has decreased since 1990. Nevada was the state in 2021 that had the highest marriage rate in the United States, due to easy accessibility to get married there. In 2021, Nevada was also the state with the highest divorce rate in the country.

Release Date: 2022-12-15.Release Schedule:.The data in this file come from the 2021 Annual Survey of Manufactures data files released in December 2022. For more information about the Annual Survey of Manufactures data, see About: Annual Survey of Manufactures...Key Table Information:.Includes only establishments of firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Total fringe benefits ($1,000) .Relative standard error for estimate of total fringe benefits (%) .Total cost of materials ($1,000) .Relative standard error for estimate of total cost of materials (%) .Cost of materials, packaging, etc. used ($1,000) .Relative standard error for estimate of cost of materials, packaging, etc. used (%) .Cost of resales ($1,000) .Relative standard error for estimate of cost of resales (%) .Cost of purchased fuels consumed ($1,000) .Relative standard error for estimate of cost of purchased fuels consumed (%) .Cost of purchased electricity ($1,000) .Relative standard error for estimate of cost of purchased electricity (%) .Cost of contract work ($1,000) .Relative standard error for estimate of cost of contract work (%) .Quantity of electricity purchased for heat and power (1,000 kWh) .Relative standard error for estimate of quantity of electricity purchased for heat and power (%) .Quantity of generated electricity (1,000 kWh) .Relative standard error for estimate of quantity of generated electricity (%) .Quantity of electricity sold or transferred (1,000 kWh) .Relative standard error for estimate of quantity of electricity sold or transferred (%) .Total inventories, beginning of year ($1,000) .Relative standard error for estimate of total inventories, beginning of year (%) .Finished goods inventories, beginning of year ($1,000) .Relative standard error for estimate of finished goods inventories, beginning of year (%) .Work-in-process inventories, beginning of year ($1,000) .Relative standard error for estimate of work-in-process inventories, beginning of year (%) .Materials and supplies inventories, beginning of year ($1,000) .Relative standard error for estimate of materials and supplies inventories, beginning of year (%) .Total inventories, end of year ($1,000) .Relative standard error for estimate of total inventories, end of year (%) .Finished goods inventories, end of year ($1,000) .Relative standard error for estimate of finished goods inventories, end of year (%) .Work-in-process inventories, end of year ($1,000) .Relative standard error for estimate of work-in-process inventories, end of year (%) .Materials and supplies inventories, end of year ($1,000) .Relative standard error for estimate of materials and supplies inventories, end of year (%) .Total capital expenditures (new and used) ($1,000) .Relative standard error for estimate of total capital expenditures (new and used) (%) .Capital expenditures for buildings and other structures ($1,000) .Relative standard error for estimate of capital expenditures for buildings and other structures (%) .Capital expenditures for machinery and equipment ($1,000) .Relative standard error for estimate of capital expenditures for machinery and equipment (%) .Capital expenditures for automobiles, trucks, etc. for highway use ($1,000) .Relative standard error for estimate of capital expenditures for automobiles, trucks, etc. for highway use (%) .Capital expenditures for computers and peripheral data processing equipment ($1,000) .Relative standard error for estimate of capital expenditures for computers and peripheral data processing equipment (%) .Capital expenditures for all other machinery and equipment ($1,000) .Relative standard error for estimate of capital expenditures for all other machinery and equipment (%) ....Geography Coverage:.The data are shown for employer establishments and firms for the U.S. and State levels that vary by industry..For information about 2021 Annual Survey of Manufactures, see About: Annual Survey of Manufactures...Industry Coverage:.The data are shown at the 2-digit 2017 NAICS code levels for the U.S. and States. For information about NAICS, see Annual Survey of Manufactures (ASM): Technical Documentation: ASM Product Class Codes and Descriptions...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/asm/data/2021/AM1831BASIC03.zip..API Information:.Annual Survey of Manufactures API data are housed in the Census Bureau API. For more information, see ASM API..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only..To comply with disclosure avoidance guidelines, data rows with fewer than th...

Release Date: 2022-12-15.Release Schedule:.The data in this file come from the 2021 Annual Survey of Manufactures data files released in December 2022. For more information about the Annual Survey of Manufactures data, see About: Annual Survey of Manufactures...Key Table Information:.Includes only establishments of firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Sales, value of shipments, or revenue ($1,000) .Relative standard error for estimate of sales, value of shipments, or revenue (%) .Annual payroll ($1,000) .Relative standard error for estimate of annual payroll (%) .First-quarter payroll ($1,000) .Relative standard error for estimate of first-quarter payroll (%) .Number of employees .Relative standard error for estimate of number of employees (%) .Production workers for pay period including March 12.Relative standard error for estimate of production workers for pay period including March 12 (%) .Production workers annual hours (1,000) .Relative standard error for estimate of production workers annual hours (%) .Production workers annual wages ($1,000) .Relative standard error for estimate of production workers annual wages (%) .Total fringe benefits ($1,000) .Relative standard error for estimate of total fringe benefits (%) .Employer's cost for health insurance ($1,000) .Relative standard error for estimate of employer's cost for health insurance (%) .Employer's cost for defined benefit pension plans ($1,000) .Relative standard error for estimate of employer's cost for defined benefit pension plans (%) .Employer's cost for defined contribution plans ($1,000) .Relative standard error for estimate of employer's cost for defined contribution plans (%) .Employer's cost for other fringe benefits ($1,000) .Relative standard error for estimate of employer's cost for other fringe benefits (%) .Total cost of materials ($1,000) .Relative standard error for estimate of total cost of materials (%) .Cost of materials, packaging, etc. used ($1,000) .Relative standard error for estimate of cost of materials, packaging, etc. used (%) .Cost of resales ($1,000) .Relative standard error for estimate of cost of resales (%) .Cost of purchased fuels consumed ($1,000) .Relative standard error for estimate of cost of purchased fuels consumed (%) .Cost of purchased electricity ($1,000) .Relative standard error for estimate of cost of purchased electricity (%) .Cost of contract work ($1,000) .Relative standard error for estimate of cost of contract work (%) .Quantity of electricity purchased for heat and power (1,000 kWh) .Relative standard error for estimate of quantity of electricity purchased for heat and power (%) .Quantity of generated electricity (1,000 kWh) .Relative standard error for estimate of quantity of generated electricity (%) .Quantity of electricity sold or transferred (1,000 kWh) .Relative standard error for estimate of quantity of electricity sold or transferred (%) .Value added ($1,000) .Relative standard error for estimate of value added (%) .Total inventories, beginning of year ($1,000) .Relative standard error for estimate of total inventories, beginning of year (%) .Finished goods inventories, beginning of year ($1,000) .Relative standard error for estimate of finished goods inventories, beginning of year (%) .Work-in-process inventories, beginning of year ($1,000) .Relative standard error for estimate of work-in-process inventories, beginning of year (%) .Materials and supplies inventories, beginning of year ($1,000) .Relative standard error for estimate of materials and supplies inventories, beginning of year (%) .Total inventories, end of year ($1,000) .Relative standard error for estimate of total inventories, end of year (%) .Finished goods inventories, end of year ($1,000) .Relative standard error for estimate of finished goods inventories, end of year (%) .Work-in-process inventories, end of year ($1,000) .Relative standard error for estimate of work-in-process inventories, end of year (%) .Materials and supplies inventories, end of year ($1,000) .Relative standard error for estimate of materials and supplies inventories, end of year (%) .Total capital expenditures (new and used) ($1,000) .Relative standard error for estimate of total capital expenditures (new and used) (%) .Capital expenditures for buildings and other structures ($1,000) .Relative standard error for estimate of capital expenditures for buildings and other structures (%) .Capital expenditures for machinery and equipment ($1,000) .Relative standard error for estimate of capital expenditures for machinery and equipment (%) .Capital expenditures for automobiles, trucks, etc. for highway use ($1,000) .Relative standard error for estimate of capital expenditures for automobiles, trucks, etc. for highway use (%) .Capital expenditures for computers and peripheral data...